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Webinar IAPA - Reimagining Public Administration Education in the Digital Era

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0:00

kebajikan.

0:02

Ee Bapak, Ibu sekalian, selamat datang

0:06

di ee dalam webinar nasional IAPA

0:10

bertajuk Reimaging Public Administration

0:13

Education in Digital Era atau merumuskan

0:17

kembali masa depan pendidikan

0:19

administrasi publik di era digital.

0:23

Jadi perkenalkan saya dr. Nyiah Hutari

0:26

Dewi. Selain bertugas sebagai moderator

0:29

pada hari ini, saya juga merupakan ee

0:33

wakil ketua umum bidang kerjasama

0:35

Nasional dan DUDIKA IAPA serta direktur

0:39

Program Pasca Sarjana Universitas

0:41

Ngurahrai.

0:43

So, good morning ladies and gentlemen.

0:45

Welcome to the IA

0:48

webinar reimagining public

0:51

administration education in the digital

0:54

era. Allow me to introduce myself. I'm

0:57

Dr. Nyomandriahutari Dewi. In addition

1:00

to moderating today sessions, I serve as

1:04

the vice president for national

1:07

cooperation and industry academic

1:09

partnerships at IAPA. and also the

1:13

director of the postgraduate program.

1:19

So admit the rapid dynamics of

1:23

technology we have gathered with expert

1:26

and practitioners to

1:30

how

1:32

public administration education

1:34

transform. Today we will gain profound

1:37

insights from our three distinguished

1:39

speakers who are joining us. Today,

1:44

sebelum kita memulai sesi diskusi utama

1:47

dengan para narasumber, marilah kita

1:50

dengarkan sambutan hangat sekaligus

1:53

pembukaan resmi acara ini.

1:56

Ee untuk itu

1:58

kami mengundang Ketua Umum Indonesian

2:02

Association for Public Administration

2:05

eh IAPA, Prof. eh Kirul Muruk untuk

2:09

memberikan kata sambutan. Before we

2:13

proceed to our main discussion with the

2:16

speakers, let us begin with a warm

2:19

welcome and the official opening of this

2:21

event. For that, we would like to invite

2:25

the president of the Indonesian sport

2:27

public administration,

2:29

Yapa. Dr. Kir Muruk eh to deliver the

2:33

welcome speech. Prof. Muluk the screen

2:36

is thank you.

2:40

Terima kasih, Bu Dia. Asalamualaikum

2:43

warahmatullahi wabarakatuh. Selamat

2:45

Waalaikumsalam.

2:47

Selamat pagi dan salam sejahtera untuk

2:49

kita semua. Good morning distinguished

2:52

speakers Prof. Alfred Ho, Prof.

2:55

Andiwijaya, Dr. Rino Ardian and my

3:00

college Bu Diah Putari Dewi as a

3:03

moderator and for all participant from

3:07

across Indonesia and beyond.

3:11

Pertama kita panjatkan puji syukur ke

3:13

hadirat Allah Subhanahu wa taala Tuhan

3:15

yang maha esa karena hari ini kita untuk

3:19

pertama kalinya dalam kepengurusan IAPA

3:21

saat ini ee melaksanakan webinar ya

3:26

mungkin yang kedua karena bulan lalu

3:27

juga sudah ada ya tapi ee hari ini

3:30

tentang webinar series

3:33

ee Ibu Bapak sekalian I will combine

3:36

opening remarks both in Indonesian and

3:40

English ya we are living now in an era

3:44

marked by rapid digital transformations

3:47

artificial intelligence big data

3:49

analytic platform governance

3:53

and algorithm driven decision making

3:56

that are saping the way govern

3:58

governments operate and interact with

4:02

with citizens

4:04

digitalization is no longer merely an

4:06

administrative tool it has become a new

4:09

architecture of governance.

4:12

Satu hal yang saat ini tidak bisa kita

4:15

hindari bahwa ee disrupsi digital sudah

4:19

kita alami saat ini. Ada kecerdasan

4:22

artificial, ada big data, ada platform

4:25

governance, ada perubahan

4:28

pola interaksi antara negara dengan

4:30

warga negara. Digitalisasi saat ini

4:33

bukan lagi sekedar alat bantu

4:35

administrasi.

4:37

Ia digitalisasi sekarang telah menjadi

4:40

arsitektur baru dalam governance.

4:45

The reality resist a fundamental

4:47

questions.

4:49

Is our public administration education

4:51

system still adequately prepared for

4:54

this transformation?

4:56

A our curricula our curriculum still

5:00

rooted in the 20th century bureaucratic

5:04

models while governance practices have

5:07

already moved into the digital

5:09

ecosystems of the 21st century.

5:13

We need reimagining education does not

5:15

simply mean updating costly only. It

5:19

requires us to rethink our paradigms,

5:22

our competencies, and even our

5:25

professional identity.

5:28

Saat ini pertanyaannya, Ibu sekalian

5:30

adalah apakah pendidikan administrasi

5:32

publik kita sudah cukup responsif

5:34

terhadap perubahan governance digital

5:37

governance tersebut? Apakah kurikulum

5:39

kita masih berbasis pada

5:42

model birokrasi abad ke-20? Sementara

5:45

praktik pemerintah sudah bergerak

5:46

menjadi ekosistem digital abad ke-21.

5:51

Di sini kita perlu membayangkan kembali,

5:54

reimagining, membayangkan kembali kita

5:57

tidak sekedar akan memperbarui silabus

6:00

RPS, kurikulum kita, tapi kita sedang

6:03

menata paradigma kita.

6:08

At least we have three major challenges

6:11

that facing public administration

6:14

education globally I think including

6:16

Indonesia.

6:18

First is epistemic challenges, tantangan

6:22

epistemic.

6:23

Dan yang kedua adalah tantangan

6:25

pedagogic, pedagogical challenges.

6:28

And the third one is normative and

6:31

ethical challenges.

6:35

Secara global pendidikan administrasi

6:37

publik memang akan menghadapi tiga hal

6:39

tersebut. Epistemik, pedagogik, dan

6:43

norma dan etika dalam menghadapi digital

6:46

governance.

6:48

Ibu Bapak sekalian, distinguished

6:50

participans,

6:53

eh in Indonesian context this challenges

6:55

are even more complex. We face

6:58

disparities in digital infrastructure,

7:01

variation in institutional capacity

7:04

across regions and diverse sociocultural

7:07

realities.

7:09

Therefore, reimagering public

7:11

administration education Indonesia must

7:12

address three strategic agendas.

7:16

Situasi di Indonesia tantangannya

7:19

menjadi lebih kompleks karena kita

7:21

menghadapi disparitas infrastruktur

7:24

digital.

7:25

Ada yang sudah maju, ada yang sangat

7:27

tertinggal. Ada banyak variasi dalam

7:31

kapasitas kelembagaan

7:34

dan ada realitas perbedaan sosiokultural

7:38

di masyarakat kita. Oleh karena itu,

7:41

pendidikan publik saat ini saya kira

7:43

kita sedang menghadapi ee tiga agenda

7:47

strategis, ya. Satu, membangun

7:49

kompetensi digital aparatur.

7:53

ini ee SDM penting bagi kita termasuk

7:56

literasi data, desain kebijakan digital,

8:00

evidence based policy. Yang kedua,

8:03

agendanya adalah menguatkan kepemimpinan

8:05

publik yang adaptif

8:07

yang mampu bekerja dalam situasi

8:08

ketidakpastian dan kompleksitas. Dan

8:11

yang ketiga adalah meneguhkan kembali

8:14

nilai publicness.

8:16

Publicness ini penting. Banyak isu yang

8:18

sedang kita hadapi. Bahwa teknologi

8:21

hanya adalah sekedar instrumen.

8:25

Teknologi adalah instrumen. Teknologi

8:27

bukan tujuan. Tujuan kita tetap publik.

8:31

Tujuan kita tetap kesejahteraan dan

8:32

keadilan sosial.

8:36

Technology

8:39

as a mere instrument but our proposes

8:43

actually the public itself. public

8:46

interest

8:47

and including promotes inclusive

8:49

development.

8:51

Ibuak sekalian sebagai organisasi

8:54

profesi dan akademik IAPA tetap memiliki

8:57

tanggung jawab moral dan intelektual

8:59

untuk memimpin diskursus ini. Kita tidak

9:02

boleh sekedar menjadi pengamat

9:04

perubahan. Kita harus menjadi arsitek

9:08

perubahan.

9:09

melalui forum ini saya berharap nanti

9:12

dan ini bukan yang pertama Ibu Bapak

9:14

sekalian jadi akan ada seri-seri

9:16

berikutnya saya berharap nanti kita

9:19

lahir dari IAPA gagasan konkret gagasan

9:23

konkret tentang pembaharuan kurikulum

9:26

termasuk model kolaborasi antara kampus

9:29

dan pemerintah serta roadmap penguatan

9:33

pendidikan vokasi pendidikan akademik

9:36

dan profesi administrasi publik di era

9:37

digital. Ibu Bapak sekalian, di

9:41

Indonesia administrasi publik masih

9:43

memiliki dua jenis pendidikan,

9:45

pendidikan akademik dan pendidikan

9:47

vokasi. Kita berusaha juga membangun

9:51

pendidikan profesi administrasi publik.

9:54

Still, we have to we have two kind of

9:58

higher education eh platform in

10:00

Indonesia, vocational and academic. But

10:03

we need in the future we have

10:05

professions eh education in public

10:08

administrations.

10:11

Webinar ini sekali lagi hari ini bukan

10:13

akhir. Mudah-mudahan ini awal dari

10:15

percakapan kita yang lebih besar. Kita

10:18

akan mendorong konsolidasi nasional

10:20

untuk merumuskan standar kompetensi dan

10:23

arah pengembangan pendidikan

10:24

administrasi publik Indonesia yang

10:27

adaptif terhadap transformasi digital.

10:31

Ee pada akhirnya saya menyampaikan

10:35

apresiasi dan terima kasih kepada

10:37

seluruh narasumber.

10:40

Eh,

10:43

my sincer gratitude to our distinguished

10:45

speakers for sharing their insight.

10:47

Prof. Eh, Alfred Ho, Prof. Andi

10:51

Ftawijaya, Pak Rino and of course Bu

10:56

Diah ya.

10:59

Dan saya kira ini menjadi tantangan kita

11:02

ke depan, masukan kita ke depan.

11:05

Mudah-mudahan kita bisa membangun

11:06

disiplin ilmu kita dan profesi kita

11:09

lebih maju lagi. Saya kira demikian IAPA

11:13

ini secara resmi ee kita mulai, kita

11:17

buka, kita mulai. Mudah-mudahan membawa

11:19

manfaat bagi administrasi publik di

11:21

Indonesia. Terima kasih. Asalamualaikum

11:23

warahmatullahi wabarakatuh.

11:30

warahmatullahi wabarakatuh. Terima kasih

11:32

kepada Ketua

11:34

Umum IASA sambutan yang sangat

11:37

inspiratif. Dan Bapak Ibu sekalian yang

11:39

ada di Zoom meeting pada hari ini.

11:42

Sebagaimana telah disampaikan pendidikan

11:44

administrasi publik memang harus

11:46

bertransformasi.

11:48

Nah, untuk membedah strategi tersebut

11:51

kita telah menghadirkan tiga pakar luar

11:53

biasa. Jadi izinkan saya memperkenalkan

11:56

mereka satu persatu. Eh, thank you to

12:00

the president of Yapa for the truly

12:03

inspiring remarks. Ladies and gentlemen,

12:07

as previously mention, public

12:10

administration education must transform.

12:13

To this strategies we have invited three

12:17

exordinary experts please allow me to

12:20

introd

12:22

the

12:26

Prof. Alfred T

12:29

M PhD. So Prof. Alfred is IAPA

12:34

International

12:35

Honorary Members and the dean of the

12:39

College of Liberal Arts and Social

12:43

Science class city University eh of Hong

12:47

Kong. So I read some of eh

12:52

eh Prof. Alfred eh articles and it's

12:56

quite eh impressive.

12:59

So I would like to you know to read your

13:04

short bio first so everybody will know

13:06

who you are. So eh Alfred Tatho. Prof.

13:11

Alfred itu adalah chair profesor bidang

13:13

kebijakan publik dan tata kelola serta

13:17

Dekan College of Liberal Art dan Social

13:21

Science di City University of Hong Kong.

13:24

Jadi beliau merupakan FILO eh overseas

13:28

dari National Academy of Public

13:30

Administration and Vice President eh

13:33

untuk Asia di International Research

13:36

Society for Public Management. Fokus

13:39

penelitian beliau adalah meliputi

13:41

manajemen kinerja pemerintah,

13:44

e-goverment, partisipasi warga, dan

13:47

kolaborasi lintas sektor. Beliau juga

13:49

berkolaborasi dengan berbagai organisasi

13:53

internasional seperti United Nations

13:55

Stade and Development and ASEAN

13:59

Development Bank. dan eh beliau meraih

14:02

gelar sarjana dari Chinese University of

14:04

Hong Kong serta gelar MPA dan PhD dari

14:08

Indiana University Bloomington, USA dan

14:11

telah mengajar lebih dari 20 tahun di

14:14

Amerika Serikat sebelum kembali ke

14:16

Hongkong pada tahun 2020.

14:20

So I saw in one in your in the article

14:24

in the news that Prof. Alfred is eh

14:28

given you know the US experience

14:30

provided

14:32

eh Prof. had many opportunities to

14:35

develop his professional and academic eh

14:38

career

14:39

and eh you know I interest to your some

14:44

of your foods that I took from the news

14:47

that you initiated that because you felt

14:51

that you may be to distance from

14:53

students so you have been gone for so

14:56

long and there are probably multiple

14:58

generation or other gaps between you and

15:02

young

15:09

leaders department across

15:13

together in the summer you examine the

15:17

purpose of competence based educations

15:21

and discuss how you would redesign your

15:24

department programs with extraculitural

15:28

activities be to better equip students

15:32

for the 20th century and over Richard

15:36

University. So this is quite impressive

15:40

and this is you know it's a long eh bio

15:44

of eh Profo. So we cannot read this now.

15:49

So you guys can look googling him. There

15:53

are a lot of article about him. So tanpa

15:56

menunda waktu lama lagi mari kita

15:59

memulai sesi pemaparan. Jadi

16:01

masing-masing narasumber akan diberikan

16:04

waktu 20 menit. So without eh without

16:08

further ado, let us begin the

16:10

presentation sessions. Speaker will have

16:14

20 minutes. So to our first speaker,

16:18

Prof. Ho, the screen is yours. Thank

16:21

you.

16:22

Thank you so much for your generous

16:24

introduction and thank you for

16:27

uh telling uh your audience a little bit

16:30

about my background. I I am not quite

16:33

sure actually I live up to all those uh

16:34

wonderful words. So I will try my best

16:37

um to share some of the lessons I've

16:39

learned. Um I am sharing this screen.

16:43

Could you see it? Okay. The full screen

16:45

of my PowerPoint. Yep. Okay.

16:47

Okay.

16:48

Yep. Okay. Good. So, um I think I have

16:50

30 minutes to go through my slides. Is

16:53

that right?

16:55

Yep.

16:55

Okay.

16:56

Yep. And everyone could hear me. Okay.

16:58

Yes.

16:59

Yep. So um I'm going to uh talk a little

17:02

bit about um uh government in the

17:06

digital era for uh president will look

17:09

uh point about the reality that we are

17:13

in the digital era government has to use

17:15

a lot of digital tools and then we will

17:18

talk a little bit about the big data

17:20

world uh which is already happening and

17:22

then also a lot something about the data

17:24

applications uh in different public

17:26

management and also some of the lessons

17:29

We have learned from the US experience

17:31

also uh from the Asian or Chinese

17:34

government experience and then some of

17:36

the implications finally on the proper

17:38

administration education and I would uh

17:40

love to share with you what we are doing

17:42

at City University of Hong Kong and then

17:45

have some concluding thoughts. By the

17:47

way um since all of you are in the

17:48

public administration world so um I

17:51

could tell you that uh we are very

17:53

honored to have the opportunity to work

17:54

with the internation association of

17:56

public administration. Uh some of your

17:58

leadership have been here and some of

18:00

also your members have been here to

18:02

participate in a uh hotline service

18:05

management conference last year in

18:07

November. So they have already kind of

18:09

seen what we are doing in e-government

18:11

and also uh digital government service

18:14

delivery in the region including some of

18:17

the represent from Kazastan and so we

18:20

are really looking to this our

18:22

university or our public administration

18:24

uh department called public and

18:26

international affairs department uh

18:28

which I am part of is actually highly

18:30

ranked. Um uh according to the QS

18:33

ranking we are ranked 37 in the world in

18:35

the Shanghai ranking we are actually

18:37

ranked number seven in the world because

18:39

of our research and so that actually

18:41

means we actually have surpassed Chingha

18:43

Pikingu and Oxfor and Cambridge on

18:46

public administration so uh we have a

18:49

lot of international faculty members uh

18:52

we have about 45 faculty members in

18:53

public administration department and so

18:55

it's almost like a school so we have a

18:58

lot of experts uh in this area and I

19:01

have to say that I am now not the

19:03

cutting edge. Um uh some of my

19:05

colleagues are much better than I am. So

19:07

I'm actually summarizing some of the

19:09

research um that some of them have done

19:11

and I have done. Hopefully all of you

19:13

will have a chance to come here to Hong

19:14

Kong and and meet my colleagues and we

19:17

will also send our colleagues to come to

19:19

Indonesia and meet with you and so that

19:21

we could really have some international

19:22

exchange. Right? So I will um go through

19:25

this very quickly. Um I think all of you

19:28

already know this and so I will actually

19:29

go through this quickly. First of all um

19:32

we indeed we are using a lot of data

19:34

analytics to improve service delivery.

