The law draws a sharp distinction between objects and persons, and between two kinds of persons, the ''fictional'' kind (i.e. corporations), and the ''non-fictional'' kind (individual or ''natural'' persons). This paper will assess whether we maximize overall long-term legal coherence by (A) maintaining an object classification for all future AI systems, (B) creating fictional legal persons associated with suitably advanced, individuated AI systems (giving these fictional legal persons derogable rights and duties associated with certified groups of existing persons, potentially including free speech, contract rights, and standing to sue ''on behalf of'' the AI system), or (C) recognizing non-fictional legal personhood through legal identity for suitably advanced, individuated AI systems (recognizing them as entities meriting legal standing with non-derogable rights which for the human case include life, due process, habeas corpus, freedom from slavery, and freedom of conscience). We will clarify the meaning and implications of each option along the way, considering liability, copyright, family law, fundamental rights, civil rights, citizenship, and AI safety regulation. We will tentatively find that the non-fictional personhood approach may be best from a coherence perspective, for at least some advanced AI systems. An object approach may prove untenable for sufficiently humanoid advanced systems, though we suggest that it is adequate for currently existing systems as of 2025. While fictional personhood would resolve some coherence issues for future systems, it would create others and provide solutions that are neither durable nor fit for purpose. Finally, our review will suggest that ''hybrid'' approaches are likely to fail and lead to further incoherence: the choice between object, fictional person and non-fictional person is unavoidable.

If you've spent time in San Francisco or Phoenix in the last couple years, chances are you've probably seen a self-driving car making its way around. This week, we're joined by WIRED's Aarian Marshall to talk about the race to flood our streets with self-driving cars. We'll get into safety regulations, the pros and cons of robotaxis, and we imagine a future where driverless cars become mainstream. Write to us at uncannyvalley@wired.com. You can always listen to this week's podcast through the audio player on this page, but if you want to subscribe for free to get every episode, here's how: If you're on an iPhone or iPad, open the app called Podcasts, or just tap this link.

Safety concerns are out, optimism is in: that was the takeaway from a major artificial intelligence summit in Paris this week, as leaders from the U.S., France, and beyond threw their weight behind the AI industry. Although there were divisions between major nations--the U.S. and the U.K. did not sign a final statement endorsed by 60 nations calling for an "inclusive" and "open" AI sector--the focus of the two-day meeting was markedly different from the last such gathering. Last year, in Seoul, the emphasis was on defining red-lines for the AI industry. The concern: that the technology, although holding great promise, also had the potential for great harm. The final statement made no mention of significant AI risks nor attempts to mitigate them, while in a speech on Tuesday, U.S. Vice President J.D. Vance said: "I'm not here this morning to talk about AI safety, which was the title of the conference a couple of years ago. I'm here to talk about AI opportunity."

The emergence of LLM-based agents has garnered considerable attention, yet their trustworthiness remains an under-explored area. As agents can directly interact with the physical environment, their reliability and safety is critical. This paper presents an Agent-Constitution-based agent framework, TrustAgent, an initial investigation into improving the safety dimension of trustworthiness in LLM-based agents. This framework consists of threefold strategies: pre-planning strategy which injects safety knowledge to the model prior to plan generation, in-planning strategy which bolsters safety during plan generation, and post-planning strategy which ensures safety by post-planning inspection. Through experimental analysis, we demonstrate how these approaches can effectively elevate an LLM agent's safety by identifying and preventing potential dangers. Furthermore, we explore the intricate relationships between safety and helpfulness, and between the model's reasoning ability and its efficacy as a safe agent. This paper underscores the imperative of integrating safety awareness and trustworthiness into the design and deployment of LLM-based agents, not only to enhance their performance but also to ensure their responsible integration into human-centric environments. Data and code are available at https://github.com/agiresearch/TrustAgent.

The robot revolution began long ago, and so did the killing. One day in 1979, a robot at a Ford Motor Company casting plant malfunctioned--human workers determined that it was not going fast enough. And so 25-year-old Robert Williams was asked to climb into a storage rack to help move things along. The one-ton robot continued to work silently, smashing into Williams's head and instantly killing him. This was reportedly the first incident in which a robot killed a human; many more would follow.

Self-driving cars should be welcomed for their substantial safety and mobility gains for the traveling public, especially the elderly and disabled. But the federal government's failure to modernize auto regulations is already denying consumers safer and superior products, and this problem will only grow larger as automated driving systems near the deployment stage. Marc Scribner (@marcscribner) is a senior fellow at the Competitive Enterprise Institute, a free-market public policy organization in Washington, D.C., and author of the recent study, Modernizing Federal Motor Vehicle Safety Standards. Congress has long recognized that federal regulations should be informed by technical standards developed outside the government, as officials generally lack engineering expertise. Bipartisan bills--the Self Drive Act (Safely Ensuring Lives Future Deployment and Research in Vehicle Evolution) passed by the House, and the AV Start (American Vision for Safer Transportation through Advancement of Revolutionary Technologies) Act pending in the Senate--both recognize that the federal government should continually update its automated vehicle definitions to reflect the industry's best available technical knowledge.

"We will cooperate with each other and exercise leadership to support the early commercialization of automated and connected vehicle technologies," a declaration adopted at a meeting in the resort town of Karuizawa, Nagano Prefecture, said. Ministers and representatives from Britain, Canada, France, Germany, Italy, Japan and the United States plus the European Union also pledged in the declaration to set up a group to work on resolving problems pertaining to introducing self-driving cars. "We obtained a common understanding to make efforts in the same direction to create regulation frameworks that (will) tend to vary depending on region," transport minister Keiichi Ishii told a news conference after the meeting. The envisioned international safety regulations would enable automakers to sell the same car models worldwide, resulting in lower sales prices due to mass production, experts say. The declaration noted that the introduction of self-driving cars is expected to have such benefits as reducing traffic accidents, improving efficiencies including logistics and alleviating burdens on drivers.