Mamdani vs Amazon, AI Replacing Doctors, DSA Member Is $108K Behind On Rent | Weekly Recap

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ATT Business: Switch to AT&T Business at business.att.com Ketone IQ: Visit https://ketone.com/IMPACT for 30% OFF your subscription order Netsuite: For the first time ever you can try NetSuite Next for free. If your revenues are at least in the seven figures, go to https://NetSuite.ai/Theory. The team reacts to DSA-affiliated activist Tracy Rosenthal, who—per the reporting the host cites—has withheld an estimated $108,000 in rent and openly encourages tenants in their building to do the same, with their landlord reportedly an immigrant now losing the building. The host is careful to say he hasn't independently verified every detail, but uses it to make his central argument: that "just don't pay rent" activism, however it's framed as helping the poor, actually lands hardest on the people it claims to protect. He argues Rosenthal—whose father he says is a multiple-Grammy-winning musician and who grew up wealthy—has a safety net ("they can always go back to mom and dad") that the working families they're advising do not, so when a landlord can no longer maintain or run the building, tenants end up in unmaintained housing, and those who join rent strikes risk landing on tenant-screening "do not rent" lists that follow them, push them toward fewer economic opportunities, and make housing harder to secure. He frames the whole thing as reasoning from resentment—aimed at hurting a perceived "capital class"—rather than from what actually helps poor people, and warns that if you make it impossible to run housing as a business, the only remaining owner is the government, which can only subsidize until the "engine of prosperity" breaks. He argues this path repeatedly ends in stagnation, using Cuba as his example. The team reacts to Mayor Mamdani's new video targeting Amazon's delivery model—where drivers wear Amazon branding and follow Amazon-set routes and hours but are technically employed by subcontractors—and his support for the Delivery Protection Act, which would push responsibility for those workers back onto Amazon. Drew presses the steelman throughout: if the setup is illegal or strips workers of deserved protections (the way the Uber/Lyft contractor debate played out), shouldn't the government step in? The host agrees that if a company is breaking the law you enforce the law—but argues this specific move is a case of a candidate promising affordability while doing something that will make deliveries more expensive, calling the two goals "matter and antimatter." His core argument is about preserving choice: independent-contractor status is a real tradeoff that many workers actively want (flexibility, control), and banning it doesn't magically convert those into higher-paying jobs—companies instead do less, automate, or leave, and a subclass of lower-skilled workers loses the on-ramp entirely. He draws the Uber-beat-the-taxis parallel, argues minimum-wage hikes disproportionately wipe out teen and entry-level jobs, and points to Austin and Houston loosening building regulations to bring housing costs down as evidence that over-regulation is often the choke point. He frames the government's proper role with a sports metaphor—referees who set and enforce fair rules are essential, but when the refs outnumber the players and start tripping the best performer to even the score, the whole game gets worse. Threaded through is his contested thesis that this is driven by resentment and an "overproduction of elites," and a nuanced exchange with Drew about when market intervention is genuinely warranted versus when it becomes a barnacle. The team digs into three new Google research papers that, in the host's read, show large language models already outperforming human doctors—even in the messy, sometimes adversarial reality of real patient interactions. The host, careful to stay honest about both AI's risks and its capabilities, walks through the numbers: in a randomized clinical exam of 100 scenarios across 300 live video consultations with patient actors, graded by 20 board-certified physicians, the AI scored 83% to the doctors' 68%, with correct first-guess diagnoses at 91% vs 77%, clinical reasoning 90% vs 76%, guiding a physical exam over video 72 vs 39, and—strikingly—empathy rated higher for the AI (82 vs 71), echoing earlier findings in AI therapy studies. The AI also finished exams slightly faster. A second paper tracking patients across three visits with shifting symptoms found the AI's care rated appropriate 95% rising to 98% by the third visit, while human doctors actually got worse over follow-ups (72% to 81%)—which the host speculates is because doctors "back off too soon" once they think they've found the answer, whereas the AI keeps refining. A third paper used reinforcement learning across 57,000 simulated encounters—including thousands where patients actively try to deceive the doctor, hiding medications or insisting chest pain is just heartburn—with up to 60 conversational turns, producing a model that beats the already-superior AI 87.6% of the time head-to-head. The host argues the gap will likely keep growing, predicts that within a few years failing to at least consult AI could be treated as malpractice, and forecasts a near-term future of human-assisted-by-AI care rather than fully autonomous machines—because AI is probabilistic, not deterministic, so a human stays in the loop the way pilots remain in an autopilot cockpit. His bottom line: this is one of those cases where the technology may genuinely become what we hoped for, even if the economic transition to get there is turbulent. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.