AI bias

LLMs consider unrelated information when recommending medical treatments

A big language model (LLM) deployed to make treatment recommendations might be...

3 Questions: How one can help students recognize potential bias of their AI datasets

Q: How does bias get into these datasets, and the way can...

Navigating AI Bias: A Guide for Responsible Development

AI is revolutionizing industries worldwide, but with this transformation comes significant responsibility. As these systems increasingly drive critical business decisions, firms face mounting risks related to bias, transparency, and compliance. The implications of unchecked...

These recent AI benchmarks could help make models less biased

“We've got been form of stuck with outdated notions of what fairness and bias means for a very long time,” says Divya Siddarth, founder and executive director of the Collective Intelligence Project, who didn't...

Unmasking Bias in Artificial Intelligence: Challenges and Solutions

The recent advancement of generative AI has seen an accompanying boom in enterprise applications across industries, including finance, healthcare, transportation. The event of this technology may even result in other emerging tech similar to...

Empowering systemic racism research at MIT and beyond

On the turn of the twentieth century, W.E.B. Du Bois wrote concerning...

The Ethical Minefield of AI Scaling: Constructing Trustworthy AI for Large-Scale Deployments

A couple of years ago, a tutoring company paid a hefty legal settlement after its artificial intelligence powered recruiting software disqualified over 200 applicants based solely on their age and gender. In one other...

The Pillars of Responsible AI: Navigating Ethical Frameworks and Accountability in an AI-Driven World

Within the rapidly evolving realm of recent technology, the concept of ‘Responsible AI’ has surfaced to handle and mitigate the problems arising from AI hallucinations, misuse and malicious human intent. Nonetheless, it has proven...

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