The Rip Current with Jacob Ward

The United States has a split personality when it comes to AI data centers. On the one side, tech leaders (and the White House) celebrate artificial intelligence as a symbol of national power and economic growth. But politicians from Bernie Sanders to Ron DeSantis point out that when it shows up in our towns, it drains water, drives up electricity prices, and demands round-the-clock power like an always-awake city.Every AI prompt—whether it’s wedding vows or a goofy image—fires up racks of servers that require enormous amounts of electricity and water to stay cool. The result is rising pressure on local water supplies and power grids, and a wave of protests and political resistance across the country. I’m covering that in today’s episode, and you can read the whole report over at Hard Reset.

For most of modern history, regulation in Western democracies has focused on two kinds of harm: people dying and people losing money. But with AI, that’s beginning to change.This week, the headlines point toward a new understanding that more is at stake than our physical health and our wallets: governments are starting to treat our psychological relationship with technology as a real risk. Not a side effect, not a moral panic, not a punchline to jokes about frivolous lawyers. Increasingly, I’m seeing lawmakers understand that it’s a core threat.There is, for instance, the extraordinary speech from the new head of MI6, Britain’s intelligence agency. Instead of focusing only on missiles, spies, or nation-state enemies, she warned that AI and hyper-personalized technologies are rewriting the nature of conflict itself — blurring peace and war, state action and private influence, reality and manipulation. When the person responsible for assessing existential threats starts talking about perception and persuasion, that stuff has moved from academic hand-wringing to real danger.Then there’s the growing evidence that militant groups are using AI to recruit, radicalize, and persuade — often more effectively than humans can. Researchers have now shown that AI-generated political messaging can outperform human persuasion. That matters, because most of us still believe we’re immune to manipulation. We’re not. Our brains are programmable, and AI is getting very good at learning our instructions.That same playbook is showing up in the behavior of our own government. Federal agencies are now mimicking the president’s incendiary online style, deploying AI-generated images and rage-bait tactics that look disturbingly similar to extremist propaganda. It’s no coincidence that the Oxford University Press crowned “rage bait” its word of the year. Outrage is no longer a side effect of the internet — it’s a design strategy.What’s different now is the regulatory response. A coalition of 42 U.S. attorneys general has formally warned AI companies about psychologically harmful interactions, including emotional dependency and delusional attachment to chatbots and “companions.” This isn’t about fraud or physical injury. It’s about damage to people’s inner lives — something American law has traditionally been reluctant to touch.At the same time, the Trump administration is trying to strip states of their power to regulate AI at all, even as states are the only ones meaningfully responding to these risks. That tension — between lived harm and promised utopia — is going to define the next few years.We can all feel that something is wrong. Not just economically, but cognitively. Trust, truth, childhood development, shared reality — all of it feels under pressure. The question now is whether regulation catches up before those harms harden into the new normal.Mentioned in This Article:Britain caught in ‘space between peace and war’, says new head of MI6 | UK security and counter-terrorism | The Guardianhttps://www.theguardian.com/uk-news/2025/dec/15/britain-caught-in-space-between-peace-and-war-new-head-of-mi6-warnsIslamic State group and other extremists are turning to AI | AP Newshttps://apnews.com/article/islamic-state-group-artificial-intelligence-deepfakes-ba201d23b91dbab95f6a8e7ad8b778d5‘Virality, rumors and lies’: US federal agencies mimic Trump on social media | Donald Trump | The Guardianhttps://www.theguardian.com/us-news/2025/dec/15/trump-agencies-style-social-mediaUS state attorneys-general demand better AI safeguardshttps://www.ft.com/content/4f3161cc-b97a-496e-b74e-4d6d2467d59c

President Trump has signed a sweeping executive order aimed at blocking U.S. states from regulating artificial intelligence — arguing that a “patchwork” of laws threatens innovation and America’s global competitiveness. But there’s a catch: there is no federal AI law to replace what states have been doing.In this episode, I break down what the executive order actually does, why states stepped in to regulate AI in the first place, how this move conflicts with public opinion, and why legal experts believe the fight is headed straight to the courts.This isn’t just a tech story. It’s a constitutional one.Read the full analysis in my weekly column at HardResetMedia.com.

