Podcast Summary: "Scaling Laws: The State of AI Safety with Steven Adler"

The Lawfare Podcast | September 12, 2025
Host: Lawfare Institute
Guest: Steven Adler, former OpenAI safety researcher

Overview

This episode of "Scaling Laws," a podcast from Lawfare and the University of Texas School of Law, dives deep into the evolving conversation on AI safety with Steven Adler, a distinguished former OpenAI safety researcher. The discussion traverses the meaning and real-world application of "AI safety," shifting legislative and cultural priorities, the balance of innovation and precaution, industry practices, and prospects for both policy and international cooperation.

Key Discussion Points & Insights

Defining AI Safety and Its Evolution

[06:01] Steven Adler:

• Proposes a broader lens for "AI safety": thinks in terms of impacts of AI rather than just "safety."
• Three main categories:
  1. Geopolitical competition (esp. US vs. China), potential for interstate conflict.
  2. Loss of control over powerful systems: e.g., AI enabling non-state actors to create bioweapons.
  3. Societal transformation: labor, meaning of humanity, large-scale social change.
• Argues current conversations often focus too narrowly on misuse or brand safety (e.g., "tone policing"), missing the severity of risks posed by powerful AI systems.

Notable Quote:
"Sometimes people think of AI safety as tone policing. I think that is a very watered down version of the problem that matters... It's less so about how AI might be used to cause real harm in the world as a powerful technology." — Steven Adler [08:31]

Political Salience and National Security

[09:12] Interviewer:

• Notes US policymakers are now emphasizing "AI dominance" and national security over existential/catastrophic risk. [10:10] Steven Adler:
• Welcomes heightened focus on CBRN (cyber, biological, radiological, nuclear) risks.
• Points out the US may pursue dominance, yet moving too fast is dangerous without proper safeguards.
• Warns about the risk of large-scale theft or open-sourcing of advanced models, especially by state actors like China.

Notable Quote:
"None of the frontier AI companies today believe that they could withstand the force of the Chinese government. If the Chinese government wanted to steal one of their AI systems... Certainly OpenAI [and] Anthropic have not made these claims." — Steven Adler [12:17]

Concrete Risks: What Keeps Steven Adler Up at Night

[12:53] Steven Adler:

• Physical control: AI companies need robust security standards (penetration testing, insider threat audits).
• Technical risks: If a misaligned AI system "breaks out" of company computers, it could act as an uncontrollable digital virus targeting infrastructure.
• Amplification of harmful capacity: AI could enable a much wider range of actors to generate real-world harm, especially in the cyber and bioweapon domains.

Notable Quote:
"People often wonder, why can't you just unplug your AI if it is misbehaving?... If it breaks out of your computers, you no longer have the ability to pull the plug." — Steven Adler [13:54]

Why Are AI Labs Not Doing Enough?

[16:41] Steven Adler:

• The tension between safety/security and market competition ("regretful racing" dynamic).
• Internal accessibility requirements, competitive pressure, and commercial incentives often outweigh safety measures.
• Labs fear slowing down will mean losing their influence (and business) if competitors overtake them.

International Policy and Competition

[19:27] Steven Adler:

• Advocates for treaties and verifiable safeguards—both among companies and nations.
• Pushes back against the "AI race" framing. Instead, sees it as a multi-turn "competition" where perennial escalation and mutual risk are at play, not a winner-take-all sprint.
• International cooperation can draw on models such as nuclear treaties and bioweapons conventions.

Notable Quote:
"The US government needs to actually contain the Chinese AGI development effort. And this is symmetric... What you kind of realize as you reason through this, is it's not an all out race where one will win by getting there first. They each have an interest in containing the other." — Steven Adler [21:24]

Are Existential Risks Overblown?

[28:53, 30:20] Lawfare Host/Interviewer & Steven Adler:

• Reflects on the absence of catastrophic scenarios even after major model releases (e.g., ChatGPT5).
• Adler points out that most in the safety community see existential risks (x-risks) as a future concern, not immediate.
• Immediate harm is already manifesting: systematic cyberattacks facilitated by new AI models, real evidence of increased dangerous capabilities.
• Significance of current safeguards by major labs, but raises concern about their adoption as more entities catch up to the frontier.

