Podcast: Navigating the Ethical Landscape of Generative AI with Michelle Yi
Learn about cutting-edge developments in AI and data science from the experts who know them best on ODSC’s Ai X Podcast. Each week we release an interview with a leading expert, core contributor, experienced practitioner, or acclaimed instructor who is helping to shape the future of the AI industry through their work or research.
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In this episode of ODSC’s Ai X Podcast, join Michelle Yi, technology leader and board member at Women in Data, for an exploration of the causes, effects, and possible solutions for several of the ethical concerns raised by generative AI models and applications
These ethical concerns can be broken down into several categories:
- Lack of explainability
- Incorporation of human bias Inherent English and European bias of training data
- Lack and impact of regulation, now and in the future
- Fear of apocalyptic outcomes
- Lack of accountability by developers’ impact on the environment
- Effect on labor
In this episode, Michelle will focus on the impact of lack of explainability, legal and regulatory challenges, and how we move forward with this new technology responsibly.
You’ll learn about the current state of bias in the generative AI ecosystem, including the effect of lack of diversity on bias and the limitations of the current slate of tools and techniques used for detecting and mitigating bias.
Next, Michelle will discuss her favorite tools for improving generative AI for bias detection, mitigation, explainability, and transparency. She’ll also address how to get buy-in from practitioners to prioritize privacy, transparency, and safety in Generative AI.
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Finally, you’ll look at ways to balance the needs of safety and security with innovation in the realm of generative AI. Start listening now to fully explore the current landscape of bias in generative AI and ways to create a better future, and don’t forget to subscribe to ODSC’s Ai X Podcast to ensure you never miss an episode. Finally, like what you hear? Leave a review or share it with a friend! You can listen on Spotify, Apple, and SoundCloud.
Originally posted on OpenDataScience.com
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