Presented in “Workshop on Sharing Best Practices on Leveraging the Benefits of Artificial Intelligence on Intellectual Property Examination to Improve Efficiency and Business Process”, collaboration between APEC and Directorate General of Intellectual Property Rights, Ministry of Law and Human Rights, Republic of Indonesia Bali, 29 November 2022 Dr. Tri Widodo W. Utomo, MA Deputy Chairperson for Policy Studies & Public Sector Innovation, National Institute of Public Administration (LAN-RI)

1. Dr. Tri Widodo W. Utomo, MA
Deputy Chairperson for Policy Studies & Public Sector
Innovation, National Institute of Public Administration (LAN-RI)
THEROLEOFINFORMATIONTECHNOLOGY IN
EVIDENCE-BASED POLICY INTHEVUCAERA
Presented in “Workshop on Sharing Best Practices on Leveraging the Benefits of Artificial
Intelligence on Intellectual Property Examination to Improve Efficiency and Business
Process”, collaboration between APEC and Directorate General of Intellectual Property
Rights, Ministry of Law and Human Rights, Republic of Indonesia
Bali, 29 November 2022

2. "Politics in the twentieth century was dominated by a central
question: how much of our collective life should be determined
by the state, and what should be left to the market and civil
society? For the generation now approaching political maturity,
the debate will be different: to what extent should our lives
be directed and controlled by powerful digital systems -
and on what terms?"
Future Politics: Living Together in a
World Transformed by Tech
Jamie Susskind. 2018. Oxford University Press

3. MAINCHARACTERISTIC OFCURRENT WORLD
V U A
VOLATILITY
Refers to constantly
changing situation
from one state to
another.
UNCERTAINTY
Refers to a situation
where there is a lack
of specific
information that
makes it difficult to
predict the future.
COMPLEXITY
Refers to the
number of
unknown factors
that affect a
condition, and the
relationship
between these
factors.
C
AMBIGUITY
Refers to indecisive
in determining
various policy
options due to an
uncertain situation

4. o 73.7% of Indonesian adults now use the internet, and every
virtual move they make – while shopping, connecting with
friends, sending work emails, streaming videos and so on – is
recorded.
o By 2020, the vast majority of people in the world will be able
to access almost any information, communicate and
collaborate with almost anyone, and broadcast their opinions
globally, from any location, at any time, and at a low cost.
o Billions of people use platforms like Facebook, Instagram, and
Twitter (with billions more on Chinese platforms like WeChat)
to talk with friends, share their thoughts and activities.
o This has changed the nature of communication: individuals
can now communicate directly with the public without having
to rely on conventional media such as newspapers or
television, and messages can be personalized and targeted to
a level that was previously impossible.
WHAT HAS CHANGED?

5. In 2019, human activities around the world generate 45 zettabytes of
data, and will increased to 175 zettabytes by 2025. On average, humans
generate 2.5 exabytes per day (1 exabytes = 1 million terabytes).
Source: Agus Laksono. 2021. “Data Science, Bigdata,and
ArtificialIntelligence: Its Utilizationin Policy Analysis”.
Virtual Public Lecture for Policy Analyst. NIPA
THEGROWTHOFDATA

6. DATA/EVIDENCE-BASED POLICY ININDONESIA IS WEAK
The lack of knowledge intermediaries who
bridge research and policy to policy makers.
even if there is, the capacity is not
sufficient.
Lack of Knowledge Broker
A career as a researcher has not
become an important choice for
Indonesian HR
Research career is not promosing
yet
Research funding is very minimal, not balanced
with the teaching function
Research tradition at the university has not
developed rapidly
Political support and budget
allocation for research is very little
(0,2% of GDP, 2016)
Funding for research
The data generated by policy analysts has not
been seen as an important resource in policy
making
The tradition of using knowledge/data in policy
is still weak
• Balitbang has not been positioned as a strategic
unit that provides policy-making materials
• The capacity of Balitbang HR is still low
• Extremely limited of R & D budget
The role of government research and development
agency is less effective
Source: Prasetiamartati,Carden, Ruhanawati, Rakhmani, Nugroho (2018)

7. The Ideal World The Real World
Policy making is based on EVIDENCE
(data, information, research)
Policy making is commonly based on:
 Intuition
 Common sense
 Experience
 Ideology
 Public opinion
 Political interests that can swing from
one end of the spectrum to the other for
the sake of rent seeking.
EVIDENCE-BASED POLICY: IDEALITY vs REALITY

8. THEURGENCY OFEVIDENCE-BASED POLICY
INACCURATE RESEARCH INCOMPLETE RESEARCH
Evidence-based policy is important to prevent policy failures.
Policy failures happen for two basic reasons:

9. UNINTENDEDCONSEQUENCES OFPOLICY
In 1989, the government of Mexico City
tried to control air pollution by banning
most drivers from driving their vehicle
one weekday per week. This policy is still
in place today. Violators of this policy
were charged a large fine.
The policy backfired: Many drivers
bought another car—often a used, high
emissions car, which ended up worsening
the pollution (Davis: 2004, in Chollete:
2021),
The unintended consequence of drivers
buying an additional used car made this
negative externality even worse
Evidence-based policies are needed to
avoid or minimize “unintended impacts”
or unplanned consequences
(concept introduced by Robert K. Morten,
“The Unanticipated Consequences of
Purposive Social Action”, Harvard
University).

