エピソード

  • 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

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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.
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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.
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    8 分
  • Understanding Ethical AI: Shadow AI Tools: How to Audit

    Understanding Ethical AI: Shadow AI Tools: How to Audit
    2026/07/14
    In this episode, in a world where AI is making life-or-death decisions faster than regulators can blink, Ethical AI: Let's Make Sense Of This Sht cuts straight through the hype and hand-wringing to ask what "doing the right thing" actually looks like when the code ships.

    This episode digs into the real friction points—algorithmic bias that quietly screws over entire demographics, the privacy tightrope companies walk between useful data and creepy surveillance, and the accountability gaps that leave no one responsible when models go off the rails. You'll hear unfiltered takes on whether current ethics frameworks are toothless theater, how organizations can bake genuine safeguards into their pipelines without killing innovation, and why ignoring these issues now guarantees bigger headaches (and lawsuits) later.

    Ready to stop nodding along at buzzwords and start making sense of the mess? Hit play, then drop your own hot takes in the comments—we're listening.

    📩 Have questions or want to share your experience? Reach out at ethical@senseofthisshit.com.
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    8 分
  • Navigate Ethical AI: AI Hallucination Risk

    Navigate Ethical AI: AI Hallucination Risk
    2026/06/30
    In this episode, welcome to Ethical AI : Let's Make Sense Of This Sh*t. I'm Morgan. Team leads and marketers who send AI generated drafts straight to clients face a clear problem. AI hallucination risk turns a fast draft into a liability when facts shift without warning.

    Welcome to Ethical AI : Let's Make Sense of This Sh*t. I'm Morgan. Team leads and marketers who send AI generated drafts straight to clients face a clear problem. AI hallucination risk turns a fast draft into a liability when facts shift without warning. However, these errors often hide inside confident sentences that read well at first glance. For example, a report might invent a regulation date or misstate a competitor statistic, and the mistake travels straight to the client inbox. Meanwhile, guidance from the EU AI Act and NIST frameworks stresses human checks on outputs used in professional settings. The reality is that speed without review creates downstream fixes that cost time and trust. In other words, a short verification pass before delivery catches the issues while they remain internal.

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    9 分
  • Navigate Ethical AI: AI Vendor Due Diligence

    Navigate Ethical AI: AI Vendor Due Diligence
    2026/06/29
    In this episode, welcome to Ethical AI : Let's Make Sense Of This Sh*t. I'm Morgan.

    Welcome to Ethical AI : Let's Make Sense of This Sh*t. I'm Morgan. Many teams now face a common problem when they add new software because AI features hide inside most modern SaaS tools. Team leads and marketers often sign contracts based on price or speed alone however they later discover hidden risks around data use and bias. This episode focuses on AI vendor due diligence and gives you five practical questions to ask before any purchase. Educators and knowledge workers share the same challenge because a quick decision can expose the whole group to copyright issues or unexpected training data practices. The reality is that regulators already watch these deals closely therefore skipping review now costs more later.

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    📩 Have questions or want to share your experience? Reach out at ethical@senseofthisshit.com.
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    8 分
  • Navigate Ethical AI: Copyright and AI Output

    Navigate Ethical AI: Copyright and AI Output
    2026/06/06
    In this episode, ever feel like AI is rewriting the rules of society faster than we can agree on what “fair” even means? In this no-BS episode of Ethical AI: Let’s Make Sense Of This Sh*t, we cut through the hype and the hand-wringing to confront the real ethical landmines hiding in the code we’re already using every day.

    We dig into algorithmic bias that quietly shapes hiring, lending, and policing, unpack who’s actually accountable when an AI screws up, and explore whether regulation can keep pace without killing innovation. You’ll hear straight talk on transparency, data consent, and the uncomfortable truth that “ethical AI” isn’t a feature you toggle—it’s a constant, messy negotiation we all have to join.

    Ready to stop nodding along at AI headlines and start thinking critically about what’s next? Hit play, then drop your toughest question in the comments—we’ll tackle the best ones in future episodes.

    📩 Have questions or want to share your experience? Reach out at ethical@senseofthisshit.com.
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    6 分
  • Navigate Ethical AI: AI at Work: Disclosure Scripts

    Navigate Ethical AI: AI at Work: Disclosure Scripts
    2026/06/06
    In this episode, welcome to Ethical AI : Let's Make Sense Of This Sh*t. I'm Morgan. If you lead a marketing team or manage projects where tools like copilots now shape first drafts and research summaries, you already know the stakes. Using those systems speeds up routine work, yet it also raises questions about credit, ownership, and client expectations.

    Welcome to Ethical AI : Let's Make Sense of This Sh*t. I'm Morgan. If you lead a marketing team or manage projects where tools like copilots now shape first drafts and research summaries, you already know the stakes. Using those systems speeds up routine work, yet it also raises questions about credit, ownership, and client expectations. Many organizations still lack clear habits for noting when an assistant contributed text or ideas. Without a simple script, one person might flag the contribution while another stays silent, and the inconsistency creates friction later. Regulators in Europe have started reviewing similar transparency gaps under the EU AI Act summaries, and guidance from the FTC points in the same direction. The result is that teams spend extra time clarifying what came from a person and what came from a model. A short disclosure line placed at the right moment solves mos

    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.
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    6 分