19:36

We're using all kinds of technologies

19:38

enhance the uh governance and also

19:40

service delivery. Governance is broadly

19:43

defined including the relationship

19:45

between citizens and the government. a

19:48

lot of citizen participation now is done

19:50

through digital means also uh in in a

19:54

large extent we are now also looking to

19:57

the infrastructure to develop uh the

19:59

digital government because we need to

20:01

have a software system with a hardware

20:03

system now I'm sure Indonesian um uh

20:07

governments local or national are all

20:10

look in the AI and with AI another

20:13

infrastructure issue is about energy

20:15

where you get going to get your energy

20:17

to run all this big data model and AI

20:19

models. Right? So infrastructure also

20:21

has become very important but

20:23

infrastructure also has to go with not

20:25

only the hardware infrastructure,

20:26

physical infrastructure but also the

20:29

social infrastructure and the

20:31

technological and also the human

20:32

capacity and so uh a government in the

20:35

digital also need to think about talents

20:37

and abilities of the government sector

20:40

and so uh very quickly uh behind all the

20:43

digital uh tools uh about data uh we

20:47

have a lot of data but let me first of

20:49

all define what big data means because

20:51

it is very controversial. Now of course

20:53

big data some for some people it really

20:55

means a lot of data the volume is very

20:57

important but also it talk a little bit

21:00

about the complexity of data meaning

21:02

that we now getting all kinds of data

21:04

not only in terms of text form but also

21:06

we be getting video form uh files etc

21:10

and so it's a very complex file uh

21:13

complex format structure and also

21:15

unstructured data and how we harness the

21:17

uh the the information together is very

21:19

important also we are talking about

21:23

the volatility volatility means actually

21:26

key question now we are struggling in

21:28

government uh is how long you will keep

21:31

your and save your data buuse we have

21:34

the uh legal responsibility

21:36

accountability government sometimes have

21:38

to show some record to be accountable to

21:41

the legislature and to citizens right so

21:43

do you store your data in six months 2

21:47

years 5 years 10 years right storing

21:51

data actually become a very big

21:52

questions but then sometimes we have big

21:54

data every minute every second is

21:56

happening sometimes the data after 5

21:58

minutes is waste is no use but do you

22:01

still need to store the data so big data

22:03

have this kind of uh volatility issues

22:06

also we have variability issues in

22:08

meaning that sometimes the data actually

22:11

could fluctuate a lot there's nothing

22:13

nothing but the in social media if

22:15

there's a explosion of some social

22:18

events or some controversy sudden you

22:20

get a

22:22

social media data then you need to deal

22:24

with it right so emergency response etc

22:27

so this kind of variability of data

22:30

really trigger what analytical tools you

22:32

need to think about so since you are

22:34

talking about public administration

22:36

education so sometimes the traditional

22:39

methods that we are learning uh

22:42

regression etc actually don't deal with

22:44

the big data methods anymore so we need

22:46

new new new learn and use some new data

22:49

tools to do it and Also another issue is

22:51

about veracity

22:53

veracity means that in big data world we

22:56

have to assume that there were errors we

22:58

have to assume that there will be biases

23:00

so in the perfect world all all data are

23:03

clean and etc in the big data world you

23:05

have no time sometimes to clean all the

23:06

data etc so if there are if there errors

23:10

what do you do with that and so there

23:11

are some kind of issues about that uh in

23:14

the big data world and also there are

23:15

possibilities of personalization uh in

23:18

public admission education Since we are

23:20

all talking about this uh I just had a

23:22

meeting yesterday uh with my colleagues

23:25

uh talking about AI and implication of

23:28

AI for education for university

23:29

education for primary school and

23:31

secondary school education there are now

23:34

possibilities with AI that we could

23:36

personalize what you learn so I'm sure

23:39

IAPA in the future may do it uh local

23:42

office shows in budgeting they have a

23:44

whole sequence of uh uh training

23:47

whatever modules right some of the local

23:49

official may go through that faster.

23:51

Some of them have certain question about

23:53

accounting or about auditing or about um

23:57

uh budgeting participation etc. There

24:00

are different modules and so in theory

24:02

based on the interest or based on the

24:04

competition needs you could personalize

24:06

all these through the AI tools and

24:08

platform and so uh there are great

24:11

possibility of personalizing by tracking

24:13

what people look at or what people

24:16

interest in tracking through the text.

24:18

Um and so we could actually personalize

24:20

some of the service delivery and so

24:22

that's another issue about public

24:24

service public administration education

24:26

now we really tailor our public service

24:29

vary to the individual citizen needs and

24:32

so that's a great possibility and it

24:33

will change our education model also of

24:36

course there will be vulnerability uh

24:38

because there will be attack there will

24:40

be cyb security concern etc and so uh

24:43

some of this have been talked about in

24:44

my long time ago talk about the IBM

24:46

report and so indeed We have a lot of

24:49

tools now. Um, and so I think many of

24:52

you have used some of these tools. I

24:54

just want to also say that despite uh

24:57

while you're seeing all this and we of

24:59

you use these tools, I actually also

25:01

have to go back to one issue. I don't

25:02

know whether that's true in Indonesia

25:05

but in Hong Kong also in China we still

25:08

need to think about some part of the

25:10

population will not use digital tools.

25:13

They have to see a person. they have to

25:15

see a a customer service person. So in

25:20

government here in Hong Kong as well as

25:21

in even in Chinese cities they still

25:23

have the customer service center. In

25:25

fact we just had a project with Hong

25:27

Kong police talking about how to

25:29

actually improve the service center in

25:32

different districts because there will

25:34

be some citizen who still go to that

25:36

district and so of course inside the

25:38

district office they could have digital

25:40

tools and kios etc but they will still

25:42

need a physical space. So I think we

25:44

have to think about digital tools are

25:46

everywhere you use it a lot but then how

25:48

you combine the digital tools with in

25:50

person tools are very important and also

25:52

tailor these tools for different

25:54

different demographic groups and so uh

25:56

another issue there and of course we are

25:58

in the internet uh of things in the IoT

26:01

world and there are so many gadgets so

26:03

many things that are capturing uh our

26:05

data now um so in the government uh data

26:09

reach I want to show you uh this uh

26:12

slide first of all for some of you who

26:14

are older or who are more mature I would

26:16

say I should not use the word old now

26:18

all of all of us are young in heart but

26:21

for some of us who work in the

26:22

government for longer time I don't know

26:24

what you recognize these pictures first

26:26

of box and boxes of paper right those

26:29

are public record now could you digitize

26:31

them scan for all the into turn into

26:33

text of PDF and images right there's one

26:36

big task how you keep all the records

26:38

and archive them but also some of them

26:41

the data are in actual

26:43

tape files in some of the government

26:45

agents, they may still have this old

26:46

data in old tape files. What do you do

26:48

with all this old old data? Right? Of

26:50

course, we have internet information, we

26:53

have social media content, we have

26:54

communication data. I'm sure in your

26:57

police force you have a lot of digital

26:59

tools uh now and so in the Hong Kong

27:02

also in many cities I know there are all

27:04

kinds of cameras in front and in behind

27:06

and all the communication tools. All the

27:09

policemen now have camera and they are

27:11

all kinds of uh digital tools to capture

27:14

on the roads now sensors on the road to

27:17

capture transportation data and

27:18

transportation uh congestion issues CCTV

27:22

uh mobile phones uh smart meter etc so

27:25

all these will give us a lot of data and

27:28

so basically data analytics tools are

27:31

there and so for public admission

27:33

education now we in the data rich world

27:35

how we should harness all this data to

27:37

do planning

27:38

to do customer service to do citizen

27:41

communication to do resource allocation

27:43

budgeting to do logistic management

27:45

personnel management procurement

27:48

performance evaluation in in

27:50

governmental in the departmental

27:52

collaboration um all these will actually

27:54

impact how we change and we think public

27:57

administration education so i don't know

28:00

uh in your curriculum now uh I'm sure

28:03

you have strategic planning I'm sure you

28:05

have customer service I'm sure you have

28:07

personnel management Right? All these

28:09

are traditional causes but since you're

28:12

talk about public administration

28:13

education in the digital era to watch

28:16

then when you talk about all these

28:17

topics do you have your professors have

28:20

your colleagues think about how digital

28:22

tools are included into all these topics

28:24

right give you one example personnel

28:27

management so we are talking about that

28:29

in our office here since I'm now uh the

28:32

dean of a college we have seven

28:33

departments here about 200 uh some

28:36

faculty members

28:38

about um 8000 students etc. And so we

28:41

are talking about personnel management

28:43

as as a university as college right um

28:47

now uh of course we have a lot of

28:48

paperwork so first of all uh we could uh

28:51

digitize all the paperwork and now we

28:54

have a platform to approve this approve

28:56

that etc right but in theory now in

28:59

theory uh suppose we actually could uh

29:03

use uh digital tools to track a a a

29:07

staff career development and see what

29:10

companies they are looking at whether

29:12

they are performing good in certain

29:14

areas etc and then do some staff

29:16

development etc and also theoretically

29:20

now we could use AI to do some of the

29:22

work so in personal management suddenly

29:24

we have uh some issues about to extent

29:27

we could actually eliminate some of the

29:29

human management of uh paperwork and use

29:32

AI to replace the human then some of

29:35

stuff should uh to should do some other

29:37

work and also In America I know for sure

29:40

that in theory they could actually have

29:42

a office screen and they could actually

29:44

look at what you are doing every minute

29:46

and so you could indeed track whether

29:47

that staff is actually doing work uh

29:50

effectively or they are actually just

29:52

open up the computer and then walk away

29:54

right so to ex you're using these tools

29:57

and should you use some of these tools

29:59

very interesting uh proposition there

30:01

and so um so again uh I just want to a

30:04

case study um and I think uh professor

30:07

Oscar professor Muk have seen this uh

30:09

when they were in Hong Kong. In China

30:12

now a lot of uh cities have what they

30:15

call one two three f system. So what

30:18

that means is we talk about customer

30:20

service right. So in Hong Kong or in

30:23

many cities they used to actually say

30:25

okay if you have a problem about seer

30:27

system you call one number if something

30:29

about garbage problem you call the

30:30

garbage department you something about

30:32

traffic you call the traffic

30:34

transportation department right

30:36

different numbers different email

30:37

different website for different people

30:39

in China now they have what they call

30:41

one two f used to be just a phone number

30:45

so you call one two th 4 f by phone and

30:48

they will answer any questions any

30:50

problems no departmental differentiation

30:53

then they will handle it behind the

30:54

scene one stop shopping right now they

30:57

have evolved into they have phone they

30:59

have airforce in person customer service

31:02

desk in a building or in some district

31:04

offices they also have a a web portal

31:07

that means they have a online website

31:09

they now have a mobile phone app and so

31:12

everything now is captured through all

31:14

this means and so they will track all

31:17

this where they have problems what time

31:20

they have issues and they have this

31:21

dashboard behind the scene in the 12345

31:24

uh uh digital center and track where

31:28

those issues are minute by minute and

31:30

also in different areas of the city so

31:33

that they know how to handle these

31:34

issues. They have now involved in such a

31:37

way that they are now talking about how

31:39

to do predictive analytics. meaning that

31:42

they know for sure in certain time

31:44

period at certain time in certain season

31:47

in certain areas these issues may pop up

31:50

so now they actually will prevent these

31:53

things of happening by intervene early

31:55

to try to solve this problem so that

31:57

citizen don't need to complain they are

31:59

doing predictive analytics to really

32:01

address the citizen concern and they now

32:04

have gone into some other issues and

32:06

this is where since you talk about

32:07

public administration education in a

32:10

traditional public administration we are

32:12

government focus right we are training

32:15

local officials to look at what we do in

32:17

the departments in government uh

32:20

boundary within government boundary but

32:22

now in China also in some other cities

32:24

in the US also they are now building

32:26

what you call interdepartmental

32:28

intersectoral collaboration meaning that

32:31

even though things are not happening

32:32

within the government is happening in

32:34

society happening in businesses they

32:37

will harness all the data and solve the

32:39

problems together So now in one two th 4

32:41

f system it's not just government

32:44

service they have now working they are

32:45

now working with business and investment

32:48

companies etc to look at how they to

32:51

address business problems so that they

32:53

could make the city more business

32:55

friendly when a business want to apply

32:57

for licenses or certain services or etc

33:00

they now are using one two th 4 f system

33:02

to address the pinpoints they are also

33:05

working with NGO non-profit

33:06

organizations societal and neighbored

33:09

organizations

33:10

to look at some of the issues they are

33:12

also scanning through social media to

33:14

look at what citizen talk about so these

33:17

are the social media like you know we ch

33:19

you know know all this platform now they

33:22

are not opered by the government agency

33:24

but they actually scan through the

33:25

social media to look at what c talk

33:27

about and then they will actually adjust

33:28

those issues proactively don't wait for

33:31

c to call the hotline so now they're

33:33

even doing that so i'm what I'm telling

33:35

is that means the government

33:37

administration education Now is going

33:39

beyond what you are dealing with in your

33:42

government office. They're looking to

33:43

society. Now we are looking to what they

33:46

call societal governance issues. It's

33:49

society wide governance. public

33:51

administration is now broaden into this

33:53

social governance issues and so it's

33:56

very interesting and and so again if you

33:58

look at uh some of the within government

34:00

world I have done this report some time

34:02

ago I think it's still valid is how you

34:04

harness different data and you need to

34:07

you do need to think about um as organ

34:09

again we talk about all kinds of data

34:10

mobile data in uh administrate data

34:13

survey data you have survey data still

34:15

maybe uh uh sensor data etc but I think

34:18

it's very important also to look into

34:20

how you harness all the data together

34:23

and also how you think about the policy

34:25

and laws and ethical boundaries. We'll

34:27

come back to that a little bit. Um so

34:30

and then you after you have done some uh

34:32

some of this and then you actually think

34:33

about how to use explorated data how you

34:35

actually do a data visualization have

34:38

some internal decision making to talk

34:40

about the data insight and then change

34:42

the decision making and then actually go

34:45

back and improve your service and then

34:46

you evaluate the results outputs and

34:49

outcomes and then you actually feedback

34:51

and look at the impact on society and on

34:53

businesses and then you go back and

34:54

collect more data right so you see this

34:56

complete information complete cycle of

34:58

information and I would say if you look

35:01

at this graph this diagram when you

35:03

think about what it means about public

35:05

administration education in the digital

35:07

era this tells you what we're doing I'll

35:10

give you an example since uh uh

35:12

professorari you asked about you

35:14

mentioned I want to improve the

35:16

competency uh several years ago when I

35:18

was a department head and now I'm the

35:20

dean so uh I don't look at the

35:23

departmental level uh work directly

35:25

anymore however when I was department I

35:28

forced or I beged my colleagues to say

35:32

um now you look at my diagram I did

35:34

research and so I look at my own

35:35

students in public administration these

35:37

are undergraduate and also master

35:38

assistance and said look data analytics

35:41

are very important so I asked a question

35:44

are they learning data analytics are

35:46

they learning Python

35:48

now was before p AI come up and now

35:51

people say you don't need to learn

35:52

programming anymore because of AI but I

35:54

think learning some basic Python is

35:55

still very important because then you

35:57

could at some AI troops right so at that

35:59

time I look at my public administration

36:00

students undergraduate student I say

36:02

have are they learning Python of course

36:04

these are you know social science and

36:06

humanity students right so say oh we

36:08

don't learn Python I said no no no so at

36:10

that time I I force and I beg my

36:13

colleague say let's change the

36:14

curriculum now in my public

36:16

administration department now we

36:18

actually change the curriculum we have

36:20

two choices of languages they have to do

36:24

have to pick uh

36:27

what call choice meaning that first you

36:30

have to learn a computer language

36:32

meaning python or they have to pick it

36:35

or if you say oh no I really hate

36:37

statistics I really don't want to learn

36:39

out or Python that's okay then we

36:41

basically required to learn a foreign

36:43

language now unfortunately we haven't

36:46

asked them to uh offer Indonesian yet

36:49

but we have we are offering French and

36:51

Italian etc so with that I think in the

36:53

publicion era I think we look so we are

36:56

actually asking our students to look

36:58

into all this um and so um and so we are

37:01

actually practicing things because we

37:03

actually expect our students to be more

37:05

data litera data literate and so they

37:08

have to have some data uh programming

37:10

background so we are forcing them to do

37:12

this and so uh I'm skip some of this um

37:15

uh um and so I would just like to say

37:18

that in the propion world uh this is

37:20

happening uh there are a lot of data

37:22

center etc now Um by the way facial

37:26

recognition is also another new tools

37:28

that a lot of us are using now in all

37:31

the cities 10 15 years ago people

37:33

complain about it about privacy concern

37:35

etc.

37:36

Now it's everywhere and now if you come

37:39

to Hong Kong airport

37:41

you don't even need to use your passport

37:43

anything facial recognition you pass the

37:45

gate right you go to a office building

37:48

facial rec you go through now in my

37:50

university I actually don't even need to

37:53

have ID card we have a gate to come in

37:55

the university campus and there's facial

37:57

recognition and they look at my face and

37:59

then they let me come into the office so

38:01

we are using all these tools now now

38:03

that means there are also data behind

38:05

right facial recogn all digital data. So

38:07

of course there's a drone uh is also uh

38:10

being used now. We are using a lot of

38:12

surveillance also collecting data from

38:14

the air. I just want to tell you that

38:15

this is nothing new. When I was in the

38:17

US uh 10 years ago they were actually

38:20

talking about using drone fly up there

38:22

to look at the border and so look at

38:24

drug trafficking. So in Mexico etc using

38:27

US technology to make basic monitor how

38:30

the drug uh uh they they go to one spot

38:33

do some harms and kill some people etc.

38:35

And then they run away right so if they

38:37

have a drone sitting in the air for 2

38:39

hours looking down the street looking

38:41

down in the city they could always

38:43

monitor that city uh 24 hours. Right?

