AI Frontiers

Center for AI Safety
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AI Frontiers is a platform for expert dialogue and debate on the impacts of artificial intelligence. Sign up for our newsletter: https://ai-frontiers.org/subscribe

  1. 6 DAYS AGO

    “The Quadrillion-Dollar Disagreement on AI and the Economy” by Anton Shenk

    In the three years since OpenAI launched ChatGPT, economists and AI researchers have published forecasts projecting that, over the next decade, AI will add to annual growth by amounts ranging from as little as 0.1% to as much as 30%. By 2035, the gap between these forecasts nears a quadrillion dollars: an amount that exceeds a decade's worth of current global output. The Quadrillion-Dollar Delta Projected US GDP Under Alternative AI Growth Estimates, 2026-2035 Source: 2025 Q4 US GDP from Federal Reserve Economic Data. Estimates sourced from Goldman Sachs (2023), McKinsey (2023), Acemoglu (2024), OECD (2024), Korinek & Suh (2024), Arnon (2025), Cowen (2025), Clark (2025), and Epoch AI (2025). Not all estimates model US GDP directly: Epoch AI models Gross World Product; McKinsey models productivity across 47 countries; Korinek & Suh calibrate to advanced-economy baselines. Growth rates from these sources are applied to the US GDP baseline for comparability. Where ranges are reported, the median is used. Where excess growth is reported rather than levels, a baseline 2% GDP growth is assumed. Skeptical forecasts describe a future world barely different from today's: one with modest productivity gains and manageable labor-market adjustments, all governed with incremental policy tweaks. Other forecasts [...] --- Outline: (03:11) Question 1: Which Jobs Can AI Actually Automate? (04:19) The Skeptical Case: AI Faces a Hard Tasks Wall (07:07) The Explosive Case: Difficult Tasks Can Be Surmounted (09:25) Question 2: Can the Economy Absorb What AI Companies Produce? (10:13) The Skeptical Case: Institutions Are Stickier Than Markets (11:49) The Explosive Case: Markets Fund What Works (13:55) Question 3: Can AI Automate Innovation Itself? (14:12) The Skeptical Case: AI Will Provide a One-Time Economic Boost (15:27) The Explosive Case: AI Will Produce Ideas (19:13) Indicators to Resolve These Questions --- First published: May 11th, 2026 Source: https://aifrontiersmedia.substack.com/p/the-quadrillion-dollar-disagreement --- Narrated by TYPE III AUDIO. --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.

    22 min

  2. 20 APR

    “Catalytic Regulation: Incentivizing Safety During a Regulatory Drought” by Yonathan Arbel

    Yonathan Arbel — April 20, 2026 In 1959, a midsize Swedish car company did something its competitors thought was myopic, if not reckless. It effectively open-sourced the three-point seat belt, the greatest safety innovation in automotive history. The prevailing industry wisdom at the time was blunt: “Safety doesn’t sell.” Just three years prior, Ford had offered seat belts for a $9 surcharge, as part of its 1956 Lifeguard campaign; despite Robert McNamara's championing of the program, the safety push failed to give Ford a competitive edge. Henry Ford II reportedly grumbled, as he was dialing back its campaign, “McNamara is selling safety, but Chevrolet is selling cars.” But Volvo was neither myopic nor reckless; in fact, it saw further than any of its competitors. While they competed fiercely for dominance in a race for horsepower, engine efficiency, and design, Volvo could see that consumers cared about safety and reliability, too. The bet paid off: Volvo became one of the most recognized automotive brands in the world. According to Volvo, seat belts have since saved over 1 million lives. American AI needs its Volvo moment. The aim of catalytic regulation is to enable this moment. It is a family of [...] --- Outline: (02:24) Why Catalytic Regulation? (09:13) From Principles to Practice: The Catalytic Regulation Bundle (09:34) Corporate Incentives (12:26) Demand-Side Incentives (15:10) Market Guarantees (17:06) The Power of Prestige (20:39) A Seat Belt for AI (21:33) Discussion about this post (21:37) Ready for more? --- First published: April 20th, 2026 Source: https://aifrontiersmedia.substack.com/p/catalytic-regulation-incentivizing --- Narrated by TYPE III AUDIO.