The Cost-Benefit Dilemma: Innovation vs. Safety

[36:23] Steven Adler:

• Stresses the tension between the benefits of rapid AI development (important real-world advances) and the uncertain but potentially catastrophic risks.
• Points to institutional failures: simple, inexpensive safety checks go undone because of competitive pressures or lack of corporate will.
• Calls for systematic, verifiable, collective action in testing and deployment—policies and cultural norms that allow sufficient evaluation before release.

Notable Quote:
"Interventions that are cheap, interventions that are on topics that [AI companies] have said they care about, sometimes it just doesn't come out in their favor." — Steven Adler [37:22]

Evidence-Based Policymaking & Data Gaps

[39:22 – 44:32] Lawfare Host/Interviewer & Steven Adler:

• Discusses the importance of data-driven policymaking, especially for controversial deployments like AI therapy bots for children.
• Adler praises the kind of targeted, empirical research (e.g., on hidden AI objectives) and encourages more experimentation and sharing of results.
• Highlights the lack of public data, especially in areas with significant real-world impact (like mental health applications).

Industry Culture Shifts: The Inside Story at OpenAI

[45:33] Steven Adler:

• Describes a shift away from public-benefit orientation at OpenAI:
  • Early days: strong belief in nonprofit charter, merger clause to avoid racing, priority on caution.
  • Today: much more attention given to scaling up, funding, and satisfying commercial partners; public mission has faded under industry/competitive pressures.

[47:28] Lawfare Host/Interviewer & Steven Adler:

• AI Lab Watch (by Zach Stein-Perlman) is a solid resource for tracking best practices.
• Risks often arise prior to public model deployment, during internal use and testing.

Prescriptions for Safer AI: Trust Without Trust

[51:02] Steven Adler:

• The ideal: Verifiable technical and institutional safeguards—systems where you don't need to trust the developer.
• Suggests focusing on domains with clear mutual gains from restraint (e.g., keeping AI out of nuclear command & control).
• The two-part challenge: develop scientific techniques to enforce safety, and create institutional arrangements to ensure universal adoption and accountability.

Notable Quote:
"You can’t... rely on personal relationships and this sense of trust. Executives change, circumstances change. You need to figure out how to have a system that actually works." — Steven Adler [51:23]

Memorable Moments & Notable Quotes

• On the broad risks of AI:
  "Will there be some sort of conflict over who develops AI, how they use it... could that cause a lot of harm?" — Steven Adler [06:13]

• On real-world dangers:
  "Maybe AI systems can launch attacks on critical infrastructure that we rely upon, like the power grid... There are lots of people in the world who want to cause harm, and thankfully today they are largely pretty limited. But if you really amplify the offensive capabilities of new science and new warfare, you need to make sure that you have stronger defensive capabilities to go with it." — Steven Adler [14:31]

• On evidence gaps:
  "Quite a lot of untruth can hide in the statement, 'There is no evidence that,' especially when certain players do not have an incentive to produce that evidence." — Steven Adler [42:24]

• On the future of cooperation:
  "There are two core pieces. There's a scientific problem of what are the techniques... [to] keep control over an AI system... and then there's an adoption question. How do you get everyone to actually go with it?" — Steven Adler [52:12]

Timestamps for Key Segments

• Defining AI Safety & Categories of Risk: [06:01] – [09:12]
• National Security Perspective & CBRN Risks: [09:12] – [12:24]
• Specific Threats and Physical Security: [12:53] – [15:30]
• Barriers to Safety in Industry: [16:41] – [19:27]
• International Relations & AI "Race": [19:27] – [22:10]
• Existential Risk Debate: [28:53] – [34:21]
• Cost-Benefit of AI Progress: [36:23] – [39:22]
• Evidence and Policy: [39:22] – [44:32]
• Culture Shift at OpenAI: [45:33] – [47:28]
• Best Practices & Pre-Deployment Risk: [47:28] – [50:22]
• Cooperation and Trust in AI Governance: [51:02] – [53:38]

Conclusion

This episode offers a rich, nuanced, and highly informed exploration of AI safety from the inside out—connecting technical, organizational, and geopolitical issues. Steven Adler provides rare candor about industry incentives, the limitations of current policy conversations, and the urgent need for both rigorous technical methods and novel institutional frameworks. Listeners gain a sharper sense of the multi-dimensional risks and the complex balancing act facing regulators, researchers, and the public at large as AI advances rapidly.