In a special event hosted by SRI Research Lead Ashton Anderson, Spotify’s Senior Director of Research Mounia Lalmas shared insights into how the platform’s recommender systems craft personalized listening experiences.

In a session at Absolutely Interdisciplinary 2022, SRI Associate Director Peter Loewen, Jonathan Stray of the Berkeley Center for Human-Compatible AI, and Taylor Owen of McGill University discussed what methods and principles might be used to redesign the algorithms that decide what billions of people see in accordance with democratic values.

The Schwartz Reisman Institute’s academic conference hosted eight panels featuring 30 presenters, with sessions offering innovative responses to the challenges of today’s technological landscape, including questions of data privacy, explainable AI, evolutionary approaches to system design, digital rights, and recommender algorithms.

In a recent SRI Seminar, philosopher Seth Lazar of Australian National University explored the implications of the widespread use of algorithms in digital public spaces, and the questions they raise for governance, power, and justification. SRI Graduate Fellow Morgan MacInnes reflects on Lazar’s presentation.

The practice of sortition, in which random selection is used to generate citizens’ assemblies, is a method of political representation as old as democracy itself. In a recent SRI Seminar, Harvard professor Ariel Procaccia discussed how better algorithms can ensure this process accurately represents population demographics. SRI Graduate Fellow Lillio Mok reflects here on the implications of Procaccia’s research.

In a new paper published, SRI Faculty Affiliate Ashton Anderson uses machine learning to demonstrate the 2016 rise in online political polarization was driven by a growth in new, largely right-wing, users, rather than the radicalization of existing users. Anderson’s data challenges the theory that online echo chambers are a primary cause of polarization.

Everyone from users to scholars to regulators has demanded greater transparency around recommender algorithms. What kind of information would be useful to ensure transparency, and can we even agree on what we mean by “transparency”? Guest contributor Jonathan Stray explores these questions on the Schwartz Reisman blog.

How are algorithms influencing the production and consumption of culture? A new white paper on AI, music recommendation, and cultural consumption released by the Schwartz Reisman Institute argues their impacts are profound and far-reaching.

What is the alignment problem and how can we encourage the development of human-aligned AI? What is normativity and how do humans channel appropriate behaviour? If normativity is central to human intelligence, how can it apply to artificial intelligence as well?