I School Lectures

Open data infrastructures promise transparency, collaboration, and democratized access to scientific knowledge. But what happens when these same principles enable challenges to scientific consensus? 

Xiang Zheng analyzes large-scale faculty datasets to reveal connections between tenure, incentives, and innovation.

Zackary Okun Dunivin’s work examines cultural phenomena at scale, including political discourse, mythmaking, information systems, and organizational communication.

Online misinformation is a growing concern. Dr. Madeline Jalbert identifies the underlying psychological processes, the role that feelings play, and the criteria people use to assess truth. 

Jerry Chai describes governmental censorship programs and their risks and outlines real-world circumvention and resistance strategies.

Many of today’s most pervasive digital security and privacy threats come not from distant hackers, but from the individuals around us.

Sayash Kapoor is coauthor of AI Snake Oil and author of the newsletter AI as Normal Technology. He explains the stakes of misplaced optimism about AI in science, medicine, and more.

How do users actually feel about deepfakes? Does it matter how the technology is used or what it is called?

Preslav Nakov discusses large language models’ problems with factuality and new tools to use LLMs to fight misinformation.

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.