Intelligent Machines 846: "Chivelord"

Podcast: All TWiT.tv Shows (Audio)
Date: November 20, 2025
Host: Leo Laporte
Co-Hosts: Paris Martineau, Jeff Jarvis
Special Guest: Jimmy Wales (Founder of Wikipedia)
Theme: Trust, Community, and the Future of AI in Knowledge Creation

Episode Overview

This episode features a wide-ranging and sharp conversation centered on trust in online communities and knowledge, featuring an in-depth interview with Wikipedia founder Jimmy Wales about his new book, "The Seven Rules of Trust." The hosts and guest reflect on Wikipedia’s origins, its model of community moderation, the challenges and opportunities of adopting AI in collaborative knowledge bases, and lessons that apply to today's tech giants and platforms. The latter half veers into live demos of new AI models, AI’s impact on media and content, the state of AI regulation, and broader questions of Internet culture.

Guest Introduction & Community Creation

Jimmy Wales is introduced as the "legendary" founder of Wikipedia, bringing with him his new book "The Seven Rules of Trust," described by Leo as essential for understanding how to build sustainable, trustworthy communities online ([02:00]).
Wales recounts Wikipedia’s transformative impact compared to previous encyclopedias and describes Wikipedia as a “temple of the mind.” ([01:56])
The early days of Wikipedia: Wales shares the story of its origin, stemming from the failures of Nupedia—a top-down, expert-driven encyclopedia that stalled after just 21 articles due to bureaucracy ([07:03]).
Wales credits the switch to wiki software and open editing to a moment of "last chance" innovation—"just screw it, we've got to try it" ([10:04]).
Notable quote:

"We were already having discussions...what are the qualifications? ...I was really in the camp of like, well, does it really matter? It's really the work that matters, not the qualifications."
— Jimmy Wales ([10:04])

Building Trust: The Wikipedia Model

Stats & Scope

Size and Contributors: Wikipedia has “70,000–80,000” active editors each month making meaningful contributions ([03:36]).
Global Reach: Over 7 million English articles, Wikipedia in 300 languages, "93 times bigger than Britannica" ([03:47]).

Trust-Building Principles

Wales' book draws from Frances Frei’s "Trust Triangle"—authenticity, empathy, logic—as essential and academic frameworks for cultivating trust ([15:15]).
Notable quote:

“Building trust is very practical...Airbnb had an enormous crisis of trust...if people generally believe that if I put my house on, it's going to get trashed, they’re not going to do it...How do we make sure people don't have that feeling?”
— Jimmy Wales ([21:31])
Early Wikipedia relied on:
- Low-risk, open exploration
- Letting anyone, not just experts, begin
- Vigilance through community, not just Wales—e.g. "there's this guy in Australia, and when I'm asleep, he’s on…” ([14:12])

Community Versus Algorithms

The importance of persistent identities (even pseudonymous) in building trust and accountability, contrasting with the “atomistic interaction” and anonymity of social networks like Twitter/X ([19:32]).
Notable quote:

"If you post almost anything on Twitter...some absolute random sends you an angry message. You've never seen them before, you'll never see them again...Whereas just having a...reputation for being a decent person...makes a difference."
— Jimmy Wales ([20:36])

Purpose as the North Star

Rule #3 from the book: The necessity of “a strong, clear, positive purpose” ([22:23]).
Wikipedia’s clarity (“build an encyclopedia”) enables effective self-management and consensus, whereas platforms like Facebook and Twitter “never had that North Star” ([22:23], [24:08]).
Notable quote:

"With Wikipedia, there's no box that says, 'What's on your mind?'...No, we're here to build an encyclopedia."
— Jimmy Wales ([24:39])

Ads, Nonprofit Model, and Wikipedia’s Ethos

Wikipedia famously rejected advertising and corporate incentives.

