A lively tour from Cold War “The Thing” to today’s surveillance capitalism—showing how audio capture, too much data, and automation pressures helped turn listening into AI.

• Dr. Toby Heys — Professor at the School of Digital Arts (SODA), Manchester Metropolitan University; co-founder of the AUDINT sonic research unit; co-author of Listening In
• Dr. David Jackson — Senior Lecturer in Digital Visualisation at SODA, Manchester Metropolitan University; researches AI’s cultural impact; founded the Storytellers + Machines conference (2023); co-author of Listening In.
• Marsha Courneya — Canadian writer/editor; teaches Digital Dramaturgy at the International Film School of Cologne; doctoral researcher in Digital Culture and Communication at Birkbeck, University of London; co-author of Listening In.

• “The Thing” (1945): passive bugging, resonance, why it went undetected
• Cold War escalation: normalization of listening, Five Eyes, PRISM/Snowden
• Stasi data glut: informants, dossiers, “collecting as mania,” behavior change
• Language under surveillance: cryptolects, slang, coded speech, hip-hop as evasion
• Surveillance capitalism: smart homes, smart toys, wearables, “data promiscuity”
• Kids + data: baby monitors/crib cams, school biometrics, “data twins” before birth
• AI training + intimate life: accidental recordings, human review, terms-of-service reality
• Future tensions: convenience vs autonomy, regulation lag, ownership erosion (“enshittification”)

• Audio surveillance scales into an “automation problem.” Once you can record everything, the bottleneck becomes listening fast enough, pushing intelligence services toward automated analysis.
• Surveillance changes behavior—even when nobody is actively listening. The possibility of being overheard bends speech, jokes, and self-presentation (Stasi dynamics → modern smart devices).
• “Too much data” doesn’t make it harmless. The danger isn’t only what’s heard today, but the creation of a searchable “permanent record” that can be reinterpreted later.
• The home becomes the most valuable capture zone. People drop the public mask at home; that intimacy makes in-home audio uniquely revealing and therefore lucrative/powerful.
• Children are captured early—often via “safety” and parental anxiety. Baby tech, smart toys, school systems, and medical records create a data trail before kids can consent or understand it.
• Snowden shocked—but didn’t trigger lasting mass refusal. The episode argues leaks often lead to resignation/memeification (“the intel officer listening”) rather than sustained backlash.
• AI + ownership is the next front. Beyond privacy, the guests worry about erosion of ownership (you can’t fully “own” digital goods or refuse totalizing platforms as easily).

• Toby: “There was nothing to detect.”
• Marsha: “It ruptures language completely.”
• David: “data isn’t secure and safe.”

🎙 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 former Silicon Valley insider explains how MBA-style “spreadsheet management” is breaking software—and why it’s making tech, AI, and everyday products worse.

Darryl Campbell is a former tech industry insider who spent 15 years in Silicon Valley at companies including Amazon and Uber and at early-stage startups. He’s the author of Fatal Abstraction: Why the Managerial Class Loses Control of Software.

• What “managerialism” is and how MBAs took over tech
• Why software moved from serving users to extracting value
• Industrial-era management vs. internet-scale systems
• Boeing 737 MAX, Uber self-driving, and systemic risk
• Enshittification and the decline of product quality
• AI hype, weak ROI, and incentives to do harmful things
• Monopoly power, captured regulation, and why markets don’t self-correct
• Whether real innovation has slowed since the 1970s
• What comes next: backlash, regulation, or a paradigm shift

• The “managerial class” optimizes for financial metrics that don’t capture safety, quality, or real-world harm.
• Industrial-era management worked better because physical constraints forced slower feedback and respect for expertise.
• Software removes constraints: you can ship instantly at global scale, so errors and incentives can become catastrophes.
• Enshittification is a predictable outcome when monopoly power + financial targets replace user value.
• AI is under extreme financial pressure (huge capex vs. limited revenue), which encourages risky monetization.
• Traditional checks—shareholders, competition, regulators—often fail against near-monopolies.
• Meaningful improvement may require a broader public backlash or a major “paradigm shift.”

• “Anything, literally anything, is permissible as long as it makes you more money.”
• “It’s impossible to ignore… the only way to stay current is to pay us $200 a year for the rest of your life.”
• “It feels like we’re in a black and white phase right now, and I’m really interested to see what the color phase afterward looks like.

🎙 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!

MIT Free Speech Alliance president Wayne Stargardt explains how a few high-profile cancellations can drive widespread faculty self-censorship—even at a STEM powerhouse like MIT.

Wayne Stargardt is the president of the MIT Free Speech Alliance (independent of MIT) and an MIT alumnus (Class of 1974) who focuses on academic freedom, free expression, and open debate at STEM universities.

• “Silencing Science at MIT” and what MIT faculty surveys suggest about self-censorship
• The Dorian Abbott Carlson Lecture cancellation (2021) and the alumni response
• Why faculty fear student retaliation (bias reporting, administrative escalation)
• FIRE campus free-speech rankings and what they measure
• MIT’s revenue model (research/endowment vs tuition) and why incentives differ from most schools
• K–12 socialization, in loco parentis, and why students arrive primed for “shout-down” norms
• DEI rebranding (“community and belonging”) and the claim that pressures went underground
• Risks to MIT: recruiting/retaining top faculty and research dollars
• MIT reinstating SAT requirements (post-2020 test disruption)
• MIT vs Harvard: data/analysis vs decision-making under uncertainty (“intuition”)
• AI as a tool: value depends on the questions/tasks you set

• Multiple MIT faculty surveys—asked different ways—cluster around ~50–55% reporting some self-censorship in at least some settings.
• You don’t need “many” cancellations: a few public examples can trigger self-protective silence across a campus.
• The Abbott episode was a catalyst: MIT was “caught by surprise,” and faculty + alumni backlash made repeat events less likely—but speakers may be quietly filtered out earlier.
• FIRE rankings reflect student attitudes + institutional policies; MIT’s rank improved partly because others worsened, not because MIT’s score surged.
• MIT’s finances reduce tuition dependence; the bigger vulnerability is faculty environment → research strength → prestige/funding.
• Administrative culture shift (more “professional administrators”) can amplify complaint systems when they’re sympathetic to activist norms.
• Stargardt is cautiously optimistic: broader American free-speech culture pushes universities either to course-correct or fade amid demographic headwinds.

• “You don't have to cancel too many professors at a university… they catch on real quick… and… self-censor.”
• “MIT is a multidisciplinary research institute, which happened to have a small specialized trade school attached to it.”
• “You don't have to cancel a whole lot of people to scare the faculty. You just have to cancel a few.”

🎙 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!