Yannis Charalabidis gave a presentation on AI in governance. He discussed how AI is being used in various areas of public administration like service provision, back office processes, and policy design. He believes AI will have an enormous learning potential and impact areas like developing digital twins of cities, simulations to help with policy design and democracy, and developing truly smart city applications and agents. However, he notes that universal algorithms for complex societal simulations do not yet exist and more basic research is needed in areas like developing generic public sector agents and understanding systems.
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Digital Governance & Artificial Intelligence
1. AI in Governance:
Why, What and How
Yannis Charalabidis
Professor, Digital Governance
University of the Aegean
yannisx@aegean.gr
2. Your invited speaker, in one slide
• Born in Athens, origin from the island Samos, Greece
• Electrical & Computer Engineer (BSc/Msc), PhD in complex information systems, National
Technical University of Athens
• Trained in Entrepreneurship Development at UC Berkley and U Amsterdam
• A certified professional coach, specializing in mentoring students and startupers
Since 10 years old, I am having fun while working:
• 10 years a part-time employee in the family business (B2B liquor store)
• 10 years a researcher in R&D projects for businesses and governments
• 10 years a manager in the software industry, at SingularLogic SA (Greece, The Netherlands,
Poland, US, India and the world).
• 10 years a professor at University of the Aegean, teaching and researching on digital
governance and innovative entrepreneurship (while wandering around the world)
Getting senior, steadily:
• 2016: The 8th most prolific scholar on digital governance, worldwide
• 2018: Among the 100 most influential people on digital governance, worldwide
3. “Rules of the game”
• My aim : to help you find an answer and develop ten new questions
• Have a question ?
1. You can put it in the chat, I will see while I speak
2. If relevant and burning, you take the floor and ask in person
• Relax, focus, and enjoy !
5. Definition - #1
Digital (or Electronic) Governance
refers to the utilization of
Information and Communication Technologies (ICT’s), by
Public Administration at National or Local Level,
aiming at providing high quality digital public services
to citizens and businesses
(Wikipedia)
6. The 5 automation levels of digital services
Level
Level 0: No information on the service online
Level 1: I can only find information online
Level 2 : Can find information and forms online.
Level 3: I can only apply for the service online
Level 4: Fully digital, one stop, one second
Level 5: Service starts by its own, is pre-
completed for citizens
Paper
100%
90%
70%
30%
0%
0%
Time
Days
Days
Hours
Hours
Minutes
Seconds
7. More people are connected (Internet, Web, Social Media, IoT)
More machine
intelligence is
available (AI, HPC)
More data is available
(Big data, Open data,
Linked data, Blockchain)
2030
2010
Presented in Samos Summit, 2010
9. Government 1.0
Division of labor,
rules of Economy,
French Revolution,
US Constitution
Post Kingdom -
democracies
1789 1870 1950
Government 2.0
Processes,
Bureaucracy,
Management Science,
Workflow, Project
Management,
Logistics,
Typewriter
Post-Empire
Democracies
Government 3.0
Computers, Information
Systems, Software, Service
science, Interoperability
Standards, Mobile devices
Postwar democracies
Government 4.0
Cyber-physical Systems
AI, IoT, Smart solutions,
Bid Data, Analytics,
Policy modelling and
simulation, stance
classification, opinion
mining, sentiment
analysis
New forms of
Democracy ?
dGOV1.0 dGOV2.0 dGOV3.0
Connected Open Smart / Disruptive
Governance Governance Governance
From Gov 1.0 to Gov 4.0
10. Definition - #2
Digital Governance is
a social phenomenon, in which
(a) the provision of services by the state to citizens and businesses,
(b) the collaboration between administrations and citizens,
(c) the decision-making and policy development,
and the overall operation of the Public Sector,
and mainly performed by digital means
(Definitions / Gov30 project / www.gov30.eu)
11. The generations of Digital Governance
dGOV 1.0
1990 +
dGOV 2.0
2010 +
dGOV 3.0 / 4.0
2020 +
Main Goal Better Services Openness &
Collaboration
Societal problem
solving, quality of
living
Main Method Connected
Governance
Open and
Collaborative
Governance
Smart / Disruptive
Governance
Usual Application Level National Local Local to International
Key Tool Portal Social Media Smart Phone
Key Obstacle / Risk Public Sector
Mentality
Public Sector
Mentality
Problem Complexity
Key ICT area Interoperability Open Data, e-
participation
AI, IoT, HPC
Most needed
disciplines, beyond ICT
Management
(BPR)
Sociology,
Marketing
History, Psychology,
Law, Political Science
12. The Domains of Digital Governance
Digital Governance
Digital Governance 1.0
(Service Provision)
Digital Governance 2.0
(Open & Collaborative Governance)
Digital Governance 3.0 / 4.0
(Smart & Disruptive)
Service Automation and BPR
Legal, Organisational,
Semantic & Technical
Interoperability
e-Authentication
Digital Signatures
Service Portals
Mobile applications
Cloud Infrastructures
e-Participation
e-Voting
Open Governmental Data (OGD)
Linked Data
e-Collaboration
(Collaborative Service Design)
Crowdsourcing
Community Awareness Platforms
Big Data-Driven Decision Making
Artificial Intelligence in Governance
Blockchain in Governance
Internet of Things
Policy modelling
Societal Simulation
Opinion Mining / Sentiment Analysis
13. Part B:
AI in the public sector - The Status
Time in Samos should now be: 17:10
14. Cases of AI in
Governance,
in European Union
Member States
(EC/JRC AI Watch
Report, 2020)
1
3
2
17. Estimated savings in US Federal Government (~2.5m employees)
(Deloitte analysis, 2022)
That’s 25% of the total
workforce hours, of the 2,5M
Federal Gov. employees
Akshardham Temple, New
Delhi : 30M hours to build
Building 3 to 30 big
temples, every year.