"Organizations ultimately do follow the money...Our business model, the funding for Wikipedia, is the vast majority small donors."
— Jimmy Wales ([27:47])
Notable moment: The average donation is “just over $10,” and appeals are tied to community, not profit ([29:10]).

Wikipedia and AI—Opportunities & Perils

Wikipedia as AI Training Data

Wales acknowledges almost all AI models are trained on Wikipedia content, raising questions about knowledge provenance and responsibility ([29:40]).

Early AI Tool Experiments

Wales describes a script for citation-checking using AI: “Is there anything in the sources that isn’t in Wikipedia but should be? Is there anything in Wikipedia not supported by sources?” ([30:33])
Community is skeptical about using AI for content creation due to hallucinations and accuracy concerns ([31:29]).

Notable quote:

"Most people who haven't really worked in the knowledge space...don't realize how bad the hallucination problem is. ...They tend to be quite plausible."
— Jimmy Wales ([31:24])

Plausibility versus Fact

Wales relays a story about querying various language models about his wife, Kate Garvey; models generate plausible-sounding but false narratives, demonstrating AI’s inherent unreliability with specific facts ([32:49]).

Right AI Use Cases

Wales sees the best AI use for Wikipedia in tools that automate “the boring bits”—e.g., finding dead links, suggesting replacement sources, or aiding with translation ([37:23]).
AI is “remarkably creative,” defying early expectations that it would be merely a fact-regurgitator ([37:47]).

AI’s Broader Impacts, Regulation, and the Trust Crisis

Grok and Competing AI Knowledge Bases

Wales is skeptical of Grokopedia, Elon Musk's AI-powered Wikipedia competitor—citing both hallucinations and ideological bias, quipping:

“Apparently...it seems surprisingly aligned with some of his more intriguing political views.”
— Jimmy Wales ([38:50])

AI Slop & the “Trust Apocalypse”

The panel reflects on the looming "trust apocalypse"—AI slop, hallucinations, misinformation—creating new and more acute trust crises ([29:40], [41:50]).

Live Demos: Gemini 3, ChatGPT, and More

Co-hosts test Google’s Gemini 3 model, critiquing new writing and AI curation features, and discuss issues with AI summarization, up-to-date content, and code generation ([53:22]-[76:29]).
Notable moment: Gemini 3 is asked for a critique of a viral “bamboo” metaphor in a recent piece by Ryan Lizza, producing a nuanced answer:

"The bamboo metaphor is the article’s primary thematic anchor, functioning as a heavy handed literary device...overworked, making the piece feel calculated and overly polished rather than raw or authentic.”
— Gemini 3 ([74:11])

AI Regulation & Industry

Breaking News: White House Preemption Order

Paris Martineau breaks a story (from The Information): The White House is working on an executive order to preempt state-level AI regulation, with recommendations to block broadband funding to non-compliant states and task the DOJ with suing states that pass their own AI laws ([103:57]).
The order, lobbied by industry figures, faces skepticism and was previously voted down in Congress ([104:20]-[109:34]).

Industry Updates

Nvidia’s quarterly profits and the continued boom in AI hardware sales ([109:54]), AI investment bubbles, and Jeff Bezos’s new AI startup, Project Prometheus, are discussed ([112:23]).
Yann LeCun’s departure from Meta to found a new AI company focused on more grounded models ([93:03]), and the debate about whether LLMs can achieve AGI.

Internet & Media Culture

Monetization Models & Community Support

Patreon’s Jack Conte is discussed as he tries to build a non-advertising, membership-supported creator model but faces real tensions between mission and VC-backed scale ([115:07]).
Leo Laporte reflects on TWiT’s own community-supported “Club TWiT” as analogous to Wikipedia’s donor model ([120:20]).

AI & Content Slop

AI-generated slop in search, Bindwell’s AI pesticides, and attempts at human/community moderation of “AI slop” in web search (e.g., Kagi) ([78:54], [80:07]).
Fireflies AI “fake it till you make it” origin story—manual meeting transcription marketed as AI ([85:03]).

