Andrew Yang Says White-Collar AI Layoffs Force US Toward Basic Income
Ai4
As competitive pressure compels corporations to replace white-collar workers with automation, the state must redistribute concentrated productivity gains through basic income to avert severe social collapse.
## Background
Published by Ai4 on YouTube on August 28, 2025, this fireside chat features former presidential candidate and Forward Party founder Andrew Yang in conversation with veteran technology reporter Nancy Scola. According to the description, the session examines how rapid AI automation will transform the economy and redefine human labor, making the case for Universal Basic Income and cash relief as essential foundations for an AI-driven future.
## TL;DR
Andrew Yang argues that generative AI is driving an unprecedented wave of white-collar layoffs as competitive enterprise pressures force companies to automate knowledge work. He highlights that while AI will generate hundreds of billions in corporate productivity, macroeconomic growth means little to displaced workers without structural dividend mechanisms like Universal Basic Income and expanded Child Tax Credits. Pointing to eroding institutional trust and generational disaffection, Yang warns that the nation faces a stark choice between proactive policy adaptation or chaotic social collapse, framing the technological future as a crossroads between shared abundance and extreme inequality.
## Atmosphere & style
The session balances dry, self-deprecating humor with a sobering, urgent appraisal of the American economic and political landscape. Yang's delivery is conversational and candid, mixing behind-the-scenes anecdotes from corporate boardrooms and campaign stops with sharp critiques of political inertia and pop-culture analogies. Scola's direct questioning keeps the dialogue grounded, creating a fast-paced, pragmatic, and thought-provoking exchange about an impending societal turning point.
## Key takeaways
- [01:20](https://www.youtube.com/watch?v=YmK44MAL8FY&t=80s) Unlike previous waves of automation that decimated blue-collar manufacturing, modern AI directly threatens the roughly 35% of the US workforce in white-collar and office roles.
- [03:41](https://www.youtube.com/watch?v=YmK44MAL8FY&t=221s) Massive corporate spending on AI infrastructure is already causing quiet hiring freezes and rolling layoffs, masking economic weakness under job growth concentrated in healthcare.
- [06:17](https://www.youtube.com/watch?v=YmK44MAL8FY&t=377s) Federal AI policy largely misses the immediate crisis by prioritizing deregulation and perceived model bias over the displacement of millions of workers.
- [06:17](https://www.youtube.com/watch?v=YmK44MAL8FY&t=377s) Corporate executives privately acknowledge that AI will enable them to slash workforce headcount while increasing corporate profitability and stock values.
- [09:46](https://www.youtube.com/watch?v=YmK44MAL8FY&t=586s) Universal Basic Income is essential to prevent AI productivity gains from flowing solely into corporate balance sheets at the expense of displaced workers.
- [09:46](https://www.youtube.com/watch?v=YmK44MAL8FY&t=586s) Public anxiety around technological progress is driven by the rational realization that everyday citizens will not benefit from AI efficiencies without an ownership stake or dividend mechanism.
- [12:18](https://www.youtube.com/watch?v=YmK44MAL8FY&t=738s) Humanity Forward proved the viability of direct cash transfers by helping secure the federal Child Tax Credit expansion, distributing approximately $80 billion annually to families.
- [14:54](https://www.youtube.com/watch?v=YmK44MAL8FY&t=894s) The adoption of basic income mechanisms is an inevitability under AI acceleration; the only choice is whether the transition happens proactively or through social crisis.
- [16:00](https://www.youtube.com/watch?v=YmK44MAL8FY&t=960s) Unmitigated economic dislocation erodes institutional trust and degrades essential social traits like conscientiousness and agreeableness among younger generations.
- [17:51](https://www.youtube.com/watch?v=YmK44MAL8FY&t=1071s) Competitive market dynamics force individual companies to adopt AI to survive, shifting the responsibility for protecting displaced labor entirely onto government policy.
- [19:29](https://www.youtube.com/watch?v=YmK44MAL8FY&t=1169s) AI has the potential to eliminate baseline resource scarcity and boost per capita GDP, but avoiding dystopian inequality requires deliberate policies to share technological abundance.
## Detailed walkthrough
### [00:04](https://www.youtube.com/watch?v=YmK44MAL8FY&t=4s) Political Dysfunction and the Need for a Third Party
Technology reporter Nancy Scola opens the discussion by highlighting the unprecedented intersection between artificial intelligence and national politics, introducing Andrew Yang as someone who has been sounding the alarm on automation far longer than most. Yang immediately leans into self-deprecating humor, recalling how he spent time five years prior at an Iowa truck stop telling voters, "Guys, the robots are coming," before adding dryly, "And obviously that's why I'm president today and things are going so well."
Scola presses Yang on recent news reports detailing discussions between him and Elon Musk’s team regarding third-party efforts, asking why the rapid rise of artificial intelligence necessitates an alternative political party. Yang clarifies his view on the American two-party duopoly with a running joke: "the worst number of parties you can have is one. Second worst is two. Third worst is three," leaving the audience to judge whether the United States currently has any functional political parties at all.
[01:20](https://www.youtube.com/watch?v=YmK44MAL8FY&t=80s) The Anatomy of the American Workforce and the AI Wave
Yang traces his entry into presidential politics back to 2016 and 2017, when he recognized that the automation of roughly 4 million manufacturing jobs across key swing states—Ohio, Michigan, Pennsylvania, and Wisconsin—had directly paved the way for Donald Trump's victory. When he went to Silicon Valley to urge tech leaders to alert the public that AI was about to hit the country "like a freight train," tech executives unanimously declined to be the public messengers. Yang realized he would have to make the case himself.
To illustrate why modern AI will disrupt the country even more severely than past automation, Yang outlines the fundamental structure of the US labor market:
- **Educational attainment:** Only about 35% of Americans graduate from college; two-thirds of the population hold only a high school diploma.
- **Top 5 occupations (broadly representing half of the entire US workforce):**
1. Clerical and administrative support (including roughly 2 million call center workers).
2. Retail sales.
3. Food preparation and food service.
4. Truck driving and transportation.
5. Manufacturing.
While manufacturing was decimated over several decades, Yang points out that the current AI wave is directly targeting office workers and the 35% of college graduates whose positions are evaporating at rapid speed.