This week I sat down with the woman who permanently rewired my understanding of human nature — and now she’s turning her attention to the nature of the machines we’ve gone crazy for.Harvard psychologist Mahzarin Banaji coined the term “implicit bias” and has conducted research for decades into the blind spots we don’t admit even to ourselves. The work that blew my hair back shows how prejudice has and hasn’t changed since 2007. Take one of the tests here — I was deeply disappointed by my results. More recently, she’s been running new experiments on today’s large language models.What has she learned?They’re far more biased than humans.Sometimes twice or three times as biased.They show shocking behavior — like a model declaring “I am a white male” or demonstrating literal self-love toward its own company. And as their most raw and objectionable responses are papered over, our ability to understand just how prejudiced they really are is being whitewashed, she says.In this conversation, Banaji explains:Why LLMs amplify bias instead of neutralizing itHow guardrails and “alignment” may hide what the model really thinksWhy kids, judges, doctors, and lonely users are uniquely exposedHow these systems form a narrowing “artificial hive mind”And why we may not be mature enough to automate judgement at allBanaji is working at the very cutting edge of the science, and delivers a clear and unsettling picture of what AI is amplifying in our minds.00:00 — AI Will Warp Our DecisionsBanaji on why future decision-making may “suck” if we trust biased systems. 01:20 — The Woman Who Changed How We Think About BiasJake introduces Banaji’s life’s work charting the hidden prejudices wired into all of us. 03:00 — When Internet Language Revealed Human BiasHow early word-embedding research mirrored decades of psychological findings.05:30 — AI Learns the One-Drop RuleCLIP models absorb racial logic humans barely admit. 07:00 — The Moment GPT Said “I Am a White Male”Banaji recounts the shocking early answer that launched her LLM research. 10:00 — The Rise of Guardrails… and the Disappearance of HonestyWhy the cleaned-up versions of models may tell us less about their true thinking.12:00 — What “Alignment” Gets Fatally WrongThe Silicon Valley fantasy of “universal human values” collides with actual psychology.15:00 — When AI Corrects Itself in Stupid WaysThe Gemini fiasco, and why “fixing” bias often produces fresh distortions.17:00 — Should We Even Build AGI?Banaji on why specialized models may be safer than one general mind.19:00 — Can We Automate Judgment When We Don’t Know Ourselves?The paradox at the heart of AI development.21:00 — Machines Can Be Manipulated Just Like HumansCialdini’s persuasion principles work frighteningly well on LLMs. 23:00 — Why AI Seems So Trustworthy (and Why That’s Dangerous)The credibility illusion baked into every polished chatbot.25:00 — The Discovery of Machine “Self-Love”How models prefer themselves, their creators, and their own CEOs. 28:00 — The Hidden Line of Code That Made It All Make SenseWhat changes when a model is told its own name. 31:00 — Artificial Hive Mind: What 70 LLMs Have in CommonThe narrowing of creativity across models and why it matters.34:00 — Why LLM Bias Is More Extreme Than Human BiasBanaji explains effect sizes that blow past anything seen in psychology. 37:00 — A Global Problem: From U.S. Race Bias to India’s Caste BiasHow Western-built models export prejudice worldwide.40:00 — The Loan Officer Problem: When “Truth to the Data” Is ImmoralA real-world example of why bias-blind AI is dangerous. 43:00 — Bayesian Hypocrisy: Humans Do It… and AI Does It MoreModels replicate our irrational judgments — just with sharper edges. 48:00 — Are We Mature Enough to Hand Off Our Thinking?Banaji on the risks of relying on a mind we didn’t design and barely understand.50:00 — The Big Question: Can AI Ever Make Us More Rational?

Australia just imposed a blanket ban on social media for kids under the age of 16. It’s not just the strictest tech policy of any democracy — it’s stricter than China’s laws. No TikTok, no Instagram, no SnapChat, that’s it. And while Washington dithers behind a 1998 law written before Google existed, other countries are gearing up to copy Australia’s homework (Malaysia imposes a similar ban on January 1st). What happens now — the enforcement mess, the global backlash, the accidental creation of the largest clean “control group” in tech-history — could reshape how we think about childhood, mental health, and what governments owe the developing brain.00:00 — Australia’s historic under-16 social-media ban01:10 — What counts as “social media” under the law?02:04 — Why platforms — not kids — get fined03:01 — How the U.S. is still stuck with COPPA (from 1998!)04:28 — Why age 13 was always a fiction05:15 — Psychologists on the teenage brain: “all gas, no brakes”07:02 — Malaysia and the EU consider following Australia’s lead08:00 — Nighttime curfews and other global experiments09:11 — Albanese’s pitch: reclaiming “a real childhood”10:20 — Could isolation leave Aussie teens behind socially?11:22 — Why Australia is suddenly stricter than China12:40 — Age-verification chaos: the AI that thinks my uncle is 1213:40 — The enforcement black box14:10 — Australia as the first real longitudinal control group15:18 — If mental-health outcomes improve, everything changes16:05 — The end of the “wild west” era of social platforms?