When Context Becomes the Primary Means of Production

When Context Becomes the Primary Means of Production

Begin with a strong assumption: artificial superintelligence arrives within the next five to ten years; human intelligence becomes far weaker than AI intelligence; and 99% of a person's value at work comes from a long-accumulated personal knowledge base that AI can call as context.

This is not a prediction about the ASI timetable, the relative abilities of humans and AI, or the literal accuracy of the 99% figure. It is a thought experiment. Its purpose is to make one institutional question impossible to avoid: if general intelligence becomes a machine that anyone can rent, does context become a person's most important means of production? If it does, when should that context belong to a company, and when should it remain with the individual?

The central conclusion is that context will become a primary means of production, but it cannot coherently be awarded as one indivisible object either to the person or to the company.

A company may control work facts, trade secrets, proprietary bindings, and expressly commissioned deliverables. An individual must retain an inalienable measure of cognitive continuity and general capability. Value jointly created by a person, a team, and company resources requires shared governance. Data about customers and colleagues can only be held in trust for legitimate purposes; it is not the absolute property of either side.

In plainer terms, a worker may carry away the method, but not the customer. A company may keep the process, but it should not permanently and freely possess a former employee's digital double.

The apparent ownership question therefore needs to be decomposed into at least six separately configurable rights. Access and continuity asks who may keep consulting and calling the context after an exit, acquisition, or system migration. Use and execution asks who may let AI reason from it, invoke tools, or act externally, for which purpose and under which authority. Modification and training asks who may correct, aggregate, transform, or use it to train an embedding, adapter, agent, or other derived model. Export and transfer asks who may carry away an original, a sanitized representation, or a contribution attestation, and who may license or sell it to a third party. Exclusion and deletion asks who may reject a new purpose, stop identity replication, revoke credentials, or require a version and its derivatives to be deleted. Audit and revenue asks who may inspect use, verify provenance, allocate risk, and participate in a license fee, buyout, royalty, or collective dividend.

These operating rights sit on top of distinct legal and institutional interests: custody of source facts, ownership of fixed expression and work product, cognitive continuity in general methods, duties of confidentiality and privacy, limits on training and continued deployment, and governance of jointly produced value. The decomposition matters because the right to retain a document need not imply a right to train a digital double, and a right to use a method need not imply a right to export its secret inputs.

These rights can point in different directions at the same time. A company can own a particular document without owning the underlying general method. A worker can retain a method without being entitled to disclose the secret inputs through which it was learned. A team can create an important workflow without any single member being entitled to sell all of it. A customer can have privacy interests in information that neither the worker nor the employer may treat as freely alienable property. The question is therefore not simply, "Who owns the database?" It is, "Which rights attach to which layer of context, for which purpose, for how long, and under what accountability?"