```mermaid
flowchart TD
accTitle: Labor Force Distribution and Automation Impact
A["Total US Labor Force"] --> B["Non-College Educated (~65%)"]
A --> C["College Educated (~35%)"]
B --> D["Top Blue-Collar & Service Jobs<br/>(Retail, Food Prep, Trucking, Call Centers, Mfg)"]
C --> E["Office Workers, Middle Managers & Tech Roles"]
D -.->|"Decimated by Blue-Collar Automation"| F["Economic Disruption"]
E -.->|"Rapidly Targeted by Generative AI"| F
```
[03:41](https://www.youtube.com/watch?v=YmK44MAL8FY&t=221s) The Hidden Job Cuts and Political Inertia
Yang argues that it is absurd to imagine tech companies spending a trillion dollars on AI infrastructure without it having a radical, labor-reducing effect on enterprise operations. For the past nine months, corporate executives have privately confided in him over dinners that they are quietly instituting hiring freezes and executing rolling layoffs because of AI automation. Yang points out that this reality recently surfaced in official economic data when labor numbers for May, June, and July were revised downward, revealing that approximately 75% of newly created jobs were confined entirely to the healthcare sector—largely because hands-on roles like phlebotomists remain difficult to automate.
Instead of preparing society for this structural transformation, the current political system remains entirely inert, focused instead on tribal grievances and partisan point-scoring. Discontented voters who supported Trump seeking economic relief have received policy proposals like sweeping tariffs and the federalization of local Washington, DC police forces—measures Yang argues will only spike consumer prices and devastate trade-dependent agricultural states like Iowa.
[06:17](https://www.youtube.com/watch?v=YmK44MAL8FY&t=377s) White-Collar Bloodbath and the Failure of AI Policy
Scola points to the Trump administration's AI action plan, which focuses on deregulation, streamlining permits for data centers, and curbing perceived "ideological bias" in artificial intelligence models. Yang responds that these priorities completely miss the real crisis unfolding on the ground. He argues that model bias is immaterial to the 2.8 million call center workers facing immediate obsolescence, the engineering graduates forced to work at Chipotle or drive for Uber, and the 50-year-old middle managers being quietly eliminated across corporate America.
Yang forcefully rejects the contrarian Washington narrative that warnings of a "white-collar bloodbath" are merely marketing hype from AI labs like Anthropic and OpenAI. He shares the recurring script he hears in private from tech leaders:
> "Hey, I'm the CEO of a publicly traded tech company. I've got I'm just going to make up a number 5,000 workers. I've just cut a thousand of them. I think I'm going to cut another 1500 in the next 12 to 18 months and I think my profitability is going to go up and my stock's going to go up. How do I feel about this? Very ambivalent. Like I'm a human being so I dislike firing lots of people, but what are you going to do?"
Yang laments that media commentators downplaying this reality are simply trying to "score points to accrue Substack subscribers," rather than addressing the structural displacement of white-collar labor.
[09:46](https://www.youtube.com/watch?v=YmK44MAL8FY&t=586s) The Economic Logic of UBI and "The Future Of"
Making his core case for Universal Basic Income (UBI), Yang emphasizes that the US produces an immense gross domestic product of approximately $82,000 per capita—a metric that AI will boost by hundreds of billions of dollars in pure economic productivity. However, because these productivity windfalls flow straight to corporate balance sheets while workers lose their jobs, society must establish a dividend mechanism to distribute newly generated wealth across the broader public.
Yang illustrates the growing public dread of technological transformation with an anecdote from his tenure at CNN:
- CNN network executives approached Yang to host a television series titled *The Future of with Andrew Yang*, exploring domains like education and transportation.
- After running focus groups, the executives returned with the verdict: "Hey, Andrew, bad news. Americans don't like the future."
- While focus groups liked Yang personally, the concept of "the future" provoked widespread anxiety because everyday citizens intuitively understand that technological efficiencies will not enrich them unless they own massive equity stakes in tech monopolies.
This dynamic has triggered a widespread "scramble for steady ground" in American life, driving populist agitation and deepening economic division.
[12:18](https://www.youtube.com/watch?v=YmK44MAL8FY&t=738s) Humanity Forward and the Enhanced Child Tax Credit
When asked if the mainstream emergence of tools like ChatGPT has made Universal Basic Income an easier sell over the past seven years, Yang admits that while citizens frequently approach him on the street saying, "Man, you called it," hearing that provides "cold comfort when someone's like, 'Hey man, you called it.' I'm just like, 'Well, we didn't do shit.'" Asked whether he plans another run for the presidency, Yang remarks that with roughly 30 years left in public life, he is "too young almost not to."
Yang emphasizes that his advocacy extends beyond rhetoric, citing the legislative achievements of his nonprofit advocacy organization, Humanity Forward:
- Humanity Forward spent years lobbying on Capitol Hill to expand the federal Child Tax Credit.
- The organization successfully helped secure an expansion that raises payments from $1,000 up to $2,200 per child per year.
- This policy directs roughly $80 billion annually into the pockets of struggling, lower-income American families.
Quoting science fiction to explain his motivation, Yang notes that just as "fear is the mind killer in *Dune*", "Poverty is the mind killer in real life."
[14:54](https://www.youtube.com/watch?v=YmK44MAL8FY&t=894s) UBI Research and the Two Paths Forward
Scola challenges Yang by citing recent academic literature, including a working paper from the National Bureau of Economic Research (NBER) suggesting that direct cash transfers showed mixed or limited short-term positive effects on children. Yang pushes back, pointing to long-term longitudinal studies of cash dividends among Native American tribal communities that showed significant, lasting increases in children's conscientiousness and agreeableness. He wryly observes that regardless of academic white papers, if you ask recipient families whether they want the cash support to continue, "They probably would say yes."
Yang concludes that the country will ultimately be forced to adopt basic income mechanisms as the AI revolution compounds economic dislocation. The fundamental choice facing society is not whether basic income happens, but whether the nation arrives there through an enlightened, proactive transition or through a chaotic, destructive crisis.
[16:00](https://www.youtube.com/watch?v=YmK44MAL8FY&t=960s) Institutional Trust, Generational Shifts, and the Uphill Battle for UBI
Reflecting on the deeper social fallout of rapid economic dislocation, Andrew Yang warns that much of the societal damage cannot simply be undone once it starts. Comparing the situation to trying to put "toothpaste back in the tube," he points out that once people fall through the cracks and suffer, restoring their faith in institutions or convincing them that doing the right thing will eventually pay off becomes nearly impossible. To illustrate this cultural unraveling, Yang references a study compiled by *Financial Times* data journalist John Burn-Murdoch analyzing generational personality traits, which found that conscientiousness and agreeableness have "gone off a cliff" among younger cohorts. When young people routinely see that positive contributions go unrewarded, their willingness to show up for work shifts or honor commitments deteriorates, placing society "in the soup" when basic social contracts fail.
Yang draws a direct parallel to parenting, noting that raising a child requires imperfect parents to show up every single day, model good behavior, and reinforce values over years in the hope that their children will thrive. Societal institutions—such as public schools, places of worship, and the news media—are supposed to play that exact role for the public. It breaks his heart to see those pillars eroding, leaving him convinced that while Universal Basic Income may eventually be adopted out of sheer necessity, achieving it will require weathering a painful and arduous transition.