AI Note-Taking & Privacy

Discussion about the etiquette of AI assistants in meetings, privacy concerns, and the rise of local AI language models for enhanced security ([87:01]).

AI and Everyday Life

Tinder’s AI “Chemistry” and Hinge’s AI review of dating profiles—creeping AI into love and relationships ([123:03]).
Use of AI for wedding planning, and even writing vows and separation agreements ([125:02]).
Demo of Google Labs’ GenType for creating fonts from custom prompts (e.g., "font of cats") ([147:34]).

Notable Quotes & Moments

“Wikipedia is a temple for the mind and I enjoy it.” — Jimmy Wales ([27:47])
“Trust is the most practical of all human virtues.” — Leo Laporte ([14:12])
“They asked, what did you do? I got rid of all the experts, opened it up, and hoped for the best.” — Paraphrased summary by Leo ([11:08])
“If I were giving a kid I liked a bit of money, when they turned 25, I'd give them $25, so that seems about right [for Wikipedia’s 25th anniversary].” — Jimmy Wales ([48:54])

Fun & Cultural Interludes

Explainer of cat islands in Japan, return pallets from Amazon ("polyster mountain"), and the saga of a man who posts daily “chive cutting” progress on Reddit until the community declares it perfect ([141:04]-[137:20]).
Extended group digression analyzing media scandals and employing AI to critique overwrought writing about “bamboo” in Ryan Lizza’s viral story ([54:10]-[76:29]).
Nick Cage’s latest film "The Carpenter’s Son" and its “teen Jesus” memes ([150:03]).

Important Timestamps

[02:27] — Jimmy Wales welcomed, early story about Wikipedia’s origins
[03:36] — Stats on Wikipedia’s size & contributors
[07:03] — Switching from Nupedia to wikis
[15:15] — Frances Frei’s “Trust Triangle”
[19:07] — Can Wikipedia be started today? — Usenet wasn’t as utopian as we remember
[20:36] — Persistent identity as the backbone of good communities
[21:31] — Real-world companies (Airbnb) and trust crises
[22:23] — Clarity of purpose; critique of Facebook/Twitter
[27:10] — Wikipedia’s anti-ad ethos
[29:40] — Wikipedia’s use in LLM training; AI slop
[31:12] — Community wariness about AI in knowledge production due to hallucinations
[37:23] — Right use-cases for AI: “the boring bits”
[38:50] — Grokopedia skepticism
[103:57] — Breaking news: “White House to preempt state AI regulation”
[109:54] — Nvidia profit update, AI investment
[141:04] — Cat Island, Amazon returns, chive-lord on Reddit

Summary

This wide-ranging episode provides unique insight into the creation and ongoing stewardship of the world’s largest collaborative knowledge base. Jimmy Wales’ perspective offers a powerful reminder that successful, trustworthy digital platforms require careful community cultivation, clarity of purpose, and relentless resistance to perverse incentives. As AI increasingly mediates what we read, write, and trust, Wikipedia’s hard-fought lessons are more urgent than ever—especially as tech, government, and culture wrestle with the implications of AI slop, misinformation, and a rapidly accelerating pace of change.

For Further Listening

Jimmy Wales – "The Seven Rules of Trust"
Wikipedia's 25th Anniversary: Donate here
Next guest: Ahmad Mostak (founder, Stable Diffusion & Intelligent Internet)
Listen at twit.tv or your favorite podcast app

Intelligent Machines 846: "Chivelord"

