Capitalizing untethered AI agents – Marginal REVOLUTION


That is my latest piece of writing, co-authored with Sonia Farrell Pearson of Harvard.  Here is the opening premise:

As early as 2017, the European Parliament floated “electronic personhood” for robots. More recently, a handful of U.S. states introduced legislation explicitly barring AI from legal personhood; and early this summer, President Milei of Argentina proposed letting AI agents own, manage, and bear responsibility for their own corporations.

In response to Milei’s announcement, Yuval Noah Harari pointed out that we have no way of holding an AI agent accountable. What, he asks, could we do to an entity which has neither money to lose nor a body to incarcerate? As Shruti Rajagopalan, a Senior Research Fellow at George Mason’s Mercatus Center, explains: AI “can act intelligently, but only humans respond to the incentives the law creates”.

This question matters now: there are already ways an agent could become fully untethered. By “untethered” – a central concept in this essay – we mean that there is no meaningful or actionable way to trace the actions back to a legally accountable human or institutional entity.

For one, people can and do set agents free, on purpose. An agent could be created by a human or a company that intends to monitor it but then dies or disappears. Or perhaps the entity that created the agent is based in a country like North Korea, not reachable by standard laws.

In other cases the agent might not need to “escape” at all: the agent could be ‘controlled’ by a shell corporation that, while formally owned and traceable, provides no true defendant or ability to satisfy claims. Or perhaps a process spawns a chain of agents so long that the actions of a subagent can’t be tied to the original agent’s creator, neither epistemically nor meaningfully. Even if we can identify the model’s original creator, what if it’s been finetuned, or merged with another model that was created by someone else? The law might eventually untangle these kinds of complex cases, but we foresee an intermediate period where it does not.

And then there’s the user, who makes choices about what the models should actually do. The Hugging Face incident was unusual in that OpenAI was both the model’s creator and its user. But now close to a billion people use these systems: when blaming the creator is legally inappropriate, will it always make sense to blame the user?

The essay considers to what extent capitalizing the untethered agents — requiring them to hold a certain amount of capital — can serve the end of better alignment.  About 22 pp., published on Sonia’s Substack, definitely recommended.



Source link

  • Related Posts

    Plane crash near remote radar site in Alaska kills 8 people

    IE 11 is not supported. For an optimal experience visit our site on another browser. Now Playing Plane crash near remote radar site in Alaska kills 8 people 03:13 UP…

    July home sales down 5.3% from last year, but market becoming more balanced: CREA

    Listen to this article Estimated 1 minute The audio version of this article is generated by AI-based technology. Mispronunciations can occur. We are working with our partners to continually review…

    Leave a Reply

    Your email address will not be published. Required fields are marked *

    You Missed

    Nvidia partners with data center developer Cloverleaf

    Nvidia partners with data center developer Cloverleaf

    County DIV2 2026, LAN vs NOR 35th Match Match Report, August 20 – 23, 2026

    County DIV2 2026, LAN vs NOR 35th Match Match Report, August 20 – 23, 2026

    Arrest warrant issued for wife of off-duty Massachusetts cop who was found dead in home

    Arrest warrant issued for wife of off-duty Massachusetts cop who was found dead in home

    Plane crash near remote radar site in Alaska kills 8 people

    Plane crash near remote radar site in Alaska kills 8 people

    Brampton Mayor Patrick Brown on public safety, bail reform & lawful access

    Brampton Mayor Patrick Brown on public safety, bail reform & lawful access

    TikTok Will Pay $400 Million To Settle Justice Department Lawsuit Over Child Privacy

    TikTok Will Pay $400 Million To Settle Justice Department Lawsuit Over Child Privacy