Finance professor Spencer Barnes explains research showing postseason officiating systematically favors the Mahomes-era Chiefs—consistent with subconscious, financially driven “regulatory capture,” not explicit rigging.

Guest bio: Dr. Spencer Barnes is a finance professor at UTEP. He co-authored “Under Financial Pressure” with Brandon Mendez (South Carolina) and Ted Dischman, using sports as a transparent lab to study regulatory capture.

Topics discussed (in order):

• Why the NFL is a clean testbed for regulatory capture
• Data/methods: 13,136 defensive penalties (2015–2023), panel dataset, fixed-effects
• Postseason favoritism toward Mahomes-era Chiefs
• Magnitude and game impact (first downs, yards, FG-margin games)
• Subjective vs objective penalties (RTP, DPI vs offsides/false start)
• Regular season vs postseason differences
• Dynasty checks (Patriots/Brady; Eagles/Rams/49ers)
• Rigging vs subconscious bias
• Ratings, revenue (~$23B in 2024), media incentives
• Gambling’s rise post-2018 and bettor implications
• Taylor Swift factor (not tested due to data window)
• Ref assignment opacity; repeat-crew effects
• Tech/replay reform ideas
• Broader finance lesson on incentives and regulation

Main points & takeaways:

• Core postseason result: Chiefs ~20 percentage points more likely than peers to gain a first down from a defensive penalty.
• Subjective flags: ~30% more likely for KC in playoffs (RTP, DPI).
• Size: ~4 extra yards per defensive penalty in playoffs—small per play, decisive at FG margins.
• Regular season: No favorable treatment; slight tilt the other way.
• Ref carryover: Crews with a prior KC postseason official show more KC-favorable outcomes the next year.
• Not universal to dynasties: Patriots/Brady and other near-dynasties don’t show the same postseason effect.
• Mechanism: No claim of rigging; consistent with implicit bias under financial incentives.
• Policy: Use tech (skycam, auto-checks for false start/offsides), limited challenges for subjective calls, transparent ref advancement.
• General lesson: When regulators depend financially on outcomes, redesign incentives to reduce capture and protect fairness.

Top 3 quotes:

• “We make no claim the NFL is rigging anything. What we see looks like implicit bias shaped by financial incentives.” — Spencer Barnes
• “It only takes one call to swing a postseason game decided by a field goal.” — Spencer Barnes
• “If there’s money on the line, you must design the regulators’ environment so incentives don’t quietly bend enforcement.” — Spencer Barnes

Links/where to find the work: Spencer Barnes on LinkedIn (search: “Spencer Barnes UTEP”); paper Under Financial Pressure in the Financial Review (paywall) and as a free working paper on SSRN (search the title).

🎙 The Pod is hosted by Jesse Wright
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How human babies, big brains, and social life likely forced Homo sapiens to invent precise speech ~150–200k years ago—and what that means for learning, tech, and today’s kids.

Guest Bio:
Madeleine Beekman is a professor emerita of evolutionary biology and behavioral ecology at the University of Sydney and author of Origin of Language: How We Learned to Speak and Why. She studies social insects, collective decisions, and the evolution of communication.

Topics Discussed:

• Why soft tissues don’t fossilize; language origins rely on circumstantial evidence
• Three clocks for timing (~150–200k years): anatomy; trade/complex tech/art; phoneme “bottleneck”
• Why Homo sapiens (not Neanderthals) likely had full speech
• Language as a “virus” tuned to children; pidgin → creole via kids
• Second-language learning: immersion over translation
• Bees/ants show precision scales with ecological stakes
• Evolutionary chain: bipedalism → narrow pelvis + big brains → helpless infants → precise speech
• Ongoing human evolution (archaic DNA, altitude, Inuit lipid adaptations)
• Flynn effect reversal, screens, AI reliance, anthropomorphism risks
• Reading, early interaction, and the Regent honeyeater “lost song” lesson
• Universities, online classes, and “degree over learning”

Main Points:

• Multiple evidence lines converge on speech emerging with anatomically modern humans ~150–200k years ago.
• Anatomical and epigenetic clues suggest only Homo sapiens achieved full vocal speech.
• Extremely dependent infants created strong selection for precise, teachable communication.
• Children’s brains shape languages; kids regularize grammar.
• Communication precision rises when mistakes are costly (bee-dance analogy).
• Humans continue to evolve; genomes show selected archaic introgression and local adaptations.
• Tech-driven habits may erode cognition and language skill; reading matters.
• AI is a tool that imitates human output; humanizing it can mislead and harm, especially for teens.
• Start early: talk, read, and interact face-to-face from birth.

Top Quotes:

• “Only Homo sapiens was ever able to speak.”
• “Language will go extinct if it can’t be transmitted from brain to brain—the best host is a child.”
• “The precision of communication is shaped by how important it is to be precise.”

🎙 The Pod is hosted by Jesse Wright
💬 For guest suggestions, questions, or media inquiries, reach out at https://elpodcast.media/
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A candid conversation with psychologist Gerd Gigerenzer on why human judgment outperforms AI, the “stable world” limits of machine intelligence, and how surveillance capitalism reshapes society.

Guest bio: Dr. Gerd Gigerenzer is a German psychologist, director emeritus at the Max Planck Institute for Human Development, a leading scholar on decision-making and heuristics, and an intellectual interlocutor of B. F. Skinner and Herbert Simon.

Topics discussed:

• Why large language models rely on correlations, not understanding
• The “stable world principle” and where AI actually works (chess, translation)
• Uncertainty, human behavior, and why prediction doesn’t improve much
• Surveillance capitalism, privacy erosion, and “tech paternalism”
• Level-4 vs. level-5 autonomy and city redesign for robo-taxis
• Education, attention, and social media’s effects on cognition and mental health
• Dynamic pricing, right-to-repair, and value extraction vs. true innovation
• Simple heuristics beating big data (elections, flu prediction)
• Optimism vs. pessimism about democratic pushback
• Books to read: How to Stay Smart in a Smart World, The Intelligence of Intuition; “AI Snake Oil”

Main points:

• Human intelligence is categorically different from machine pattern-matching; LLMs don’t “understand.”
• AI excels in stable, rule-bound domains; it struggles under real-world uncertainty and shifting conditions.
• Claims of imminent AGI and fully general self-driving are marketing hype; progress is gated by world instability, not just compute.
• The business model of personalized advertising drives surveillance, addiction loops, and attention erosion.
• Complex models can underperform simple, well-chosen rules in uncertain domains.
• Europe is pushing regulation; tech lobbying and consumer convenience still tilt the field toward surveillance.
• The deeper risk isn’t “AI takeover” but the dumbing-down of people and loss of autonomy.
• Careers: follow what you love—humans remain essential for oversight, judgment, and creativity.
• Likely mobility future is constrained autonomy (level-4) plus infrastructure changes, not human-free level-5 everywhere.
• To “stay smart,” individuals must reclaim attention, understand how systems work, and demand alternatives (including paid, non-ad models).

Top quotes:

• “Large language models work by correlations between words; that’s not understanding.”
• “AI works well where tomorrow is like yesterday; under uncertainty, it falters.”
• “The problem isn’t AI—it’s the dumbing-down of people.”
• “We should become customers again, not the product.”

🎙 The Pod is hosted by Jesse Wright
💬 For guest suggestions, questions, or media inquiries, reach out at https://elpodcast.media/
📬 Never miss an episode – subscribe and follow wherever you get your podcasts.
⭐️ If you enjoyed this episode, please rate and review the show. It helps others find us.

Thanks for listening!