{"version":1,"type":"rich","provider_name":"Libsyn","provider_url":"https:\/\/www.libsyn.com","height":90,"width":600,"title":"Artificial, but not Intelligent: How biased data can affect AI employment models.","description":"In this episode of Ellis Conversations, Jamil Ellis and retired Federal Magistrate Judge Hon. Ronald L. Ellis continue their two-part conversation on employment discrimination, civil-rights enforcement, and the future of equal opportunity. Part One looked at the history of employment discrimination law, disparate impact, and the role of the EEOC, Justice Department, courts, and civil-rights lawyers in building protections for workers. In Part Two, the conversation turns to a newer and less visible frontier: algorithmic hiring systems. Jamil and Judge Ellis discuss what happens when software platforms, recruiting tools, and AI-driven screening systems sit between job applicants and employers. If these systems score, sort, rank, or filter applicants before a human being ever sees them, are they simply neutral tools \u2014 or are they powerful gatekeepers that must be accountable under civil-rights law? The episode focuses on the legal and moral questions raised by cases like Mobley v. Workday, where plaintiffs allege that algorithmic hiring tools can reproduce bias based on race, age, and disability. Jamil and Judge Ellis explore why machine-learning systems trained on past employment patterns may risk automating old discrimination in new forms, and why transparency, data, state-level regulation, and accountability for technology middlemen may become essential civil-rights issues. At the heart of the episode is a simple question: Civil-rights law cannot stop at the edge of the algorithm. If technology helps decide who gets opportunity, who makes sure the technology is fair?   Related Ellis Conversations Episodes This episode builds on a longer Ellis Conversations thread about civil rights, courts, democracy, and the systems that decide who gets full access to opportunity. Related episodes: \u201cIn Sheep\u2019s Clothing: When facially neutral policies and practices mask intentional discrimination\u201d A direct companion to this episode. We discuss employment discrimination, disparate impact, and why neutral-looking rules can still produce unequal outcomes. https:\/\/podcasts.apple.com\/us\/podcast\/in-sheeps-clothing-when-facially-neutral-policies-and\/id1485019282?i=1000776614155 \u201cThe American Dream at 250\u201d Connects the AI accountability conversation to the larger question of who gets access to the American promise. https:\/\/podcasts.apple.com\/us\/podcast\/the-american-dream-at-250\/id1485019282?i=1000775453951 \u201cLoving Day, The Warren Court, The rights they want to erase\u201d Looks at the Warren Court\u2019s civil-rights legacy and today\u2019s rollback of protections \u2014 background for why new AI systems need civil-rights accountability. https:\/\/podcasts.apple.com\/us\/podcast\/loving-day-the-warren-court-the-rights-they-want-to-erase\/id1485019282?i=1000712580199 \u201cDeliberate, But No Speed\u201d Explores how rights can exist on paper while enforcement is delayed, narrowed, or resisted \u2014 a key theme in thinking about algorithmic discrimination. https:\/\/podcasts.apple.com\/us\/podcast\/deliberate-but-no-speed-how-supreme-court-rulings-have\/id1485019282?i=1000710549539 \u201cClaudine Gay: The Latest Victim in the Debate over DEI, Affirmative Action, and Meritocracy\u201d Connects to how claims of \u201cmerit\u201d and \u201cneutrality\u201d can ignore historical exclusion \u2014 the same concern raised by AI hiring tools marketed as objective. https:\/\/podcasts.apple.com\/us\/podcast\/claudine-gay-the-latest-victim-in-the-debate-over\/id1485019282?i=1000641006303 Full Ellis Conversations archive: https:\/\/podcasts.apple.com\/us\/podcast\/ellisconversationss-podcast\/id1485019282 ","author_name":"ellisconversations's podcast","author_url":"https:\/\/ellisconversations.tumblr.com\/","html":"