38:46

And so so drone technology has been used

38:48

for surveillance etc like this very a

38:50

lot of

38:53

case study etc etc about

38:55

drone usage now and they are now using

38:58

it more and more in Hong Kong now we are

39:00

now using drones to actually look at a

39:02

forest fire risk and also put out fire

39:05

so because there are some forest uh

39:07

issues there and so we are now using

39:09

drones to do that and so um um of course

39:13

uh not coming down to that uh very

39:15

quickly I administrative data,

39:16

nonvermental data, survey data, social

39:18

media, etc. We are all putting all this

39:20

together. I think this is actually

39:22

something that is actually maybe

39:24

relevant to you. This study was done uh

39:27

more than 10 years ago in the US. I did

39:29

this study. However, I actually have to

39:32

say that this issue is still there.

39:34

Okay. I I don't know about Indonesian

39:36

local government. A lot of the

39:38

digitalization issues is about first off

39:40

we have outdated IT system. So there's a

39:43

lot of concern about that. Also there's

39:45

insufficient training. Okay. I don't

39:48

know whether that you face the same

39:49

issue also that we don't have enough

39:52

high quality programmers officials and

39:55

though they are lot of concern about

39:56

data quality. Yes, we have lot data but

39:58

the in paper form or some of the data

39:59

have errors and not clean out data

40:02

issues right and also there's not enough

40:04

support from the department and so these

40:07

are all some of the concerns and I'm

40:10

sure uh uh this is very common in many

40:13

governments local governments even

40:14

national government agencies and so what

40:17

I would say is that the implications

40:18

quickly let me just wrap up is we need

40:21

to think about uh of course we need to

40:23

embrace we need to have more engagement

40:25

with practitioners especially companies

40:27

and see how we go with companies

40:28

together and uh professor Oscar I know

40:31

you have a company doing this already so

40:33

you are now the cutting edge we need to

40:35

learn from your example but also we need

40:37

to think about procurement and counting

40:39

health a lot of the service now could

40:41

not be done within government that means

40:43

a lot of this have to be done through

40:45

procurement service so government

40:47

actually means a lot is about contract

40:48

procurement so that that means so that

40:51

means in the public administration

40:55

education

40:56

Do you have a lot of at least have one

40:58

class on procurement when we did our

41:01

study a lot of public administration

41:05

curriculum actually have no class on

41:07

procurement

41:09

so that's there's a limit there not not

41:11

much not many people talk about

41:12

procurement and and and conturing out

41:14

and so um be think about data management

41:17

uh and uh I do want to say uh a little

41:21

bit about so this uh we already talk

41:23

about competency and governance issue. I

41:26

just want to uh I will skip all this. Um

41:28

I'm sure you know there are all kind of

41:30

ways to visualize the data. I'll skip

41:32

all this but I think this is actually a

41:34

maybe a final point I want to uh make

41:36

given the time.

41:39

I think the major data governance issues

41:42

uh could be summarized in this table.

41:44

Okay. This a two by two matrix. Number

41:47

one is what can be done given the

41:49

technology and your capacity. Okay. Now

41:51

I actually emphasize not only technology

41:54

but also giving you staffing and

41:56

resource capacity right what can be done

41:58

because there are all kinds of AI tools.

42:00

There are all kinds of e-government

42:02

tools right but what are your limits

42:04

right and you need to know your limit

42:06

and what your budget etc. And then you

42:08

look at uh what cannot be done yet given

42:12

your limit right so you need to think

42:13

about these two but then you look at the

42:15

left hand side what should be done is a

42:18

is a um is ethical also policy and legal

42:22

issue what should be done given a

42:25

community's social legal political and

42:27

cultural context and then what should

42:29

not be done I would say this is a key

42:33

issue summarizing data governance issue

42:35

facing different local government or

42:36

different different countries

42:38

In some government, in some culture, in

42:40

some governance system, you could do a

42:42

lot of things with data but if you go to

42:44

another country, go to another legal

42:46

context even though they have data you

42:48

cannot use that because of the legal

42:50

constraint for example in Hong Kong now

42:52

we have a lot of privacy constraint and

42:54

so even within between departments some

42:57

of the department data are not shared in

42:59

Hong Kong now because of some legal

43:01

boundaries so that they cannot share the

43:03

data yet and so we cannot do what

43:06

Beijing or Shanghai are doing because of

43:09

our existing legal limits. Now we're

43:11

trying to break down some of the sidles

43:12

now passing through new legislation etc.

43:15

But this table really showcase some of

43:18

the governance issues and I think uh for

43:20

Indonesia I think uh it will be good for

43:22

you all to talk about your current

43:24

situation and also think about what you

43:26

want to do in the future but there are

43:28

also cultural context and so uh do you

43:30

have all these issues and also there are

43:32

some deeper issues about data governance

43:35

who should own the data now with AI this

43:37

data ownership issue become bigger when

43:40

you upload everything to chat GBT and G

43:43

uh Gemini You basically surrender all

43:46

your data to uh Open AI and also to uh

43:48

Google.

43:50

Are you willing to do that? So in Hong

43:53

Kong government now a lot of times the

43:55

agencies themselves keep all the data

43:56

and they just load the programming the

43:59

AI tools into the agency without

44:01

surrender data up. So there are a lot of

44:03

data governance issues also the roles of

44:05

private industry and propnership also to

44:08

what extent you should regulate or

44:10

should let the government uh uh the

44:11

market to do it and uh who should pay is

44:14

a very important issues. I think uh for

44:17

public administration education to wrap

44:19

up if you think about some of the

44:21

digital eras the financing and budgeting

44:24

issues are very important how you should

44:26

finance the digital infrastructure

44:28

become a very important topic I have

44:31

prepared a lot more slides but I think

44:32

um um uh some of the value questions

44:35

also there are all of issues about

44:37

digital participation and there are all

44:39

kinds of ways uh that we could leverage

44:42

that but because of time I I probably

44:43

should stop here and I will

44:46

be happy to come back and look at some

44:48

of these issues also there some risk

44:49

analysis of risk issues and so maybe

44:52

I'll just stop here. Thank you so much.

44:57

Thank you, Professor H. I know that time

45:00

is very limited right

45:03

but you know Bapak Ibu bisa undang Prof.

45:06

Ho ya kalau untuk further apa eh

45:09

discussion atau kuliah umum nanti eh ke

45:13

depannya. So, what a outstanding

45:17

presentation. So, eh apa yang bisa kita

45:21

apa eh kita dapatkan tadi pada

45:25

presentasi eh Prof adalah ada beberapa

45:28

key

45:31

transformation itu adalah pergeseran

45:34

dari birokrasi kaku ke digital era

45:38

governance yang lebih responsif dan

45:40

kolaboratif. Dan ada juga eh big data

45:43

ekosistem bagaimana kita memanfaatkan 5V

45:46

volume, velocity, variety, verity and

45:50

value. Bukan sekedar sebagai tumpukan

45:53

data, melainkan alat pengambilan

45:55

keputusan berbasis bukti atau evident

45:58

base. Nah, ada juga eh Prof. Ho

46:00

menyebutkan smart application. Jadi,

46:03

bagaimana penggunaan analitik data untuk

46:05

layanan publik yang proaktif dan

46:07

prediktif mulai dari manajemen darurat

46:10

hingga deteksi ee untuk korupsi. Dan ada

46:14

key

46:16

learn yang dipelajari adalah teknologi

46:19

hanyalah alat keberhasilan utama

46:22

bergantung pada restruksi

46:24

ee

46:26

restrukturisasi

46:27

organisasi dan keamanan data. Nah,

46:30

bagaimana future education kita menurut

46:32

Prof. adalah pendidikan administrasi

46:34

publik harus mencetak pemimpin yang data

46:37

save atau m-kata jadi dengan fokus kuat

46:41

pada integrasi teknologi dan etika ya

46:45

semua sudah mengalami di sini bagaimana

46:48

kita ee harus ee ee melag

46:52

terutama dalam pengelolaan di dalam

46:55

perguruan tinggi. Jadi bagaimana untuk

46:58

eh saving waktu dan eh saving data dan

47:03

lain sebagainya. Oke, thank you very

47:05

much for your presentation.

47:08

Hold eh moment. Jadi, tahan

47:11

pertanyaannya ya, Bapak, Ibu. Karena

47:12

kita akan ada sesi eh Q&A di terakhir ee

47:17

pada saat ee pembicara terakhir nanti

47:21

Prof. ee Prof.

47:25

Jadi kita eh sekarang akan let's move to

47:29

our next perspective to deep our

47:32

understanding of how this strategies are

47:35

implemented. Eh we will welcome Prof.

47:38

Dr. Drs. Andi Wijaya, MDA, PhD. Beliau

47:44

adalah Prof. Andi PEPA is the advisory

47:48

boards of IAPA and also the dean of

47:50

faculty administration science

47:53

Universitas Brawijaya Malang for period

47:55

of eh 2021 until 25.

48:01

Eh Profepta

48:04

also

48:06

eh one of my em lecture before. Senang

48:11

bertemu kembali Prof. Eh dan juga

48:16

eh saya akan bacakan

48:18

dari Prof. eh Andi FTA. Jadi eh Prof.

48:22

Andi Feptawijaya is professor at

48:25

Universitas Brawijaya who previously

48:27

served as the dean of the faculty of

48:30

administrative science for the 2021

48:34

until 25. He is a faculty member in the

48:38

department of public administration and

48:40

teaches in the masters and doctoral

48:43

program in administrative science. So he

48:47

completed his undergrade studies at

48:50

Universitas Brawijaya, earn his masters

48:53

degree from Australian National

48:56

University and obtain his PhD from

48:59

Flinders University and special

49:03

specialisting in public management. In

49:07

addition to teaching, Professor Andi is

49:09

actively engaged in research, community

49:12

service and

49:14

publications and is widely recognized

49:17

for his academic oration on a public

49:21

policy model based on collaborative

49:23

governance plus multielix.

49:27

Jadi demikian adalah video dari eh Prof.

49:31

Andi eh jadi untuk mempersingkat waktu

49:34

eh the screen is thank you.

49:37

Oke, thank you Ibu Dia Hutari as

49:40

moderator. Eh, please let me to share my

49:43

screen.

50:09

Iya.

50:11

Eh, anybody can see Bu moderator? Bu

50:15

Dia, can you see my screen?

50:19

Yes. Yes, Prof. Clearly.

50:22

Oke. Oke. Thank you. Eh, I will please

50:26

let me start my presentation. Eh, thank

50:29

you very much eh kepada Prof. Eh, Mulu,

50:34

Prof. Koirul Mulu as the head of eh

50:36

Ayapa and also thejen eh Mas Oscar PhD.

50:42

I would like to thanks to the IAPA to

50:45

invite me as a eh pemateri ya to give eh

50:49

to present about eh my title I pick up

50:53

as architecting the digital state

50:56

framework for reimagining public

50:59

administration education. And I first of

51:02

all I would like to say hello to the all

51:06

people who are already join in this in

51:09

this eh seminar or conference ya. And eh

51:15

to those eh kehendak eh

51:19

fasting ya eh saya mendoakan supaya ee

51:23

fastingnya barokah dan bisa berjalan

51:25

dengan lancar. eh dan juga untuk eh

51:29

seluruh member of I would like to thanks

51:33

and say hello to all of them and then

51:35

also my student I invite here to join

51:39

with this program including

51:41

undergraduate student and postgraduate

51:43

student in Malang also in Jakarta and

51:47

also some international student eh who

51:50

join with us today. I invite some

51:53

doctoral student eh who eh come from eh

51:59

some country ya the I eh now as a

52:02

promotor of their dissertation and I

52:06

invite them to have experience in this

52:08

very good event and I also to thanks to

52:10

the others eh

52:14

eh pemateri eh ke speakers ya Prof.

52:20

Alfred Ho and also eh Prof. eh

52:27

satu lagi Pak anu ya dari

52:30

Mbak Rino.

52:31

Pak Rino ya Pak Rino ya. Baik

52:33

dari UNS.

52:35

Dari UNS baru aja kemarin kita visit to

52:38

UNS. Nah ini fotonya waktu dewan pakar

52:41

ya. And I would like to thanks to EI ya

52:46

AI artificial intelligency because I

52:49

create many picture

52:52

eh using AI ya to give a presentation

52:57

today ya. This is just eh the picture is

53:01

imagination ya because eh meeting of our

53:04

dewan pakar expert eh council in Ipa eh

53:09

dihadiri oleh Donald Trump dan Putin.

53:12

Nah ini creation of eh AI ya eh yang

53:16

mana kita bisa mengcreate dalam

53:19

education kita, dalam presentation kita

53:21

atau dalam materi-materi kita dengan

53:24

menggunakan AI. So I would like to

53:26

thanks to AI also who as a machine ya to

53:28

help me to create eh many eh pictures

53:32

ya. Eh oke I would like to start my

53:35

agenda. We have six point here.

53:39

Empirical condition and problem, core

53:41

digital competencies, literature review

53:45

and theoretical framework.

53:47

The three pillars of reimagine public

53:50

administration education and policy

53:52

recommendation digital ready public

53:55

administration education and core

53:57

strategic pillars. Let me jump in the

54:01

first point ya about eh the current

54:05

situation. This is eh the problem

54:08

statement

54:10

eh eh we have the disconnect ya between

54:13

traditional Liberian bureaucratic

54:15

training and the demand of digital era

54:18

governance atau DEG and eh as we know

54:23

that eh Weberan birocracy as the old

54:27

public administration era still eh

54:30

dominate ya in term of eh conceptual in

54:35

and conceptually conceptually and

54:37

practically in running eh eh Indonesian

54:42

public management we are now try to move

54:45

to the new public management and

54:48

governance eh but eh the percentage eh

54:51

of the success is really depend on the

54:54

what happen in the field I guess that

54:57

practically we still up eh apa tuh buon

55:02

50% ya we still in the in thean

55:07

birocracy even though we try to move ya

55:11

to the npm andn governance but we still

55:14

have the condition like that so the

55:17

significancy of this why eh technical

55:21

literacy is no longer an elective but a

55:25

requirement for a democratic

55:26

accountability so i saw how the trump in

55:32

the picture ya eh get Heik ya ketika

55:35

menghadapi transformation from Weberian

55:39

birocracy in USA to digital era of

55:41

governance ya. So not only Indonesia who

55:44

have

55:46

in transforming to the digital era and

55:50

then after that eh we look to the data

55:53

ya comparison table ya population versus

55:57

internet user early 2026 ya and eh in

56:02

the world ya eh we have eh 5.2 20 eh 5

56:08

eh million million eh miliard ya

56:12

billiard ya pers ya kalau Indonesia itu

56:14

miliard ya 8,25 miliar internet usernya

56:19

in the world sudah mencapai 73.2%.

56:24

Nah in compare ya the user internet

56:28

still in Europe ya 91.5%

56:32

of European eh inhabitant itu sudah

56:37

menggunakan internet gitu ya. In eh

56:41

Amerika is the second ya, America in

56:43

total ya. Ini termasuk Amerika Latin dan

56:45

lain-lain. This is 85.2%.

56:49

Indonesia it's quite amazing ya. From eh

56:53

285

56:54

eh million people 80.5%

57:00

eh use internet. So

57:05

quite big number ya in term of Indonesia

57:08

as a state ya. So eh as the key point ya

57:13

Europe and America have the highest

57:15

penetration meaning most of their

57:17

population is already online. Ya.

57:21

Indonesia performance Indonesia is stand

57:23

out by having a higher penetration. Ya,

57:26

Rate tadi eh 80.5%

57:29

compared to overall Asian average Asian

57:32

average only 91.7%

57:35

so the digital divide Africa reminds the

57:39

region with the most significant offline

57:41

population representing

57:44

opportunity for future infrastructure

57:46

growth. Ya. So Afrika still left behind

57:50

eh to compare to the other regions and

57:54

eh UN golf development index ya XG this

57:58

is the indicators ya to show eh how far

58:03

eh the commit to the internet eh

58:07

development ya. So eh we can compare

58:11

this is the top three global seat ASEAN

58:14

in Indonesia. So global seat the top

58:17

three is Denmark, Estonia and Singapore.

58:21

The countries are the gold standard ya

58:24

they have achiev near to totalization of

58:28

public services. Singapura hold a dual

58:32

title as about the top three global seat

58:35

and the first rank in ASEAN serving as a

58:38

regional benchmark. So if you want to do

58:42

benchmarking ya I think eh better we see

58:45

ketika kita ingin mengadakan benchmark

58:47

ya. Tiga negara ini sebagai top seat

58:50

saat ini di bidang ini yaitu Denmark,

58:53

Estonia dan tetangga kita Singapura ya.

58:55

Indonesia milestone ya. Indonesia made a

58:58

significant jump ya lompatan yang

59:01

signifikan. kita lempat jump of certain

59:04

rank ya 13 ranking eh from dari 77

59:08

ranking in 2022 ke 64 rank in 2024. Nah,

59:15

Indonesia eh masuk dalam high club ya

59:18

for the first time Indonesia score cross

59:22

the 0.75

59:25

ya moving from the high category into

59:27

the very high category. Nah, in Asian

59:31

dynamic Indonesia is no firmly position

59:33

in the top four of ASEAN out performing

59:37

the Philippine and Vietnam. Eh, the gap

59:39

but the gap between Indonesia in

59:41

Malaysia and Thailand is narrowing but

59:43

eh Singapore already far away eh on the

59:46

top of usia and Indonesia score 0.7991

59:51

7991.6382

59:57

ya.