- **Generational Trait Collapse**: Citing John Burn-Murdoch's reporting in the *Financial Times*, personality indicators like conscientiousness and agreeableness have plummeted among young people who feel hard work and reliability no longer provide tangible security.
- **Institutional Erosion**: Schools, religious institutions, and the media are struggling to perform the steady, long-term societal role modeling essential for civic health.
---
[17:51](https://www.youtube.com/watch?v=YmK44MAL8FY&t=1071s) Competitive Pressure on Organizations and Dario Amodei's Warning
```mermaid
flowchart TD
accTitle: Individual Enterprise AI Dilemma
A["Enterprise AI Dilemma"] --> B["Option 1: Resist AI Adoption"]
A --> C["Option 2: Aggressive AI Adoption"]
B --> D["Crushed by AI-Powered Competitors"]
D --> E["Business Fails & All Workers Fired"]
C --> F["Drives Operational Efficiency"]
F --> G["Forces White-Collar Displacements"]
G --> H["Macro Policy & Taxation Needed"]
```
Opening the floor to audience questions, Ron Schmelzer from *Forbes* asks what path businesses and international organizations should take regarding AI adoption, development, and regulation given that the technology is already out in the wild. Yang distinguishes between the realities of running a business and the role of government policy makers. For individual companies, adopting AI is a matter of pure survival in a competitive market: refusing to implement automation to protect headcount simply guarantees that an AI-powered competitor will run them out of business, resulting in every single employee losing their job anyway. Yang notes that while he has strong opinions on what public policy should dictate, he cannot fault corporate leaders who are forced into this dilemma.
Addressing tech industry motives, Yang defends Anthropic CEO Dario Amodei against critics who claim AI leaders hype automation risks purely to serve their own corporate interests. He highlights that Amodei has openly sounded alarms about AI devastating white-collar professions and went so far as to call for higher corporate taxes on tech firms—an explicit policy stance that traditional CEOs do not take unless they harbor genuine, deep-seated concern about the structural crisis ahead.
- **Market Imperative**: Organizations that refuse AI integration face competitive extinction, shifting the burden of safety nets and transition policies entirely onto the state.
- **Corporate Stance on Taxation**: Tech leaders like Anthropic's Dario Amodei have broken corporate orthodoxy by publicly endorsing higher taxes to address white-collar displacement.
---
[19:29](https://www.youtube.com/watch?v=YmK44MAL8FY&t=1169s) Growing the Pie: Technological Abundance, Star Trek vs. Mad Max, and 2028
An audience member asks whether AI adoption can expand the overall economic pie rather than merely driving cost-cutting and efficiency gains at the expense of workers. Yang agrees that while individual enterprises remain laser-focused on bottom-line efficiency, the technology will supercharge innovation on a massive societal scale. AI promises unprecedented breakthroughs, such as extending the human lifespan by finding cures for multiple forms of cancer and Alzheimer's disease, as well as unlocking scalable, sustainable energy systems. However, he cautions that macroeconomic abundance means very little to an individual worker sitting at home without an income, watching their family struggle with depression and financial ruin.
```mermaid
flowchart LR
accTitle: Divergent Futures of Abundance
A["AI Innovation & Productivity"] --> B["Potential Abundance ($100k-$180k per capita)"]
B --> C["Cooperative Evolution: Star Trek"]
B --> D["Inequality & Resource Conflict: Mad Max"]
```
Yang closes with a vision of potential post-scarcity prosperity, urging the audience to imagine an economy generating $100,000 or $180,000 per capita. For the first time in human history, artificial intelligence could eliminate baseline resource scarcity, leaving humanity with a fundamental choice: evolve cooperatively into an era of shared abundance or tear itself apart. As Yang puts it, "I vastly prefer *Star Trek* to *Mad Max* as a future I'm going to leave for my kids." Moderator Nancy Scola playfully caps off the session by asking if he plans to run for president in 2028, to which Yang jokingly replies that he cannot make an official announcement on stage before thanking the room.
- **Transformative Milestones**: Expected AI dividend includes breakthroughs in cancer therapies, Alzheimer's eradication, and clean energy infrastructure.
- **The Abundance Paradigm**: The economic output could surge to $100,000–$180,000 per capita, transforming humanity's primary challenge from managing resource scarcity to preventing social collapse amidst unprecedented wealth.
## Notable quotes
> [00:04](https://www.youtube.com/watch?v=YmK44MAL8FY&t=4s) Guys, the robots are coming — Andrew Yang
> [00:04](https://www.youtube.com/watch?v=YmK44MAL8FY&t=4s) And obviously that's why I'm president today and things are going so well. — Andrew Yang
> [00:04](https://www.youtube.com/watch?v=YmK44MAL8FY&t=4s) the worst number of parties you can have is one. Second worst is two. Third worst is three — Andrew Yang
> [06:17](https://www.youtube.com/watch?v=YmK44MAL8FY&t=377s) Hey, I'm the CEO of a publicly traded tech company. I've got I'm just going to make up a number 5,000 workers. I've just cut a thousand of them. I think I'm going to cut another 1500 in the next 12 to 18 months and I think my profitability is going to go up and my stock's going to go up. How do I feel about this? Very ambivalent. Like I'm a human being so I dislike firing lots of people, but what are you going to do? — Andrew Yang
> [09:46](https://www.youtube.com/watch?v=YmK44MAL8FY&t=586s) Hey, Andrew, bad news. Americans don't like the future. — CNN network executives
> [12:18](https://www.youtube.com/watch?v=YmK44MAL8FY&t=738s) Man, you called it — Voters / Citizens
> [12:18](https://www.youtube.com/watch?v=YmK44MAL8FY&t=738s) Well, we didn't do shit. — Andrew Yang
> [12:18](https://www.youtube.com/watch?v=YmK44MAL8FY&t=738s) Poverty is the mind killer in real life. — Andrew Yang
> [14:54](https://www.youtube.com/watch?v=YmK44MAL8FY&t=894s) They probably would say yes. — Andrew Yang
> [19:29](https://www.youtube.com/watch?v=YmK44MAL8FY&t=1169s) I vastly prefer Star Trek to Mad Max as a future I'm going to leave for my kids. — Andrew Yang
## Mentioned
Andrew Yang, Nancy Scola, Forward Party, Elon Musk, Donald Trump, Silicon Valley, Chipotle, Uber, Anthropic, OpenAI, Dario Amodei, CNN, Humanity Forward, Dune, National Bureau of Economic Research (NBER), Financial Times, John Burn-Murdoch, Ron Schmelzer, Forbes, ChatGPT, Star Trek, Mad Max
## Video description
Nancy Scola, veteran technology reporter
Andrew Yang, Former Presidential Candidate, Bestselling Author, Founder, Forward Party
Abstracts
How will AI transform our economy — and what happens to people when the robots come for our jobs?