Episode Overview

Guest Introduction & Community Creation

Jimmy Wales is introduced as the "legendary" founder of Wikipedia, bringing with him his new book "The Seven Rules of Trust," described by Leo as essential for understanding how to build sustainable, trustworthy communities online ([02:00]).
Wales recounts Wikipedia’s transformative impact compared to previous encyclopedias and describes Wikipedia as a “temple of the mind.” ([01:56])
The early days of Wikipedia: Wales shares the story of its origin, stemming from the failures of Nupedia—a top-down, expert-driven encyclopedia that stalled after just 21 articles due to bureaucracy ([07:03]).
Wales credits the switch to wiki software and open editing to a moment of "last chance" innovation—"just screw it, we've got to try it" ([10:04]).
Notable quote:

"We were already having discussions...what are the qualifications? ...I was really in the camp of like, well, does it really matter? It's really the work that matters, not the qualifications."
— Jimmy Wales ([10:04])

Building Trust: The Wikipedia Model

Stats & Scope

Size and Contributors: Wikipedia has “70,000–80,000” active editors each month making meaningful contributions ([03:36]).
Global Reach: Over 7 million English articles, Wikipedia in 300 languages, "93 times bigger than Britannica" ([03:47]).

Trust-Building Principles

Wales' book draws from Frances Frei’s "Trust Triangle"—authenticity, empathy, logic—as essential and academic frameworks for cultivating trust ([15:15]).
Notable quote:

“Building trust is very practical...Airbnb had an enormous crisis of trust...if people generally believe that if I put my house on, it's going to get trashed, they’re not going to do it...How do we make sure people don't have that feeling?”
— Jimmy Wales ([21:31])
Early Wikipedia relied on:
- Low-risk, open exploration
- Letting anyone, not just experts, begin
- Vigilance through community, not just Wales—e.g. "there's this guy in Australia, and when I'm asleep, he’s on…” ([14:12])

Community Versus Algorithms

The importance of persistent identities (even pseudonymous) in building trust and accountability, contrasting with the “atomistic interaction” and anonymity of social networks like Twitter/X ([19:32]).
Notable quote:

"If you post almost anything on Twitter...some absolute random sends you an angry message. You've never seen them before, you'll never see them again...Whereas just having a...reputation for being a decent person...makes a difference."
— Jimmy Wales ([20:36])

Purpose as the North Star

Rule #3 from the book: The necessity of “a strong, clear, positive purpose” ([22:23]).
Wikipedia’s clarity (“build an encyclopedia”) enables effective self-management and consensus, whereas platforms like Facebook and Twitter “never had that North Star” ([22:23], [24:08]).
Notable quote:

"With Wikipedia, there's no box that says, 'What's on your mind?'...No, we're here to build an encyclopedia."
— Jimmy Wales ([24:39])

Ads, Nonprofit Model, and Wikipedia’s Ethos

Wikipedia famously rejected advertising and corporate incentives.

"Organizations ultimately do follow the money...Our business model, the funding for Wikipedia, is the vast majority small donors."
— Jimmy Wales ([27:47])
Notable moment: The average donation is “just over $10,” and appeals are tied to community, not profit ([29:10]).

Wikipedia and AI—Opportunities & Perils

Wikipedia as AI Training Data

Wales acknowledges almost all AI models are trained on Wikipedia content, raising questions about knowledge provenance and responsibility ([29:40]).

Early AI Tool Experiments

Wales describes a script for citation-checking using AI: “Is there anything in the sources that isn’t in Wikipedia but should be? Is there anything in Wikipedia not supported by sources?” ([30:33])
Community is skeptical about using AI for content creation due to hallucinations and accuracy concerns ([31:29]).

Notable quote:

"Most people who haven't really worked in the knowledge space...don't realize how bad the hallucination problem is. ...They tend to be quite plausible."
— Jimmy Wales ([31:24])

Plausibility versus Fact

Wales relays a story about querying various language models about his wife, Kate Garvey; models generate plausible-sounding but false narratives, demonstrating AI’s inherent unreliability with specific facts ([32:49]).

