Today, TechFreedom Associate Counsel Andy Jung delivered remarks at the FTC’s Open Commission Meeting. His oral remarks, beginning at 20:42, are presented here, lightly edited for clarity.

Remarks of Andy Jung:

Good morning. I’m Andy Jung, Associate Counsel at TechFreedom. 

This month, the Office of Technology uploaded a blog post describing the benefits and risks associated with open-weight artificial intelligence models. The OT correctly notes that open-weight models enable “innovation, driv[e] competition, improv[e] consumer choice, and reduc[e] costs.” Some open-weight models run directly on consumers’ devices, rather than third-party servers, “improv[ing] privacy, security, and auditability.” 

But open-weight models are not without risk. The “lowered costs and barriers” of open models allow malicious actors to use AI to put consumers at risk of “spam, scams, and other harmful uses.” 

AI consumer harms are right in the Commission’s wheelhouse of unfair and deceptive acts or practices. The FTC’s deception authority allows the Commission to police AI usage that is likely to mislead consumers acting reasonably in the circumstances. And unfairness authority empowers the Commission to tackle AI applications that “cause[] or [are] likely to cause substantial injury to consumers which is not reasonably avoidable by consumers themselves and not outweighed by countervailing benefits to consumers or to competition.” 

Regulating open-weight AI using existing FTC authority is superior to novel approaches percolating in the federal and state governments. California’s SB 1047, for example, would create a state agency to license open-weight AI models and impose severe punishment on even well-meaning entrepreneurs whose models are misused, discouraging development of this valuable technology. 

UDAP authority is time-tested and involves checks and balances to ensure consumers remain protected while allowing innovative technologies to flourish. And the Commission is wise to publicly celebrate, rather than stigmatize, open-weight models. This is the correct approach to regulate open-weight AI.

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