In this talk, I’ll explain why Universal Basic Income (UBI) is not just a policy idea, but a necessary foundation for an AI-driven future that works for everyone. I’ll share how accelerating automation will reshape industries, redefine the value of human work, and demand bold, practical solutions to keep communities strong and families secure. You’ll hear real-world lessons from my presidential campaign, Humanity Forward’s cash relief efforts, and my ongoing work to modernize democracy through the Forward Party. Join me to explore how we can balance innovation with economic dignity — and walk away ready to shape a future where AI helps us all thrive.
杨安泽称白领AI裁员潮倒逼美国走向基本收入
随着竞争压力迫使企业用自动化取代白领员工，国家必须通过基本收入重新分配集中的生产力红利，以避免严重的社会崩溃。
杨安泽指出，企业间的竞争压力迫使公司将知识工作自动化，生成式AI正掀起一场前所未有的白领裁员潮。他强调，尽管AI将为企业带来数千亿美元的生产力提升，但若缺乏全民基本收入（UBI）和扩大儿童税收抵免等结构性红利机制，宏观经济增长对被替代的劳动者来说毫无意义。鉴于机构信任度日趋瓦解以及代际不满的蔓延，杨安泽警告称，国家正面临前瞻性政策调整与混乱的社会崩溃之间的严峻抉择，并将技术的未来视作共享繁荣与极端不平等之间的十字路口。
与过去冲击制造业的自动化不同，现代 AI 正直接威胁占全美约 35% 拥有大学学历的白领与办公室群体；巨额 AI 基础设施投资正悄然引发广泛的招聘冻结与持续裁员。 (1:20)
当前的联邦 AI 政策过于聚焦去监管与模型偏见，脱离了数百万普通员工技术性失业的现实；企业高管私下坦言，通过自动化裁员提高利润与股价已成为行业常态。 (6:17)
公众对技术转型的广泛焦虑源于普通人无法享有 AI 带来的生产力红利；全民基本收入（UBI）是应对失业冲击的必然手段，核心区别仅在于社会是主动建立保障机制还是因危机爆发而被动应对。 (9:46)
AI 的生产力跃升有望将人均经济产出推高至 10 万至 18 万美元，人类面临的根本抉择在于通过协同分配迈向共享繁荣的《星际迷航》式未来，还是滑向资源极度分化的《疯狂的麦克斯》式危机。 (19:29)
Reading summary
Andrew Yang argues that rapid advancements in artificial intelligence will decimate white-collar and administrative employment while concentrating corporate profits, making Universal Basic Income an unavoidable mechanism to prevent widespread social and institutional collapse.
Workforce Vulnerabilities and the Generative AI Shock (1:20)
While past waves of automation eliminated approximately 4 million manufacturing jobs across industrial swing states, Yang emphasizes that generative AI directly threatens the 35% of Americans who hold college degrees alongside millions in administrative roles. The US labor market remains heavily concentrated in vulnerable positions, with its top occupations including roughly 2 million call center staff, retail clerks, food service workers, and drivers, while approximately two-thirds of the population holds only a high school diploma.
Yang contends that massive corporate investments in AI infrastructure are already driving rolling layoffs and quiet hiring freezes. Official labor statistics reflect this shift: recent revisions revealed that roughly 75% of newly added jobs were confined to hands-on healthcare roles, such as phlebotomists, which currently resist technological automation.
Market Pressures and Misguided Federal Policy Responses (6:17)
At the enterprise level, Yang observes that business leaders face an existential dilemma: refusing to implement AI automation guarantees defeat by leaner competitors, ultimately endangering every employee's job. He rejects claims that white-collar displacement warnings are mere marketing hype, citing private admissions from executives planning deep workforce cuts to increase profitability. He also notes that Anthropic CEO Dario Amodei has broken corporate norms by publicly calling for higher corporate taxes to help mitigate workforce displacement.
Despite these market pressures, Yang argues that current political proposals remain counterproductive. Policies prioritizing model-bias investigations, data-center deregulation, or sweeping tariffs fail to address the core dilemma facing displaced corporate middle managers, underemployed graduates, and the 2.8 million call center workers facing obsolescence.
The Economic Rationale for Universal Basic Income (9:46)
With US gross domestic product standing at approximately $82,000 per capita, Yang asserts that AI productivity gains will direct hundreds of billions of dollars to corporate bottom lines without naturally reaching dislocated workers. To prevent a widespread economic panic, he advocates for direct wealth distribution through basic income. Citing progress by his organization, Humanity Forward, Yang points to federal Child Tax Credit expansions from $1,000 to $2,200 per child, which directed $80 billion annually to lower-income households.
Addressing mixed short-term findings on direct cash transfers from a National Bureau of Economic Research working paper, Yang points to longitudinal studies of cash dividends among Native American tribes. Those findings showed sustained, long-term increases in children's conscientiousness and agreeableness, reinforcing his view that sustained liquidity provides essential structural stability for families.
Institutional Decay and the Scarcity-Abundance Dilemma (16:00)
Beyond labor metrics, Yang warns that prolonged economic dislocation causes irreversible cultural damage. Referencing data compiled by the Financial Times, he highlights that personality traits like conscientiousness and agreeableness have dropped precipitously among younger generations who see that diligence no longer guarantees stability, while foundational institutions like schools and media lose their civic authority.
Yang suggests that while AI could theoretically elevate economic productivity to $100,000 or $180,000 per capita and yield breakthroughs in energy and medicine, abundance at the top does not resolve individual hardship. Society faces a stark choice between a cooperative, post-scarcity economy and extreme inequality and unrest.
Yang concludes that the adoption of Universal Basic Income is an eventual certainty under AI-driven automation, leaving unresolved only whether the nation will implement it through proactive, orderly policy or in the wake of an acute economic crisis.
[0:04] Andrew Yang: Guys, the robots are coming
[0:04] Andrew Yang: And obviously that's why I'm president today and things are going so well.
[0:04] Andrew Yang: the worst number of parties you can have is one. Second worst is two. Third worst is three
[6:17] Andrew Yang: Hey, I'm the CEO of a publicly traded tech company. I've got I'm just going to make up a number 5,000 workers. I've just cut a thousand of them. I think I'm going to cut another 1500 in the next 12 to 18 months and I think my profitability is going to go up and my stock's going to go up. How do I feel about this? Very ambivalent. Like I'm a human being so I dislike firing lots of people, but what are you going to do?
