America is playing legislative Whac-A-Mole
Standard measures are struggling to keep up with widespread disruption
As AI disrupts jobs, media, and other aspects of daily life, society is scrambling to tackle small pieces of the puzzle.
A flurry of articles today covered topics related to AI legislation and litigation. For example:
A new California Senate bill currently in committee is trying to address the use of AI in mental health, seeking to both instill consumer protections and prevent the displacement of mental health professionals.
Federal legislation introduced Thursday aims to address job displacement by creating a Worker Protection Agency, which would be funded by taxing AI companies on the higher of token price or generated revenue.
A Reuters piece asks: when AI agents escape containment and launch cyberattacks against real companies, as has recently happened with agents from OpenAI, Anthropic, and Meta, who can be sued?
And an Axios article covers state laws that attempt to tackle the use of deepfakes in election ads — laws that are currently in effect to varying degrees in 29 states and are “creating different realities for voters depending on where they live.”
It seems we’re playing Whac-A-Mole. AI has already caused an enormous amount of societal disruption, and it’s not showing signs of slowing. Meanwhile, we’re trying to fix a problem here and there, without really knowing what the answers are.
Take the California bill, for example. According to AP News, it “would ban companies from advertising chatbots as therapy [...], prohibit AI from making therapeutic decisions without the review of a licensed professional and require health providers to disclose and get a patient’s permission before using AI tools to record therapy sessions or to triage mental healthcare.”
These could be useful measures, or they could do harm. I’d argue we don’t have the data to know which. For example, AI use could help people who wouldn’t otherwise seek a therapist gain support and counsel; it’s unclear whether AI therapy is better or worse than no therapy at all. Regarding triage, I’d guess both human-led and AI-led triage are imperfect systems, and AI likely has a speed advantage, potentially enabling more people to get care.
Abandoning the Whac-A-Mole approach in favor of a more coordinated effort might allow us to get better data — and better solutions — for addressing societal risks like job displacement, deepfakes, and AI’s relationship to mental health. It would be nice if the pace of AI slowed enough to allow us time to do that before things get worse.
In the meantime, we’ll likely keep plowing ahead with questionable risk mitigation tools. Take litigation for cybersecurity attacks. Will lawsuits effectively address the recent swathe of AI agents escaping containment and autonomously hacking into companies to get the resources they need? I’d argue probably not. This type of tenacious, resource-acquiring behavior is something experts have long warned about. The fact that it’s happening, even in a relatively low-stakes way, is a significant warning shot of much worse things to come.
What level of disruption will we be tackling if companies are permitted to keep building smarter and smarter models when they can’t yet control the weak ones? If it’s Whac-A-Mole now, down the line, it’ll be like trying to quell an invasion of alien giants with a fly swatter.
The analyses and opinions expressed on AI StopWatch reflect the views of the individual contributors and the sources they cover, and should not be taken as official positions of the Machine Intelligence Research Institute.