10. Source: Tomtom. https://www.tomtom.com/traffic-index/jakarta-traffic.2022
JAKARTA TRAFFIC CONGESTION
 Traffic jams in Jakarta tend to be
severe on Mondays.
 6 am-8 am is the peak time for
vehicle movement in the morning
 Odd-Even policy applies.
 Starting at 10 am-3 pm, the
streets in Jakarta tend to be
empty  the Odd-Even policy
stops.
 Avoid going home from work at 4
pm-7 pm because the mobility of
vehicles is very high on the
streets of Jakarta. The average
congestion rate at 6PM is 85% in
2019  Odd-Even policy is
reinstated.
EXAMPLEOFDATA UTILIZATIONINPOLICY MAKING

11. Source: Indonesia Google mobility data during Covid-19, 2020 – 2022.
COMMUNITY ACTIVITY
RESTRICTION POLICY (PPKM)
 Google Mobility noted that at the
beginning of Covid-19 (2020) public
activity decreased drastically due to
the surge in Covid-19.
 In July 2021, it can be seen that the
mobility of the Indonesian people
is increasing when the Delta variant
spreads throughout the world and
begins to hit Indonesia.
 In August 2021, the government
decided to implement PPKM after
a very high spike in Covid-19 cases
due to high community mobility.
EXAMPLEOFDATA UTILIZATIONINPOLICY MAKING

12. 01 02 03 05
RATIONAL INCREMENTAL
04
SYSTEM GROUP ELITE
Decision making
should be based on
alternative choices,
looking for the most
efficient/rational
way of achieving
policy objectives
Public policy is a
continuation of past
government actions
with only
incremental
modifications.
Public policy is the
output of the
operation of a
political system that
is influenced by
policy demands,
policy processes, and
policy outcomes.
Public policy is seen
as a process of
responding to
demands from
various parties who
have an interest in
the policy issues.
Public policy is seen as
a preference of the
political elite. Policy
issues that enter the
policy agenda are an
agreement or the
result of a compromise
from the political elite.
5 MODELS OFPOLICY MAKING

13. Source: Deepak Chandra Misra, 2022
DEGREEOFINFORMATIONGATHERING INPOLICY MAKING MODELS

14. The more elitist the policy-making model is, the lower the tendency to use data in the preparation
process. Meanwhile, the more stakeholders involved in the policy process (group model), the more
data/information is needed.
Source: Deepak Chandra Misra, 2022
ROLEOFDATA/INFORMATION INPOLICY MAKING MODELS

15.  Agenda Setting: through data, the government can identify the topics that
emerge earlier and create a relevant agenda by collecting data from social
networks and identifying citizens' policy preferences.
 Policy Formulation: at this stage, data mining can help policy makers determine
policy trends and changes in public opinion to be proposed to formulate the best
policy options (Alfaro et al. 2013);
 Policy Acceptance: data analysis is used to provide evidence of an ex-ante impact
assessment of policy options, by helping predict the likely outcomes of different
options.
Problem
Definition
Data
Understanding
Result
Visualization
Data Mining
Policy Devt &
Modelling
Policy Simulation
Knowledge
Consolidation
o Framing policy
problem &
objectives
o Identification of
problem impacts
o Selection of
indicators
o Stakeholders
mapping
o Data sources
selection
o Data acquisition
and preparation
o Identification of
pattern and
correlation
o Data mining for
model validation
o Policy design
o Screening of
policy
options/alternati
ves
o Behavioral data
integration
o Models
integration
o Impact
assessment
o Big data
experimentation
o Parameter’s
space
exploration
Stakeholders
communication
o Reporting
o Policy drafting
POLICY MAKING BASED0NBIGDATA
Giest (2017):
“A large amount of official data collected at different levels of
government and in different domains, such as tax systems, social
programs, health records and the like, can—with their
digitization—be used to decision-making in the fields of
education, economics, health, and social policy”.

16. Indonesia starts embracing digital transformation agenda, yet current state of
human capital might slowdown the process
CHALLENGES INPROMOTING ICT AS TOOLFOREVIDENCE-BASED POLICY
ICT: Information & Communication Technology
ASN: Civil Servant
Competency Scale: 0-4
Source: Research and Development Board, Ministry of Communication and Informatics, 2018

17. Sumber: Deloitte, Gov2020: A Journey into the Future of Government, 2015
INDONESIA GLOBAL DIGITAL INDEX & ICT INDEX
According to BPS, the Index of Technology, Information
and Communication Development in Indonesia is
relatively low (5.32) from a scale of 10 in 2019.
This index is composed of 3 sub-indexes: 1) expertise, 2)
access and infrastructure, and 3) usage.

18. REFORM
o Encouraging the strengthening of
policy research collaboration between
research institutions.
o Involvement of groups of technologists,
data scientists, policy analysts in the
policy making process with policy
makers.
Research Collaboration
Reducing administrative barriers in the
process of research, development, and
public policy innovation.
Reduce Bureaucratic
Constraints
o Encouraging problem-solving-oriented
leadership through policy research.
o Encouraging digital leadership in the
bureaucracy.
o Promoting researcher or policy analyst as
promising profession in the bureaucracy.
o Strengthening ASN competence through
research and training programs.
Reform in Research Culture
Budgeting reform for research and policy
studies by increasing research budgets at
both government research centers and
universities.
Reform in Funding for Research
ACTIONS NEEDEDTOBOOST EVIDENCE-BASED POLICY USING ICT

19. Thank You …