Research Schwartz Reisman Institute Research Schwartz Reisman Institute

AI agents pose new governance challenges

How do we successfully govern AI systems that can act autonomously online, making decisions with minimal human oversight? SRI Faculty Affiliate Noam Kolt explores this challenge, highlighting the rise of AI agents, their risks, and the urgent need for transparency, safety testing, and regulatory oversight.

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Research Schwartz Reisman Institute Research Schwartz Reisman Institute

Unequal outcomes: Tackling bias in clinical AI models

A new study by SRI Graduate Affiliate Michael Colacci sheds light on the frequency of biased outcomes when machine learning algorithms are used in healthcare contexts, advocating for more comprehensive and standardized approaches to evaluating bias in clinical AI.

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Research Schwartz Reisman Institute Research Schwartz Reisman Institute

Safeguarding the future: Evaluating sabotage risks in powerful AI systems

As AI systems grow more powerful, ensuring their safe development is critical. A recent paper led by David Duvenaud with contributions from Roger Grosse introduces new methods to evaluate AI sabotage risks, providing insights into preventing advanced models from undermining oversight, masking harmful behaviors, or disrupting human decision-making.

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Research Jo-Ann Osei Twum, Michael Colacci, Felix Menze Research Jo-Ann Osei Twum, Michael Colacci, Felix Menze

Innovating care: Exploring the role of AI in Ontario’s health sector

What opportunities and challenges are there for the use of AI in healthcare? At a recent SRI workshop, experts explored how AI is transforming Ontario's healthcare sector, highlighting its potential to improve care and exploring pressing challenges around patient involvement, health equity, and trustworthy implementation.

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