AI and Public Interest

AI for the public interest focuses on how to incorporate public interest objectives and KPIs into AI programs run by the government and by private stakeholders whose mission involves promotion of the public interest.

AI and Public Interest

AI can disrupt business models, social structures, employment, and even democracy

But AI can also be used for good: improving care for vulnerable people, reducing social exclusion, detecting discrimination, curing disease, enhancing environmental transition, creating new training opportunities, matching social programs with people who need them most.

AI-Ethics_AI-for-the-public-interest

Research in progress

Research in this area began in the first quarter of 2020.
The research news and events related to the axis will be published progressively on this page.

If you are interested in participating in the research work of this axis, please contact David Bounie or Winston Maxwell.

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6 research areas

Our research and teaching gravitate around the most pressing problems facing high-risk AI use cases, regardless of the kind of technology deployed (GenAI, deep learning, symbolic AI)

Algorithmic explainability

Algorithmic explainability

Explainability sounds like a good idea, but designing the right explanation for the right purpose, the right audience and at the right time requires a deeper understanding of the drivers of explainability, as well as human-centred design methodology used in HCI.
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Algorithmic bias and fairness

Algorithmic bias and fairness

As uncomfortable as this may sound, no algorithmic system can satisfy all definitions of fairness. Choosing the right fairness parameters, and justifying trade-offs such as decreases in accuracy created by debiasing, require multidisciplinary discussions and governance,
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AI and Public Interest

AI and Public Interest

AI systems, particularly those deployed by states, must maximise public interest objectives. These objectives include protection of fundamental rights, but may also involve ways for AI to make citizens’ lives better and to protect the planet.
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Robustness and safety

Robustness and safety

We want AI systems to have high level of accuracy, robustness and cybersecurity. Behind these terms lie a host of complex trade-offs.
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Governance and regulation

Governance and regulation

The European AI Act requires comprehensive risk management systems for high-risk AI systems, involving data governance, risk assessments, technical documentation, human control and ongoing audits.
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Charting AI and AI Ethics

Charting AI and AI Ethics

Clarifying the roles of actors and power structures in the AI ecosystem
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Team & Partners