Regulation of artificial intelligence

Key people

• Frauke RostalskiJurist and university teacher
• Ko Hak-sooChair of the PIPC since 2022
• Einat AlbinIsraeli law scholar

Timeline

• 2016Since 2016, numerous AI ethics guidelines have been published in order to maintain social control over the technology.
• 2019One of the first specific instruments issued was the CONPES 3920 of 2019, the National Policy on Exploitation of Data (Big Data).
• 2020In February 2020, the European Union published a white paper for promoting and regulating AI.
• 2022In June 2022, the government of Canada started a second phase of the Pan-Canadian Artificial Intelligence Strategy.
• 2023In May 2023, a new bill was passed, superseding the 2021 bill.

Read

• Regulating Artificial Intelligence in IndustryDamian M. Bielicki · 2021Book
• Fintech Artificial Intelligence and the LawAlison Lui · 2021Book
• We, the Robots?Simon Chesterman · 2021Book
• Artificial Intelligence and International Economic LawShin-yi Peng · 2021Book

Listen

• AI ReportAlexander Klöpping en Wietse HagePodcast
• {ungeskriptet} - Der Meinungsfreiheit verpflichtet.Ben BerndtPodcast
• The FARcast: Navigating Federal Acquisition Regulations with AIChief Digital and Artificial Intelligence OfficePodcast

By the numbers

• 4.7CO₂ per person (t) — global, 2024 (World Bank)
• 31.1Forest area (% land) — global, 2023 (World Bank)

Debates

• Should AI development be paused to ensure safety?One view: Pausing AI development allows time to establish robust safety protocols and ethical guidelines before advanced systems are widely deployed. · Another: Halting AI development could stifle innovation, cede technological leadership to other nations, and delay solutions to global challenges.Open question
• Who should primarily regulate artificial intelligence?One view: International bodies should lead AI regulation to create consistent global standards and prevent a 'race to the bottom' in safety and ethics. · Another: National governments are better positioned to regulate AI, as they can tailor rules to local societal values, legal frameworks, and economic needs.Open question
• How strict should regulations be on AI's autonomous decision-making?One view: Regulations must be very strict, requiring human oversight and clear accountability for AI systems that make critical decisions affecting lives or rights. · Another: Overly strict regulations on autonomous AI could hinder its potential benefits in areas like healthcare or disaster response, where speed and efficiency are vital.Open question

Glossary

• Artificial Intelligence (AI)Computer systems designed to perform tasks that typically require human intelligence, such as learning, problem-solving, and decision-making.
• Algorithmic BiasSystematic and unfair prejudice in an AI system's output, often due to biased data used during its training.
• AI EthicsA field studying the moral principles and values that should guide the design, development, and use of artificial intelligence.
• Data PrivacyThe protection of personal information collected, stored, and processed by AI systems from unauthorized access or misuse.
• AI GovernanceThe framework of rules, policies, and practices used to manage and control the development and deployment of AI technologies.
• Transparency (in AI)The ability to understand how an AI system works, what data it uses, and why it makes certain decisions.

Careers

Roles this can lead toward

Student research

Published policy papers by One Young India delegates — every delegate leaves published under their own name.

• Leveraging Artificial Intelligence to Prevent Armed Conflict through Predictive Trade PoliciesDaivik Suri
• Global Inflation after the Pandemic: Cyclical Pressures, Structural Drivers, and Policy MisstepsGayatri Satish
• Global Emissions and Carbon Offsetting: Examining Conservational Approaches and Regulatory GapsVinayak Raj
• The Future of Cybersecurity: Is Artificial Intelligence a Friend or Foe?Pradhyumna Prakash
• The Decline of Regional Languages in India – Preserving Linguistic Diversity in a Globalized EraSajinkya Sharan Gupta
• Transforming Education Through Artificial Intelligence: Personalization, Accessibility, and Efficiency in the 21st Century ClassroomSrinja Mallik

Threads 8

Where this connects to other fields — and why it's worth knowing.

• AI & Technology Regulation Law

  New technology comes with a nasty catch called the Collingridge dilemma. Early on, it's easy to steer but you can't yet see what harm it'll cause. By the time the harm is obvious, the tech is so woven into daily life you can't steer it anymore. Too soon to know, too late to fix.

• The Industrial Revolution History

  When factories first roared to life, kids worked the machines and people got maimed for years before any law said 'stop.' The Luddites who smashed looms weren't dumb tech-haters; they were workers watching their jobs vanish in real time. Every powerful new tool shows up first and the rulebook limps in late.

• Philosophy of Technology Philosophy

  The printing press, the car, and the social media feed each changed how people behave long before any rules caught up. By the time we notice a tool has rewired us, the change is already baked in and hard to undo. New power reshapes us first and gets its rulebook second, every single time.

• Religious Authority Religion

  More and more, we trust AI answers we can't fully question or understand. History says that's a familiar move: priesthoods gained power precisely by guarding mysteries no one could interrogate. Something we can't see inside easily becomes an oracle we simply obey.

• Corporate Governance Business

  Getting an AI to actually do what humans want is an old business puzzle in new clothes. Bosses have always struggled to control workers whose goals differ and whose actions they can't fully watch. Now swap 'worker' for 'AI': how do you steer something you can't monitor and that might not share your aims?

• Procedure & Evidence Law

  In court, you have the right to ask 'why?' and get reasons for a decision against you. But an AI can spit out a verdict with no explanation it can give. That breaks the basic tool courts use to keep power in check.

• Logic, Proof & Verification Mathematics

  Engineers can mathematically prove a bridge or a computer chip will work, guaranteed. But an AI that learns on its own can only be tried out on examples, never fully proven safe. Using it means giving up the certainty engineering usually insists on.

• Free Will and Responsibility Philosophy

  To blame someone, we usually need a person who could have chosen differently. But when a complex AI with no single author causes harm, there's no clear "someone" to point at. That old philosophy puzzle about free will suddenly becomes a real courtroom question: who pays?