Right AI Use Cases

Wales sees the best AI use for Wikipedia in tools that automate “the boring bits”—e.g., finding dead links, suggesting replacement sources, or aiding with translation ([37:23]).
AI is “remarkably creative,” defying early expectations that it would be merely a fact-regurgitator ([37:47]).

AI’s Broader Impacts, Regulation, and the Trust Crisis

Grok and Competing AI Knowledge Bases

Wales is skeptical of Grokopedia, Elon Musk's AI-powered Wikipedia competitor—citing both hallucinations and ideological bias, quipping:

“Apparently...it seems surprisingly aligned with some of his more intriguing political views.”
— Jimmy Wales ([38:50])

AI Slop & the “Trust Apocalypse”

The panel reflects on the looming "trust apocalypse"—AI slop, hallucinations, misinformation—creating new and more acute trust crises ([29:40], [41:50]).

Live Demos: Gemini 3, ChatGPT, and More

Co-hosts test Google’s Gemini 3 model, critiquing new writing and AI curation features, and discuss issues with AI summarization, up-to-date content, and code generation ([53:22]-[76:29]).
Notable moment: Gemini 3 is asked for a critique of a viral “bamboo” metaphor in a recent piece by Ryan Lizza, producing a nuanced answer:

"The bamboo metaphor is the article’s primary thematic anchor, functioning as a heavy handed literary device...overworked, making the piece feel calculated and overly polished rather than raw or authentic.”
— Gemini 3 ([74:11])

AI Regulation & Industry

Breaking News: White House Preemption Order

Paris Martineau breaks a story (from The Information): The White House is working on an executive order to preempt state-level AI regulation, with recommendations to block broadband funding to non-compliant states and task the DOJ with suing states that pass their own AI laws ([103:57]).
The order, lobbied by industry figures, faces skepticism and was previously voted down in Congress ([104:20]-[109:34]).

Industry Updates

Nvidia’s quarterly profits and the continued boom in AI hardware sales ([109:54]), AI investment bubbles, and Jeff Bezos’s new AI startup, Project Prometheus, are discussed ([112:23]).
Yann LeCun’s departure from Meta to found a new AI company focused on more grounded models ([93:03]), and the debate about whether LLMs can achieve AGI.

Internet & Media Culture

Monetization Models & Community Support

Patreon’s Jack Conte is discussed as he tries to build a non-advertising, membership-supported creator model but faces real tensions between mission and VC-backed scale ([115:07]).
Leo Laporte reflects on TWiT’s own community-supported “Club TWiT” as analogous to Wikipedia’s donor model ([120:20]).

AI & Content Slop

AI-generated slop in search, Bindwell’s AI pesticides, and attempts at human/community moderation of “AI slop” in web search (e.g., Kagi) ([78:54], [80:07]).
Fireflies AI “fake it till you make it” origin story—manual meeting transcription marketed as AI ([85:03]).

AI Note-Taking & Privacy

Discussion about the etiquette of AI assistants in meetings, privacy concerns, and the rise of local AI language models for enhanced security ([87:01]).

AI and Everyday Life

Tinder’s AI “Chemistry” and Hinge’s AI review of dating profiles—creeping AI into love and relationships ([123:03]).
Use of AI for wedding planning, and even writing vows and separation agreements ([125:02]).
Demo of Google Labs’ GenType for creating fonts from custom prompts (e.g., "font of cats") ([147:34]).

Notable Quotes & Moments

“Wikipedia is a temple for the mind and I enjoy it.” — Jimmy Wales ([27:47])
“Trust is the most practical of all human virtues.” — Leo Laporte ([14:12])
“They asked, what did you do? I got rid of all the experts, opened it up, and hoped for the best.” — Paraphrased summary by Leo ([11:08])
“If I were giving a kid I liked a bit of money, when they turned 25, I'd give them $25, so that seems about right [for Wikipedia’s 25th anniversary].” — Jimmy Wales ([48:54])

Fun & Cultural Interludes

Explainer of cat islands in Japan, return pallets from Amazon ("polyster mountain"), and the saga of a man who posts daily “chive cutting” progress on Reddit until the community declares it perfect ([141:04]-[137:20]).
Extended group digression analyzing media scandals and employing AI to critique overwrought writing about “bamboo” in Ryan Lizza’s viral story ([54:10]-[76:29]).
Nick Cage’s latest film "The Carpenter’s Son" and its “teen Jesus” memes ([150:03]).