18. Part C:
My View of the Future
& Recommendations
Time in Samos: 17:20
Greece is a Finalist !
@European eGovernment Awards,
Malmoe 2009
19. My view of AI
Autonomous
Vehicles & Robots
Soft-Bots
& Chatbots
Digital Twins
Societal Modelling
Self-adapting
Simulation
Automated
Reasoners
Intelligent
Systems
Large Corpus
Understanding
Decision
Support
20. AI System Domain Key Tech Learning Potential Applicability My Opinion
Chatbots Service Provision NLP / Machine
Learning
Supervi
sed
Medium Enough Let it happen
Reasoning
SoftBots / RPA
agents
Service Provision &
BackOffice Process
Automation
NLP / Rule execution /
WF’s
Supervi
sed
Big Enough Go for it, try
a few
Other full
learning
SoftBots
SP & BO &
Policy Design
NLP / (Deep) Machine
learning / HPC
Autono
mous
Enormous Partial /
sectoral
Invest in that
City / Urban
Digital Twins
Policy Design, Smart
City, Democracy
IoT / Model based
learning / HPC
Autono
mous,
Deep
Big Medium Big trend,
big efforts
Societal
Simulation
Systems
Policy design, better
democracy
Model based & fuzzy
reasoning / Agents
Autono
mous,
Deep
Big Sectoral,
still no
universal
algorithms
Will be a
common
“base”, you
need it.
My bets … 5 / 10
21. AI System Domain / Aim Key Tech Learning Potential Applicability My Opinion
Vision
Recognition
Systems
Security, Service
Provision
Image and Video
Processing / Machine
Learning
Semi –
autono
mous
Medium Enough Regulation
testbed
Robots and
autonomous
vehicles
Service Provision,
Internal Processes,
Security,
Kinetic Systems /
Machine Learning
Autono
mous
Big Enough Industry will
lead
Legislation
Understanding
Systems
Better legislation and
justice
NLP / Machine
Learning / HPC
Legal Modelling
Supervi
sed
Big Need some
years of
research
Invest in
that, if within
your scope
Really Smart
City Apps &
Agents
Mobility, Health,
Security, Work, Quality
of Life
IoT / Machine
Learning / NLP
Autono
mous
Enormous Enough That’s a
shiny road
The bots
university
Basic research,
education, nextGen Bots
NLP, Machine
Learning
Supervi
sed
Enormous Need some
years
My far guess
Generic Public
Sector Agents
Basic Research, Machine Learning,
NLP,
Autono
mous
Enormous Need some
years
My far guess
My bets … 10/10 + 1
22. Why ? – Example 1
AI in
Legislation
- Draft Legislation Checking (e.g. Digital-ready Legislation, AI-
conforming legislation)
- Citizen opinion processing, for collaborative decision making
- Standardised Law production
- Fully automated Law analysis, interrelation, translation, and
publishing
- Press/media information processing, for impact assessment
- Citizens understand and navigate the law, can say their opinion during
law design, can generate their own legislation checks (citizen science)
- Parliaments easily consult other legislations, automate legislation checks,
produce well codified laws.
- MP’s control the key parts of the system, in parliament.
- Law professionals have analytical tools to navigate 200 years of legal
documents in 200 languages, for any issue
- Governments and local administrations have access to codified law,
easing digital transformation to rule based reasoning systems
What is the goal
How
is done
www.manylaws.eu
23. Why ? – Example 2
City Twin &
Citizen Science
- City digital twin for key infrastructures and layers
- Citizen sensors for air and water quality, traffic, waste, etc
- A constantly running simulator, on top of the digital twin
(showing the next stages of several city systems, adapting as
time goes)
- Specialised projections and visualisations for every important
city decision. Scenaria with possibilities.
- A new city operation and design, with better decision making and fast
response
- Citizens become part of the research “infrastructure” of the city, acting as
probes and running small labs, while being aware and changing attitudes
- City council decisions are based on evidence, experimental results and
simulation
- Local administrations have a system with memory, operational capacity
and forecasting abilities
What is the goal
How
is done
www.wecompair.eu