59:59

Nah, eh key performance indicators ya

60:02

some related to the to the this eh rel

60:06

to the e performance ya human capital

60:09

index and telecommunication

60:11

infrastructure

60:12

in electronic participation globally we

60:15

ranking certified globally and human

60:19

capital index also eh reminds a

60:22

challenge ya this masih tantangan untuk

60:24

Indonesia to compare to Europe eh

60:27

teknologi already exist but digital

60:29

literacy among general public and civil

60:31

se is still catching up. So kita eh

60:35

literasi digital eh di antara eh publik

60:40

secara umum dan ASN kita itu masih coba

60:43

untuk mengejar ya ketertinggalan dalam

60:46

ee digital literasi ini eh PR dalam atau

60:51

home homework ya untuk human capital

60:53

kita atau sumber daya manusia kita

60:55

terutama yang di ASN juga. Kemudian

60:58

telecommunication infrastructure

61:00

Indonesia score is rushing du to karena

61:03

kita mengaplikasikan sekarang sudah

61:05

menginstal ya the palaping or 5G

61:09

expansion eh meskipun ya walaupun still

61:13

lag ya masih lag behind ya masih di

61:18

tertinggal dari highly defense fiber

61:20

network of Europe and East Asia gitu

61:23

kan. Nah, eh problem of public

61:26

administration education in in digital

61:29

era. Jadi melihat situasi data dan fakta

61:33

yang sudah saya sampaikan tadi. Apa

61:35

problem eh public administration

61:38

education eh in digital era. Nah,

61:41

digitalization bring highly complex

61:44

challeng to public administration

61:45

education. The core issue is no longer

61:48

just how to use a computer but how to

61:51

sive a rigid bureaucratic mindset into a

61:55

adaptive one. So we move to rigid

61:57

bureaucratic mindset to an adaptive one.

62:00

So the first one about legging eh

62:03

legging curriculum ya kurikulum yang

62:05

terbelakang legging. Many public

62:07

administration study program still focus

62:09

on classical theories yaan the emphasis

62:13

hierarchy and formal procedure problem

62:16

curricula often lead incorporating

62:19

strategic material such as data analytic

62:22

artificial intelligency in public policy

62:25

and cyber security

62:27

nah ini ilustrasi karikatur ini juga

62:30

saya coba menggunakan artifill intellig

62:34

ya saya juga langsung mengaplikasikan

62:36

Dan ini sekarang ee alhamdulillah ee ada

62:39

sedikit apa ya kompetensi improvement

62:42

untuk saya dan beberapa teman yang ee

62:46

involve di sini ee sehingga kompetensi

62:49

kita memang harus terus ditingkatkan

62:51

untuk hal-hal yang seperti ini. So,

62:53

impact graduate understand ya how to run

62:56

a birocracy but struggle ya when

62:59

managing a dynamic digital ecosystem.

63:01

Jadi tidak hanya perlu hanya bagaimana

63:04

merunning sebuah birokrasi, tetapi yang

63:06

paling penting adalah kita me-manage a

63:09

dynamic digital ecosystem ya, ekonomik

63:12

ekosistem digital yang dynamic gitu loh.

63:15

Nah, ini bagaimana e capacity ini yang

63:17

perlu kita tingkatkan ke mahasiswa kita.

63:20

Eh, the second adalah eh problem digital

63:24

literacy gap. I'll illustr illustrated

63:27

in the previous discussion. Ya,

63:29

technologi often arrive faster than the

63:32

human capacity humanity. Jadi selalu

63:35

teknologi itu datangnya lebih cepat dari

63:38

kapasitas ee sumber daya manusia

63:40

sehingga kita harus kacap terus menguber

63:43

atau atau harus terus berusaha ya

63:46

menguasai teknologi itu. Nah, problem

63:49

education frequently focus on producing

63:51

operator. Jadi pendidikan itu

63:53

seringkiali fokusnya pada memproduksi

63:56

operator technical skill. Whereas eh the

64:00

actual need is for digital architecture

64:03

atau the digital architect where the

64:05

strategic ability to design integrated

64:08

public service systems. Ya, jadi civil

64:12

for example in civil se atau di ASN isu

64:16

ya aparatur civil negara kita many

64:18

senior officials still really on manual

64:22

analog methods yaven when digital system

64:25

are available creating a double

64:28

inefficiency ya processing boot manually

64:31

and digitally nah ini juga inefisiency

64:34

karena secara manual kita juga harus

64:36

menyediakannya secara digital kita

64:39

memprovidingnya karena bahkan ASN yang

64:41

di dalam pemerintahan kita juga masih ee

64:45

alergi dengan ee digital literasi karena

64:47

masih mereka tergantung pada manual

64:50

analog gitu ya. Nah, ini yang ketiga ya.

64:54

Problem yang ketiga adalah

64:55

interoperability

64:57

issues and silo mentality gitu ya. Nah,

65:01

in nah ini alhamdulillah ini ee apa

65:06

memberikan

65:07

ilustrasi gambar seperti ini di mana

65:10

kementerian itu ee bekerja

65:13

sendiri-sendiri sifatnya silo. Ee tapi

65:16

memang saya memberikan prom prom ya

65:19

kepada AI. Nah, ini teman-teman juga

65:21

harus ahli dalam prom ya kalau

65:23

menggunakan AI tergantung promnya gambar

65:26

yang ditampilkan oleh AI. Nah, problem

65:28

education of jadi in public

65:31

administration also everyd department

65:34

tend to create its own independent

65:36

application. Nah, bukan hanya di

65:38

kementerian, di masing-masing fakultas

65:41

di universitas seringkiali masing-masing

65:44

eh faculty of departement itu create its

65:46

own independent application. Nah, di

65:49

kementerian juga refleksinya seperti itu

65:51

ya. Education often fail to emphasize

65:54

the importance of interoperability.

66:01

nya

66:05

menjadi terpisah silo bisa dijalankan

66:08

hanya untuk kepentingan unit itu sendiri

66:11

where cen must

66:13

of different account for different

66:16

services. Jadi dengan banyaknya servis

66:19

layanan yang diberikan mereka harus ee

66:22

masuk kepada different account yang

66:24

berbeda-beda yang disediakan oleh

66:26

masing-masing kementerian atau

66:28

masing-masing unit ya. Whereas they

66:30

ideally only need one digital identity,

66:34

single sign on. Nah, ini kita sedang eh

66:37

menuju ke sana, kita sudah sudahed

66:39

meng-create di beberapa hal eh apa sigle

66:43

sign on ya ee walaupun dengan beberapa

66:46

kendala.

66:47

Kemudian for digital ethic and data

66:49

privacy digitalization involve the

66:52

massive collection of citizen data

66:55

problem education often overlook the

66:58

aspect of data ethic and privacy

67:00

protection

67:02

impact the increases eh the risk of data

67:05

lag eh or

67:08

algo eh algorithmic eh bias which can

67:12

discriminate against certain social

67:14

group during the distribution of social

67:17

aid or other eh public eh services. Nah,

67:22

five eh cultural resistancy to to change

67:25

ya. Eh public administration is

67:29

historically designed to be stable and

67:32

slow to ensure eh digitalization demands

67:37

agility.

67:39

Eh, jadi eh historically public

67:42

administration itu didesain yang stable

67:45

atau slow untuk to ensure caution ya,

67:49

kehati-hatian dalam arti konteks bahwa

67:52

kita memerlukan agility tuntutan dalam

67:54

era digitalisasi. Nah, desain pendidikan

67:57

kita masih mengarah kepada hal yang

67:59

stable ya. public administration

68:02

education has not fully success in

68:04

teaching agile agile governance impact

68:08

birocrat feel threaten by the

68:11

transparency

68:12

broke by digitalization because their

68:15

power previously derived from

68:17

information exclusivity is now open to

68:20

the public. Jadi eh bisa jadi birokrat

68:24

itu eh protect terhadap dirinya sendiri

68:27

dan tidak support the digitalization ya

68:31

karena eh information exclusivity yang

68:34

mereka ingin keep ya ingin eh jaga. Nah,

68:38

jadi conclusion the greatest problem

68:40

lies eh on not in the availability of

68:43

tools but in human capital. Ya, tidak

68:46

hanya saja kepada ketersediaan alat atau

68:50

aplikasi ya, tetapi juga pada kapital,

68:52

human capitalnya ya. Nah, bagaimana eh

68:56

SDM kita? Public administration

68:58

education must transform from simply

69:01

teaching state governance into becoming

69:03

an innovative innovation laboratory that

69:07

prioritize efficiency data security and

69:10

easy of access for all levels of

69:14

society. And then the next eh point

69:17

adalah the core the core digital

69:20

competency that modern public

69:21

administration student sold master.

69:24

The first is the important one is data

69:27

literasiy and analytic ya. Administrator

69:30

no longer just manage people. They

69:32

manage information. Evident based

69:35

policy. Nah, ini juga sangat diperlukan

69:37

ya. the ability to use a big data to

69:40

identify trends, predict social needs,

69:43

and evaluate policy outcome. And the

69:46

third basic statistic and visualization

69:49

proviency in tool like tablue, Power BI

69:53

or even advance Excel to turn compact

69:56

data into understandable narrative for

69:59

for the public and stakeholders and eh

70:02

laboratorium in my class ya including eh

70:07

S1, S2, S3. kami juga menerapkan ee

70:11

penggunaan AI ini dalam bantuan

70:14

menggunakan case study base ya untuk

70:16

masing-masing eh subjek yang ada di yang

70:19

kebetulan yang saya asuh gitu ya.

70:21

Kemudian digital strategy and agile

70:24

governance. Digitalization is not about

70:27

eh

70:29

digitizing a paper atau

70:33

digitzation ya but redesigning the

70:37

process ya. digital transformation.

70:40

So understanding how manage project in

70:43

interactive cycle rather than the slow

70:45

traditional waterfall bureaucratic

70:47

method. So kita perlu me-manage project

70:50

in iterative cycle dan ini juga bisa

70:53

menjadi case base daripada student kita.

70:56

Kemudian intro. Nah intro. Nah, ini juga

70:59

saya membawa eh master class, we have

71:02

master class double degree linkage

71:04

dengan Jepang yang dulu saya inisiasi

71:07

mulai 200627

71:09

ya. Ini Mas Oscar, Our Sekjen ini dulu

71:13

adalah ee apa istilahnya sekretaris saya

71:17

ya untuk merunning ini dan sampai

71:19

sekarang ee join degree kelas ini masih

71:22

eksis ya dan kita menggunakan ee

71:25

beberapa project sampai sekarang. Nah,

71:27

ini juga saya menginvite ya student

71:31

double degree to Japan. Nanti mereka

71:34

akan berangkat ke Jepang 1 tahun dan

71:36

juga ada yang ke Australia kelas double

71:39

degree Australia dan saya juga invite

71:41

mereka untuk join di sini. And all of

71:45

them adalah ASN yang eh apa e yang

71:50

cemerlang ya karena bisa tembus dalam

71:54

kelas ini yang scholarship from the

71:56

government.

71:57

and then interoperability awareness ya

72:00

understanding how to design system that

72:03

talk each other across different

72:04

government against affect data silus ya

72:09

any any com sorry

72:12

and third ya human center design ya eh

72:16

this is modern public service is

72:19

measured by user experience

72:22

service design learning how to map a

72:24

cizen journal journey Ya. How a citizen

72:27

apply for a birth certificate and

72:29

simplifying it reduce a friction. So

72:33

inclusivity no exclusivity ya ensuring

72:35

digital platform are accessible to

72:38

eldery people with disability and in

72:41

remote area with low bandwid.

72:43

for digital ethic and cyber eh security

72:47

ya as a cadian of citizen data and

72:51

administrative primary in protection

72:54

two thing in digital ethic that

72:56

important ya data privacy and also cyber

73:00

hig ya data privacy is knowledge of the

73:02

legal and ethical framework for handling

73:05

personal information

73:07

cyber higin understanding the basic of

73:09

network security and the risk of social

73:12

engineering to prevent data bridge in

73:15

government offices. And then the fifth

73:18

ya AI literacy and algo rhthmic

73:23

accountability

73:24

eh AI oversight ya understanding how AI

73:28

can be used eh for like traffic

73:30

management or social ad distribution

73:33

while being aware algorithmic bias

73:36

preventing the AI from being unfair to

73:40

certain group. Nah, ini kita juga harus

73:42

cek eh

73:44

algorithmic bias yang mungkin terjadi ya

73:47

sehingga AI itu kemungkinan juga menjadi

73:49

unfair to certain group. Nah, ini kita

73:52

juga harus eh harus eh evaluate and

73:55

monitor ya bagaimana AI bekerja. Walau

73:59

bagaimanapun AI adalah mesin gitu ya.

74:02

seperti saya mengcreate beberapa picture

74:04

ini beberapa kali kadang tidak sesuai

74:06

dengan prom yang saya inginkan sehingga

74:08

kita harus merubah prom lagi gitu ya

74:11

karena memang ini adalah mesin gitu.

74:13

Nah, from engineering the ability to use

74:16

generative AI tool to draft report

74:20

summariz regulation or research policy

74:22

alternative efficient and literature

74:26

review and theoretical framework related

74:28

to this I think I just mention it ya

74:30

transitioning from new public management

74:34

efficiency or market based to digital

74:35

era governance reintegration and

74:38

holistic

74:39

digitization

74:41

digitization ya, references dan LAVI at

74:45

all. Kemudian sociotechnical lens ini

74:48

juga eh theoretical framework yang

74:51

usually use kalau kita menulis tentang

74:53

hal ini. Understanding that technology

74:56

in govern government is embeded in

74:58

social and political power structure.

75:00

Ya. Kemudian competency gap analying

75:04

current scholarship on why public sector

75:07

field at IT procurement and digital

75:10

transformation.

75:13

Nah, kita jump to the next point ya.

75:16

Three pillars of reimagine public

75:18

administration education. The first one,

75:21

the first pillar is data stewardship and

75:24

algorithmic

75:25

ethic. The second pillar is agile

75:28

methodology and public design. And the

75:31

third pillar is network leadership. Ya.

75:34

So, the first pilar ya kita moving using

75:37

tools to governing tools ya. Jadi kalau

75:40

sebelumnya itu hanya menggunakan alat,

75:43

sekarang kita harus governing alat,

75:45

mengelola alat itu untuk eh PA education

75:48

kita. Focus on data privacy, bias in AI

75:53

and ethical automation.

75:56

Kemudian the second adalah agile

75:58

methodology teaching human center design

76:01

for public services shifting from rigid

76:04

5 years plan to iterative prototyping.

76:07

Nah, ini yang kedua metodologinya agile

76:10

ya yang kita improve. Kemudian the third

76:14

adalah network network leadership ya

76:16

managing platform government and coction

76:20

with citizens. Nah, itu saya

76:22

ilustrasikan di dalam gedung putih ya.

76:26

Saya mengimajinasikan saya sedang

76:27

mengajarkan network leadership di depan

76:30

Donald Trump, Putin, dan beberapa

76:33

pemimpin dunia ya, jin eh shipping dari

76:36

Cina dan lain-lain. Nah, ini ya guyonan

76:39

aja ya. Jangan dibuat serius ya karena

76:41

ini apa? creativity ya dari penulis ya

76:45

untuk membuat prom yang seperti ini

76:47

untuk apa supaya enggak apa enggak bosan

76:51

presentasinya.

76:52

Nah, policy recommendation digital ready

76:55

for administration education first

76:58

radical curriculum redesign from

77:00

bureaucratic to agile ya mandatory AI

77:03

and data sence integrated data analytic

77:06

for public for policy and AI in a

77:09

government as a core subject. Nah, kita

77:11

harus membawa ini menjadi core subject

77:13

daripada public administration specially

77:16

data analytic for policy. Nah, karena

77:18

saya mengajar juga public policy

77:21

analisis baik S2 di kedokteran untuk

77:24

para calon ee kepala rumah sakit gitu ya

77:28

dan juga di S2 kita gitu ya. Nah, ini

77:31

kita coba menggunakan data analytic for

77:34

policy untuk dan AI in education ya,

77:39

egile governance ya. shift teaching

77:41

model from traditional hierarchy

77:43

birocracy to agile methodology. Nah, ini

77:45

juga yang perlu di-improve. Kemudian

77:47

yang kedua, interdisciplinary synergy

77:50

dismantling academic silo. Yang kemung

77:53

nanti kalau misalkan di education di ee

77:58

pendidikan dia sudah silo, apalagi nanti

78:00

kalau dia sudah bekerja. Kemungkinan

78:02

juga akan silo ini budaya silo ini akan

78:05

dibawa ketika dia pindah ke kementerian

78:07

misalkan. So we need cross faculty

78:10

integration establish degree program

78:13

between faculty for example public

78:16

administration and computer science to

78:19

create digital technocrat ya governance

78:22

innovation lab kita juga punya

78:24

governance lab yang Prof mulu sebagai

78:27

head-nya dan mengembangkan eh yang

78:30

terutama adalah yang penting simulation

78:32

center where student work on

78:34

interdepartemental data sharing project

78:37

preparing them to brie

78:39

Prevalent inan ministries ya. Nah,

78:43

kemudian ketiga, priority prioritizing

78:46

eh digital ethic and data sovereignity.

78:49

Legal and ethical literacy ini penting

78:51

ya. Explicitly teach the implication of

78:54

personal data protection law ya.

78:57

Graduate must be the guardians of

79:00

citizen privacy not just user of

79:02

technology and algorithmic

79:05

accountability in corrupted model on

79:08

identifying and mitigating bias in

79:10

automated system to ensure digital

79:13

public service remain fair and

79:15

inclusive. Karena kalau tidak digital

79:18

public service itu bisa juga eksklusif

79:21

atau unfair kalau desainnya tidak kita

79:25

pelototi gitu ya. Makanya algorithmic eh

79:29

accountability-nya juga harus kita lihat

79:31

gitu ya. Nah, faculty upscaling and eh

79:35

faculty upskilling and practitioner

79:37

integration

79:39

digital residency for academic ya

79:41

implement mandatory training. Jadi

79:43

program memang training ini diperlukan

79:45

to improve a senior faculty member to

79:48

keep pace in the 2026 digital landscape.

