AI Regulatory Challenges - OECD...2020/02/26 · AI Regulatory Challenges Theodoros Evgeniou...

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AI Regulatory Challenges

Theodoros EvgeniouProfessor Decision Sciences and Technology Management,INSEADtheodoros.evgeniou@insead.edu

[Presentation available on LinkedIn]

All previous technologies were at best decision support tools

AI can take increasingly complex decisions

It is essential to align the regulation with key characteristics of the underlying technology (AI).

Experience + Learning (Human) Intelligence

Experience for Humans = (Big) Data for Machines

(Big) Data + Machine Learning Artificial Intelligence

Learning is at the Core of Intelligence

Big Data vs Machine Learning vs AI

5 Key AI Challenges for Policy Makers

Challenge 1: “Buying AI” vs “Hiring AI”

Challenge 2: “Values Built in AI” vs “Values Built in Data”

Challenge 3: Managing AI Trade-offs

Challenge 4: Managing Uneven AI Innovation and Adoption

Challenge 5: Playing Catch-up with Rapid Technological Innovation

Challenge 1

“Buying AI” vs “Hiring AI”

Challenge 2

“Values Built in AI” vs “Values Built in Data”

Emphasis on “AI based on European values” and call for EU to “export its values across the world.”

European Commission White Paper on AI,February 19, 2020

Traditional Tech: People Write the Rules/Programs

Computer Output

ComputerData

Output Program

(Adopted from Domingos, 2017)

AI Tech: Machines Write the Rules/Programs

DataProgram

AI is the Mirror of Data,Data is the Mirror of the Culture

Challenge 3

Managing AI Trade-offs

Balancing:- AI Performance - Explainability (What?)- Fairness (many versions)- Privacy- Security- IP- Incentives- …

“The Price of Values”?

The “AI Polanyi’s Paradox”?

Machines, like humans, know more than they can tell

Explainable AI?

Challenge 4

Managing Uneven AI Innovation and Adoption

AI Sticky Factors:- Data- Skills- Culture- Context

Challenge 5

Playing Catch-up with Rapid Technological Innovation

Federated Learning

Privacy Preserving AI

Quantum Computing

Small Data Learning

Encryption and AI

Adversarial Attacks

Multi-Task Learning

…AI requires a Holistic Approach…

…hence a (Urgent) Need for Interdisciplinary Work…

There is a Lot to Do...

Data Engineering and Quality Management

Machine Learning and Analytics

Project Management

IT infrastructure and Management

Organizational Change

Industry Transformation

Regulation

Principles and Philosophy (e.g., Ethics)

A Final Key Message: AI requires a Holistic Approach

5 Key AI Challenges for Policy Makers

AsiaEurope Middle East| |

Theodoros EvgeniouProfessor Decision Sciences and Technology Management,INSEADtheodoros.evgeniou@insead.edu

[Presentation available on LinkedIn]

AI Regulatory Challenges - OECD...2020/02/26 · AI Regulatory Challenges Theodoros Evgeniou...

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