    22 min

  3. 13 APR

    “The Right Way to Sell Chips to China” by Alasdair Phillips-Robins, Noah Tan

    Last December, President Trump announced that the United States would allow Nvidia to sell its powerful H200 AI processors to customers in China. Officials in the Trump administration have long argued that the best way to win the AI race is to promote the export of US technology around the world, not to restrict it. Selling H200s, the administration claims, will boost the market share of US chip-makers while preserving the US hardware lead. Critics warn of national security risks to selling advanced chips, but the administration appears committed to its course. Taking a pro-export framework as a given, policymakers can balance between market share and national security by managing a quantity that currently doesn’t receive enough attention: the United States’ relative compute advantage. Total AI compute for a country is calculated as its stock of AI processors weighted by the effectiveness of each processor; the US currently enjoys a roughly 10-to-1 compute advantage over China. That advantage matters because more compute can support more domestic R&D, more customers served by American AI products, and more ability for the US government to influence the development and use of AI. Relative compute advantage is about the quantity of chips as [...] --- Outline: (02:20) A Return to Relative Advantage (05:46) Selling Chips Without Selling Out (08:17) Making Relative Advantage Work in Practice (11:18) Discussion about this post (11:22) Ready for more? --- First published: April 13th, 2026 Source: https://aifrontiersmedia.substack.com/p/the-right-way-to-sell-chips-to-china --- Narrated by TYPE III AUDIO.

    12 min

  4. 27 MAR

    “The Robot in Your Living Room Has No Rulebook” by Tristan Ingold

    In late 2025, Figure AI placed its third-generation humanoid robot into real homes for alpha testing. The Figure 03 has hands with 16 degrees of freedom, tactile sensors that detect forces as small as three grams, and foam-padded limbs designed for safe operation around people. It charges wirelessly and responds to natural language commands. It can learn in real time, adapting to its environment. A few months earlier, Unitree started shipping the R1, a home-capable robot priced at $4,900. TIME included it among the Best Inventions of 2025. You can order one today and have it in weeks: it's the most commercially accessible humanoid robot on the planet. These robots have graduated from prototyping. They’re consumer products with price tags, shipping dates, and marketing campaigns. It's easy to imagine a world in which every family relies on one or several robots to conduct daily life, especially as AI becomes more capable. But what rules govern a learning, physically capable, always-on AI device operating inside someone's home? Unfortunately, we’re far from a coherent answer. Existing US regulations were developed with Roombas and robot arms in mind, not autonomous humanoids, resulting in a confusing patchwork of obligations. That doesn’t mean the [...] --- Outline: (01:56) What Robotics In 2030 May Look Like (04:15) The Governance Gap (10:50) What Should the US Do? (14:42) Conclusion (15:51) Discussion about this post (15:54) Ready for more? --- First published: March 27th, 2026 Source: https://aifrontiersmedia.substack.com/p/the-robot-in-your-living-room-has --- Narrated by TYPE III AUDIO. --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.

    16 min

  5. 2 MAR

    “How AI Could Benefit the Workers it Displaces” by Benjamin Jones

    Last week, Jack Dorsey, a co-founder of Twitter, announced that his company Block is cutting its head count from 10,000 to fewer than 6,000 because AI tools mean it needs fewer workers. It is not the first company to make such an announcement, and won’t be the last. But it raises a question: if AI takes jobs, are workers doomed? To many observers, the answer must be yes. Negative consequences for the labor force seem like an inevitable byproduct of advancing AI. Indeed, machines that automate work seem to promise exactly such outcomes: they start performing tasks that labor once did, which seems to imply that workers will experience worse economic prospects. Faced with the possibility of being displaced, many might hope that AI progress will slow or even stall, allowing humans to remain competitive. But, in evaluating AI's implications for the workforce, it's misleading to think of AI as simply a replacement for labor. To complete the picture, we need to consider the fuller set of forces that are unleashed when machines automate types of work. In particular, we must engage two other economic features that sharply condition outcomes for labor: first, how machines affect prices, and second [...] --- Outline: (02:36) Automating Agriculture and Computing (06:21) Machines and Prices (09:05) Bottlenecks (13:03) Three Caveats (20:08) Discussion about this post (20:11) Ready for more? --- First published: March 2nd, 2026 Source: https://aifrontiersmedia.substack.com/p/how-ai-could-benefit-the-workers --- Narrated by TYPE III AUDIO.