79:52

Ya. and then clinical professor from

79:54

teach from tax sector recruit chief

79:58

technology officer and digital

80:00

transformation expert from the private

80:02

sector to serve as visiting lecturers

80:05

bridging the gap between theory and

80:07

industry realities. Nah, ini juga

80:09

kesempatan visiting profesor kalau bisa

80:12

kita ee ahli ee di bidang ee IT ya untuk

80:18

mungkin ke ee civitas akademi kita kita

80:21

untuk bisa diupskilling ya. Kemudian

80:25

project based learning and digital

80:27

ecosystem immersion GAFtech prototype ya

80:30

replace traditional tesis ya ataupun

80:33

dissertation with project based cupstone

80:37

where student develop digital solution

80:39

for real world issue such as blockchains

80:42

based land administration or AI driven

80:46

su social assistant distribution and

80:49

strategic internship. Jadi kita eh tesis

80:52

atau disertasi diarahkan juga kepada

80:55

kepada yang sifatnya digitalization and

80:58

strategic internship. Kita bermitra

81:00

dengan unicorn and digital first

81:02

government agency like Jabar Jabawa

81:05

Barat ya digital services or GFTCH

81:07

education to immer student in high

81:10

performance digital work cultures

81:13

and K take away ya the go the the goal

81:16

is to move by an electronic government

81:18

towards smart governance next generation

81:21

of civil servant view technology as a

81:23

fundamental strategicet rather than only

81:26

an optional tool So eh the summary ya eh

81:32

we know eh rapid acceleration of global

81:35

digital and we still have a gap ya and

81:40

eh we need a road map transition

81:42

Indonesia public administra education

81:45

from a procedural paper based focus to

81:48

an agile data driven and ethical

81:50

framework. So the final ya core

81:54

strategic pillar I recommend three thing

81:57

ya criculum modernization theile shift

82:00

ya the foundation of public

82:01

administration education must move

82:04

classical management action integrate

82:07

data analytic ai governance and cyber

82:10

security as nonnegotiable competency

82:14

goal to produce graduate who can lead

82:16

smart governance initiative rather than

82:19

managing a government tool

82:21

Second, interdisciplinary integration.

82:24

Digital governance is a

82:26

multidisciplinary challenge that cannot

82:29

be solved with a single faculty. Action

82:32

launch a joint degree program and

82:34

governance innovation laboratorium in

82:37

collaboration with information

82:38

technology department. goal to break

82:41

down the institutional silos by training

82:44

future birocrat to work across technical

82:47

and administrative boundaries and the

82:49

third ya ethical stewardship and data

82:52

privacy as digital service scale the

82:55

risk of the risk to citizen privacy

82:58

increases action formalize the study of

83:01

digital ethic and the personal data

83:03

protection law goal to ensure digital

83:06

transformation does not come at the cost

83:09

of public trust or human right bridge a

83:12

theory practice gap ya the ledging

83:14

nature of current education steam from

83:18

like exposure to modern work culture so

83:22

action implement project based learning

83:24

where student build functional gftech

83:27

prototype and in internship with high

83:32

growth firms and modern government

83:35

digital agency goal to foster a mindset

83:46

public administration education is not a

83:49

technical upgrade it is a culturally

83:52

necessity by adapting this

83:54

recommendation Indonesia can cultivate

83:56

new generation of digital fluent civil

84:00

servant capable of delivering high

84:02

quality transparent and agile public

84:05

services particularly in critical

84:16

national audit exting

84:18

m program doctoral program in public

84:21

administration curriculum and second

84:24

pilot the governance label in the top

84:27

tire national university and third

84:29

establish a certification standard for

84:33

digital policy professional nah in my

84:36

case I already develop eh individual

84:39

certification

84:41

eh to my student ya yang dapat pas

84:44

terutama theoretical understanding about

84:47

eh eh material yang saya ajar ya. Nah,

84:51

itu saya sudah menyusun ya eh

84:53

sertifikasi tapi ini yang di-publish

84:55

individually gitu ya. Dan semua

84:58

mahasiswa saya biasanya saya tes itu

85:00

kalau mau ee sukses ya dalam ee subjek

85:04

yang dia tempuh. Nah, ini dari saya.

85:06

Terima kasih. Thank you eh for all dan

85:10

saya return back to the moderator ya.

85:13

Terima kasih. Wasalamualaikum

85:14

warahmatullahi wabarakatuh.

85:16

Waalaikumsalam warahmatullahi

85:17

wabarakatuh. Terima kasih banyak Prof.

85:20

AndiA. Luar biasa ya. Thank you very

85:22

much Prof. Andta for that insight

85:25

presentation.

85:27

I'm particularly struck by your picture

85:32

AI picture where the advisory board of

85:35

IA

85:37

was that with

85:39

President Trump and Putin

85:42

that was wonderful idea.

85:47

Oke

85:47

luar biasa

85:50

luar biasa

85:50

dikunjungi Trump sama Donald Trump acara

85:53

Yapa.

85:54

Iapa memang hebat ya, Prof ya.

85:58

Ah, jadi ee kita juga harus hati-hati

86:02

terhadap apa foto-foto kita yang beredar

86:05

di luar juga karena AI ada dua mata

86:07

pisau. Bisa untuk ee positif ataupun

86:11

negatif. Jadi, core message atau pesan

86:14

utama yang kita dapat tadi adalah

86:16

pendidikan

86:18

adminasi

86:20

publik harus menjadi jembatan antara

86:23

publik dan teknologi. Jadi, masa depan

86:26

administrasi publik adalah tentang

86:27

bagaimana membangun negara sebagai

86:30

platform, government as a platform.

86:34

Baik, terima kasih banyak Prof. V sekali

86:36

lagi dan sekarang kita akan ee tiba di

86:41

sesi berikutnya di final speaker speaker

86:44

ketiga. Now we have our final speaker to

86:48

complete this academic journey. Before I

86:51

hand over the screen, allow me to read a

86:53

brief

86:55

biography of our distinguished guest,

86:59

Bapak Rino Ardian Nugroho, Estos MTI,

87:03

PhD. ini ahli masternya TI. Bapak, Ibu

87:08

semuanya, adik-adik mahasiswa. Jadi, Pak

87:11

Rino adalah rekan kita di IAPA juga baru

87:14

saja menyelenggarakan ee apa event di

87:18

UNS di Solo. Senang bertemu kembali Pak

87:22

Rino online. Jadi ee saya akan bacakan

87:27

ee

87:28

video singkat dari Pak Rino ya. Jadi eh

87:33

Bapak Rino Adrian Ardian Nugroho SOS MTI

87:38

PhD is a lecture in the public

87:41

administration study program at the

87:43

faculty of social and political science

87:46

Universitas 11 Maret UNS Indonesia Solo.

87:51

He

87:52

he holds a bachelor degree in public

87:55

administration and then a master of

87:58

information technology or MTI and a PhD

88:04

in electronic government. His expertise

88:08

lies at the intersection of public

88:11

administration and information systems

88:14

particularly in electronic government

88:17

and innovation adoption in the public

88:20

sector. In addition to his academic and

88:23

research activities reflected in various

88:26

scholarly publications and research

88:29

contributions, he currently served as FI

88:33

dein for student Affairs and alumni at

88:36

Visip UNS and as coordinator for of the

88:41

innovation and government research

88:44

group. Jadi juga adalah chairperson of

88:49

the IAPA regional board atau DPD for

88:52

Central Java. Jadi eh untuk

88:56

mempersingkat waktu, the screen is

88:59

yours, Pak. Silakan

89:02

ya. Terima kasih, Bu Diah. Eh, saya coba

89:05

share screen dulu ya.

89:08

Eh, apakah bisa dilihat?

89:12

Yes, sampun, Pak. Ya.

89:15

Em, pertama-tama asalamualaikum

89:18

warahmatullahi wabarakatuh. Selamat pagi

89:20

Bapak Ibu semua yang terhormat Pak

89:22

Muluk, Mas Oscar, Prof. Andta, dan Prof.

89:27

H yang pada hari ini sudah bersama-sama

89:31

menyampaikan materi dan saya jadi

89:32

bingung Prof. In mau menyampaikan apa

89:33

lagi karena semua sudah ya.

89:36

So in this occasion I will complete all

89:39

of the discussion that has been by

89:42

previous speakers

89:45

as well as Prof and I would like to add

89:48

some of the dimension

89:50

towards the the newest

89:53

to reimagining the curriculum for the

89:55

public administration educations toward

89:59

towards the digital era especially I

90:01

would like to emphasize on the what what

90:04

research have been conduct so far. So

90:06

currently I'm still doing on

90:09

understanding about the AI attitude in

90:12

terms of the public policy making. So

90:15

that might be something that I would

90:17

like to emphasize to eh I would like to

90:21

give an insight on how actually the

90:23

curriculum will need to be adjusted for

90:26

for

90:28

the AI era. So let me begin with the big

90:31

pictures. So public administration is

90:34

not experience is not experiencing the

90:36

incremental changes. It's undergoing a

90:38

structural transformation across four

90:41

waves. So there are four waves that we

90:43

would like to I would like to discuss in

90:45

my sessions. So the first one about the

90:48

digital transformation the second one

90:50

about the collaborative governance the

90:53

third about the government as a platform

90:55

as has been mentioned by professor

90:57

AndiFTA and lastly about the AI era. So

91:02

they are the fourth the four wave of the

91:05

public administration digital era that

91:07

we need to eh cop with and how does it

91:11

relates with what the traditional

91:12

bureaucracy that we have been taught so

91:14

far in the class that something that I

91:17

would like to explain in the in the last

91:20

section of my presentation.

91:22

So this is the one if we would like to

91:25

understand about in my way of thinking

91:27

we have come to the four way for digital

91:30

governance. So, so the first one will be

91:32

the digital transformation.

91:37

Usually the digital transformation talk

91:40

about

91:42

how to transform from the manual process

91:44

to the digital process. And the second

91:47

one is about the collaborative

91:48

governance.

91:50

The second wave is about the

91:51

collaborative governance.

91:54

So in the second wave in the

91:56

collaborative governance here government

91:59

is not only the central of all of the

92:01

processes using the intervention

92:03

technology but eh we also invite all of

92:08

the stakeholders to be collaborate in

92:11

some extent and the third one is

92:14

government as a platform so it

92:18

strengthen again in this area.

92:19

government platform mostly discuss about

92:23

how we put the government in the center

92:25

of all of the process during

92:29

some activities in activities that is

92:31

related to the public needs and the last

92:34

one if

92:36

the wave four is about the AI augmented

92:39

state. So this is the fourth wave of

92:42

state evolution in terms of the digital

92:44

era in my opinion. So in here digital

92:48

government sometimes is of misunderstood

92:50

as digitization but not. Jadi digital eh

92:55

digital government itu tidak tentang

92:57

hanya tentang digitalisasi tapi juga

92:59

tidak hanya tentang tchnikal tapi juga

93:01

tentang bagaimana meredesain organisasi

93:04

meredesain administrative. So not only

93:06

about the technical conversion but also

93:09

about the administrative redesign.

93:12

So the data driven decision making the

93:14

citizen centric service architecture

93:17

transparency

93:18

it's not only about the technology

93:21

let say about the big data professor

93:25

already told us about how the big data

93:26

will transform the public policy and so

93:28

and so for it's not only about the data

93:30

itself it's not about the infrastructure

93:33

of the data but then how the data is

93:36

restored and so on and so forth if we

93:38

talk about the SPBE or the pemerintah

93:40

digital government on the Indonesian

93:43

version of rankings of electronic

93:46

government

93:48

they always talk about the data but

93:51

before becoming the data there's a

93:53

process call the business process that

93:55

should be with some procedures.

93:58

So that's why eh if we talk about the

94:02

the eh the data it's not only the data

94:06

but also the process beside it the

94:09

social infrastructure

94:12

before the technical infrastructure.

94:16

Eh however

94:18

the current curriculum still prioritize

94:20

the organizational charts and legal

94:22

compliance structures of our digital

94:24

system. So not deeply understand about

94:27

how does the data should be stored let's

94:31

say and how the data should be used for

94:33

the public policy and so and so forth.

94:37

So that's why the gap between the

94:38

administrative reality and

94:40

administrative education is wiing so

94:43

far.

94:44

Now if we would like to emphasize here

94:48

so our education system mostly still use

94:50

the wave one logic that is the digital

94:52

transformation whereas the government

94:55

now already entering the wave. So kalau

94:58

kalau kita bertanya tentang beberapa

95:00

pemerintah daerah apa yang mereka

95:01

inginkan? Sebagian besar ingin smart

95:03

city dan bagian smart city apa yang

95:05

mereka inginkan? Biasanya mereka ingin

95:06

bicara AI. Padahal di kelas masih

95:09

diajarkan tentang digital transformasi

95:11

belum sampai ke AI-nya. Jadi dalam sisi

95:15

kurikulum masih ada lag di sana, masih

95:18

ada jarak yang cukup jauh gitu. So they

95:21

are still lacking on differentiating

95:24

between what the education system teach

95:26

and what the government needs

95:31

to be if we would like to look further

95:33

about the wave let's say about the

95:36

digital governance first usually they

95:38

talk about some characteristic the

95:41

characteristic can be about the data

95:44

driven

95:46

and about the citizen centric about the

95:48

transparency and about the optimized

95:50

process usually it talks about how the

95:53

decision by real time data how the data

95:58

was collected and then presented in in a

96:03

timely manner so that it fulfill all of

96:05

the five all of the five fees that has

96:07

been professor who mentioned before. how

96:10

the data is collected how data is stored

96:13

and how data is retrieved in in a timely

96:16

manner that it really needs by the

96:17

government to to be communicate with the

96:21

public.

96:22

Secondly about citizen centric that's

96:24

about the how services design around

96:27

people so how the services are design to

96:31

with what people needs and so for and

96:36

transparent meaning that government

96:39

tries to be transparent and then can be

96:42

seen by anyone and so for

96:46

eh last one is about optimized how the

96:49

government

96:51

structure to be streamline the process

96:53

to be narrow and then it usually it

96:57

become faster than before.

97:00

So that's why in this era government has

97:04

tried to become networks. So the state

97:06

is not a longer prior meet and it needs

97:08

a network orchestration behind it.

97:12

And the

97:15

main criteria of this wave is about

97:17

shifting from the paper based hierarchy

97:19

into the integrated digital ecosystem.

97:22

Students must understand system not just

97:24

rules. Why eh if we would like to

97:28

emphasize our students understanding

97:30

about the digital governance with one of

97:33

the eh

97:35

digital needs in public administrations

97:38

is trying to push the student to

97:41

understand the systems not just rules

97:43

how the system works and so on so

97:46

wave two talks about the collaborative

97:48

governance so this eh in this era the

97:52

states become become in a govern

97:55

government net governance networks

97:58

eh in this a wave the public value is

98:01

increasingly coproduce so not only by

98:04

the government but also the private

98:06

actors the civil society and the digital

98:08

communities government has government

98:11

governance has become network the state

98:14

is no longer a pyramid it is a node of

98:16

an ecosystem and then this requires new

98:18

competencies network or cross sector

98:22

negotiation stakeholder alignment and

98:24

government

98:25

under complexity

98:28

and here what can we learn from this

98:31

second wave is about that how we we

98:35

should put government as a governance as

98:38

a networks not only government itself

98:43

so the traditional public administration

98:47

here has trains about capabilities on

98:51

network orchestration how can di

98:55

eh discuss each other bagaimana kita

98:57

menjalin orkestrasi jaringan, bagaimana

99:00

kita melakukan cross sektor negosiasi,

99:03

bagaimana kita menyatukan stakeholder

99:05

gitu. Jadi ini menjadi salah satu PR

99:07

juga di era e digital ini bahwa

99:10

kolaboratif eh collaborative governance

99:12

atau kurikulum tentang eh public

99:15

administration harus didorong mengarah

99:17

ke bagaimana

99:20

coproduksi itu dilakukan antara public

99:22

dan private civil society dan digital

99:24

communities.

99:26

Wve the is about government as a

99:28

platform. As has been mentioned by Prof.

99:30

And previously, eh government now works

99:35

as a platform not only as a server but

99:38

as a platform. So meaning by by meaning

99:42

as a platform all of the stakeholders

99:45

can access the government.

99:49

So government only provide datas only

99:52

provide processes but not all of the

99:56

services. Some of the services can be

100:00

born to civil society or can be given to

100:05

the eh the private sectors but the data

100:09

should be kept by government.

100:11

So in this wave government as a platform

100:14

requires students to understand about

100:17

the how the infrastructure what are the

100:19

infrastructure need eh how

100:23

can here government act as the

100:26

infrastructure provider let's say about

100:29

sikd misalnya sistem kependudukan

100:32

digital itu adalah contoh government a

100:34

platform jadi pemerintah menyediakan

100:38

database-nya dan itu diakses semua orang

100:40

baik swasta, pemerintah dan sebagainya

100:43

untuk kemudian ee bisa menggunakan data

100:47

yang sama. Nah, dengan cara itu maka apa

100:50

yang disebut dengan keformment platform

100:52

sudah tercapai. Ee beberapa contoh lain

100:55

juga ada yang dilakukan di Indonesia,

100:57

tapi itu adalah contoh yang paling

100:58

mudah. Kemudian eh AP EPI regulator. Di

101:00

situ pemerintah berfungsi sebagai

101:03

meregulasi EPA apa saja yang bisa

101:05

dihubungkan dan apa saja yang bisa

101:07

diambil. Ee as well as become the data

101:10

orkestrator data menjadi satu. Itu yang

101:12

dilakukan Indonesia sekarang dengan

101:13

melakukan satu data Indonesia gitu ya.

