A presentation about recent advancements in AI developed for gene sequencing/analysis, predictive analysis, diagnosis and treatment plan development for cancer patients with a specific focus on Melanoma. Additional conversation will revolve around social considerations of AI and the hope that, via artificial intelligence and the elimination of human error, processes and activities will become more efficient, beneficial, and advantageous for humanity. But is this the case? Will the tide of AI raise all boats? How does human bias influence the systems and structures of AI models, such as large language models, ethics, selective data, and models emerging from non-diverse institutions? This session will present an engaging, interactive discussion about bias in the world of generative AI from a few perspectives, including:
- The back end (coders, developers, owners, technologists, industry perspectives)
- How technology generates vastly disparate consequences for different communities, and
- Best practices
The session will also consider how different communities feel about AI tools such as, facial recognition, surveillance, identity data and predictive modeling, what historical events or circumstances should cause people to be cautious or concerned, where does rational concern turn into paranoia and conspiracy theory, and, ultimately, what does the future look like for AI in cancer research and other areas?
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