Your Power Bill Just Went Up $340 to Fund an AI Capability Nobody Can Measure

Your Power Bill Just Went Up $340 to Fund an AI Capability Nobody Can Measure

Send us Fan Mail [https://www.buzzsprout.com/2567506/fan_mail/new] Three days before this episode, the grid operator serving 67 million people across 13 states cleared its latest power auction at $16.4 billion — $6.3 billion of it data centers. Across the last four auctions, data centers have added $29.4 billion to the electricity bill of those 67 million Americans. That number is filed, audited by an independent market monitor, and hasn't moved. Everything else in the AI conversation has: the forecasters, the CEOs, the EU, and the famous AI 2027 report all moved their timelines this year — some of them twice, in opposite directions. So instead of grading the forecast, we measured the noise. We walk through what AI 2027 actually says (and where its own two lead authors disagree with each other), run four simple filters — publish your update history, tell us if the ruler moved or the world did, know the difference between a mode and a median, and show us the meter — against every major voice in this fight (Kokotajlo, Hassabis, Sutskever, LeCun, Amodei, Huang), and land on the one number in the whole story nobody disputes: what's already on your power bill. Along the way: why a March 2026 Gallup poll found Americans more opposed to a data center moving in next door than a nuclear plant (a 18-point gap), what "Automated Coder" actually means as a definition (it's a layoffs threshold, not a sci-fi milestone), why METR's own randomized controlled trial found AI coding tools slowed experienced developers down while Anthropic's internal survey found the opposite, and the bad-actor scenario the entire report never scores. We also disclose plainly: this show runs on Anthropic's models, so when we're covering Anthropic's regulatory asks, that's held to the same four filters as everyone else's. Resources: https://drive.google.com/file/d/1OMvaT-kVyDfEaE6XzTjS03VtSiTDlWzV/view?usp=drive_link Surviving AI publishes every Monday and Wednesday. Subscribe on YouTube, Apple Podcasts, and Spotify. Please visit our website for more information - Surviving AI: Navigate the Future [https://www.survivingai.co/]

The Most Dangerous AI Misconception, according to a 40-Year IT Veteran, CEO Joe Turso of Hivepoint

Send us Fan Mail [https://www.buzzsprout.com/2567506/fan_mail/new] "AI doesn't replace the human; it enhances the human." That's the flat answer Joe Turso — Co-Founder/CEO of HivePoint Group, a managed service provider that has spent the last several years building an AI-native operating system for small and mid-sized businesses gives when asked whether AI is costing his clients jobs. In this Season 5 closing guest conversation, Joe walks Carlo and Ainsley through what actually happens when small businesses adopt AI without a plan: shadow AI instances popping up department by department, data silos that never talk to each other, and — the episode's real turning point — the most dangerous misconception he sees in the field: that AI can fix a broken process. It can't. It just makes a bad process fail faster. Joe also lays out the framework behind his own product: governance before adoption, "Experience Level Agreements" instead of just SLAs, and a concept he calls the "living persona" — an AI trained closely enough on how you work that it can answer for you when you're out. And in a genuinely candid turn for someone who's built his business on AI, he says plainly: he doesn't trust AI himself — which is exactly why his product keeps every client's data centralized rather than sending it to a model. This episode closes Season 5's human-skills arc from the employer's side: what businesses actually hand to AI, and what they keep human on purpose. Chapters: 00:00 Intro Meet Joe Turso, HivePoint Group 01:54 The philosophy: AI enhances, doesn't replace 04:53 Real-world enhancement the email-triage example 05:46 AI hype vs. reality: shadow AI and data silos in small business 09:15 Is AI different from the cloud, mobile, and cybersecurity waves? 10:15 Why governance has to come before adoption 12:30 What AI adoption failure actually looks like 14:03 Experience Level Agreements vs. SLAs 16:02 Early warning signs your AI is going off the rails 18:06 Trust, feedback, and the "one-person corporation" myth 20:10 Where to start: AI Readiness and the Four Ps 25:33 Hiring in the AI era: culture first, human first 28:41 The "Living Persona" and building HivePoint from scratch 34:24 The most dangerous misconception — and what to tell scared owners 38:22 Where to find Joe, and closing Find Joe and HivePoint Group at hivepointgroup.ai. Subscribe: Apple Podcasts · YouTube · Spotify — new episodes every Monday and Wednesday. Please visit our website for more information - Surviving AI: Navigate the Future [https://www.survivingai.co/]

