Presentation given at the Service Design and Delivery in a Digital Age - Academies for EaP countries organised by the SIGMA Programme and the GiZ Eastern Partnership Regional Fund. Topic 2: Digital transformation.
3. A
joint
initiative
of
the
OECD
and
the
EU,
principally
financed
by
the
EU.
Who am I?
• Programme Director for AI – Digital Nation
• PhD Researcher, TalTech
• Former External Expert to the European Commission’s AI Watch
research team on AI in the public sector
• Research activities:
• Understanding the concept of AI in government and
refining the concept based on empirical use cases
• Requirements needed for using AI technologies in
government organizations
• Policy initiatives and strategies for facilitating AI in
government
• Impact and consequences of AI deployed in public
services
• Governance of AI technologies and ensuring responsible
use
10. A
joint
initiative
of
the
OECD
and
the
EU,
principally
financed
by
the
EU.
AI for policymaking
SATIKAS to detect mowed grass of
farmers, Estonia
The Dublin Beat
analyses citizen
tweets
Object Detection, Amsterdam
CitizenLab to analyse
citizen input
• AI to improve various stages of policy
making
• Detecting social issues more
quickly
• Estimate potential effects of
policy options
• Improve and fasten decision
making
• Monitor ongoing implementation
of policy
• Evaluate existing policy
• Include citizens in policymaking
11. A
joint
initiative
of
the
OECD
and
the
EU,
principally
financed
by
the
EU.
AI for public service delivery
BüroKratt AI, Estonian
Government
Misty II to assist the elderly in
Barcelona
JobBereik to assist in reskilling, VDAB,
Belgium
• AI could be used to deliver public services to
businesses and citizens
• Enhance information delivery about
government services
• Improve public services to citizens and
businesses, through personalization
• Automate redundant processes and
reducing on-site meetings
• Develop completely new services through
AI
• Reduce corruption and improve trust in
public service delivery
• Empower civil servants through decision
support tools
12. A
joint
initiative
of
the
OECD
and
the
EU,
principally
financed
by
the
EU.
AI for internal management purposes
Tengai interviewing job
applicants, Sweden
AI to detect anomalies
in X-Road, Estonia
VeriPol to detect false police
reports, Spain
• AI to improve internal management
operations
• Improve recruitment services
• More efficient allocation of human
resources
• Improved financial management
• Strengthen cybersecurity
• Predictive maintenance
• Modernize public procurement
processes
• Improve detection of fraud
13. A
joint
initiative
of
the
OECD
and
the
EU,
principally
financed
by
the
EU.
Illustrative examples
Agricultural Registers and
Information Board (ARIB)
Estonia
SATIKAS
Detection of the mowing of grasslands with COPERNICUS
Description
The AI system combines machine learning methods to
analyse satellite data together with other data sources. Used
to optimize inspection capacity of ARIB and enforcement of
subsidy requirements.
Lessons learned
Collaboration and sharing of resources crucial to ensure
adoption and implementation.
Amsterdam
the Netherlands
Description
The city of Amsterdam uses AI to identify housing fraud by
assisting tracking down people renting out their homes
illegally. This assessment was priorly done by people.
Lessons learned
There is a considerable risk for mistakes by the system.
This is why the AI system makes no decisions whether
someone is fraudulent – if there is a likelihood of 50% or
more that fraud might take place, a human inspector still
have to determine the fraud in person.
AI to discover illegal renting
Predicting fraudulent renting of homes
14. A
joint
initiative
of
the
OECD
and
the
EU,
principally
financed
by
the
EU.
Illustrative examples
Municipality Upplands-Bro
Sweden
Tengai
Robot to make recruitment processes less biased than
traditional interviews
Description
Tengai is a robot interviewer part of the recruitment and
staffing agency of the municipality. It follows years long
efforts of making recruitment less prone to bias
Lesson learned
Collaboration between humans and robots crucial to
complement strengths and weaknesses
Greek Government
Greece
Description
During the COVID-19 Crisis, the Greek government has
been using an AI system in all border control points
which helps the selection of which travellers to test
upon arrival at the border.
Lesson learned
Eva was not developed in a mathematically optimal way
but was designed to be practical, effective, transparent
and explainable. Black-box algorithms were avoided to
avoid opacity.
Eva
Targeted COVID-19 Border Checking
15. A
joint
initiative
of
the
OECD
and
the
EU,
principally
financed
by
the
EU.
Illustrative examples
Register for Enterprises
Latvia
UNA
Chatbot supporting citizens
Description
UNA is a Chatbot able to answer frequently asked questions
about the registration of their businesses as well as the
liquidation, merchants, companies and organizations and their
application processes.
Effects
It is said that 44% of the questions asked are easily taken care of
by the Chatbot. Other non-standard issues are still handled by
the support staff, who now have more time for other tasks
Estonian Government
Estonia
BüroKratt
Siri for government
Description
Described as the Siri on steroids for
government, it is planned to be the first
Assistant for all public services through a single
assistant.
Effects
The system is still under development but
there is great interest in the application and
has been awarded prices.
17. A
joint
initiative
of
the
OECD
and
the
EU,
principally
financed
by
the
EU.
AI in government = digital transformation
• "The technology community in government is often expected
to drive transformation on behalf of business leaders. However,
most digital change decisions are made by the business leaders –
such as permanent secretaries, chief executives, chief operating
officers and directors general.(…) The success of these decisions is
dependent on these leaders having the digital fluency to make the
best choices and fully understand the consequences of their
decisions for digital transformation.“ – UK National Audit Office,
March 2023
19. A
joint
initiative
of
the
OECD
and
the
EU,
principally
financed
by
the
EU.
Getting started with AI
• AI is not just data + algorithms + computing
• Just getting started is already a barrier
• Awareness
• Willingness
• Enabling conditions and foundations
Interdisciplinary barriers
• Environmental
• Organisational
• Innovation-related
• Individual
• Public sector is not the private sector
20. A
joint
initiative
of
the
OECD
and
the
EU,
principally
financed
by
the
EU.
Some activities AI strategies describe
Improving data access and management
Ethical AI design principles
Facilitating partnerships with the private sector
Improving internal competences
Improving knowledge and awareness of AI
Introduction and review of legislation
New teams or institutions for AI in the government
26. A
joint
initiative
of
the
OECD
and
the
EU,
principally
financed
by
the
EU.
Looking for the best practices
Think big, but start small
Partners, not clients of the private sector
Collaboration from the start
AI project management practices
Demystify expectations of AI – both good and bad
Ethical and legal risks tackled from the start
Take into account the bigger picture of implementation
27. A
joint
initiative
of
the
OECD
and
the
EU,
principally
financed
by
the
EU.
We are still at the beginning of
the AI-journey in government.
Let’s explore it together.
Digital Nation
digitalnation.eu
info@digitalnation.eu
LinkedIn
57 Telliskivi, Tallinn
Harju maakond, 10412
Estonia
Colin van Noordt
Programme Director AI - Digital Nation
PhD Researcher - TalTech
colin.vannoordt@digitalnation.eu