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The Data Diva E146 - Cari Miller and Debbie Reynolds
Manage episode 375280192 series 2897113
Debbie Reynolds, “The Data Diva” talks to Cari Miller, Sr. Principal, Practice Lead, Responsible AI Governance & Research at The Center for Inclusive Change. We discuss the lack of employee data rights in the US and Cari Miller's research into the Full Spectrum Employee Data Taxonomy, which includes PII, sensitive voluntary information, credentials, position history, and company/enterprise data. We discuss the implications of AI, such as the over-collection of data, systemic bias, and the need for guardrails. We also discuss New York State's requirement for companies to do audits of AI systems. We conclude that governance does not have to be difficult, but it is important to think through and figure out what makes the most sense. Cari is concerned about the lack of rules and regulations surrounding the use of AI in the employee life cycle, which can lead to discrimination, alienation, and a lack of well-being. She believes that the right guardrails need to be put in place to ensure that AI is used responsibly and that it is tested and built by diverse people. Debbie Reynolds agrees and brings up an example of how AI can be used to target people with disabilities. Cari Miller discussed the need for data minimization, usage assessments, and deletion rules in order to protect data privacy. She also highlighted the need for a US Federal Data Privacy law to avoid companies having to comply with different laws in different states. Finally, she discussed the need to protect children's data, as it is often used to make decisions about them, and her hope for Data Privacy in the future.
257 에피소드
Manage episode 375280192 series 2897113
Debbie Reynolds, “The Data Diva” talks to Cari Miller, Sr. Principal, Practice Lead, Responsible AI Governance & Research at The Center for Inclusive Change. We discuss the lack of employee data rights in the US and Cari Miller's research into the Full Spectrum Employee Data Taxonomy, which includes PII, sensitive voluntary information, credentials, position history, and company/enterprise data. We discuss the implications of AI, such as the over-collection of data, systemic bias, and the need for guardrails. We also discuss New York State's requirement for companies to do audits of AI systems. We conclude that governance does not have to be difficult, but it is important to think through and figure out what makes the most sense. Cari is concerned about the lack of rules and regulations surrounding the use of AI in the employee life cycle, which can lead to discrimination, alienation, and a lack of well-being. She believes that the right guardrails need to be put in place to ensure that AI is used responsibly and that it is tested and built by diverse people. Debbie Reynolds agrees and brings up an example of how AI can be used to target people with disabilities. Cari Miller discussed the need for data minimization, usage assessments, and deletion rules in order to protect data privacy. She also highlighted the need for a US Federal Data Privacy law to avoid companies having to comply with different laws in different states. Finally, she discussed the need to protect children's data, as it is often used to make decisions about them, and her hope for Data Privacy in the future.
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