101:17

Ee semua data dimasukkan ke satu data

101:19

Indonesia. Ee dan ekosistem enabler

101:23

bagaimana terhubung satu sama lain dari

101:25

atas ke bawah. yang dilakukan pemerintah

101:27

dengan ee SPBE atau sistem pemerintahan

101:30

berbasis elektronik yang didesain untuk

101:33

seimbang. Dan terakhir adalah

101:34

transgenter. Di sini pemerintah

101:36

berfungsi untuk meyakinkan misalnya

101:39

apakah korteks ini memang aman loh gitu.

101:41

Jadi mengingatkan pada ee semua pihak

101:44

bahwa ee korteks itu aman misalnya itu

101:46

adalah bentuk dari upaya pemerintah

101:48

sebagai platform untuk meyakinkan. So

101:51

that's why the wave 3 can be can be

101:54

concluded as government as a platform

101:57

where here government needs to be the

102:00

infrastructure provider regulator and

102:02

until the tas quarantor

102:05

here the education must therefore move

102:07

beyond teaching administrative

102:08

management it must teach governance

102:10

architecture design so in eh in a sense

102:14

that the curriculum for the public

102:16

administration should be a with this

102:18

kind of platform how the platform and

102:21

how students can move from the

102:24

traditional thinking of administrative

102:26

management into how think about platform

102:31

and what technical issues will follow

102:34

those platform and the last one if we

102:37

for the last wave of the digital a

102:40

public administration is the AI

102:41

augmented state.

102:45

So now we enter the AI era artificial

102:48

intelligence is no longer experimental

102:49

in government context.

102:52

It can do the policy drafting. It can do

102:55

the regulatory simulation. It can do the

102:58

predict the governance and also do the

103:01

citizen interaction through some of the

103:03

let's say eh automatic answering. Let's

103:08

say if you have a WhatsApp and then kita

103:10

pengin nanya dananya ke Telkomsel

103:12

otomatis itu AI sebetulnya. untuk

103:15

citizen interaction and also detection

103:18

so AI able to do to do such and such and

103:21

such eh me myself I'm trying to do the

103:24

policy drafting using the AI and it can

103:27

happens even they can do the regulatory

103:30

analysis using the AI as well it can

103:32

happens as well. So this transform the

103:35

state into an algorithmically augmented

103:37

system. So the government

103:41

not only about the data not only about

103:45

the documents by having the AI now

103:48

government should switch into the

103:51

algorithm how to switch into algorithm

103:55

so that's why here the state becomes an

103:57

algorithmic argument proton s so

103:59

education must integrate AI governance

104:01

capacity

104:04

eh are we educating public

104:06

administration can supervis Get and

104:08

govern AI systems or are we educating

104:11

administrator for a preaucracy?

104:13

So so far we still thinking about

104:15

preaucracy not the bureaucracy after AI.

104:19

This would be very different.

104:22

Misalnya kualitas pelayanan yang tadinya

104:24

dijawab secara manual sekarang sudah

104:26

menggunakan bot, sudah menggunakan

104:28

chatbot gitu. Jadi pelayanan bisa 24/7

104:32

gitu ya. 24 jam 7 hari tidak perlu lagi

104:34

ada jam tutup gitu.

104:37

Nah, ee kemudian itu yang perlu

104:39

dipikirkan bagaimana di era AI augmented

104:41

ini, di era AI ini kemudian kita

104:43

mengembangkan pendidikan yang ee

104:47

menempatkan AI sebagai tools, bukan

104:50

sebagai ee apa namanya? Bukan sebagai

104:53

rajanya. Jadi, AI di sini harus sebagai

104:55

tools untuk

104:57

eh from engineering. So, this is there

105:00

is about AI. Sometimes AI will have

105:03

something good and mostly bad but we

105:07

don't really understand that is bad. So

105:12

eh the key points on managing AI as our

105:17

tools is about how we prompt the AI.

105:20

Jadi bagaimana kita melakukan prompt

105:21

engineering dalam AI itu.

105:25

This is where prom engineering becomes

105:26

strategically important. Jadi even

105:29

sekarang ada mesin untuk

105:31

meng-engineering prom gitu ada juga.

105:33

Jadi ada eh supaya kita masuk ke AI

105:36

dengan perintah yang benar itu ada pro

105:39

mesine gitu loh sebelum masuk ke AI.

105:42

Jadi engineering is not merch scripting.

105:44

It's structured proy framing. It is

105:46

algorithm steering. It is cognitive

105:48

governance and a prom determines what

105:52

the AI analyze, how it interprets data,

105:54

what scenal it generates and so and so

105:56

forth.

105:58

The problem with AI adalah eh terkadang

106:01

ini hasil eh analisis sebelumnya bahwa

106:04

sometimes AI is a lazy machine. Jadi

106:09

kadang AI itu malas sehingga

106:13

dia ingin membuat kita berpikir seperti

106:15

apa yang dia pikirkan. Maka kalau

106:18

misalnya kita pakai generative AI, kita

106:20

pakai eh prompting, maka dia akan kasih

106:23

opsi 1 2 3 karena dia ingin membuat kita

106:26

mengikuti apa maunya dia.

106:29

Nah, oleh karena itu kita perlu

106:30

berhati-hati tentang hal itu dan perlu

106:32

berpikir critical thinking kita tetap

106:34

harus ada supaya eh prom engineering

106:38

yang kita kembangkan itu menjadi hal

106:40

baru menjadi ee tidak tergantung dari

106:43

kemampuan AI-nya. kitalah yang harus

106:45

mengendalikan AI, bukan AI yang

106:47

mengendalikan kita. So, that's eh the

106:50

prom engineering will be the key the key

106:53

changer for the future policy analysis.

106:57

So how we can we can put all of the

107:00

condition into the prom and how we put

107:02

all of the emotional

107:05

eh emotional condition of the people

107:09

where we do the policy analysis into

107:11

prom is something that would be the game

107:13

changer for the future.

107:16

So in a sense of that that's why we we

107:21

need to put the engineering skills into

107:23

the education into the curriculum of the

107:26

public administration. So in the future

107:29

eh our graduates can comply with all of

107:32

the necessary requirement all the needs

107:35

by the market

107:37

about the use of AI in doing the policy

107:40

analysis and all of the works related to

107:42

the government.

107:45

So now that's why here prompting becomes

107:48

the administrative literacy. How about

107:50

the do the policy framing? How to do the

107:52

algorithm steering? How to mitigating

107:56

the bias and also the accountability

107:58

interface that becoming

108:02

important in the future of public

108:04

administration curriculum.

108:07

And that's why I propose the five

108:11

pilots for the next generation public

108:13

administration education starting from

108:16

the digital governance literacy and then

108:19

the platform architectural design and

108:22

ecosystem orchestration here for the

108:25

platform. So how can we orchestrate all

108:28

the stakeholders with government using

108:31

the technology and also number four is

108:34

about AI governance and ethics. So not

108:37

only about how to do the prompting, how

108:39

to do the technical development of the

108:41

big data analysis but also how we can we

108:45

maintain the ethical eh concern about

108:48

the policy that has been generated by

108:51

the AI because sometimes AI will be very

108:55

mean and very cruel in terms of giving

108:58

eh very cruel and dry in terms of giving

109:02

the policy

109:05

formulation.

109:07

and also the engineering for policy. So

109:10

this five pillar competency model is

109:12

important in my opinion is important for

109:15

the next public administration

109:16

curriculum.

109:18

By having the digital governance

109:19

literacy

109:21

students can understand

109:23

what actually digital governance that is

109:25

not only digitalization but also talking

109:29

about the improving the processes inside

109:32

the government and second how the

109:35

platform architecture design so student

109:38

understand

109:40

how actually relating putting government

109:43

as the center all of the communication

109:46

between the stakeholders

109:50

and how students can orchestrate

109:54

between the stakeholders between the

109:56

ecosystem

109:58

and also learning about AI also

110:01

important so that's why they they need

110:03

to understand about the governance

110:05

ethics and using it and also how to do

110:08

the prom engineering so that the public

110:10

policy analysis can be done in a in fast

110:15

and as well as the good quality

110:19

eh without them probably eh the

110:21

administrative education remains

110:23

structurally outdated

110:26

so this is the curriculum design

110:28

blueprint

110:30

so that's why the curriculum conceptual

110:32

reform must translate into curriculum

110:34

reform at the foundational level here in

110:37

the foundational level eh need to

110:40

understand about the digital era

110:41

governance and then the platform state

110:43

theory about the government eh

110:46

government platform and the algorithmic

110:48

government philosophi not the

110:50

algorithmic technical algorithmic one

110:52

but only the philosophy one so this will

110:55

be the foundation of understanding the

110:58

eh public administration in the govern

111:01

and the digital governance era and then

111:04

we talk about the core talk about the

111:06

government as a platform and then talk

111:08

about the data in governance and talk

111:11

about the AI in public administration so

111:13

this three is the core eh in the middle

111:16

of the pyramid and the last one if we

111:18

talk about the master's degree eh upward

111:22

we talk about the prom engineering and

111:24

we talk about the algorithmic

111:26

accountability and we talk about the AI

111:27

policy simulation studio. It might be eh

111:33

curriculum redesign blueprint for the

111:36

AI era here learning becomes

111:39

experimental not theoretical so we put

111:41

emphasize more on the labs eh rather

111:44

than in classical class.

111:47

So that's why in in the next

111:51

slide I would like to propose the from

111:54

lecture hall to governance lab. So the

111:56

old model will be and the

112:00

pedagogi should be transformed from the

112:03

old model to the new model where the

112:05

static lectures policy essays and

112:07

historical case analysis should be

112:09

transformed to the AI simulated policy

112:11

labs governance and box and prom audit

112:14

workshops also live data dashboard so

112:16

that by having said that eh

112:21

students would understand clearly and eh

112:24

more reason about the implementation of

112:28

eh digital governance. So that's why

112:31

education must mirror the AI driven

112:33

state. So starting from now of course

112:35

it's not like flipping the coins but it

112:38

needs times to do so that all of the

112:42

requirements that there with the public

112:44

the digital era can be achieved by the

112:46

public administration.

112:49

That's why

112:52

if we still talking about the

112:54

traditional public administration mode

112:56

of teaching so why this is something

112:59

that we need to understand more the

113:02

traditional birocracy actually is not

113:04

really comply with the AI era gitu. Jadi

113:08

ee birokrasi tradisional enggak terlalu

113:10

cocok dengan EA era ini karena ada

113:12

beberapa hal. Yang pertama rigid

113:13

hierarchy and then slow decision cycles,

113:16

fragmented data systems. Tadi seperti

113:18

sampaikan Prof. Andi ada silo gitu ya,

113:20

banyak silo. Dan kemudian institutal

113:23

resistance toomation eh regulatory

113:26

reform alone can cannot solve this all

113:29

of this. Eh so education becomes the

113:32

foundational reform mechanism. Jadi ini

113:34

memang kondisi ee birokrasi sekarang

113:37

gitu yang masih hierarkinya ketat,

113:40

lambat dalam memutuskan sampai dengan

113:43

data yang terpisah-pisah dalam sao. Nah,

113:45

kalau ini diubah dengan pendidikan yang

113:47

tadi ada lima pengetahuan dasar tadi itu

113:49

akan mengubah cara berpikir birokrat ke

113:52

depan sehingga birokrasi ke depan akan

113:53

lebih kompuhan teknologi. Jadi akan

113:57

lebih kompl smart city dan segala

113:59

macamnya sehingga itu lebih eh sesuai

114:02

dengan apa yang diinginkan oleh eh pasar

114:04

yang ke depan sangat driven by AI. Eh

114:08

lastly so educating educating the

114:11

platform in the in the AI state. So we

114:15

need to do the digital the digital

114:17

transformation will change our system.

114:20

Jadi adanya perangkat-perangkat digital

114:22

itu mengubah sistem birokrasi secara

114:24

umumnya. Dan kemudian

114:27

the platform government digital asset

114:29

platform to mengubah structure changing

114:31

the structure. So where before

114:34

government is everything, now government

114:36

is the the central of of all of the

114:39

things. So not everything but the

114:41

central of all of the things. Kemudian

114:44

AI change cara berpikir kita. Jadi yang

114:46

tadinya kita mengandalkan pola berpikir

114:49

sendiri, sekarang kita bisa dibantu.

114:50

Bisa lebih cepat tapi terkadang juga

114:52

menghasilkan hasil yang tidak tepat.

114:55

So AI change the way we thinking not

114:57

only it can

115:00

sometimes it can it can make our

115:02

decision faster but sometimes the

115:05

decision is not as good as if we decide

115:08

ourself.

115:09

Education must change leadership. So by

115:12

having the education correctly in terms

115:15

of upcoming the digital era especially

115:18

in the AI era we can change we have to

115:22

change how the leaders in the future

115:25

face the reality of bureaucracy.

115:28

So the future of bureaucracy depends on

115:31

how we educate today. Thank you. I think

115:33

that's for my session. digital

115:35

transformation change system platform

115:37

government change structure artificial

115:39

intelligence change cognition now we as

115:42

educators we must change leadership so

115:44

the future ofy depends on our education

115:48

today thank you bu to

115:51

thank you pakin terima kasih banyak

115:54

bapakino atas paparan

115:57

komprehensif ya masternya

116:02

jadi thank you for very

116:06

and

116:08

particularly

116:10

regarding theal

116:13

of leadership and regional collaboration

116:18

digital transformation

116:20

so to the Q&A session and there are a

116:24

lot of questions already in the chat box

116:27

I'm so sorry because our time is very

116:29

very limited so I will read the question

116:33

in the chat box eh because they were you

116:38

know writing this since eh

116:42

you know sometimes ago. So I would like

116:46

to read

116:48

eh first of all give me second.

116:56

So first question

116:58

is

117:00

eh from

117:02

Risma Niswati Universitas Negeri

117:06

Makassar. So this is from Makassar.

117:09

Eh so the question is considering the

117:13

nation that notion that raw data is an

117:17

oximoron which implies that data are

117:20

never truly neutral or context free. How

117:24

can public administration education in

117:27

the digital era integrated ethical

117:29

reasoning into data governance? Special

117:33

specifically how can we ensure that

117:36

future government policy makers not only

117:39

develop technical data literacy but also

117:43

normative sensitivity in using data for

117:48

public policy? Eh, first question I will

117:52

address to eh Prof. Ho please eh all the

117:57

speakers make it short because we have

117:59

very a lot of questions so that

118:02

everybody can ask eh so the I will give

118:06

the question to FR Ho first please from

118:09

prof ho answer the question

118:11

so very quickly um thank you so much for

118:14

the question I think you point out a

118:15

very important person a lot of people

118:17

think data is objective and which is not

118:19

true. If you look at some of the social

118:21

media data especially they are very

118:23

biased and so I think first of all in

118:25

the public administration program we

118:27

should first of all let

118:30

war want the students to to be aware of

118:33

that that's number one basic requirement

118:35

and so I think we should we should do

118:37

that and then also tell them that there

118:39

are different perspective and different

118:40

ways to frame the data and also

118:42

different ways to collect the data that

118:43

will lead to different results so they

118:45

have that understanding I think that is

118:47

very important and then what I would do

118:50

And what we have done also in different

118:51

program is to introduce case studies.

118:54

Through case studies so talk about it

118:56

and see the biases and then think about

118:58

what it would do differently. Um I think

119:01

uh that is one way or one approach we

119:04

are doing. Thank you.

119:07

It's short quick and sh. So next eh Prof

119:12

Andi Fepta please ya. Baik eh Bu Dia.

119:16

Jadi saya langsung aja untuk data ini

119:19

memang mitos netralitas data ini

119:23

juga menjadi perbincangan ya di

119:25

administrasi publik. Jadi ee kita perlu

119:29

melihat ya dalam konteks data ini eh

119:33

in term of representation

119:35

who count in this data ya. Siapa yang

119:38

kita hitung dalam data dan siapa yang

119:40

tidak. one of my eh doctoral student eh

119:45

eh talking about eh eh UMKM ya, usaha

119:49

mikro ya.

119:51

Bahkan sebenarnya mikro itu katanya bisa

119:53

didown ee didegradasi lagi menjadi lebih

119:56

kecil lagi. Karena ada juga ee pedagang

120:01

yang bermain di ee dana sekitar R juta R

120:04

juta dan itu masuk mikro. Nah, padahal

120:06

mikro itu 2 miliar ke bawah. Nah, ini

120:09

sebenarnya dia kita harus lihat

120:11

bagaimana mengklasifikasikannya. siapa

120:13

yang dihitung dalam data tersebut. ee

120:16

bagaimana mengklasikannya

120:18

apa terjadi bias algoritme. Nah, jadi

120:22

data itu juga ee apa kita perlu perlu

120:26

lihat lagi lebih teliti ya karena eh

120:29

data sometimes eh also tidak tidak

120:32

netral juga gitu loh. Nah, oleh karena

120:34

itu kita harus melihat ee apakah data

120:38

ini muncul dari adanya ee komit apa

120:43

istilahnya agreement eh tentang data

120:45

yang dikumpulkan. Jadi publik harus tahu

120:48

ya ini accountability of data present by

120:51

government the data who we choose

120:55

involved in data and what classification

120:58

and then also eh apakah ini eh sudah

121:01

menjawab eh public eh will and public

121:05

need eh related to the data that we use

121:08

ya karena kalau tidak nanti AI dan

121:11

lain-lain hanya membaca apa adanya

121:13

terhadap data yang disajikan itu. belum

121:15

tentu itu menjawab konteks real yang

121:17

ada. Nah, kita juga harus hati-hati

121:19

dalam melihat eh data tersebut ya.

121:22

Terima kasih. I think we return back to

121:24

the moderator, Budia. Thank you.

