Can you trust what you hear? This episode dives into a startling incident involving an AI-powered deepfake of Secretary Marco Rubio's voice reaching high-level government officials through Signal. We explore the growing threat of AI-driven deception in diplomacy, highlighting how vulnerabilities exposed by recent incidents could impact international trust and security. With alarming statistics on human susceptibility to fake voices and past electoral interference, we uncover who might benefit from this chaos. Listeners will gain insight into the urgent need for systemic reform in digital communication to protect against AI impersonations. Don't forget to subscribe, share, and leave a review! 

FULL TRANSCRIPT: From The New York Times, this is AI Daily. I'm Harry Kermode.

Imagine picking up your phone and seeing an encrypted message from the U.S. Secretary of State. It's urgent, collaborative, and entirely believable—marked with familiar speech patterns and diplomatic language. You trust it, act upon it. Only later do you discover you've been fooled: not by traditional hackers, but by something new and more disturbing—an AI-powered deepfake voice impersonating Secretary Marco Rubio himself.

Just weeks ago, this astonishing scenario played out in reality. An unknown attacker crafted an AI-generated replica of Marco Rubio's voice, created a fake account on the encrypted messaging app Signal, and proactively reached out to at least three foreign ministers, a U.S. governor, and a sitting member of Congress. The U.S. State Department confirmed the incident, leaving government officials grappling with uncomfortable questions: how could AI-driven deception breach the highest levels of diplomatic communication so easily?

To understand why this incident is more than just alarming, consider this: experts now estimate that humans fail to detect fake voices roughly seventy-five percent of the time. Today's leading software requires mere seconds of audio to create voice duplicates nearly indistinguishable from genuine speech. Even more troubling, there’s no technology currently strong enough to reliably shield diplomats and policymakers from an AI spear-phishing assault of this caliber.

The Rubio incident isn't an isolated outlier, but only the latest chapter in a troubling history. Think back to the 2024 New Hampshire primary, where voters received AI-generated robocalls of President Biden's voice urging them to stay home. The FCC responded firmly, fining the perpetrator six million dollars. Or recall the 2023 elections in Slovakia, where carefully timed deepfake audio swayed public confidence, potentially influencing the outcome. Now, tactics once confined to election meddling have invaded the realm of direct diplomacy, shaking trust among global leaders while exposing vulnerabilities at the heart of democratic systems.

Who stands to gain from this carefully executed chaos? Cybersecurity experts point fingers at state-linked hacking teams—Russian operatives known for using sophisticated AI tools to destabilize geopolitical relationships, aiming to erode trust and weaken Western alliances. But there are quieter beneficiaries, too: tech firms positioning themselves as essential gatekeepers promising protection even as their innovations inadvertently empower attacks like these.

Ironically, Marco Rubio himself foresaw these threats. In 2023, as a senator, he co-sponsored groundbreaking legislation aimed at criminalizing AI-based identity theft. Yet now, as Secretary of State, Rubio finds himself targeted by precisely those technologies he once warned about.

In response to this crisis, the Biden administration has reaffirmed their commitment to "strengthening cybersecurity" without clear new measures. However, critics warn that these reassurances do little to confront the crumbling foundations of digital trust. Without systemic reform—secure and verifiable communication infrastructures specifically—the floodgates remain open.

And so diplomats, elected officials, and even ordinary citizens face today’s most pressing question: if anyone's voice can be flawlessly cloned, how do we distinguish allies from impostors? Our institutions from infiltrators?

If we're going to survive deepfake diplomacy, it's a question we'll need answered—and soon.

From The New York Times, I'm Harry Kermode. This was AI Daily.

Deepfake Diplomacy: The AI Threat to Global Trust

What happens when AI goes rogue in the courtroom? Tune in as we explore a federal lawsuit involving MyPillow CEO Mike Lindell, where generative AI tools like ChatGPT and Google's Gemini produced fictitious legal citations, leading to attorney fines and a national stir. Discover how this alarming incident highlights a systemic issue with AI reliance in the legal realm and the broader implications for our justice system. You'll grasp the essential need for rigorous AI verification and oversight in high-stakes professions. Don't forget to subscribe, share, and leave a review to support the podcast! 

FULL TRANSCRIPT: I'm Harry Kermode, and this is AI Daily.

Imagine for a moment stepping into court—a high-stakes defamation lawsuit against a prominent public figure. Attorneys, impeccably dressed, files neatly organized, and arguments meticulously charted out. Except today, the attorneys have unknowingly brought fiction into the courtroom—not lies told by witnesses, but fabrications from an AI chatbot.

This week, that's precisely what happened in a federal courtroom, drawing national attention. Lawyers representing MyPillow CEO Mike Lindell relied on generative AI tools—common services like ChatGPT and Google's Gemini—to draft their legal documents. But rather than assisting them efficiently and accurately, the AI produced what's known as a "hallucination," inventing nearly thirty completely fictitious case citations and misquoting other legal precedents. When the deception was unveiled, the stunned attorneys were fined $3,000 each.

AI hallucinations aren't new, of course. In 2023, a now-infamous case of "phantom citations" shook the legal community in Mata v. Avianca Airlines. Lawyers there were sanctioned for using AI-generated cases—yet, two years later, these issues persist. The Lindell fiasco is more than an isolated mess-up; it represents a dangerous trend that's unfolding quietly but insistently across courtrooms worldwide, with more than 200 documented incidents of AI-induced legal errors since just this spring.

Why, despite warnings, do professional attorneys persist in gambling their reputations, their client's fates, and their financial well-being on these algorithms? The answer, in short, is efficiency—but efficiency at what price?

