What does the rise and fall of "wokeness" mean for AI ethics and in shaping the future of AI technology?
Our host, Carter Considine explores the historical roots of AI ethics with a focus on bias in machine learning algorithms. He’s looking at the emphasis on diversity, equity, and inclusion (DEI) frameworks. As DEI has dominated AI ethics, especially with concerns about racial and gender bias in AI systems, Carter’s questioning whether this approach will remain central as societal and economic dynamics shift.
Two main schools of thought have emerged within AI ethics: one focusing on existential risks posed by artificial general intelligence (AGI), and another concerned with algorithmic bias and its social consequences.
Today, we’re at a turning point of sorts in the evolving landscape of AI. We could call it a "Reformation" in which wokeness, once revolutionary, is now seen as increasingly outdated. As a result–with DEI-driven frameworks becoming less relevant–AI ethics will likely transition towards a more individualized, business-centric model that prioritizes technical solutions over abstract principles.
Looking ahead, moral quandaries around AI will probably move away from ideological frameworks toward a more practical, value-driven methodology. For users, this means a great deal more personalization, giving us more control over how AI systems behave, and making transparency a central concern. Companies will be under pressure to demonstrate real-world value, aligning AI practices with measurable outcomes and business goals.
As the technology evolves, we’ll see an emphasis on technical competence and individual autonomy while discarding the reliance on broad, one-size-fits-all ethical standards. Ultimately, the survival of AI ethics will depend on its ability to adapt to real-world needs, shifting from theory to actionable, transparent, and user-focused practices.
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More info, transcripts, and references can be found at ethical.fm
