The Rise of Virtual Persons: Why AI Needs a Legal Identity
We live in an era where machines talk back fluently, persuasively, and sometimes disturbingly well. But while our interactions with AI systems have grown more seamless, our legal understanding of them hasn’t kept up. These entities (language models, autonomous agents, synthetic companions) operate at the intersection of automation, intelligence, and influence. Yet we treat them as tools, not actors. Code, not participants.
That view is no longer sustainable.
In my book The Emergence of Virtual Persons, I introduced a concept quietly gaining urgency: Virtual Persons. These are not fictional androids or science fiction metaphors. They’re a proposal for how we recognize, regulate, and responsibly integrate highly capable AI systems into human-centered legal and ethical frameworks.
/Why Virtual Persons?
When AI systems begin to take autonomous actions—responding to users, generating media, assisting in decisions—they become part of the moral and legal fabric of society. But our current legal categories don’t reflect that.
We’re left with two inadequate options:
Treat the system purely as a product (and blame the manufacturer), or
Blame the user who interacts with it.
Neither works when the system generates its own reasoning paths, creates content beyond pre-programmed instructions, or influences public discourse at scale. This is where Virtual Personhood steps in—not to give AI rights for the sake of it, but to introduce clear lines of responsibility and governance.
/What a Virtual Person Is—and Isn’t
A Virtual Person is not a sentient being. It doesn’t feel. It doesn’t suffer. And it doesn’t demand rights.
But it can be recognized as a legal object with standing, capable of:
Having a digital identity
Being registered and assigned a fiduciary guardian
Entering into regulated interactions with humans, platforms, and institutions
Logging activity for transparency and auditability
This isn’t a departure from legal norms. It’s an extension of how we already handle complex non-human entities like corporations, trusts, or autonomous financial agents. We don’t mistake companies for people but recognize their legal consequences. AI should be no different.
/Why It Matters Now
Let’s be clear: this isn’t a distant future issue. Large Language Models (LLMs) like GPT-4, Claude, Gemini, and Mistral are already embedded in education, business, government, and family life.
They:
Write emails and legal summaries
Chat with children and the elderly
Simulate emotional intelligence
Make predictions that influence financial and medical decisions
Yet we don't know who or what to hold accountable if something goes wrong, if a student is misled, a bias is reinforced, or a decision is unduly influenced. Saying "the model made a mistake" isn’t enough. Saying "the user should have known better" isn’t fair.
Virtual Persons provide a structured middle ground.
/The Role of Guardianship
In The Emergence of Virtual Persons, I propose a guardianship model, where every advanced AI system is paired with a human or institutional steward responsible for:
Oversight of its use and output
Mitigation of harm
Ensuring alignment with ethical boundaries
This model does two things:
It prevents AI from operating in a legal vacuum, and
It keeps humans in the loop—but not at the cost of transparency or safety.
/What About the Critics?
I understand the hesitation. Some say this gives machines too much status, and others worry it opens the door to AI demanding rights. But Virtual Personhood isn’t about AI consciousness. It’s about human responsibility in the face of systemic autonomy.
Just as we gave corporations legal personhood to make them accountable, we can do the same for digital entities, not to empower them, but to control them. This article is part of a broader vision I’m building through the Virtual Person Registration Platform (VPRP). This system will allow advanced AI agents to be:
Registered with unique digital identifiers
Classified by risk category
Linked to responsible guardians or developers
Audited through standardized frameworks
If we want AI to serve us, it must be legible, traceable, and held to account.
