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This VentureBeat article highlights PAI’s latest white paper on how collecting and using data can accentuate various forms of biases.
A critical dimension is equity in access to both deepfake detection tools and the capacity to use them.
Alexis Conneau’s work has helped build AI systems that can understand dozens of languages with startling accuracy.
A crisis over a suspicious confession video in Myanmar underscores why we need a coordinated response to discern fact from fiction.
A list of incidents that caused, or nearly caused, harm aims to prompt developers to think more carefully about the tech they create.
A white paper from Partnership on AI provides timely advice on tackling the urgent challenge of navigating risks of AI research and responsible publication.
Secure sourcing will better accommodate readers’ right to know, without compromising journalists’ and sources’ rights.
At artificial-intelligence conferences, researchers are increasingly alarmed by what they see.
To ensure success, people behind algorithm auditing startups increasingly suggest stronger industrywide regulation and standards.
In recent years, the focus of AI developers has been to implement technologies that replace basic human labor. Katya Klinova shares why this is the wrong application for AI.
Madhulika Srikumar chats about managing the risks of AI research, how should the AI community think about the consequences of their research, and more.
On this episode Madhulika Shrikumar discusses their recent work Managing Risk and Responsible Publication.
Rosie Campbell discusses a white paper exploring the current debate over publication norms in AI research.