25.87% of Black Applicants Hit an AI Hiring Wall That Isn't Illegal, Yet

Send us Fan Mail [https://www.buzzsprout.com/2567506/fan_mail/new] "The silence is the tell." That's how this episode opens because if you've sent out dozens of applications and heard almost nothing back, the instinct is to assume something's wrong with you. It isn't. Roughly a quarter of everyone currently unemployed has been searching for 27 weeks or longer, and the average search now runs about six and a half months. Carlo and Ainsley dig into why: most applications today are screened by automated systems before a human ever sees them, and those systems were trained on years of historical hiring data which means they can quietly reproduce old bias at a scale no individual recruiter ever could. Amazon found this out the hard way with its own internal recruiting tool, which it scrapped in 2018 after discovering it was penalizing resumes that simply contained the word "women's." And the pattern goes further: one landmark independent study found that a meaningful share of Black applicants' submissions was consistently filtered out by the same systems across completely different companies — what researchers came to call "algorithmic blackball." So, what do you actually do with that? This episode is built around two practical moves. First, a reality checks most job seekers skip: a real chunk of live job postings may not be genuinely open at all — "ghost jobs" posted for pipeline-building or already spoken for internally — and there's a three-check test (posting age, division layoffs, visible new hires) that takes about ten minutes. Second, the human bypass: weak-tie networking, the kind of loosely connected relationships that get you in front of a person before a system decides you don't belong in the room. Carlo shares his own early-career habit of showing up at conferences outside his industry — and Ainsley connects it directly to decades of research on why acquaintances, not close contacts, are how most people actually find their next role. The episode closes with the Next-Door Challenge: a four-step, ten-minute-a-day plan for anyone in a long search, checking whether your target roles are real, running your resume through a free ATS scanner, reaching out to three people at target companies, and confirming whether your target category is actually growing. Because getting through the door is only half the job; showing up ready when it opens is the other half. Episode Resource: https://drive.google.com/file/d/1gyvmm3mgZvIyJL3B4B9aVvRxWOB7M3nn/view?usp=sharing Chapters: 00:00 Intro — "The silence is the tell" 03:15 Welcome, and the friends who've been searching for a year 04:16 Amazon's discarded recruiting tool 07:57 Proxy variables — how bias hides in plain sight 11:01 The algorithmic blackball stat, and the case for pivoting industries 16:25 Weak ties, Granovetter, and the blind-audition study 19:02 A conference habit that built a cross-industry network 22:17 Naming who this episode is actually for 23:33 The undercounted — who the unemployment number misses 25:57 Setting up the ghost job problem 27:07 Ghost jobs — the three-check reality test 30:41 Where the pivot starts, and the gig-economy question 32:46 Referrals, runway, and the EU vs. US legal gap 35:55 Reactivating a cold network 37:40 The loop AI hiring creates, and the Next Door Challenge 41:38 Carlo's closing story 44:56 Wrap-up, and next Monday 45:31 Bonus: mirror the new industry's language Subscribe: Apple Podcasts · YouTube · Spotify — new episodes every Monday and Wednesday. Please visit our website for more information - Surviving AI: Navigate the Future [https://www.survivingai.co/]

77% of Companies Say They'll Help You When AI Cuts Your Job. Only 19% of Workers Ever Find Out.

