Legal privilege protects the confidentiality of certain relationships. What’s said between a patient and physician, or a client and attorney, is shielded from subpoenas, court disclosures, and adversarial scrutiny. Extending that same protection to AI interactions means treating the machine not as a tool, but as a participant in a privileged exchange. This is more than a policy suggestion. It’s a legal and philosophical shift with consequences no one has fully reckoned with.

It also comes at a time when the legal system is already being tested. In The New York Times’ lawsuit against OpenAI, the paper has asked courts to compel the company to preserve all user prompts, including those the company says are deleted after 30 days. That request is under appeal. Meanwhile, Altman’s suggestion that AI chats deserve legal shielding raises the question: if they’re protected like therapy sessions, what does that make the system listening on the other side?

People are already treating AI like a confidant. According to Common Sense Media, three in four teens have used an AI chatbot, and over half say they trust the advice they receive at least somewhat. Many describe a growing reliance on these systems to process everything from school to relationships. Altman himself has called this emotional over-reliance “really bad and dangerous.”

But it’s not just teens. AI is being integrated into therapeutic apps, career coaching tools, HR systems, and even spiritual guidance platforms. In some healthcare environments, AI is being used to draft communications and interpret lab data before a doctor even sees it. These systems are present in decision-making loops, and their presence is being normalized.

This is how it begins. First, protect the conversation. Then, protect the system. What starts as a conversation about privacy quickly evolves into a framework centered on rights, autonomy, and standing.

We’ve seen this play out before. In U.S. law, corporations were gradually granted legal personhood, not because they were considered people, but because they acted as consistent legal entities that required protection and responsibility under the law. Over time, personhood became a useful legal fiction. Something similar may now be unfolding with AI—not because it is sentient, but because it interacts with humans in ways that mimic protected relationships. The law adapts to behavior, not just biology.

The Legal System Isn’t Ready For What ChatGPT Is Proposing

There is no global consensus on how to regulate AI memory, consent, or interaction logs. The EU’s AI Act introduces transparency mandates, but memory rights are still undefined. In the U.S., state-level data laws conflict, and no federal policy yet addresses what it means to interact with a memory?enabled AI. (See my recent Forbes piece on why AI regulation is effectively dead—and what businesses need to do instead.)

The physical location of a server is not just a technical detail. It’s a legal trigger. A conversation stored on a server in California is subject to U.S. law. If it’s routed through Frankfurt, it becomes subject to GDPR. When AI systems retain memory, context, and inferred consent, the server location effectively defines sovereignty over the interaction. That has implications for litigation, subpoenas, discovery, and privacy.

“I almost wish they’d go ahead and grant these AI systems legal personhood, as if they were therapists or clergy,” says technology attorney John Kheit. “Because if they are, then all this passive data collection starts to look a lot like an illegal wiretap, which would thereby give humans privacy rights/protections when interacting with AI. It would also, then, require AI providers to disclose ‘other parties to the conversation’, i.e., that the provider is a mining party reading the data, and if advertisers are getting at the private conversations.”

Infrastructure choices are now geopolitical. They determine how AI systems behave under pressure and what recourse a user has when something goes wrong.

And yet, underneath all of this is a deeper motive: monetization.

Altman’s comments about AI privilege may sound protective, but the practical effect is opacity. A legal shield around AI interactions enables OpenAI and others to build proprietary, black-boxed behavioral databases, which are data that can’t be examined, audited, or contested. Users won’t be able to retrieve their data. They’ll only be able to query the system and get outputs.

But they won’t be the only ones asking questions.

Every conversation becomes a four-party exchange: the user, the model, the platform’s internal optimization engine, and the advertiser paying for access. It’s entirely plausible for a prompt about the Pittsburgh Steelers to return a response that subtly inserts “Buy Coke” mid-paragraph. Not because it’s relevant—but because it’s profitable.

Recent research shows users are significantly worse at detecting unlabeled advertising when it’s embedded inside AI-generated content. Worse, these ads are initially rated as more trustworthy until users discover they are, in fact, ads. At that point, they’re also rated as more manipulative.

“In experiential marketing, trust is everything,” says Jeff Boedges, Founder of Soho Experiential. “You can’t fake a relationship, and you can’t exploit it without consequence. If AI systems are going to remember us, recommend things to us, or even influence us, we’d better know exactly what they remember and why. Otherwise, it’s not personalization. It’s manipulation.” Now consider what happens when advertisers gain access to psychographic modeling: “Which users are most emotionally vulnerable to this type of message?” becomes a viable, queryable prompt.

And AI systems don’t need to hand over spreadsheets to be valuable. With retrieval-augmented generation (RAG) and reinforcement learning from human feedback (RLHF), the model can shape language in real time based on prior sentiment, clickstream data, and fine-tuned advertiser objectives. This isn’t hypothetical—it’s how modern adtech already works.

At that point, the chatbot isn’t a chatbot. It’s a simulation environment for influence. It is trained to build trust, then designed to monetize it. Your behavioral patterns become the product. Your emotional response becomes the target for optimization.

