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Government officials advocate for safer AI product development, fostering innovation and trust in emerging technologies.

Editorial illustration for Official Calls for Safer AI Products to Boost Innovation

Safer AI Products Drive Innovation, Says Ex-DOJ Official

Official Calls for Safer AI Products to Boost Innovation

4 min read

Jonathan Kanter ran antitrust enforcement at the Justice Department under President Biden. Now he teaches law at Washington University and technology policy at Carnegie Mellon, and he's the guest for the first installment of a two-part Decoder series on where business is headed next.

The timing works because AI safety has turned into the industry's loudest fight. Researchers at Anthropic and Google DeepMind have resigned publicly, warning that current models carry real risk and that safety work is getting sidelined. Some researchers now put the odds of AI causing catastrophic harm above 10 percent. Meanwhile, the CEOs building these systems keep calling for slower development and tighter rules, including a specific ask: let us get an antitrust exemption so competitors can coordinate on safety without breaking the law.

That request is where things get messy. Critics call it a bid for regulatory capture, a setup for a cartel, or a convenient way to dodge investor pressure right before some of these companies go public. Kanter, who spent years deciding when companies get to cooperate and when that cooperation becomes illegal, has a clear read on whether AI actually needs special treatment.

Other researchers have said the chance of AI killing us all is greater than 10 percent, and the CEOs of all these companies have issued various calls to slow down development and develop regulation, including asking for antitrust exemptions so they can all coordinate on safety issues.

Why this matters

Kanter's pitch is worth watching closely because it reframes safety as a competitive advantage rather than a compliance tax, and that's a useful corrective for a field that's spent two years treating guardrails as friction. For founders and researchers, the argument cuts against the "move fast, patch later" instinct that's dominated model releases since GPT-4. If Kanter's right that asymmetric innovation, speed without security, is actually a market failure, then teams building on top of frontier models should be pricing in the cost of skipped safety work now, not after a breach or a lawsuit forces the issue.

It's also a signal about where policy is heading: a former DOJ antitrust chief talking about incentive structures for "safer and secure products" suggests regulators may start treating security posture as part of how they judge market power, not a separate box to check. Worth watching whether this shows up in actual rulemaking, or stays a talking-point on a podcast circuit.

Common Questions Answered

What is Jonathan Kanter's main argument about AI safety and competitive advantage?

Kanter reframes AI safety as a competitive advantage rather than a compliance tax, arguing that treating guardrails as friction is counterproductive. His perspective challenges the industry's "move fast, patch later" approach and suggests that asymmetric innovation without security represents a market failure that ultimately harms competition.

Why have researchers at Anthropic and Google DeepMind publicly resigned according to the article?

Researchers from Anthropic and Google DeepMind have resigned publicly because they believe current AI models carry real risk and that safety work is being deprioritized. Their departures highlight growing concerns within the industry about the adequacy of safety measures in model development.

What antitrust exemptions are AI company CEOs requesting and why?

AI company CEOs are asking for antitrust exemptions that would allow them to coordinate on safety issues without violating competition laws. This request reflects their belief that collaborative safety development requires exemptions from traditional antitrust enforcement to be feasible across competing organizations.

How does Kanter's background in antitrust enforcement inform his perspective on AI safety?

Kanter ran antitrust enforcement at the Justice Department under President Biden before transitioning to teaching law at Washington University and technology policy at Carnegie Mellon. His dual expertise in both antitrust law and technology policy positions him uniquely to analyze how competition dynamics intersect with AI safety concerns.

What do some researchers claim about the existential risk posed by current AI models?

According to the article, some researchers have stated that the chance of AI killing us all is greater than 10 percent, reflecting serious concerns about existential risk. These warnings have contributed to broader industry calls for slowing AI development and implementing stronger regulatory frameworks.

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