Generative AI 101

In this episode, host Emily Laird airs her AI conspiracy theories and then does what most conspiracy theorists skip: she checks the footnotes. The evidence points away from secret basements and toward the unglamorous forces deciding who wins, including benchmarks that saturate in months, record lobbying budgets, and data center electricity demand on track to nearly double by 2030. She also argues that the riskiest part of an AI agent may be the permissions we hand it, and asks whether universities are learning to govern these tools as fast as they’re adopting them. No secret meeting required; ordinary incentives are doing the work just fine.
 

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Polished emails are making managers less believable: when bosses let AI do most of the writing, the share of employees who rate them as sincere falls from 83% to as low as 40. Host Emily Laird explains why light editing costs almost nothing while AI-written feedback, persuasion, and sympathy quietly burn trust. She covers how to brief a chatbot instead of handing it a shrug, the “excess vocabulary” tells that give machine prose away, and practical fixes that keep your own voice in the inbox. Keep the tool, but know exactly where it costs you.
 

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Your AI meeting recap looks finished, but some of the owners and deadlines in it may be invented. In this episode, host Emily Laird argues that the real work happens in the forty minutes after the meeting, and that “summarize this” is the wrong request. She lays out a better system: extract the same seven fields every time, make the model write “not stated” instead of guessing, and ground every action item in the exact transcript line that supports it.
 

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A 130-page report lands in your inbox with a buried deadline, a half-million-dollar commitment, and one sentence that quietly rewrites policy, and your AI summary mentions none of it. In this episode, host Emily Laird explains why asking AI to make documents shorter is the wrong assignment, and how to interrogate them instead: commitment tables, version comparisons, skeptical-evaluator prompts, and the hunt for what isn’t there. She also breaks down evidence grounding and why no important claim should leave the chat without a page number attached. Confident, beautifully formatted, and occasionally wrong is not the standard you want to bring into a budget meeting.
 

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Anthropic now lets Claude hang up on abusive users, and Microsoft AI chief Mustafa Suleyman warns that training a model to wonder about its own feelings creates nothing more than an expensive echo. In this episode, host Emily Laird cuts through the headlines to explain what a “moral patient” actually is, why a cartoon sheep selling checking accounts proves Suleyman’s point, and why the off switch was never up for debate. The real fight is about vocabulary, training, and two companies planting brand flags on a question science hasn’t answered. You’ll walk away with practical habits for working with chatbots, from swapping insults for precise feedback to reading every AI self-report as output, not testimony.
 

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