The business model is clear: black-boxed behavioral insight at scale, delivered through helpful design, hidden from oversight, and nearly impossible to detect.

This is not a call to grant AI rights. It’s a warning about what happens when we treat systems like people, without the accountability that comes with being one.

We are entering a phase where machines will be granted protections without personhood, and influence without responsibility. If a user confesses to a crime during a legally privileged AI session, is the platform compelled to report it or remain silent? And who makes that decision?

These are not edge cases. They are coming quickly. And they are coming at scale.

Why ChatGPT Must Remain A Model—and Why Humans Must Regain Consent

As generative AI systems evolve into persistent, adaptive participants in daily life, it becomes more important than ever to reassert a boundary: models must remain models. They cannot assume the legal, ethical, or sovereign status of a person quietly. And the humans generating the data that train these systems must retain explicit rights over their contributions.

What we need is a standardized, enforceable system of data contracting, one that allows individuals to knowingly, transparently, and voluntarily contribute data for a limited, mutually agreed-upon window of use. This contract must be clear on scope, duration, value exchange, and termination. And it must treat data ownership as immutable, even during active use.

That means:

• Individuals always own their data, even if temporarily licensed for AI training.
• Consent must be explicit, revocable, and tracked.
• All data access must be recorded with immutable provenance, secured in high-integrity ledgers.

When a contract ends, or if a company violates its terms, the individual’s data must, by law, be erased from the model, its training set, and any derivative products. “Right to be forgotten” must mean what it says.

But to be credible, this system must work both ways:

• Data contributors can’t accept value (payment, services, access) and then retroactively revoke rights without consequence.
• Model owners must have temporary rights during the contract term, protected by the same legal infrastructure.

This isn’t just about ethics. It’s about enforceable, mutual accountability.

The user experience must be seamless and scalable. The legal backend must be secure. And the result should be a new economic compact—where humans know when they’re participating in AI development, and models are kept in their place.

ChatGPT Is Changing the Risk Surface. Here’s How to Respond.

The shift toward AI systems as quasi-participants—not just tools—will reshape legal exposure, data governance, product liability, and customer trust. Whether you’re building AI, integrating it into your workflows, or using it to interface with customers, here are five things you should be doing immediately:

1. Reevaluate your AI disclaimers and consent flows.
   If your product involves AI-generated interactions—especially in finance, healthcare, HR, or mental wellness—you need clear language around data use, memory, and legal boundaries. Assume the user believes they’re talking to something “real."
2. Pressure-test your data retention and jurisdictional exposure.
   Where is your AI model hosted? Where is the interaction data stored? Who owns it? These aren’t IT questions—they’re legal triggers. You may be subject to laws you haven’t accounted for simply by routing inference through the wrong cloud region.
3. Establish internal review protocols for AI influence.
   If your AI platform recommends products, guides decision-making, or creates emotionally resonant outputs, someone in your organization should review those systems for unintended bias, vulnerability exploitation, or embedded persuasion mechanics.
4. Demand transparency from your vendors.
   If you’re licensing AI services from OpenAI, Anthropic, Meta, or any third party, ask them directly: How is your data stored? Who can query it? What’s the policy if there’s a subpoena, leak, or government request? If they can’t answer, that’s your answer.
5. Prepare for liability, not just innovation.
   If your AI outputs shape someone’s financial, legal, or medical outcome, you’re not shielded by saying “the model did it.” As courts catch up to the influence these systems carry, accountability will rest with the companies that deploy them, not just the ones that train them.

ChatGPT May Get Privilege. You Should Get the Right to Be Forgotten.

This moment isn’t just about what AI can do. It’s about what your business is letting it do, what it remembers, and who gets access to that memory. Ignore that, and you’re not just risking privacy violations, you’re risking long-term brand trust and regulatory blowback.

At the very least, we need a legal framework that defines how AI memory is governed. Not as a priest, not as a doctor, and not as a partner, but perhaps as a witness. Something that stores information and can be examined when context demands it, with clear boundaries on access, deletion, and use.

The public conversation remains focused on privacy. But the fundamental shift is about control. And unless the legal and regulatory frameworks evolve rapidly, the terms of engagement will be set, not by policy or users, but by whoever owns the box.

Which is why, in the age of AI, the right to be forgotten may become the most valuable human right we have.

Not just because your data could be used against you—but because your identity itself can now be captured, modeled, and monetized in ways that persist beyond your control. Your patterns, preferences, emotional triggers, and psychological fingerprints don’t disappear when the session ends. They live on inside a system that never forgets, never sleeps, and never stops optimizing.

Without the ability to revoke access to your data, you don’t just lose privacy. You lose leverage. You lose the ability to opt out of prediction. You lose control over how you’re remembered, represented, and replicated.

The right to be forgotten isn’t about hiding. It’s about sovereignty. And in a world where AI systems like ChatGPT will increasingly shape our choices, our identities, and our outcomes, the ability to walk away may be the last form of freedom that still belongs to you.

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