121:26

Terima kasih, Prof. Fandi Fepta. Semoga

121:29

bisa menjawab curiosity dari Mbak Risma

121:31

ya. Berikutnya eh Pak Rino please Pak

121:35

Rino

121:36

ya. Thank you

121:38

so pertanyaan ini menarik ya. So that's

121:41

why um

121:43

in the presentation I I I show you

121:47

before eh the the person the people is

121:51

still the central of everything. So

121:54

let's say AI is only tools as well as

121:57

the big data is only tools. So

122:00

everything comes the skills of the human

122:02

beings.

122:04

How can we understand whether the data

122:07

is free value or not?

122:11

That's up to us. So technically it

122:14

should be like tidak cukup hanya satu

122:17

orang. So it's not only one person that

122:19

can judging about the data. So it might

122:22

be more than one person so that it can

122:24

be put into the right decision.

122:27

Again data itu harus dilihat dari semua

122:29

orang. Jadi yang paling penting dari

122:31

proses ini adalah seperti disampaikan

122:32

Prof. Andi transparasinya. So the

122:35

important things about transparency

122:37

about the data itself. how the data is

122:41

how the data is collected what questions

122:43

that lead to the data and how the data

122:46

is storing

122:49

the data or not it should be transparent

122:52

so by having that kind of transparency

122:54

we can measure the quality of the data

122:58

jadi kita bisa mengukur kualitasnya dari

122:59

situ.

123:01

Kita enggak bisa pastikan bahwa data itu

123:03

akan sangat sulit data itu bisa value

123:05

free gitu. So very difficult data is

123:07

very very free but we can ensure some

123:11

processes so that all of the people that

123:14

access the data can understand the

123:16

process how the data is taken so that we

123:18

can understand and we can measure

123:20

whether it can be trusted or not. Again

123:24

human is the key, not the machine.

123:26

Machine is only tools.

123:29

Itu dia dari saya.

123:32

Baik.

123:34

Ee terima kasih Pak Rino. Jadi

123:37

sebetulnya

123:39

kita masih

123:41

perlu sensitif normatif ya, bagaimana

123:45

kemampu nikah di balik-balik angka-angka

123:47

statistik. Jadi luar biasa

123:50

ee tepuk tangan buat eh narasumber kita

123:53

semuanya. Big applause for the speakers.

123:57

So next question eh this is from special

124:01

one from Prof. Wahyudi Kumorotomo from

124:05

eh Universitas of Gajah Mada. So eh

124:09

specifically eh question for propho. So

124:14

first question is given the fact that

124:18

actual data collection takes time. For

124:21

example our national sensus in conducted

124:24

every 10 years how should we reconcile

124:28

with the use of AI in most developed

124:32

countries? such as Western Europe, eh

124:35

North America, East Asia. Decision

124:37

makers remain cautious about AI but

124:41

among many Indonesian decision makers,

124:43

they tend to use AI without a reserve

124:47

norit with a serious consequence that

124:50

the decisions may not really base on

124:53

actual and correct data. What was what

124:57

has been the experience in Hong Kong and

125:00

China?

125:02

Do you want me to read the second or you

125:04

can answer question? Let's talk about

125:06

this question. This is a very complex

125:08

question.

125:10

And so again because of time I will keep

125:12

it short um because I think we should

125:14

have a separate seminar in the future

125:17

about AI. Okay. Um now this question has

125:20

several layers of issues. Number one is

125:22

that uh you ask about the the data. So,

125:25

so you have some survey data that will

125:27

be conduct every 10 years only but we

125:30

just talk about big data minute by

125:33

minute type of data social media data

125:35

etc and then you talk about AI right so

125:36

they are all kinds of issues I would

125:38

like to say that first of all the

125:40

traditional form of collecting

125:42

information is still very important okay

125:44

but I also want to tell you that what is

125:46

happening now in more advanced social

125:48

sciences now in political science in

125:50

marketing business marketing now there

125:53

are now model developed through AI and

125:56

LLM large rankage model that um they

125:59

actually use a profile of people let's

126:01

say 1000 people in Hong Kong okay they

126:06

actually track them very carefully day

126:09

by day minute by minute what they do etc

126:10

or what what kind of web they browse etc

126:13

they basically build AI agent of these

126:15

people and then they actually use uh

126:18

these agents AI models to predict what

126:21

they would buy what they would see how

126:24

to perceive events. And so what I'm

126:26

saying is that there are now new

126:28

technologies, new methods that you don't

126:30

need to do survey anymore. You don't

126:32

need to waste 10 years. You could

126:34

actually after you build a model you

126:36

actually predict whether that person

126:38

favorate

126:39

or they actually want to do something.

126:41

So what I'm saying is um there are now

126:43

new technologies that saw some of the

126:44

uses to talk about uh and they have

126:47

tracking that and the the predictive

126:49

accuracy are 80%. Okay. And so that's

126:52

one answer to your question. Number two,

126:54

uh about your AI uh skepticism. Um uh

126:58

indeed it's true. I think a lot of um uh

127:01

excitement indeed in our uh university

127:04

now we are also embracing AI in in one

127:07

aspect we are not teaching our students

127:09

that we need to learn how to do

127:10

prompting and integrate AI into all our

127:13

social science and even humanities um to

127:16

use AI to make movies right to present

127:18

information in a different way etc.

127:20

However, uh we are also very cautious

127:22

about the limitation of AI uh

127:25

hallucination and also the biases about

127:27

the underlying data and so I think we

127:30

are looking to it very cautiously and

127:33

also especially in education we also

127:36

look in the areas that we should not use

127:38

AI and so um so I will say that the

127:42

topic so big that I will I will say um

127:45

um uh we have to have a separate seminar

127:47

on this or separate conference on this

127:49

event But I would like to go back to

127:51

conclude with this. We are embracing AI

127:54

but embracing AI in a smart way ya.

128:00

Oke, thank you Prof. Ho. Jadi tetap ya

128:04

Prof. Ho itu tidak menyarankan

128:06

menggunakan AI secara sepenuhnya. Jadi

128:09

kita tetap harus bisa ee memilah-milah.

128:13

Terima kasih Prof. Wahyu untuk

128:16

pertanyaannya. kita akan ee menuju

128:20

pertanyaan berikutnya masih di chatb ya,

128:21

Pak Dr eh sabar. Nah, eh good afternoon

128:27

distinguished speakers all me introduce

128:29

myself. So this is my student Clara from

128:32

Master eh Public Administration Ngurahi

128:36

University.

128:37

Eh she would like to ask in the context

128:40

of reimagining public administration

128:43

education in the digital era, what would

128:45

an ideal curriculum design look like to

128:48

ensure that digital transformation goes

128:51

beyond merely adopting learning

128:53

technologies and in state fundamentally

128:56

receive students mindsets from an

128:59

administrative bureaucratic orientation

129:01

to one that is data driven collaborative

129:04

and adap to the complexity of public

129:08

policy. For the first question, I would

129:10

like to address to Prof. Andi

129:15

oke, thank you eh Bu moderator, Bu Dia.

129:18

Jadi if you look this question ya,

129:21

especially about eh jadi eh

129:24

transformation gitu ya. This is related

129:27

to the mindset ya. Jadi kerangka nilai

129:30

dan yang paling penting adalah kita

129:32

berpikir eh what is the benefit of eh eh

129:37

transformation ini. Jadi ee ketika k

129:42

kita lihat ya ee pendidikan

129:45

administratif publik itu ee di sini ee

129:50

ada pergeseran ya yang paling penting

129:53

kita bisa merasakan manfaatnya ada

129:56

pergeseran kurikulum change of eh the

129:59

core curriculum from procedure to

130:01

problem solving. So, we need to more

130:03

concentrate the problem solving thing

130:06

because dengan problem solving kita akan

130:09

fokus pada complexity of public policy.

130:12

Nah, kita akan membutuhkan di era

130:14

digital ini literasi data analytic atau

130:17

data driven yang lintas ya. Jadi, not

130:19

only eh sekedar eh statistik dasar gitu

130:23

ya, tapi bagaimana ability kita to

130:26

interpret ya big data in the wawasan

130:30

kebijakan ya. Jadi dalam konteks ini

130:33

mahasiswa belajar ya bagaimana

130:35

memecahkan masalah dengan big data

130:37

tersebut gitu loh. Tidak hanya ee kita

130:40

dalam konteks mere atau melaporkan dan

130:43

juga kita perlu melihat dari sistem

130:45

thinking ya mengajarkan bahwa kebijakan

130:48

publik itu tidak berdiri sendiri ya.

130:50

Jadi masih masalah di satu sektor

130:52

transportation for example ini related

130:54

to the other sector like environment or

130:57

economy. So this is interdisciplinary

130:59

approach ya. And eh ideally curriculum

131:02

is related eh eh dealing with eh

131:08

literasi digital eh eh literasi digital

131:11

dan eh data etik. Nah, ini yang juga

131:15

merupakan penting untuk memastikan

131:17

mahasiswa bahwa risiko privacy dan bias

131:20

algoritm itu ee tetap harus

131:23

dipertimbangkan ya. Sehingga kita harus

131:26

juga hati-hati dengan data ini ataupun

131:29

hal yang disampilkan. oleh big data.

131:31

Apakah itu cukup menjawab gitu loh?

131:33

Karena ee ee apa tuh ee

131:38

sense-nya itu yang yang punya kita gitu

131:40

loh. Belum tentu yang disampaikan big

131:42

data itu make a sense itulah. Nah, itu

131:45

kita harus juga menggunakan insting atau

131:47

sense kita untuk melihat itu dan ee

131:50

desainnya ya berpusat pada ee SDM ya,

131:54

human ya, yang mana ee mengubah pola

131:57

pikir jadi bagaimana dari melayani

131:59

aturan menjadi melayani warga. Jadi ini

132:02

dalam konteks governance tadi. Tadi kan

132:04

kita sudah move to governance level. How

132:07

to mengelola information ini untuk

132:10

melayani warga gitu loh. Bukan hanya

132:12

untuk mengestablish sistem saja. Dan

132:15

kolaboratif lintas sektor ini juga

132:17

penting ya. Jadi ee pendidikan itu tidak

132:21

hanya istilahnya eh pedagogi eh the

132:25

living lab ya, tidak hanya diadakan

132:26

secara ee seperti Pak Rino tadi katakan

132:29

hanya di kelas gitu loh, pasif. Tapi

132:32

kita mengubah metode pola pikir

132:34

pengajaran itu berubah dari ceramah

132:36

pasif tapi menjadi praktik nyata. We

132:38

doing the work ya. seperti yang sekarang

132:41

mahasiswa saya itu juga punya cash based

132:43

ya atau project base yang harus

132:44

dipecahkan melalui ee bantuan AI dan

132:48

lain-lain. Nah, ini kita tidak hanya eh

132:52

manually memberikan ceramah gitu loh.

132:54

Kita eh try to bring the real word ya to

132:57

give energy and motivation to them eh

133:01

untuk menjadi materi kuliah itu menjadi

133:03

menarik gitu loh. Terima kasih. Saya

133:05

pikir itu ya.

133:07

Oke terima kasih. Oke, ya. Terima kasih

133:10

Prof. Andi. Kita lanjut ya ke pertanyaan

133:14

berikutnya. Semoga Galuh apa

133:16

curiosity-nya terjawab. Eh, jadi saya

133:20

akan address to Bapak Rino supaya semua

133:24

kebagian.

133:25

Jadi, karena yang pertanyaan berikutnya

133:28

adalah ditujukan kepada Prof. lagi. Jadi

133:31

ini dari Imana Sendrato eh student at

133:37

Universitas HKBP Nensen.

133:41

Jadi Imana menanyakan ada dua

133:44

pertanyaan. Sejauh mana pemantauan

133:46

proaktif terhadap media sosial oleh

133:48

pemerintah dapat memperkuat tata kelola

133:51

demokratis dan bagaimana institusi

133:53

publik dapat menyeimbangkan pengambilan

133:56

keputusan berbasis data dengan

133:58

perlindungan hak privasi warga ee negara

134:03

dan sejauh mana negara ee digital dapat

134:07

memperkuat akuntabilitas demokrasi dan

134:10

bagaimana kerangka kerja tata kelola

134:12

digital dapat memastikan perlindungan

134:14

privasi serta keamanan data warga

134:17

sekaligus mencegah pengawasan berlebihan

134:20

dan sentralisasi

134:22

kekuasaan. Silakan Pak Rino dijawab.

134:28

Baik, terima kasih Bu Dia. Saya mungkin

134:30

akan langsung dalam satu ini ya, satu

134:33

jawaban yang sama gitu. Karena eh the

134:35

tendency of this questions is similar.

134:38

So asking about how the democracy eh be

134:41

threaten by all of the engines.

134:45

So again eh

134:49

I cannot guarantee the answer. I'm sorry

134:52

because in a sense that all the data is

134:54

collected by the government and all of

134:57

our activities are collected by the

134:59

government or by anyone else. Even I

135:03

don't really understand

135:05

does our Zoom here be analyzed by Zoom

135:08

and analyzed by Google and analy by

135:10

another AI and then go to our profiling

135:13

or not.

135:15

So

135:17

how we can ensure the democracy of

135:19

course first and foremost we need to

135:22

back to the manual processes again if we

135:25

talk about the process for digital er it

135:28

is not stand alone processes so the

135:32

digital processes comes from the manual

135:34

processes so the manual processes should

135:37

be

135:38

eh

135:40

should be

135:44

carefully

135:45

taken

135:47

so that it not ruin the democracy

135:49

itself. Jadi the manual prosesnya harus

135:51

dijaga sehingga nanti tidak terjadi pada

135:53

digital proses itu. Karena begitu data

135:56

ini sudah terkumpul, anything can

135:58

happen. If the data has been collected,

136:00

anything can happen, including bridging

136:02

the democratic culture.

136:05

Jadi termasuk eh misalnya ya eh if we

136:08

talk about the let's say about the

136:11

controlling the social media

136:14

of the countries

136:16

cannot do that but some countries do

136:19

that including Indonesia some other

136:22

countries does not do that they say does

136:25

not do that but they actually do that.

136:29

Jadi beberapa negara memang menerapkan

136:32

sosial media itu untuk memfilter

136:35

termasuk Indonesia ya apa saja tren pada

136:38

pemerintah.

136:40

Ee beberapa negara mengaku tidak

136:43

memfilter tapi sebetulnya memfilter.

136:45

Hanya mereka menggunakan cara lain untuk

136:47

mengatasinya.

136:49

Jadi ee supaya tidak supaya dianggap

136:52

tidak mengancam demokrasi, mereka

136:54

memfilter tapi kemudian membuat buzer

136:57

untuk tidak mengancam demokrasi itu. So

137:01

this making the democratic spare in the

137:04

digital space still blury and some

137:08

point.

137:09

That's why I I said before if we talk

137:12

about the digital

137:14

how how we reserve the digital democracy

137:17

it backs to the how the manual systems

137:21

develop bagaimana sistem manualnya

137:23

dibangun bagaimana demokrasi dibangun

137:25

secara manual karena begitu kita masuk

137:27

ke digital

137:29

the data is there government can see

137:31

anything

137:33

if even we login government can see

137:36

anything so I think that's the point I

137:38

cannot guarantee if the data has been

137:40

handed over to government or handed over

137:42

someone else the democracy is still

137:44

there also as you mention before even

137:47

now the cortex problem he

137:51

right

137:51

everything almost everything

137:54

and everything or our data already in

137:58

there in the AI big data whatever we are

138:02

the control of everything thank you

138:04

pakin

138:06

oke we will move to the Next question.

138:09

So this is address to eh Prof. Eh Ho. So

138:14

this is from Pak Mas Winoto from

138:17

Brawijaya, our college also. Apa kabar?

138:20

Eh Mas Winoto? So we met in Bali and

138:23

Korea also. Eh so he

138:28

Oh ada

138:30

eh maaf Prof. Prof.

138:35

So, I'm focusing on research on digital

138:39

governance and government performance

138:41

management which is highly relevant to

138:44

the model presented by Albert in

138:47

engagement in our data reach world. The

138:51

model not only illustrates the diversity

138:54

of data sources but more importantly

138:57

shows how data is proceed eh shared

139:01

across unit analy visual and then

139:04

incorporated into the decision making

139:07

cycle ultimately generating

139:10

socioeconomic and impacts. In this

139:13

regards I would like to ask within the

139:16

framework of digital governance how can

139:18

prof host propose data driven engagement

139:23

model be operationalized to strengthen

139:26

government performance management system

139:28

so that data integration not only

139:32

produce dashboards and kpi but also

139:35

actually impacts strategic planning

139:38

budget allocation and accountability for

139:41

public outcomes in a miserable

139:44

manner please propri

139:47

so thank you so much for your question I

139:51

know that there are also some questions

139:53

maybe for me about later about Beijing

139:55

Shanghai the governance model just now

139:58

uh we also have some uh comments about

140:01

democracy. I may as well just put it all

140:04

together. Okay. And then adjust in one

140:06

good swap and so that you uh you think

140:09

about right now first of all I think

140:12

indeed uh all these digital tools are

140:14

tools right but there are a lot of data

140:16

governance issue and there are also a

140:18

lot of question about democratic

140:20

governance with the data digital tools.

140:22

Right. So uh let me actually uh share my

140:26

thinking. I'm not saying that this is

140:29

this is just a very preliminary

140:30

thinking. Number one, I think we need to

140:33

go back to our original uh understanding

140:38

of democracy. Okay. Now a lot of people

140:41

assume democracy for a long time. Uh

140:44

democracy equals

140:46

uh western style of parliamentary

140:49

electoral form of governance. Okay. Now,

140:53

I'm not going to comment on that because

140:54

you could look at the news and see

140:56

whether that is working well or not,

140:58

right? You could decide right but I

140:59

would like to go back actually to

141:01

another notion of democracy which

141:03

actually was advocated by the American

141:07

uh police and the also practitioner and

141:09

the president uh Lincoln said democracy

141:12

is government for the people, by the

141:14

people and of the people. So let's use

141:17

this as a criteria with digital tools.