[9:46] CNN network executives: Hey, Andrew, bad news. Americans don't like the future.
[12:18] Voters / Citizens: Man, you called it
[12:18] Andrew Yang: Well, we didn't do shit.
[12:18] Andrew Yang: Poverty is the mind killer in real life.
[14:54] Andrew Yang: They probably would say yes.
[19:29] Andrew Yang: I vastly prefer Star Trek to Mad Max as a future I'm going to leave for my kids.
Original transcript
[0:04] Uh thank you so much everyone for being
[0:05] here. I'm so excited to be here uh and
[0:07] have this discussion with Andrew Yang.
[0:08] It's an fascinating time at the
[0:09] intersection of technology and politics,
[0:11] specifically AI and politics. And Andrew
[0:14] Yang's a p perfect person to talk about
[0:15] it because you've been talking about it
[0:16] for about as long as anybody. Uh
[0:18] >> yeah, five years ago I was in a truck
[0:20] stop in Iowa being like, "Guys, the
[0:22] robots are coming."
[0:24] >> And obviously that's why I'm president
[0:26] today and things are going so well.
[0:29] worked. Uh so I want to start with a bit
[0:31] of uh recently reported news. It was
[0:32] reported that you had a conversation or
[0:34] otherwise were in contact with Elon Musk
[0:36] or his team around the idea of starting
[0:38] a third party. You have some experience
[0:40] in that. You started the third party in
[0:41] 2021. Leaving the Democratic party, you
[0:43] started the forward party. What is the
[0:45] the rise of AI? Why does this the rise
[0:48] of AI, excuse me, necessitate the
[0:50] creation of a third or even fourth
[0:51] party? Like what is the interplay
[0:52] between those two concepts?
[0:54] >> Miss through the fourth part. Oh, that's
[0:55] fine. Um
[0:56] >> well, yours and Elon's.
[0:57] >> No, no. So,
[0:58] >> I'm sorry. Is it the same party? Are you
[1:00] starting?
[1:01] >> So, my joke is the worst number of
[1:03] parties you can have is one. Second
[1:05] worst is two. Third worst is three. See
[1:08] how it's going?
[1:09] You can determine for yourself how many
[1:11] functional parties we have right now.
[1:13] So,
[1:14] some might say, you know, zero, you
[1:17] know. Um,
[1:20] all right. So I got into public life
[1:22] because in my estimation
[1:26] uh the reason Trump won in 2016 was that
[1:29] we'd automated away about 4 million
[1:31] manufacturing jobs that were primarily
[1:33] based in Ohio, Michigan, Pennsylvania,
[1:34] and Wisconsin. All states he won. And if
[1:37] you look at the district data, you find
[1:39] that the needle starts going to the red
[1:41] as soon as you get rid of the
[1:42] manufacturing plant um or or other job
[1:45] base there. uh and my friends in Silicon
[1:47] Valley were working on something called
[1:49] AI that was going to take something
[1:51] called the jobs away
[1:54] from a lot of people. And I, you know,
[1:56] determined this in 2017 or so. And so I
[2:00] said, "Okay." I went to Silicon Valley
[2:02] and said, "Hey guys, uh, who wants to
[2:04] try and alert the American people to the
[2:05] fact that AI is going to come down like
[2:07] a freight train?" Uh, and obviously
[2:10] everyone in Silicon Valley said, "Not
[2:11] me. Not me. Not me." And so I was like,
[2:13] "All right, guys. like then I'll do it
[2:15] and uh you should at least give me money
[2:17] um to make this case the American
[2:19] people. Some of them did, some of them
[2:20] didn't. Uh so you when you talk about AI
[2:23] and its inner action with our politics,
[2:27] uh we decimated the manufacturing uh
[2:31] workforce over, you know, multi-year
[2:34] period. Uh and we're about to do the
[2:36] same thing to office workers. So
[2:38] congratulations to us. Um, no. Uh, um,
[2:42] but just to level set a little bit, what
[2:44] percentage of Americans graduate from
[2:46] college?
[2:50] >> It's about 35%. So, the population is uh
[2:53] 2/3 high school grads. What are the most
[2:56] common jobs in the US economy?
[2:59] >> Truck driving is number four, hence my
[3:01] visit to the truck stop.
[3:04] >> Retail is number two.
[3:07] Healthcare is a sector would be there
[3:08] but it's it it it has a bunch of
[3:10] different occupations. So number one is
[3:14] clerical and administrative which
[3:16] includes call center workers of which
[3:17] there are still approximately 2 million.
[3:19] Uh number two is retail. Number three is
[3:22] food service and food prep. Number four
[3:24] is truck driving and transportation. And
[3:25] number five, believe it or not, is still
[3:27] manufacturing. So that's about half of
[3:29] the American uh labor force in those
[3:32] five occupations broadly defined. And
[3:34] then you have college grads are in the
[3:36] 35%. Uh, and those jobs are now
[3:39] evaporating pretty quick. And I was
[3:42] joking with Nancy on the way up here.
[3:43] It's like, imagine if American industry
[3:46] and tech companies spent a trillion
[3:47] dollars on AI and it had no impact on
[3:51] the operations of all these companies. I
[3:54] mean, that's absurd if you think about
[3:55] it. Like, of course, it's going to have
[3:56] a profound impact. And for the last 9
[3:59] months or so, CEOs have been telling me
[4:01] in private, I'm not hiring because of
[4:03] AI. I'm quietly laying people off
[4:05] because of AI. And I kept hearing this
[4:07] and thinking, ah, when is this going to
[4:09] hit the labor data? Like, when is this
[4:11] going to hit the job data? And the it
[4:13] hit about a week and a half ago. I don't
[4:16] know if you guys saw that where u May,
[4:18] June, July got revised down. 75% of the
[4:21] new jobs created in that that period
[4:23] were just in healthcare in this one
[4:25] industry because phabbotomists still
[4:27] hard to automate. Um so you have uh so
[4:31] you have this
[4:34] title wave rolling through the American
[4:36] economy uh and then you have a political
[4:38] system that is essentially completely
[4:41] inert or unresponsive to it because our
[4:43] political system now is just scoring
[4:45] points along tribalist and ideological
[4:48] lines. There are a lot of people in my
[4:50] opinion who voted for Trump because they
[4:51] were unhappy with various economic
[4:53] circumstances. But what are they
[4:54] getting? They're getting tariffs and
[4:56] nationalization of the, you know, DC uh
[4:58] police force and a bunch of things that
[5:00] have nothing to do with the challenges
[5:03] that um I I've just uh outlined and in
[5:06] some ways are going to make them worse
[5:07] because tariffs, my opinion, raise
[5:09] prices uh you know eliminate uh a lot of
[5:12] trade-based jobs, including in places
[5:14] like Iowa where I spent a lot of time uh
[5:16] 5 years ago and they have uh like a
[5:19] trade-based agricultural economy and
[5:21] they're getting hurt a lot of they that
[5:23] was a state that went to Trump. There
[5:24] are a lot of red states that voted for
[5:26] Trump that are seeing those kinds of
[5:27] impacts. So, we're in this kind of uh
[5:31] downward spiral of uh cocktail of um
[5:36] displacement of American workers and
[5:38] then a political system and a media
[5:40] industrial complex with the exception of
[5:41] Nancy Skola who's excellent
[5:45] that that is not actually responding to
[5:49] genuinely. You should follow Nancy Skola
[5:50] on her social media platform. she's
[5:52] actually like very very fact-based and
[5:55] the rest of it.
