『Ethical AI: Making Sense of It』のカバーアート

Ethical AI: Making Sense of It

Ethical AI: Making Sense of It

著者： Morgan
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This show is for managers, marketers, educators, and knowledge workers (30–55) who use ChatGPT-class tools daily and need workplace guardrails, not prompt-engineering tricks or doomsday hype. We own responsible AI policy — disclosure, bias checks, copyright, training-data awareness, and team norms — in copy-paste checklist format. We never compete with `digital-privacy-lets-make-sense-of-this-sht` on password managers and 2FA, or with therapy slugs on AI-anxiety healing narratives. We also avoid the overcrowded "10 ChatGPT hacks" lane. Each episode answers one workplace question with a script or policy paragraph teams can adopt this week. --- Topics include: Ethical AI. Audio for this show is produced with AI assistance. Episodes are researched, scripted, and reviewed for accuracy before release.

Become a supporter of this podcast: https://www.spreaker.com/podcast/ethical-ai-making-sense-of-it--7076292/support.© 2026 Let's Work This Sh*t Out 経済学
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  • AI in Hiring: Bias Checks Before You Trust the Shortlist

    AI in Hiring: Bias Checks Before You Trust the Shortlist
    2026/08/24
    In this episode, we cover Hiring bias. The conversation opens with: Welcome to Ethical AI: Making Sense of It. I'm Morgan. If you lead a hiring team or review candidate shortlists, you have probably noticed AI tools that promise faster screening. However, those same tools can embed bias before anyone sees the results. Because many platforms train on past hiring records, they sometimes favor certain backgrounds while filtering others. Therefore, a bias check before you trust the shortlist protects fairness in your Listen for the key context, practical takeaways, and the most important points to carry forward.

    Welcome to Ethical AI: Making Sense of It. I'm Morgan. If you lead a hiring team or review candidate shortlists, you have probably noticed AI tools that promise faster screening. However, those same tools can embed bias before anyone sees the results. Because many platforms train on past hiring records, they sometimes favor certain backgrounds while filtering others. Therefore, a bias check before you trust the shortlist protects fairness in your process. In other words, adding one review step keeps decisions grounded in current standards rather than old patterns. For example, a short note in your team chat can flag when AI contributed to the initial list. Meanwhile, guidance from the EU AI Act and related reports calls attention to these risks in employment tools. Although speed matters, it does not replace human review on protected characteristics. Since your role involves choices that

    Subscribe for weekly explainers — no guru fluff, just tactics you can apply this week.

    📩 Have questions or want to share your experience? Reach out at ethical@senseofthisshit.com.
    💛 Join Our Supporters Club ($3 a month) 💛 Ad-free listening + early episodes — help keep independent media alive. Click Here: https://www.spreaker.com/podca...
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    8 分
  • Understanding Ethical AI: Year-End AI Audit

    Understanding Ethical AI: Year-End AI Audit
    2026/08/17
    In this episode, what happens when the algorithms deciding your job, loan, or medical care start reflecting human biases we never intended? In this episode of Ethical AI: Making Sense of It, we cut through the hype to explore how organizations can build AI systems that are fair, transparent, and accountable—without sacrificing innovation.

    We unpack real-world cases of algorithmic bias, examine frameworks for ethical decision-making, and reveal practical strategies leaders are using to embed responsibility into every stage of AI development. From governance models to stakeholder engagement, you’ll gain clear insights on turning ethical principles into competitive advantage.

    Ready to future-proof your AI initiatives? Listen now and join the conversation on building technology that truly serves humanity.

    📩 Have questions or want to share your experience? Reach out at ethical@senseofthisshit.com.
    💛 Join Our Supporters Club ($3 a month) 💛 Ad-free listening + early episodes — help keep independent media alive. Click Here: https://www.spreaker.com/podca...
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    6 分
  • Navigate Ethical AI: AI in the Classroom

    Navigate Ethical AI: AI in the Classroom
    2026/07/14
    In this episode, in a world where AI is making life-altering decisions faster than we can spell "accountability," figuring out what's actually ethical feels like decoding a glitchy algorithm. This episode cuts through the hype and hand-wringing to tackle the messy reality of building AI that doesn't screw people over.

    We unpack the real trade-offs between speed and safety, why bias keeps sneaking into "neutral" systems, and how companies (and regulators) are fumbling—or finally stepping up—their responsibility. You'll walk away with a clearer lens on the frameworks that actually work versus the ones that just sound good in a press release.

    Ready to stop guessing and start understanding? Hit play, then subscribe so you never miss an episode that makes the AI chaos a little less chaotic.

    📩 Have questions or want to share your experience? Reach out at ethical@senseofthisshit.com.
    💛 Join Our Supporters Club ($3 a month) 💛 Ad-free listening + early episodes — help keep independent media alive. Click Here: https://www.spreaker.com/podca...
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    8 分
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