141:20

Could the digital tools help us to make

141:24

the government serving the public better

141:26

government for the people. Okay, with

141:28

that since you have a question also

141:30

about performance and gunability right

141:32

if that is the one of the criteria of

141:35

democracy then we could actually have

141:37

some benchmark about output's

141:39

performance is that government with the

141:42

digital tools help with AI etc. Are they

141:44

doing more work, better work, more

141:47

efficient work, more cost effective work

141:49

and more transparency etc. More

141:51

accountable work for the people. That's

141:54

number one. Right? Then you also go back

141:56

to the second definition government buy

141:59

the people. Now again buy the people

142:01

could mean different ways of

142:03

participation in participant theories

142:05

there are hierarchies or layers of

142:07

participation. Right? So again if you

142:09

have all the apps, all the social media,

142:11

all this way for the people to voice

142:14

their opinion not just every four years

142:17

but you actually every 24 hours 7 days

142:20

you could voice your opinion share your

142:22

perspective all this so then you could

142:24

actually another way about government by

142:26

the people right so you could think

142:28

about that right digital tools could be

142:30

very helpful to fulfill that and of

142:33

course you have the government of the

142:34

people so we talk about digital gaps who

142:37

are included who excluded a more

142:39

inclusive smart city is government of

142:41

the people again you could look into

142:43

that and and think about whether

142:45

digitals are helping more right then

142:47

with all this I think we could kind of

142:50

rethink what it means uh uh when we talk

142:53

about democratic governance now behind

142:55

of course we also have another notion

142:57

about accountability and check and

142:59

balance this is where different system

143:01

may have different ways to make sure

143:03

checking I think early comments is also

143:05

very legit we also need to think about a

143:07

larger picture who owns the data and who

143:10

have the data government have some data

143:12

for sure right we talk about all this

143:13

know CCTV and but a lot of data actually

143:17

now not controlled by the government

143:18

it's actually controlled by some of the

143:20

large companies and to work then you

143:22

have any accability or transference

143:23

about that right and ha you even use the

143:26

data for public policy purposes so

143:28

that's another layer of democratic or

143:32

even global governance issues about data

143:34

sovereignty and security issues So we

143:37

could talk about that and see whether

143:39

there's any challenges or if there are

143:40

opportunities also for cross sectoral

143:43

even global collaboration about data

143:44

governance to enhance democracy. Yeah.

143:47

To some extent also protect security

143:49

right largely I lastly I would like to

143:52

add that um uh given all the all the

143:55

issues one thing I think is really

143:58

helpful is actually having more

143:59

transparency. If you say the government

144:02

is you know collecting all the data etc

144:04

could we actually make some of data

144:05

available now of course then you have

144:07

security and privacy concerns and there

144:09

are ways to do it. So could you make the

144:11

data anonymous? Could you actually know

144:12

screen the data? Could you actually

144:14

aggregate aggregate the data so that is

144:16

only in the district level neighbor

144:17

level so that it won't reflect any

144:19

individual data etc. So if you could

144:22

make the data more transparent uh by the

144:25

public sectors but maybe also to

144:26

something by some of the large companies

144:29

could they actually surrender some of

144:30

the data so that public agencies like

144:33

transportation department or public

144:34

health department could use some of the

144:36

data now collected by whatever big

144:38

companies in the world could we get that

144:40

data out to have a partnership with them

144:43

so that we can use the data to enhance

144:45

uh democratic governance also to enhance

144:47

even public policy effectiveness now we

144:50

are not doing yet and so I think those

144:52

are some issues we could we could think

144:54

about but I think more transparency I

144:56

think will help thank you

145:01

ok

145:03

thank you prof h I got a message from

145:07

Prof eh Wahyu so the second questions is

145:12

not answer yet can you explain about the

145:16

you know as you mention how we can rely

145:19

really reconcile

145:21

servic

145:37

we kind i address that

145:40

basic human rights right we talk about

145:42

for example protecting the the right for

145:45

people to voice the opinion etc right so

145:48

there's always a balance between uh

145:50

whether you could say anything without

145:52

any limit. I think the notion you could

145:54

say anything or put anything post

145:57

anything without limit that notion is

145:59

gone. Not even in the western call

146:01

democratic countries right I remember.

146:03

Okay. Okay. Prof. story to interrupt. So

146:06

this is actually about how you solve the

146:08

problems of privacy, the rights to

146:10

disconnect or essentially the issue of

146:13

eh panoptican society.

146:17

That's

146:19

the question he want to

146:21

so how do you disassociate with the

146:23

tools with the digital world right

146:26

is that kind of like okay now I am a

146:29

little bit um I'm a little bit

146:31

pessimistic on that. I think the notion

146:34

about privacy in the old traditional

146:36

work is gone. If you walk in the street,

146:40

even if you don't go out in the street

146:41

and lock yourself in the room, if you

146:43

use mobile phone, okay, uh you have no

146:46

privacy. In reality, you have no

146:49

privacy. All your data have been

146:50

collected through your phone in the

146:52

street there are all kinds of camera in

146:53

in the shopping mall not necessary by

146:55

the government in shopping malls going

146:58

to elevator whatever they are CCTV

147:01

everywhere and so uh and facial

147:03

recognition technologies are not used by

147:06

uh just government but actually used by

147:08

companies and so so if you argue that we

147:12

could totally detach yourself maybe you

147:14

live in an island without any

147:16

technologies but in reality in the 21st

147:19

century I think uh the old notion of

147:22

privacy I think is unrealistic however

147:26

what we want is actually have more clear

147:30

and effective legislation to protect the

147:33

data also have clear governance to make

147:36

sure who could own what data and how the

147:39

data should be used and also their

147:41

mechanism to make sure that if they

147:43

misuse the data they are mechanism to

147:45

punish them or to limit them more check

147:47

and balance more transparency about all

147:49

I think that is where we are going for.

147:51

So that's my my own understanding or my

147:54

own notion but I I could be wrong. I

147:56

could I I will be happy to look listen

147:58

different views on this.

148:01

Oke. Eh thank you Prof. Host. Semoga

148:04

bisa menjawab eh pertanyaan dari

148:07

curiosity dari Prof. Wahyu mengenai

148:10

masyarakat Penopticon. Jadi masyarakat

148:12

yang merasa selalu ee diawasi. Nah, itu

148:16

sekarang kita juga bisa apa kontrolnya.

148:19

Kalau sudah tidak mau diawasi kita

148:21

diflight mode kan saja. Jadi karena

148:24

semua sudah bisa terdetect, jadi kita

148:27

ngobrol kita ee jika kita sadari saat

148:31

kita ngobrol dengan teman-teman pada

148:33

saat HP ada di sebelah kita, tiba-tiba

148:35

di sosial media semua tampil apa yang

148:38

kita ee omongkan. Jadi itu juga salah

148:42

satu dari ee apa ya ee dari ee

148:47

Penopticon Societ eh tersebut. Baik

148:51

untuk ee selanjutnya saya akan berikan

148:55

kesempatan kepada ini Pak Dr. Andi

148:58

Alfatih ya karena dari tadi sudah angkat

149:01

tangan berkali-kali. Please ee Pak Andi.

149:06

Baik. Baik. Terima kasih eh Ibu Utari ya

149:11

eh atas kesempatannya di Itari. Alright.

149:15

E talking about reimaging public

149:19

administration education

149:22

it means we are going to develop or

149:25

advance the education of public

149:27

administration.

149:30

For this it is better to make public

149:33

administration as a profession.

149:36

It means after students of public

149:39

administration

149:41

have finished their study for sarjana or

149:45

undergraduate

149:47

or S1, they get degree like sarjana ilmu

149:51

politik or sarjana administrasi publik.

149:55

then they can take further study for one

149:59

or two years to

150:03

as the consultant for in public

150:06

administration so for this we make the

150:10

professional study level like sarjana

150:12

ekonomi you know after they have get the

150:16

degree they study one or two years to be

150:19

eh akuntan

150:22

or sarjana kedoktoran ya eh to be a

150:25

doctor they have to study again for two

150:27

years sarjana hukum to be notorist they

150:30

have to take further study as well and

150:33

then like that also for sarjana perawat

150:35

to be nurse. Nah so so sarjana

150:39

administrasi have to take further study

150:43

profession to be consulted. That's my

150:46

idea. Eh I propose to this forum. Thank

150:49

you.

150:51

Terima kasih, Pak Dr. Andi Alfatih.

150:53

Jadi, kita eh apa jika saya simpulkan eh

150:58

we need to do this profession. Jadi

151:01

profesi seperti insinyur, perawat atau

151:05

dokter untuk publik administrasi.

151:08

Right.

151:09

Jadi terima kasih banyak atas sarannya.

151:11

Semoga didengarkan oleh Prof. Eh, I hope

151:14

will respond to this.

151:16

Oke, mungkin eh Prof. mulu ya yang akan

151:19

respons

151:22

atau Prof. Andi Vepta silakan.

151:27

Baik. Eh baik Bu Dia terima kasih untuk

151:32

in this case ya ada e istilahnya pro dan

151:36

cons ya. Kalau kita membuat ee

151:39

pendidikan formal kita seperti dokter,

151:42

pengacara akuntan itu proya alasan

151:46

proya, pro argumennya itu eh standar

151:49

kompetensi menjadi jelas ya, clear ya.

151:51

Kompetensi standarnya clear.

151:53

Ee kode etiknya juga mengikat seperti

151:57

profesi kedokteran dan lain-lain gitu

151:59

ya. Hukum apa itu kan punya kode etik

152:01

yang sangat kuat gitu kan. Kemudian eh

152:04

otonomi eh dari intervensi politik ya.

152:07

Jadi profesionalisme memberikan kekuatan

152:10

ya support for birokrat to be autonomy

152:13

dari intervention politic political

152:15

intervention. Nah, namun juga argumen

152:18

yang tidak selalu baik untuk hal ini.

152:20

Jadi yang kontra ya terhadap ee posisi

152:23

yang seperti ini. Misalkan kalau kita

152:25

menjadikan seperti itu bisa jadi profesi

152:28

administrasi pabrik ee nanti bersifat

152:31

elitis gitu ya. Profesionalisme bisa

152:34

membuat birokrat merasa lebih tahu dari

152:36

warga. They eh they feel more eh know

152:40

thaning

152:42

citizen. Nah, ini bisa menjauhkan eh

152:45

pemerintah dari aspirasi rakyat kalau

152:47

terlalu fokus pada eh prosedur teknis.

152:50

Kemudian juga fleksibility gitu ya. Ini

152:53

juga kurang. Administrasi publik

152:55

membutuhkan berbagai latar belakang ya.

152:58

Jadi interdisipliner jika dibatasi hanya

153:00

memiliki gelar profesi tertentu ini

153:03

pemerintah akan kehilangan talenta

153:06

beragam. Misalkan profesi dokter itu kan

153:08

harus dari dokter S1-nya. profesi hukum

153:11

misalkan S1-nya hukum misalkan apa

153:14

misalkan insinyur apa. Nah, padahal

153:16

administrasi publik itu kan yang masuk

153:18

ee ee public policy itu bisa dari

153:20

kedokteran, dari apa ee insinyur dan

153:24

lain-lain gitu loh. Nah, ini akan

153:26

kekurangan fleksibilitas kalau kita

153:28

profesikan gitu loh. Nah, kemudian

153:30

kekakuan birokrasi juga standar

153:32

profesional yang terlalu ketat terkadang

153:35

menghambat inovasi dan kreativitas

153:37

karena dia terlalu e stik. ee pada ee

153:41

standar profesional. Nah, ini plus dan

153:44

minusnya ya mohon dilihat juga gitu loh

153:47

sehingga ketika kita itu menjadikan

153:49

profesi ada konsekuensinya juga. Terima

153:51

kasih eh return back to the eh

153:54

moderator. Thank you.

153:56

Baik, terima kasih

153:59

untuk semuanya juga maafkan karena

154:02

waktunya sudah ee habis. Jadi kita

154:06

sekarang akan sampai kepada eh penutup

154:10

acara. So ladies and we have finally

154:14

reach the conclusion of today's webinar.

154:18

So let me conclude from all of the eh

154:23

speakers and the questions and I'm very

154:26

sorry for the questions that but it's

154:29

already conclude by Prof. H for some

154:33

questions. So I would like to that the

154:37

digital transformation transformation

154:39

the digital transformation so this is

154:41

the s to digital era governance demands

154:44

proactive data driven leadership yet it

154:48

must prioritize the validation of raw

154:51

data over blind

154:54

reliance on AI to prevent flood decision

154:57

making. And then how about privacy vs

155:01

security digital tools like mass

155:03

surveillance must be balanced with the

155:06

protection of basic human rights and

155:08

privacy to avoid a panoptican society.

155:13

And then about the curriculum redesign

155:15

public administration education must

155:18

have beyond bureaucratic rules toward

155:21

mastering digital architecture and

155:23

performance management that directly

155:26

impacts budgeting and public outcomes.

155:29

And then the last one is about human

155:31

agency. AI lacks inherent context and

155:36

ethics. Therefore, the curriculum must

155:38

treat AI as a supporting tool while

155:42

maintaining critical thinking and moral

155:45

reasoning as the primary drivers of

155:48

public policy.

155:51

Eh, jadi teknologi itu bisa memberikan

155:53

kecepatan, namun nalar kritis manusialah

155:57

yang memberikan

156:03

Dewi acting as moderator and

156:05

representing the Ayapa executive board

156:09

and I would like to express my de

156:12

gratitude to our three distinguished

156:15

speakers, the board of experts and all

156:18

participants for vibrant engagement. May

156:22

the ideas generated today serve as a

156:25

blue for the better governance in the

156:28

future and I do apologize for any

156:32

shortcomings during the sessions. Thank

156:35

you for your presence and I look forward

156:37

to seeing you at our next Yapa event.

156:41

have a wonderful afternoon dan selamat

156:45

menjalankan ibadah puasa bagi

156:48

teman-teman kita semua hadirin yang ee

156:52

melakukan ibadah puasa. Jadi ee terima

156:55

kasih banyak juga Prof. ee Khairul Muluk

156:59

dan Prof. Oscar serta e seluruh ee staf

157:04

IAPA yang bertugas pada hari ini. Dan

157:10

ee pada sesi berikutnya kita akan

157:13

memberikan sertifikat kepada seluruh ee

157:18

speakers. Silakan ee Mbak Safira.

157:34

eh belum keluar. Oke, sudah. So, the

157:37

certificate of appreciation will given

157:40

to Prof. Alfred Tatko, MPD, MPA, PhD. As

157:47

a ke cannot speaker, thank you very much

157:49

for your presence today, Prof. Ho. I

157:52

hope we will meet again in the near

157:55

future maybe in Bali or Hong Kong. And

157:59

then the next

158:07

eh oke so the next is for Prof. Dr.

158:10

Randus MD Fepta Wijaya, MDA, PhD. Terima

158:15

kasih banyak Prof. sudah berkenan untuk

158:18

memberikan sharing dan insight pada hari

158:20

ini. Sepertinya mahasiswanya sudah

158:23

banyak join dan mereka apa sangat ee

158:26

senang sekali Prof. Andi bisa sharing

158:28

pada session ini. Sampai berjumpa lagi

158:31

di session berikutnya, Prof. Baik, yang

158:34

berikutnya silakan

158:38

eh kepada Bapak Rino Adrian Ardi

158:42

Nugroho, Sos, MTI, PhD. Terima kasih

158:46

banyak, Pak Rino. Semoga kita bertemu

158:50

lagi di Solo maupun di Bali.

158:53

Jangan lupa kalau ke Bali kabar-kabari

158:56

saya nggih, Pak Rino ya.

158:58

Salam buat Pak Dekan ya.

159:00

I

159:01

terima kasih banyak. Oke. Ee apakah ada

159:04

lagi Safira? Kalau gak kita ee apa? Foto

159:09

bersama

159:10

moderator Ibu.

159:12

Oke, itu untuk diri saya sendiri ya.

159:14

Terima kasih kepada diri saya sendiri

159:17

pada hari ini sudah ee semua sudah

159:20

berjalan dengan lancar. Terima kasih

159:22

juga kepada Tuhan yang Maha Esa bahwa

159:24

kita diberikan kesehatan dan bisa hadir

159:27

di acara Zoom Meeting pada hari ini.

159:30

Baik, kita sekarang seksi sesi terakhir

159:33

adalah foto bersama. Silakan eh untuk

159:35

buka kamera semuanya. Before we leave

159:39

the room, let us take a virtuual group

159:41

foto please on your cameras.

159:50

Baik, mohon izin Bapak Ibu semuanya.

159:51

Saya izin untuk memandu untuk sesi foto

159:53

bersama karena cukup banyak slide yang

159:56

ada jadi bisa langsung ee bersiap gitu

159:59

ya untuk senyum terbaiknya pada hari

160:00

ini. Baik untuk slide pertama saya

160:03

mulai. 1 2 3.

160:06

Baik untuk selanjutnya 1 2 3.

160:10

Slide selanjutnya 1 2 3.

160:15

Baik untuk karena slide yang selanjutnya

160:17

sudah tidak ada yang on kamera sudah

160:21

saya kembalikan ke Budia saja.

160:23

Baik terima kasih Mbak Safira. Mbak

160:25

Safira ini di belakang layar ya bekerja

160:27

luar biasa dan seluruh tim IAPA. Jadi

160:30

kita tutup sesian hari ini dengan ee

160:34

ucapan asalamualaikum warahmatullahi

160:37

wabarakatuh.

160:38

Om santi shanam

160:41

salam sejahtera, namo budaya dan salam

160:44

sehat untuk kita semua.

160:47

Sampai jumpa Bapak Ibu.

160:49

Thank you for all.

160:51

Thank you semuanya.

160:52

Terima kasih. Terima kasih

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