[5:56] >> Uh and and so that this is uh why we are
[6:00] where we are is that we have rising
[6:02] challenges and an unresponsive political
[6:04] system. Uh and so most Americans now are
[6:06] like okay not working so well. So then
[6:08] what is the answer? And I'm going to
[6:09] suggest the answer might have to come
[6:11] from outside of the two-party system
[6:13] because neither of the two legacy
[6:14] parties actually going to save us.
[6:17] >> So we saw you spoke with Elon Musk. I'm
[6:19] going to ask you more about that
[6:20] offstage. The um shortly afterward that
[6:23] the Trump administration released their
[6:24] AI action plan. So they tried to address
[6:26] some of these concerns about AI while
[6:28] also sort of you know sparking more
[6:30] investment uh in the field. How does
[6:32] that differ when you look it's pretty
[6:34] sweeping, right? It's like let's loosen
[6:35] up permitting for data centers. Let's
[6:37] address ideological bias, quote unquote
[6:39] ideological bias in AI. How did that uh
[6:42] plan look different than what what the
[6:44] Yang administration should that have
[6:45] come to pass would have put out on on
[6:48] AI? I I I've outlined some of it just
[6:51] now, Nancy, but
[6:53] uh
[6:55] I think that the concerns they're
[6:56] outlining and the measures you just
[6:58] described, which is, hey, you need to be
[6:59] able to build data centers and like,
[7:01] hey, you have to make sure that the um
[7:03] the messages they put out are are not
[7:06] biased, are not the main things I'm
[7:08] concerned about. The main things I'm
[7:09] concerned about are the 2.8 million call
[7:11] center workers who are going to uh be
[7:13] cashiered pretty quick. uh the
[7:17] recent college graduates uh who graduate
[7:20] with engineering degrees and are working
[7:21] at Chipotle or Uber. I don't know if you
[7:23] guys have seen these these reports. Uh
[7:25] and I have tons of friends who are in
[7:28] the field who are highly educated middle
[7:30] managers at various tech companies
[7:32] who've recently been laid off. Uh and in
[7:35] some ways like who's going to cry for
[7:37] the laid-off 50-year-old executive? You
[7:40] know what I mean? Like maybe if you're a
[7:42] 50-y old executive, you might cry that
[7:44] person, but like that that's not a
[7:46] really uh you know like sympathetic
[7:49] narrative um to the population at large,
[7:51] but then that's a real person with a
[7:53] family and then you multiply that times
[7:55] x 100,000. Um, so that's where I think
[7:59] we should be focused. Um, less so on
[8:02] whether the models are, and look, I I
[8:05] care obviously whether the models are uh
[8:07] racist or the rest of it. But, uh, but
[8:10] that that to me is going to be
[8:11] immaterial to a lot of the workers who
[8:14] are facing a very tough circumstance
[8:16] very soon. There's been a a savvy take
[8:18] in Washington, the sort of people who,
[8:20] you know, want to seem clever about this
[8:21] recently that say that the talk of the
[8:23] white collar bloodbath, that was a
[8:25] phrase that's been floating around that
[8:27] that's overblown. That's just companies
[8:28] like Anthropic, OpenAI trying to uh
[8:31] prove how powerful their tools are. How
[8:33] do you sort of how do you react against
[8:34] that? I mean, it's obviously differs
[8:35] from your perspective. How
[8:36] >> No, no. Again, I mean, um I I have
[8:39] private conversations with CEOs over
[8:40] dinner. I'm going to describe one. Hey,
[8:42] I'm the CEO of a publicly traded tech
[8:44] company. I've got I'm just going to make
[8:46] up a number 5,000 workers. I've just cut
[8:49] a thousand of them. I think I'm going to
[8:51] cut another 1500 in the next uh 12 to 18
[8:54] months and I think my profitability is
[8:56] going to go up and my stock's going to
[8:58] go up. How do I feel about this? Very
[8:59] ambivalent. Like I'm a human being so I
[9:01] dislike firing lots of people, but what
[9:03] are you going to do? Um I I've had that
[9:06] conversation or version of it dozens of
[9:09] times. So anyone who thinks that like
[9:12] the the white collar blood bath is
[9:15] nonsense is going to be wrong and then x
[9:19] months from now they're going to be like
[9:20] oh I didn't call that like you know
[9:22] didn't call that right. Um but the odds
[9:24] of them owning up to that very low. Uh
[9:26] because now we're in we're at a point
[9:28] where uh you know all you can do is try
[9:31] and score points to you know acrew
[9:33] substack um subscribers so that you can
[9:37] ek out a living. um you know that that's
[9:40] what we're now reduced to with the
[9:41] exception of Nancy Skola and her
[9:43] esteemed organization and the rest of
[9:45] it.
[9:46] >> Um your response to some of these uh
[9:48] changes in the in the labor force and in
[9:50] the job market has been universal basic
[9:51] income. Can you give your very basic
[9:53] your very quick pitch on on UBI?
[9:56] >> Sure. So uh America's GDP is up to about
[9:59] $82,000 per capita. Uh so if you were to
[10:04] try and build a foundation for Americans
[10:06] and by the way that 82,000 per capita is
[10:08] going to shoot up because of something
[10:09] called AI
[10:11] that's going to add hundreds of billions
[10:14] of dollars certainly in economic
[10:15] productivity. Uh you know it's like when
[10:17] that tech CEO fires his thousand workers
[10:20] and replaces them with AI, the company
[10:23] is going to do just fine. Uh now those
[10:26] workers are going to be in a tougher
[10:28] spot. So what you should do is you
[10:29] should start uh taking some of the newly
[10:33] generated value and distributing it more
[10:34] broadly to the American people. I'm
[10:36] going to share a quick story with you
[10:37] guys that'll that'll just for you all
[10:39] it'll be funny. So um I worked for CNN
[10:42] for a particular period of time and they
[10:44] approached me and said hey Andrew we
[10:46] want you to do a TV show called the
[10:48] future of with Andrew Yang. It was like
[10:49] the future of education the future of
[10:52] transportation. I said sounds like a
[10:54] good idea. I mean let's explore. And
[10:55] then they did a focus group and they
[10:58] came back and said, "Hey, Andrew, bad
[11:00] news. Americans don't like the future."
