Digital Landscape

Global health professionals Tina Purnat and Elisabeth Wilhelm talk about we can work to stop misinformation by understanding and delivering communities’ information needs.

Computer scientist and “godmother of AI” Fei-Fei Li explains why artificial intelligence and public life are at an inflection point—and contemplates how to unleash positive changes while mitigating risks.

Efforts to share health data across borders snag on legal and regulatory barriers. Before detangling the fine print, let’s agree on overarching principles.

Once called “living computers” by three of the founders of computer science, computational technology has pervaded society to such a degree that the humanities—which are increasingly regarded as less useful than STEM disciplines—are more crucial than ever to making sense of the present.

Recasting generative artificial intelligence as a “public problem” offers new avenues for action.

The narratives trumpeting AI’s progress obscure an underlying logic requiring that everything be translated into the technology’s terms. If it is not addressed, that hegemonic logic will continue to narrow viewpoints, hamper human aspirations, and foreclose possible futures

The perpetual expansion of data-driven machine learning should not be seen as a foregone conclusion. Instead of defaulting to tactics that augment machine learning, we need to consider that in some circumstances the very logic of machine learning might be fundamentally unsuitable to our aims.

Understanding how computer scientists use ground-truthing in the development of artificial intelligence systems can reveal inherent limitations of algorithms and catalyze more thoughtful regulation.

Whether generative AI is seen as a technological revolution or not, it is always embedded within a wider set of values. And the solution is oversight of the corporations building AI.

In an information ecosystem swamped with AI-generated content, public attention has become a finite resource.

Plans for regulating artificial intelligence focus on laying out guardrails for anticipated threats without establishing an early warning system for citizens’ actual experiences or concerns.

Today, social media—and, increasingly, generative artificial intelligence—are constantly experimenting on human subjects, but without institutional checks to prevent harm.