I School Lectures

Computer security traditionally protects digital systems from criminals or governments. Thomas Ristenpart explores “known-adversary” threat models, in which the adversary is an intimate partner, family member, or other close acquaintance.

Oliver Korn explores research into the role of embodiment in both physical and virtual spaces. 

Online abuse is getting worse, and it disproportionately harms people already marginalized in society. Miranda Wei outlines new ways to think about online abuse and what we can do to stop it.

Security and privacy solutions designed in the West can fall apart when applied to other regions, leaving end-users at risk.

The rapid adoption of generative AI has created a cycle where personal information cascades perpetually. Niloofar Mireshghallah examines generative AI’s interplay between data, people, and models.

How might AI reshape the sensory norms and moral economies of discernment of American mental healthcare?

The death by suicide of disabled Black teen Sewell Setzer III and his family’s lawsuit against chatbot company Character.AI have opened up renewed debate and uncertainty about AI safety.

Algorithms and AI impact access to work and other essential resources, especially for low-income people. Lily Irani describes  the policies, practices, and algorithms of suspicion that control workers’ access to wages and work on digital platforms.

Venture capital investors push nascent tech firms to scale as quickly as possible to inflate the value of their asset. The gains generated by tech startups are funneled into the pockets of a small cadre of elite investors and entrepreneurs, leaving workers and users to bear many of the costs and risks.

Biobanks and electronic health records systems are increasingly used to train and develop machine learning and artificial intelligence models, raising concerns for social equity and justice.

Professor Deirdre K. Mulligan was principal deputy U.S. chief technology officer at the White House Office of Science and Technology Policy and director of the National Artificial Intelligence Initiative Office (NAIIO) in the Biden-Harris Administration.

Who should make decisions about ethical and responsible technology deployments? And how do impacted communities make political claims over data technologies?

When identifying organ transplant recipients — and in other matching problems — is it better to find a match more quickly, or more slowly and carefully? Afshin Nikzad’s research weighs the tradeoffs in different circumstances.

Can we combine data from satellites, mobile phones, and financial services providers with machine learning to identify the neediest people and better target humanitarian aid?

Timothy Tangherlini uses a computational folkloristic approach to analyze conversations on the social media platform Parler leading up to the January 6th attack on the Capitol.

Jevin West breaks down the threats of scientific disinformation, predatory publishing and pseudoscience, the reproducability crisis, and generative AI.

Narges Mahyar discusses community-centered tools that empower the general public to engage in real-world sociotechnical problems.

Diag Davenport outlines an unexpected pattern of bias underlying officers’ choices to use or not use an algorithmic risk score.

Analyses of police misconduct rely heavily on self-reported law-enforcement data. Dean Knox proposes a research algorithm to deal with unreliable and distorted data.

Alex Chohlas-Wood demonstrates two ways that data science and information technology can improve outcomes in the criminal legal system.