The End Of Knowledge - Vault 4/50 - AI For Good - 2020 - How Estonia builds the next generation e-government with AI use cases

graph LR classDef main fill:#f9f9f9, font-weight:bold, font-size:14px classDef government fill:#ffcc99, font-weight:bold, font-size:14px classDef aiIntegration fill:#ccff99, font-weight:bold, font-size:14px classDef expandedAI fill:#99ccff, font-weight:bold, font-size:14px classDef opportunities fill:#ff99cc, font-weight:bold, font-size:14px classDef startup fill:#ccccff, font-weight:bold, font-size:14px A[How Estonia builds
the next generation
e-government with AI
use cases] A --> B[Estonian E-Government
and Data Management] B --> B1[Ott Velsberg,
Chief Data Officer, Estonia. 1] B --> B2[99% of government
services online. 2] B --> B3[90% citizens use
internet, mobile. 3] B --> B4[Individuals own
personal data access. 4] B --> B5[Once-only principle for
data provision. 5] B --> B6[X-Road for secure
data exchange. 6] A --> C[AI Integration
and Use Cases] C --> C1[AI for proactive,
zero bureaucracy services. 7] C --> C2[AI taskforce supports
AI adoption. 8] C --> C3[47 government
AI use cases. 9] C --> C4[Reusable AI components
available. 10] C --> C5[Use cases: hate speech,
document classification. 11] C --> C6[Investment in Estonian
language technology. 12] A --> D[Expanded AI Use
and Barriers] D --> D1[Personalized job recommendations,
satellite analysis. 13] D --> D2[Barriers: legislation, cloud,
data usage. 14] D --> D3[Lessons: simplicity, data
quality, collaboration. 15] D --> D4[KrattAI for AI
chatbots, assistants. 16] D --> D5[Goals: reduce time,
24/7 interaction. 17] D --> D6[Projects: chatbots,
message classification. 18] A --> E[Opportunities
and Limitations] E --> E1[Expand AI services
to private channels. 19] E --> E2[Data governance,
common standards essential. 20] E --> E3[Limitations in process
automation, cloud. 21] E --> E4[PISA ranks Estonia
1st in education. 22] E --> E5[Public trust gained
with transparency. 23] E --> E6[AI project evaluation:
societal impact. 24] A --> F[Startup Collaboration
and Digital Transformation] F --> F1[Startup scene benefits
from collaboration. 25] F --> F2[Ubiquitous ID card,
mobile authentication. 26] F --> F3[Open source mandated for
funded projects. 27] F --> F4[Ongoing analog to digital
data transformation. 28] F --> F5[Project management: competency,
end users. 29] F --> F6[10M budget for
AI strategy. 30] class A main class B,B1,B2,B3,B4,B5,B6 government class C,C1,C2,C3,C4,C5,C6 aiIntegration class D,D1,D2,D3,D4,D5,D6 expandedAI class E,E1,E2,E3,E4,E5,E6 opportunities class F,F1,F2,F3,F4,F5,F6 startup

Resume:

1.- Ott Velsberg is the Chief Data Officer of the Estonian government, appointed in 2018 at age 27.

2.- Estonia has over 99% of government services available online, aiming for a fully digital, paperless government.

3.- Over 90% of Estonian citizens use the internet and have access to mobile phones. Citizen-centricity is key.

4.- Individuals own their personal data and can see when government agencies access it. A consent management platform is being developed.

5.- The once-only principle means citizens should only have to provide their data to the government once.

6.- X-Road is Estonia's data exchange layer allowing secure data transfer between public and private sector organizations.

7.- Estonia aims to make government services proactive, personalized and with zero bureaucracy by utilizing data and AI.

8.- An AI taskforce was formed in 2018 to support AI uptake in the public sector, private sector, and research.

9.- Estonia has gone from 4 government AI use cases in 2018 to 47 today, with 38 more in development.

10.- Reusable AI components like translation, speech synthesis, and text analysis are available as open source for public and private sector use.

11.- Example use cases include hate speech detection, document classification, speech transcription in parliament and courts, fraud detection, and more.

12.- Estonia is investing in its own language technology as major tech companies do not fully support Estonian.

13.- Other example use cases include personalized job recommendations for unemployed citizens, satellite image analysis for agriculture subsidies and flooding.

14.- Barriers include inability to fully automate some processes due to legislation, and restrictions on cloud and data usage.

15.- Lessons learned include keeping projects simple and short, focusing on data quality and governance, reusability, and practical collaboration.

16.- Estonia is developing KrattAI, an interoperable network of public sector AI chatbots and virtual assistants to help citizens navigate government services.

17.- Goals are to reduce time spent on redirecting citizens' requests and enable 24/7 personalized interaction with government.

18.- Projects include chatbots, alternative messaging channels, citizen message classification, speech synthesis, and cross-border collaboration with Finland's AuroraAI.

19.- Opportunities exist to expand AI-based services to private sector channels like Facebook, WhatsApp, voice assistants.

20.- Data governance, common standards, visualization and dissemination of AI insights to decision-makers is crucial.

21.- Limitations still exist in process automation, cloud usage due to regulations, data protection rules restricting some data usage.

22.- PISA education rankings show Estonia 1st in Europe, enabled by personalizing education with AI and digital tools.

23.- Challenges in gaining public trust were overcome with transparency, admitting failures, keeping systems simple, and demonstrating value.

24.- Estonia evaluates AI projects based on societal impact, cost/benefit analysis starting with the problem, not the technology.

25.- Estonia's startup scene benefits from collaboration with government, procuring from startups, and providing education to nurture talent.

26.- Citizens are automatically connected to e-government through ubiquitous ID card, mobile authentication methods enable access.

27.- Open source and code reusability is mandated for publicly funded projects to prevent vendor lock-in and promote innovation.

28.- Transformation of analog to digital data is ongoing, with opportunities to leverage more automation like OCR.

29.- Key project management lessons include assessing competency gaps, focusing on problem vs tech, involving end users, and starting small.

30.- €10M budget for 2 year AI strategy, projects typically €50-60k for pilots, up to €500k for full implementations.

Knowledge Vault built byDavid Vivancos 2024