Safety Measures for Bias and AI - an Interview with Dr. Emily Barnes
I am thrilled to have had the opportunity to speak with Dr. Emily Barnes, Chief Digital Learning Officer, Lindenwood University, who discussed the critical issue of bias in artificial intelligence, particularly in academia, research, and tech.
Dr. Barnes shared her motivation for specializing in this field and explains the significance of mitigating AI bias to prevent adverse effects now and on future generations.
Real-world examples illustrate how biases in algorithms can disadvantage certain groups in ways that we may not have thought about.
Dr. Barnes also suggests strategies for companies to combat AI bias, such as creating diverse teams and demanding data transparency.
Key Takeaways:
- The safety measures for bias and AI (00:00:01)
Dr. Barnes shares the importance of safety measures for bias in AI and its impact on society. - Real-life example of bias in AI (00:06:37)
An example of Amazon's algorithm favoring male applicants due to biased historical data is discussed. - Actions for companies to address bias in AI (00:09:29)
Emily suggests steps for companies to address bias in AI, including forming task forces and ensuring diversity in IT departments. - The consequences of not addressing bias in AI (00:17:51)
The societal and business risks of not addressing bias in AI, emphasizing the need for proactive measures. - Taking personal responsibility for bias in AI (00:22:15)
Dr. Barnes encourages individuals to understand the impact of AI in their lives and demand transparency and ethical use of AI. - Safety Measures for Bias in AI (00:23:47)
Discussion on personal and corporate awareness of bias in AI and its potential future impact on revenue.
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Cheering you on, always.
- Sheryl
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