For law firms operating under pressure, generative AI promises faster turn-around on tedious research tasks, saving precious hours and billable labor. The American Bar Association promotes these AI solutions boldly, framing it as augmenting productivity. Yet the Lindell case reveals the troubling reality beneath that optimistic narrative: that AI in legal settings is treated far too casually, often delegated to junior staff without verification or adequate oversight—or worse, simply trusted blindly.

It's not just the attorneys who failed here; it's systemic. Regulatory oversight from the ABA mandates attorneys verify any AI-generated materials. Still, enforcement varies dramatically. The courts themselves remain patchy in holding practitioners accountable, occasionally sanctioning attorneys but generally overlooking rampant casual use of these powerful—and deeply flawed—generative technologies.

And here's what's most troubling: the people bearing the brunt of AI's failures may ultimately not be wealthy clients or high-stakes defendants, but rather everyday individuals—pro se litigants or smaller law offices with limited resources to audit software outputs effectively. They are the ones at greatest risk of being misled by these tools, widening inequities in our justice system even further.

So, what can we do? Some experts argue the answer will lie in stricter AI verification tools embedded into legal software. Others suggest the legal profession itself must evolve: train attorneys rigorously not just in law but in technology—embedding AI literacy right into licensing exams and professional standards. But one thing is clear: trust, once lost, is hard to recover. Every incident chips away at confidence—in the courtroom, judges are now skeptical of AI claims, and opposing attorneys will eagerly scrutinize digital fingerprints of AI reliance.

In an ironic twist, Mike Lindell, known widely for spreading conspiracy theories about election fraud, himself became the victim, inadvertently, of a very different sort of misinformation crisis—one created directly by unchecked artificial intelligence.

Ultimately, the Lindell case signals a broader trend: as AI permeates high-stakes professions, ethical guardrails and accuracy checks must become non-negotiable. The law, built upon careful reasoning and factual precision, cannot sustain itself on shortcuts. If our courts, built to seek truths, cannot even trust their own filings, then what hope do we have as society grapples with the promises—and perils—of AI technology?

I'm Harry Kermode, and this has been AI Daily.

AI Hallucinations in Court: The Lindell Case Exposes Dangerous Missteps in Legal Practice

Discrepancy

Can artificial intelligence redefine medicine and fast-track new treatments? In this groundbreaking episode of AI Daily, host Harry Kermode explores Isomorphic Labs' announcement of human trials for AI-designed drugs. Backed by DeepMind's AlphaFold breakthroughs, this marks a pivotal moment for AI's role in healthcare and drug discovery. Expect insights into the challenges and promises of such innovations, as well as ethical and workforce implications. Tune in to learn if AI truly signifies a new era for medicine. Don't forget to subscribe, share, and leave a review! 

FULL TRANSCRIPT: It's Monday, July 14th, 2025. I'm Harry Kermode, and this is AI Daily.

For decades, we've imagined artificial intelligence reshaping medicine, promising faster cures, cheaper treatments, and untold leaps in human health. Today, we're stepping closer to that promise becoming reality.

Yesterday, Isomorphic Labs, a spinoff of Google's famous AI research division DeepMind, announced that human trials for drugs exclusively designed by artificial intelligence will soon begin. This news marks an unprecedented milestone: for the first time in history, we will witness human clinical testing of medicines whose molecular structures have been discovered purely by AI algorithms.

To grasp the significance of this moment, let's step back briefly to look at its foundations. Remember, just two years ago DeepMind's AlphaFold won the Nobel Prize in Chemistry for solving one of biology's oldest and toughest challenges—accurately predicting protein structures. That discovery fundamentally transformed how scientists approach disease and treatment. Proteins and their shapes determine nearly every biological process, and knowing those structures enables scientists to precisely design molecules to target diseases.

At the intersection of biology and AI, Isomorphic Labs was born—named for the symmetry between information science and biological systems. The company set out to prove that AI could shorten the slow, costly traditional process of drug discovery, a system notorious for taking up to 15 years and billions of dollars per drug.

Fast forward to July 2025, and the world is about to see if AI can truly deliver. With over $600 million in funding and high-stakes partnerships totaling billions—including pharmaceutical giants like Novartis and Eli Lilly—Isomorphic Labs carries immense expectations on its shoulders. Investors are banking not only on revolutionary medicine, but also on transforming their financial returns. For Alphabet, Google's parent company, success means validation for their massive strategic bet on biotechnology.

Behind the press releases and optimism, there's an important conversation about risk and realism. AlphaFold's capabilities, while groundbreaking, do not yet model the full complexities and uncertainties of human biology. It's one thing to design a molecule in a digital lab; it's another entirely to ensure its safety and effectiveness in real patients. Already, respected voices in the medical community caution against seeing AI as a cure-all shortcut. Margaret Foti, CEO of the American Association for Cancer Research, reminds us that "AI accelerates hypotheses, but it will never replace clinical rigor."

There are ethical questions too: who controls this powerful technology? As breakthrough treatments created by algorithms and big data might one day flood the pharmaceutical market, will the benefits reach the broader global community, or remain out of reach, patented and prohibitively expensive?

Critics also highlight an understated human consequence—labor displacement. If AI designs drugs faster than pharmaceutical chemists, what becomes of their careers? Will the future workforce adapt, or will this technological disruption leave skilled professionals behind?

These trials, set to start within months, are indeed historic. Success might trigger regulatory shifts, new investment waves, and massive transformations in science and healthcare. Failure could lead to immense scrutiny, skepticism, and cautionary tales.

Behind every technological revolution lies a tension between its potential and its unintended consequences. Today, we find ourselves at the dawn of such a moment in medical history—hope tempered by questions, excitement balanced by caution.

AI has promised a revolution in medicine. Now, we hold our breath to see if it can deliver.

This has been AI Daily. We'll see you tomorrow.

The Unstoppable Rise of AI in Medicine: Promise or Peril?

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