Artificial Intelligence and Legal Personhood : Bhavesh Sanagapalli
Artificial Intelligence and Legal Personhood
The Case for Human Accountability
Artificial intelligence is transforming many societies. It is now used in areas such as healthcare, transportation, finance, education, and national security. According to the Stanford Human Centered AI Institute’s AI Index Report, global investment in and use of AI systems have grown dramatically in recent years, with governments and companies using AI for decision making (Stanford HAI). At the same time, many other systems are struggling to keep pace with these technological developments. The European Parliament has already begun studying new civil liability frameworks to address harm caused by AI technologies (European Parliament). The World Economic Forum similarly notes that AI systems are increasingly involved in decisions that affect people's jobs, finances, and health (World Economic Forum). With these drastic changes over the past few years, we need to ask the question, “Should AI systems be granted legal personhood, or are they tools that must always remain under human accountability?”
Supporters of AI personhood often argue that these systems are becoming increasingly autonomous, and reliable. Self driving vehicles must analyze traffic conditions and make quick decisions without any human intervention. Ai trading systems in stock markets execute thousands of transactions in just seconds, often producing results that no one can really predict (Brookings Institution). AI is also used to assist doctors in diagnosing diseases, analyze credit risk in banking, and manage logistics networks for major companies (World Economic Forum). Because these systems can operate with minimal human supervision, many researchers and people make the argument that AI should be given independence, with no human intervention.
Advocates of this view compare AI to corporate personhood. Corporations are not human beings, but are recognized as legal people that can sign contracts, sue or be sued, and also hold assets, all like a person (Harvard Law School Forum on Corporate Governance). This legal framework allows businesses to function within the legal system even though they are organizations rather than individuals. Some scholars suggest that a similar legal structure could apply to AI systems as they become more sophisticated, and complex. According to this argument, granting AI legal status could make it easier to assign liability when harm occurs.
However, this analogy does not really hold up under closer examination. Corporate personhood was created to organize human responsibility, not to eliminate it. Behind every corporation are real individuals, executives, directors, and shareholders who ultimately control the organization and will be held accountable for its actions. If AI systems were granted the same legal status, the result could be the opposite. Companies might attempt to blame harmful outcomes on the AI itself rather than on their own decisions to design, train, or deploy the system. Victims of AI related harm could find themselves trying to hold a machine responsible, something that cannot pay damages, serve legal penalties, or intentionally change its behavior. As legal scholars have noted, assigning responsibility to entities that cannot truly bear it risks creating what some may describe as a “liability gap” which is found in many emerging technologies (Center for Data Innovation).
The deeper issue in this debate concerns moral responsibility. Legal accountability has historically been tied to the ability to make intentional decisions and understand the moral consequences of actions. According to the Stanford Encyclopedia of Philosophy, moral responsibility requires the capacity to understand ethical reasons and act on them. AI systems do not possess this ability (Stanford Encyclopedia of Philosophy). They identify patterns in large datasets and generate outputs based on statistical relationships, but they do not have awareness, intention, or moral understanding. International organizations such as UNESCO and the OECD emphasize that accountability for AI must remain with human actors for precisely this reason. Their global guidelines on AI ethics explicitly state that developers and organizations deploying AI should remain responsible for the outcomes produced by these systems (UNESCO; OECD).
Economic considerations also support maintaining human responsibility. AI technologies are widely adopted because they increase efficiency, reduce costs, and improve productivity. However, research from the International Monetary Fund shows that automation can shift economic risks toward workers and consumers rather than the companies implementing the technology (IMF). If corporations could attribute harmful outcomes to their AI systems rather than to their own design and deployment decisions, they might have fewer incentives to ensure safety and fairness. Studies highlighted by MIT Technology Review show that many AI failures can be traced to human choices, including biased training data, flawed model design, and poor deployment practices (MIT Sloan Teaching & Learning Technologies). Because these systems are built and maintained by people, responsibility should logically remain with those individuals and organizations.
A Legal view also supports this position. Historically, courts have treated machines as tools rather than something independent. The U.S. Federal Trade Commission states that companies are responsible for automated decisions affecting consumers, including those produced by AI systems (Federal Trade Commission). Similarly, the European Commission’s AI Act focuses on regulating developers, providers, and users of AI rather than granting independence to the systems themselves (European Commission). The American Bar Association likewise emphasizes that legal liability generally depends on human control and foreseeability, two principles that apply to people, not machines (American Bar Association).
Another major issue is enforcement. Legal systems achieve their goals through punishment, compensation, and deterrence. These mechanisms assume that the responsible party can understand consequences and respond to incentives. AI systems cannot experience punishment, learn moral lessons from legal sanctions, or intentionally change their behavior to avoid liability. Scholars writing in the Yale Law Journal and Nature Machine Intelligence have argued that symbolic forms of responsibility can weaken regulatory systems because they obscure the real decision makers behind technological systems (Yale Law Journal; Nature Machine Intelligence). In practice, any penalties directed at AI would ultimately fall on the humans connected to it. For this reason, it is more logical to assign responsibility to those humans directly.
Human rights considerations provide an additional reason to reject AI personhood. Legal personhood historically developed as a way to protect human dignity and moral worth. The United Nations Universal Declaration of Human Rights frames rights as protections for human beings because of their inherent dignity and vulnerability (United Nations). Scholars at the Oxford Internet Institute argue that rights frameworks depend on recognizing beings capable of suffering harm and possessing moral value (Oxford Internet Institute). AI systems do not experience pain, vulnerability, or moral worth in the same way humans do. Extending rights-like status to machines risks weakening the concept of human rights itself.
Importantly, rejecting AI personhood does not mean opposing technological progress. Throughout history, innovation and regulation have developed together. Industries such as aviation, pharmaceuticals, and finance have all evolved under regulatory systems designed to protect public safety. The National Institute of Standards and Technology emphasizes that trustworthy AI systems require strong human oversight and governance structures (NIST). Organizations such as the Partnership on AI, the Alan Turing Institute, and the IEEE Global Initiative on Ethics of Autonomous Systems similarly stress that responsible innovation depends on clear lines of human accountability (Partnership on AI; Alan Turing Institute; IEEE).
Public trust is also a critical factor in AI governance. Surveys conducted by the Pew Research Center show that many citizens are concerned about who is responsible when AI systems cause harm or make controversial decisions (Pew Research Center). Democratic societies rely on clear accountability structures so that individuals can identify who is responsible for decisions affecting their lives. International institutions such as the Council of Europe emphasize that AI governance must remain grounded in human rights and human accountability rather than technological autonomy (Council of Europe).
Ultimately, the debate over AI personhood raises a question about the purpose of legal systems. Laws exist to regulate human behavior, protect individuals from harm, and maintain order. AI systems are powerful and also complex tools, but they remain tools created and used by humans. Granting them legal personhood would not clarify responsibility. Evidence from philosophy, economics, law, and governance consistently supports the same conclusion, that responsibility for artificial intelligence must remain with the human beings and organizations that design, deploy, and benefit from it.
Works cited
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