Why does AI privilege matter now?
As generative AI systems like ChatGPT become embedded in the fabric of legal research, corporate strategy, personal wellness, and even emotional support, a quiet transformation is taking place. People are beginning to speak to machines the way they used to speak to doctors or lawyers—candidly, vulnerably, and with trust.
But unlike those human relationships, these AI interactions are not shielded by legal privilege. A user might pour their deepest anxieties or most sensitive strategic plans into a chatbot, assuming confidentiality. They may later discover that such information can be reviewed by third-party moderators, used for model training, or even subpoenaed in litigation.
This tension, between the growing intimacy of AI-human interactions and the absence of protective legal frameworks, forms the basis for a new legal and governance frontier: AI privilege.
What is AI privilege?
AI privilege refers to the legal protection of user interactions with AI systems, particularly generative models, in a manner analogous to professional privileges such as attorney-client confidentiality or doctor-patient confidentiality. It is not simply about data protection. It is about shielding certain types of information from compelled disclosure, misuse, or unauthorised access, even by courts.
Why current laws fall short
While data protection laws such as the GDPR regulate how personal data is processed, they do not provide the kind of evidentiary shield that professional privilege offers. Even the new EU AI Act, while robust on transparency and accountability, stops short of recognising a user’s confidential interaction with an AI as privileged.
This creates what I call an innovation dilemma. If users fear their data can be used against them, they self-censor. But if they do not share freely, AI’s potential for tailored insight is lost. Everyone loses.
Can we build an AI privilege system? Yes. But it requires a new design philosophy
At ITLawCo, we propose that AI privilege be treated as a sui generis (fancy legal word meaning “unique”) legal framework. It should be informed by existing privileges, but not beholden to their exact requirements. This means not shoehorning AI into the role of a “digital lawyer” but recognising that a new category of privileged relationship has emerged between humans and their intelligent systems.
We call this approach privilege by design. It is a model that blends law, engineering, and ethics.
How AI privilege could work in practice
A robust AI privilege framework would need to address several key dimensions.
1. Who holds the privilege?
The user, not the AI provider, should be the holder. This ensures that individuals (or organisations) remain in control of their data and can assert privilege to prevent disclosure.
2. What is protected?
- User inputs such as prompts, uploads, and voice notes.
- AI outputs generated in direct response to those inputs.
- User-specific inferences but not the AI’s general knowledge base.
3. When does privilege apply?
Only when:
- The user has a reasonable expectation of confidentiality.
- The AI provider meets prescribed technical and organisational safeguards such as encryption, no training reuse, and secure data retention.
- No exceptions apply, for example, crime-fraud.
This conditionality incentivises ethical design and creates legal consequences for providers who breach trust.
Exceptions: when AI privilege must yield
As with all privileges, exceptions must exist for overriding public interest. These include:
- Crime-fraud, for example, using AI to assist with illegal activity.
- Imminent harm, such as threats of violence.
- Law enforcement or national security, subject to strict judicial oversight.
Such exceptions must be tightly framed, with high evidentiary thresholds to prevent abuse. This is a lesson learned from the erosion of other digital privacy rights in the post-Snowden era.
Designing for trust: accountability and safeguards
AI privilege will only gain traction if users and regulators trust the systems involved. This requires:
- Immutable audit trails.
- End-to-end encryption.
- User-controlled deletion.
- Independent audits.
- Human oversight for critical systems.
Technical safeguards and legal rules must co-evolve. Privilege, once granted, must also be respected in architecture.
International considerations: avoid a race to the bottom
If one country recognises AI privilege and another does not, we risk a world of “privilege havens” and “privilege deserts”. Harmonising principles across jurisdictions, especially with the EU AI Act’s extraterritorial scope, is essential. An international convention or mutual recognition mechanism may be required.
The road ahead: legislative action and public dialogue
The question is no longer whether we should recognise AI privilege. The real question is how we construct it. To do so, we recommend:
- Enacting dedicated legislation recognising AI privilege as a new legal category.
- Requiring privilege by design through baseline technical and organisational safeguards.
- Ensuring informed user control, meaningful transparency, and redress.
- Empowering independent oversight bodies or ombuds offices.
- Regularly reviewing the framework to match rapid advances in AI capabilities.
AI privilege is not a loophole. It is a trust anchor
In the same way that legal privilege enables clients to be open with their lawyers, AI privilege, carefully designed and judiciously applied, could be the foundation for more responsible, transparent, and ethical AI use.
To build this future, we must reimagine not just how we regulate AI but how we trust it. The law must evolve, not to shield AI, but to shield us—as humans in an increasingly intelligent world.
