ACM ByteCast
Kush Varshney - Episode 43
Sep 14, 2023
Host Bruke Kifle interviews Kush Varshney, a distinguished research scientist at IBM Research. They discuss responsible AI, operationalizing RAI principles, risks of generative AI, and coordinating AI safety. Kush also shares insights from his book 'Trustworthy Machine Learning' and his work with IBM's Science for Social Good initiative.
56:19
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Quick takeaways
- Trustworthy machine learning requires attributes like accuracy, reliability, interpretability, transparency, and value alignment.
- Operationalizing responsible AI involves diverse stakeholders, organizational governance, problem specification, and prioritizing ethics.
Deep dives
The Importance of Trustworthy and Responsible AI
The podcast explores the significance of trustworthy and responsible AI in an era where artificial intelligence is rapidly transforming various industries. As AI becomes more ubiquitous, there is a growing concern about potential biases, unintended consequences, and harm. The focus is shifting towards ensuring AI is trustworthy and responsible, distributing its benefits fairly and equitably to society at large. Dr. Kush Varshney, a distinguished research scientist, shares insights into achieving trustworthy AI with a focus on machine learning, algorithmic fairness, and international development.
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