Send us Fan Mail [https://www.buzzsprout.com/2567506/fan_mail/new] As of July 2, 2026, AI has been the number-one stated reason for U.S. layoffs for four consecutive months  101,743 jobs cut so far this year with AI explicitly named as the cause (Challenger, Gray and Christmas). That's not a projection. It's a count of what already happened. Meanwhile, a survey of 11,000 HR leaders and employees across seven countries found something almost as alarming: 77 percent of HR leaders say their organizations already have redeployment programs to move at-risk workers into new roles. Only 19 percent of employees have ever experienced or even recognized one. Fifty-eight percentage points. That's not a communication problem; that's a safety net that's functionally invisible to the people it's supposed to catch. (LHH is a talent-solutions and outplacement business worth knowing whose research this is, even though the finding itself is well-sampled and directionally credible.) This episode closes the Responsibility Trilogy — Corporate (S5E6), Government (S5E8), and now Individual with an honest ledger of what each actor actually owns. Corporate had the resources and mostly chose efficiency over people. Government had the mandate and the scale, and where the right programs exist, uptake still lags badly. Neither of those failures disappears just because this episode is about individual action. But waiting for either institution to show up is not a strategy; it's a bet, and four straight months of AI-cited layoffs says it's a losing one. The framework: Invisibility (you're more likely to be cut for being unreadable than for being bad at your job), Inventory (three separate audits AI exposure by task, human skills, relationship inventory — that most people collapse into one), and Leverage (domain depth plus AI fluency, not a pivot to prompt engineering). This isn't just a white-collar problem — the episode makes the case that the same mechanism applies whether you're a software engineer or a shift supervisor at a distribution center. And individual responsibility doesn't mean going it alone: from a nearly-900-member worker association in Africa to a regional training community in Latin America to a program reaching a million small business owners in Nigeria, people are already building this leverage collectively. Season 5 closes here. Season 6 is coming. 📌 Listener Resource: The Invisibility, Inventory, Leverage Workbook — the full framework, three audits, and the Human Edge Challenge. Link in show notes. 🎙️ Subscribe: Apple Podcasts | Spotify | YouTube 🎧 Apple Podcasts: https://podcasts.apple.com/us/podcast/surviving-ai-navigating-ai-job-displacement-and/id1864360631 ▶️ YouTube: https://www.youtube.com/@SurvivingAIRisk 🎙️ Spotify: https://open.spotify.com/show/5rd6gdFu76HPdLBuvV5K0X 🌐 survivingai.co Please visit our website for more information - Surviving AI: Navigate the Future [https://www.survivingai.co/]

The More You Trust AI, the Less You Think. 50% of Executives Are Watching Their Teams Lose It.

Send us Fan Mail [https://www.buzzsprout.com/2567506/fan_mail/new] PwC analyzed more than a billion job postings across 27 countries and found that entry-level roles most exposed to AI are now seven times more likely to require senior-level judgment and leadership skills than less-exposed roles. Those "seniorized" entry-level roles grew 35 percent since 2019 — while every other entry-level role shrank 10 percent in the same period. The ladder didn't get harder to climb. The first few rungs got removed. And the AI-skills wage premium — now 62 percent and climbing — isn't really paying for technical AI operation. It's paying for judgment about AI output. Almost nobody is teaching that. Here's what makes this urgent and measurable: a peer-reviewed Microsoft Research study of 319 knowledge workers found that confidence in AI output and confidence in your own judgment move in opposite directions. The more you trust the tool, the less critical thinking you do. The more you trust yourself, the more scrutiny you apply. The cycle is self-reinforcing — and AI is engineered to sound more confident than it has any right to be. BCG surveyed 70 C-suite and senior executives (BCG also advises those companies on AI deployment — take the finding in that context): 50 percent are already observing de-skilling inside their organizations right now. The skills disappearing fastest: judgment and problem framing. This is not a projection. This is observed, happening today. Season 5 ends here. Every human edge skill this season — empathy, story, negotiation, leadership, physical intelligence — requires someone to decide, in the moment, that their judgment is worth putting on the line. That's this episode. The Human Edge Challenge this week: Tier 1 (five minutes) — name one recurring decision where you just accept AI's first answer. Just notice it. Tier 2 (this week) — run one AI output through first principles before you use it; write down what you actually verified. Tier 3 (ongoing) — choose your AI-free zone and make it your signature. Season 6 is coming, with interviews, new ideas, and survival frameworks. 📌 Listener Resource: The Critical Thinking Audit — the trust inversion explained, the three-tier challenge, and four first-principles questions for evaluating any AI output. https://drive.google.com/file/d/1cZUfaPHnH8s-oCd57jFk4pJH068MsuMf/view?usp=sharing 🎙️ Subscribe: Apple Podcasts | Spotify | YouTube PINNED COMMENT QUESTION (see below) | CHAPTERS BELOW | SUBSCRIBE LINKS BELOW 🎧 Apple Podcasts: https://podcasts.apple.com/us/podcast/surviving-ai-navigating-ai-job-displacement-and/id1864360631 ▶️ YouTube: https://www.youtube.com/@SurvivingAIRisk 🎙️ Spotify: https://open.spotify.com/show/5rd6gdFu76HPdLBuvV5K0X 🌐 survivingai.co Please visit our website for more information - Surviving AI: Navigate the Future [https://www.survivingai.co/]