    20 min

  6. 12 FEB

    “China and the US Are Running Different AI Races” by Poe Zhao

    Last month, as three Chinese AI startups went public within days of each other, Hong Kong briefly became a scoreboard for emerging companies in the industry. On January 2, AI chip designer Shanghai Biren Technology listed in Hong Kong and raised $5.58 billion Hong Kong dollars ($717 million). About a week later, model developers Zhipu AI and MiniMax followed, raising HK$4.35 billion ($558 million) and HK$4.8 billion ($619 million), respectively. Those listings matter less as a market spectacle than as a strategy signal, and the strategy differs noticeably from that of companies across the Pacific. US startups build around abundance: raise huge capital, buy time, push the frontier. OpenAI's Stargate plan, for example, aims to invest $500 billion over four years in AI infrastructure. Meanwhile, Chinese startups adapt to different constraints: frontier training infrastructure is scarcer, so momentum comes from efficiency, targeted deployment, and market selection. As AI moves from demos to production, the binding question shifts: what does it cost to deliver useful work reliably, and who will pay? Under different economic pressures, Chinese and US companies are opting for different go-to-market strategies. The Capital Gap US AI startups attract more private investment than those in China. The [...] --- Outline: (01:37) The Capital Gap (04:04) Who Pays, and What Are They Buying? (06:39) Constraints Determine Chinas Choices (09:50) What to Watch (11:37) Discussion about this post (11:40) Ready for more? --- First published: February 12th, 2026 Source: https://aifrontiersmedia.substack.com/p/china-and-the-us-are-running-different --- Narrated by TYPE III AUDIO.

    12 min

  7. 2 FEB

    “High-Bandwidth Memory: The Critical Gaps in US Export Controls” by Erich Grunewald, Raghav Akula

    This month, mainstream media have been warning consumers that electronic devices may get pricier because of rising demand for dynamic random access memory (DRAM), a key component. The surge in DRAM costs, estimated to have risen by 50% during the final quarter of 2025, can largely be traced back to a specific cause: the AI industry's appetite for high-bandwidth memory (HBM). This demand has led memory-makers to shift production away from standard DRAM chips and toward HBM. While its contribution is often overshadowed by those of processors it supports, HBM plays a vital role in training and running advanced AI systems, so much so that it now accounts for half the production cost of an AI chip. Companies’ determination to secure this lesser-known component proves its value. In December 2024, the US announced new export restrictions on the sale of HBM chips to China. In the month before the restrictions came into effect, Huawei and other Chinese companies reportedly stockpiled 7 million Samsung HBM chips, a haul likely worth over $1 billion. The December 2024 controls specifically targeted HBM in order to slow China's domestic AI chip-production efforts. Targeting HBM in this way is possible because it is manufactured [...] --- Outline: (02:00) Why is high-bandwidth memory so important? (06:03) Mapping the global HBM industry (09:33) The gaps in current HBM controls (15:34) Tightening the regime (19:30) Conclusion (22:28) Discussion about this post (22:31) Ready for more? --- First published: February 2nd, 2026 Source: https://aifrontiersmedia.substack.com/p/high-bandwidth-memory-the-critical --- Narrated by TYPE III AUDIO. --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.

    23 min

  8. 28 JAN

    “Making Extreme AI Risk Tradeable” by Daniel Reti, Gabriel Weil

    Last November, seven families filed lawsuits against frontier AI developers, accusing their chatbots of inducing psychosis and encouraging suicide. These cases — some of the earliest tests of companies’ legal liability for AI-related harms — raise questions about how to reduce risks while ensuring accountability and compensation, should those risks materialize. One emerging proposal takes inspiration from an existing method for governing dangerous systems without relying on goodwill: liability insurance. Going beyond simply compensating for accidents, liability insurance also encourages safer behavior, by conditioning coverage on inspections and compliance with defined standards, and by pricing premiums in proportion to risk (as with liability policies covering boilers, buildings, and cars). In principle, the same market-based logic could be applied to frontier AI. However, a major complication is the diverse range of hazards that AI presents. Conventional insurance systems may be sufficient to cover harms like copyright infringement, but future AI systems could also cause much more extreme harm. Imagine if an AI orchestrated a cyberattack that resulted in severe damage to the power grid, or breached security systems to steal sensitive information and install ransomware. The market currently cannot provide liability insurance for extreme AI catastrophes. This is for two [...] --- Outline: (02:51) Catastrophe Bonds: A Blueprint for Insuring AI (07:12) A Market-Driven Safety Mechanism (10:57) Trigger Conditions (12:54) How much could AI cat bonds cover? (15:32) Conclusion (17:00) Discussion about this post (17:03) Ready for more? --- First published: January 28th, 2026 Source: https://aifrontiersmedia.substack.com/p/making-extreme-ai-risk-tradeable --- Narrated by TYPE III AUDIO. --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.

    17 min
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AI Frontiers is a platform for expert dialogue and debate on the impacts of artificial intelligence. Sign up for our newsletter: https://ai-frontiers.org/subscribe

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  • Creator
    Center for AI Safety
  • Years Active
    2025 - 2026
  • Episodes
    50
  • Rating
    Clean
  • Copyright
    © 2026 All rights reserved
  • Show Website
    AI Frontiers

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