[11:05] Now, happily, they also said they like
[11:07] you just fine. So, uh, you know, like
[11:10] we'll continue to have you on air, but
[11:12] um, but the future of no likey. So uh so
[11:17] uh well you know one of the reasons that
[11:18] most Americans sense instinctively that
[11:20] as these efficiencies pick up steam it's
[11:23] not going to benefit them you know
[11:26] because maybe they're not a major
[11:27] shareholder in that tech company. Now
[11:30] you all are probably on the other end of
[11:32] this curve probably by virtue of being
[11:35] at this conference working in this field
[11:37] doing what you're doing. Um we can all
[11:39] see that there's this divergence
[11:41] happening in the economy where it's like
[11:42] if you are a beneficiary then you know
[11:44] you go to the moon. I talked to someone
[11:46] the other day who like works for one of
[11:48] these uh companies is benefiting from AI
[11:50] and is like you know is like I'm making
[11:51] tons of money and like I have mixed
[11:53] feelings about it. Um, so what what's
[11:56] happening in American life is like a
[11:58] scramble for steady ground. And
[12:00] unfortunately that scramble is going to
[12:02] get harder and harder for most people.
[12:03] Most people in this room, I sense you'll
[12:06] probably be fine. Um, but you know that
[12:08] that that doesn't describe the normal
[12:10] situation and um, Americans sense it and
[12:12] so they're they're getting uh, agitated
[12:14] and frustrated and you're seeing that
[12:16] play out in different ways.
[12:18] >> You've been promoting the idea of
[12:19] universal basic income for about seven
[12:21] years.
[12:22] >> Yeah, sure. Chad GPT rolled onto the
[12:25] scene, got everyone's attention about
[12:27] four years ago. Has it become easier to
[12:29] sell the idea of UBI or is it sort of
[12:30] >> Yeah, guys, I uh virtually every day
[12:33] someone come to me on the street and
[12:35] say, "Man, you called it, you know, and
[12:37] again, that's why I'm president today."
[12:41] >> Um, so
[12:42] >> you going to take another crack at the
[12:43] uh at the White House?
[12:45] >> I I'm I'm like too young almost not to,
[12:48] you know what I mean? I've got like
[12:50] another 30 years uh in American life.
[12:54] Um
[12:58] yeah, so uh I mean the problems aren't
[13:00] getting any better unfortunately. Uh and
[13:04] I will say that um I do get angry and
[13:07] frustrated sometimes because it's cold
[13:09] comfort when someone's like, "Hey man,
[13:10] you called it." I'm just like, "Well, we
[13:12] didn't do shit." though I I I though I I
[13:14] do want to amend that slightly is that
[13:16] um my team has spent the last five years
[13:19] lobbying for something called the
[13:21] enhanced child tax credit. Um that
[13:23] actually got wedged into the big
[13:25] beautiful bill. Um and so uh American
[13:28] families who make below a certain amount
[13:30] of money that have kids are going to get
[13:31] an additional 80 billion a year um
[13:34] forever. Um and so this is like one of
[13:36] the greatest accomplishments I've had in
[13:39] my life because my goal is to alleviate
[13:41] poverty. I think poverty is stupid and
[13:42] unnecessary. Um, and those of you who
[13:45] are sci-fi fans, I I call it the the
[13:47] mind killer. It's like, you know, fear
[13:48] is the mind killer in June. Poverty is
[13:50] the mind killer in real life. Um, so the
[13:53] fact that my team at Humanity Forward
[13:56] managed to
[13:58] get $80 billion a year out to uh
[14:00] struggling American families is
[14:02] something that I'm very, very proud of.
[14:04] And if you donated to my campaign, then
[14:06] you helped make that happen, too. So,
[14:07] thank you. And if you didn't donate to
[14:09] my campaign, where the were you?
[14:12] >> What was that number? How much money has
[14:13] humanity for it ruled out?
[14:14] >> So, I mean, the So, the enhanced child
[14:16] tax credit will distribute about $80
[14:18] billion a year to American families.
[14:20] >> Um because it was meant to go down to
[14:22] $1,000 um per kid per year. And then um
[14:26] now it's 2,200, which I'm going to
[14:28] suggest is a much bigger number than a
[14:30] thousand.
[14:32] [Applause]
[14:36] So, you know, I'm I'm like not I'm not
[14:38] just like a dude who's like, "Oh, I was
[14:40] right. Like, you know, now I'm not blah
[14:42] blah blah." It's like I'm I'm doing
[14:43] Like, I'm a real person. I do
[14:45] I don't just hang out in Las Vegas
[14:48] ballrooms and entertain you all. Like, I
[14:49] I uh
[14:52] you know what I mean? Anyway,
[14:54] >> some of the recent research on universal
[14:56] basic income hasn't necessarily been so
[14:58] supportive of the positive effects,
[15:00] right? There's been like this trend of
[15:01] papers coming out. There's one la last
[15:03] month. It was a working paper from the
[15:05] um National Bureau of Economic Research
[15:07] suggested the impact on kids at least in
[15:09] the short term wasn't overwhelmingly
[15:10] positive. Right. That's been the sort of
[15:12] trend in research. Are you looking at me
[15:13] skeptically? Is that not
[15:15] >> I mean I've I've seen some of the white
[15:16] papers. I've seen I've seen some white
[15:18] papers in the other direction from
[15:19] Indian tribes for example where like u
[15:22] um kids levels of consciential
[15:24] conscientiousness and agreeableness went
[15:26] up when their families received a
[15:28] certain amount of money and it was like
[15:29] a very long-term longitudinal study. Um,
[15:32] I'm going to suggest that even the
[15:33] studies that have found mixed results,
[15:35] uh, if you ask the families, hey, do you
[15:36] want to keep getting this money? They
[15:37] probably would say yes. Just a guess.