Important Timestamps

[02:27] — Jimmy Wales welcomed, early story about Wikipedia’s origins
[03:36] — Stats on Wikipedia’s size & contributors
[07:03] — Switching from Nupedia to wikis
[15:15] — Frances Frei’s “Trust Triangle”
[19:07] — Can Wikipedia be started today? — Usenet wasn’t as utopian as we remember
[20:36] — Persistent identity as the backbone of good communities
[21:31] — Real-world companies (Airbnb) and trust crises
[22:23] — Clarity of purpose; critique of Facebook/Twitter
[27:10] — Wikipedia’s anti-ad ethos
[29:40] — Wikipedia’s use in LLM training; AI slop
[31:12] — Community wariness about AI in knowledge production due to hallucinations
[37:23] — Right use-cases for AI: “the boring bits”
[38:50] — Grokopedia skepticism
[103:57] — Breaking news: “White House to preempt state AI regulation”
[109:54] — Nvidia profit update, AI investment
[141:04] — Cat Island, Amazon returns, chive-lord on Reddit

Summary

For Further Listening

Jimmy Wales – "The Seven Rules of Trust"
Wikipedia's 25th Anniversary: Donate here
Next guest: Ahmad Mostak (founder, Stable Diffusion & Intelligent Internet)
Listen at twit.tv or your favorite podcast app

Intelligent Machines 846: Chivelord

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Summary

Intelligent Machines 846: "Chivelord"

Episode Overview

Guest Introduction & Community Creation

Building Trust: The Wikipedia Model

Stats & Scope

Trust-Building Principles

Community Versus Algorithms

Purpose as the North Star

Ads, Nonprofit Model, and Wikipedia’s Ethos

Wikipedia and AI—Opportunities & Perils

Wikipedia as AI Training Data

Early AI Tool Experiments

Plausibility versus Fact

Right AI Use Cases

AI’s Broader Impacts, Regulation, and the Trust Crisis

Grok and Competing AI Knowledge Bases

AI Slop & the “Trust Apocalypse”

Live Demos: Gemini 3, ChatGPT, and More

AI Regulation & Industry

Breaking News: White House Preemption Order

Industry Updates

Internet & Media Culture

Monetization Models & Community Support

AI & Content Slop

AI Note-Taking & Privacy

AI and Everyday Life

Notable Quotes & Moments

Fun & Cultural Interludes

Important Timestamps

Summary

For Further Listening

Summary

Intelligent Machines 846: "Chivelord"

Episode Overview

Guest Introduction & Community Creation

Building Trust: The Wikipedia Model

Stats & Scope

Trust-Building Principles

Community Versus Algorithms

Purpose as the North Star

Ads, Nonprofit Model, and Wikipedia’s Ethos

Wikipedia and AI—Opportunities & Perils

Wikipedia as AI Training Data

Early AI Tool Experiments

Plausibility versus Fact

Right AI Use Cases

AI’s Broader Impacts, Regulation, and the Trust Crisis

Grok and Competing AI Knowledge Bases

AI Slop & the “Trust Apocalypse”

Live Demos: Gemini 3, ChatGPT, and More

AI Regulation & Industry

Breaking News: White House Preemption Order

Industry Updates

Internet & Media Culture

Monetization Models & Community Support

AI & Content Slop

AI Note-Taking & Privacy

AI and Everyday Life

Notable Quotes & Moments

Fun & Cultural Interludes

Important Timestamps

Summary

For Further Listening