[15:42] So, I I think we wind up heading down a
[15:45] version of this direction. I've always
[15:47] thought so. The question to me is um, do
[15:50] you get there the positive, benign,
[15:52] enlightened way or the nasty and hard
[15:55] way? And the nasty and hard way I think
[15:57] is going to be vastly destructive over a
[16:00] period of years. And some of the damage
[16:02] that we're seeing, it's not it can't be
[16:05] undone. You know what I mean? It's like
[16:06] toothpaste out of a tube. You're like,
[16:07] "Oh, we up. We should put the
[16:09] toothpaste back in the tube." Like,
[16:10] that's not,
[16:12] you know what I mean? Like, after things
[16:14] start going south for particular folks,
[16:17] then, you know, it's hard to restore
[16:19] their trust in institutions or that if
[16:21] they do the right thing, they're going
[16:22] to benefit. Um there was a a study that
[16:25] came out last week um from this
[16:27] Financial Times journalist you're
[16:28] probably friends with John Burn Murdoch
[16:30] where he compiled uh personality
[16:33] traits across generations and
[16:35] conscientiousness and agreeableness have
[16:37] gone off a cliff for young people uh and
[16:40] there's some belief that it's like look
[16:42] they they have not actually had good
[16:44] behaviors rewarded or positively
[16:47] reinforced and so when they don't show
[16:49] up for a shift at work now it's like can
[16:51] you blame them? It's like, well,
[16:52] Like, you know, I mean, I feel for them,
[16:54] but like we're kind of in the soup if
[16:56] you can't expect anyone to show up and
[16:58] do what they, you know, said they were
[17:00] going to do. Uh, and that's very hard to
[17:03] undo as a parent. You know, like, as a
[17:05] parent, how many of you all are parents?
[17:07] It's like, so, you know, if you're a
[17:08] parent, what you do is you try and do
[17:10] the right thing, be a good role model
[17:11] for your child day in day out. you're
[17:13] not perfect, you make mistakes, and then
[17:15] you think if you like repeat that over a
[17:17] period of years, then like hopefully
[17:19] your your kid will like benefit. And
[17:21] that that's parenting, you know, and
[17:23] that's what our institutions are meant
[17:24] to do uh societywide, whether it's our
[17:27] schools, uh places of worship, news
[17:30] media.
[17:32] So I keep
[17:33] >> No, we're fine
[17:33] >> with the with the exception of um you
[17:35] know so um yeah and so it it it breaks
[17:39] my heart um that what we what we've done
[17:42] um because I think we're to the extent
[17:44] that universal basic income is achieved
[17:45] I think it's going to be through a very
[17:47] very um arduous period of years two
[17:51] minutes two audience questions let's
[17:52] make them quick yes please quick
[17:55] >> toothpaste back in the tube
[17:57] >> Ron Schmelzer from Forbes uh so question
[17:59] is about AI because the toothpaste is
[18:01] already out of the tube for AI talking
[18:03] about the the negative impact. So what
[18:05] is the suggested direction that that
[18:07] organization should go with either
[18:09] adoption of AI their development of AI
[18:11] regulations on AI restrictions what and
[18:14] this is an international situation not
[18:16] just US only.
[18:17] >> Oh sure so um the way you're asking the
[18:20] question Ron it's like what should
[18:21] individual organizations do and
[18:22] individual organizations should adopt AI
[18:25] as it suits their their goals. Uh, you
[18:27] know, it's unfortunately we're in a
[18:29] situation where if you were to be like,
[18:30] I refuse to use AI, then you'll probably
[18:32] get crushed by your competitors. And if
[18:34] you're trying to avoid firing a certain
[18:36] number of people, you're probably going
[18:36] to have to fire them all when you go out
[18:38] of business cuz like some AI powered
[18:40] competitor wrecks you. So, if you're an
[18:42] individual organization, you know, what
[18:44] are you going to do? Um, now there's a
[18:47] distinction between what an individual
[18:48] organization should do and what policy
[18:50] makers should do or what uh, you know,
[18:51] like uh, uh, government should be doing.
[18:55] Um, so I have feelings about that
[18:56] obviously, but for the individual
[18:58] organization, you like I don't blame the
[19:00] CEOs who I had dinner with who described
[19:02] this to me because it's like, man, if I
[19:03] was in your shoes, probably be doing the
[19:05] same thing, you know, like you, by the
[19:07] way, the folks who say anthropic, it's
[19:08] like, oh, I'm serving my own interest by
[19:10] saying we're wrecking white collar jobs.
[19:11] They said we should tax we should get
[19:12] taxed more is what Daario said. And I
[19:15] last I checked, that's not in the
[19:16] interest of CEOs to raise our hands and
[19:18] say, tax us more. I mean, that that
[19:19] wasn't I I actually take him at his word
[19:21] that he's genuinely concerned. One last
[19:24] one very quickly. Yes, sorry.
[19:29] >> Right now, a lot of the adoption of the
[19:31] AI seem to be focusing on efficiency
[19:33] gains. Have you seen uh anyone working
[19:35] on making the pie bigger for everyone uh
[19:38] so that we don't have to worry about,
[19:40] you know, people losing their jobs.
[19:44] >> It's true. A lot of companies are going
[19:46] to say, "Look, let me just like get my
[19:47] stuff done more efficiently." But
[19:49] they're going to be societywide gains
[19:50] like and let I'll end on this positive
[19:52] uplifting note because you guys are
[19:53] obviously for the most part like uh you
[19:56] know AI proponents. Uh are we going to
[20:00] lengthen the human lifespan because we
[20:02] we find cures to uh various forms of
[20:05] cancer and maybe even Alzheimer's? Like
[20:07] yes, I think so. Like are we going to
[20:09] have a greater chance of getting to uh
[20:13] sustainable energy? Uh yeah, I think so
[20:15] too. you know, like like AI is going to
[20:17] supercharge innovation across all sorts
[20:20] of dimensions that have massive
[20:23] uh value generating implications for the
[20:26] the public. It's just going to be
[20:28] difficult for that person to get pumped
[20:29] when they're at home uh you know like uh
[20:32] with no money and watching their their
[20:34] kids uh be depressed and and the rest of
[20:37] it. So, uh, you know, like there is an
[20:39] opportunity for abundance and and that
[20:41] that that be my closing thought to you
[20:42] is that, you know, 82,000 ahead, maybe
[20:44] it sounds like a um, you know, good
[20:46] amount to you, maybe not. Like imagine a
[20:48] h 100,000 ahead. Imagine 100 like
[20:50] $80,000 ahead. Like we could get there.
[20:53] This is the first time in human history
[20:56] where scarcity might not actually be the
[21:00] rule of the day. And the question is,
[21:01] can we evolve in an era of abundance or
[21:04] will we turn on each other and kill each
[21:06] other? Uh that that's really the choice.
[21:09] And I don't know about the rest of you,
[21:10] but I'm vastly prefer Star Trek to Mad
[21:13] Max. Um as a future I'm going to leave
[21:15] for my kids.
[21:16] >> We are out of time running in 2028.
[21:19] >> I can't announce here, Nancy, but uh you
[21:21] know, talk later.
[21:22] >> Thank you, Andrew, so much. Thank you
[21:23] all for being here. I appreciate it.
[21:24] >> Thank you all. Appreciate you all. Thank
[21:27] you.
