Even if jobs like judges are legally protected from direct AI replacement, they can be de facto automated. If every judge uses the same AI model for decision support, the outcome is systemic homogenization of judgment, creating a centralized point of failure without any formal automation.

You can't sue an AI model provider like Anthropic when an agent makes a costly mistake. Enterprises require a human-led organization, like a consulting firm, to take accountability and liability. This fundamental need for a "throat to choke" ensures the relevance of services firms in the AI era.

A crucial function for humans in an AI-driven economy is to serve as a target for lawsuits. Because you can't easily sue a data center, regulated professions will require a 'human in the loop' to take legal responsibility. This creates a valuable economic role for humans: being a legally accountable entity.

Governments will aggressively protect jobs from automation through policy, creating a significant but often overlooked barrier to AI's real-world deployment. This societal threshold for what we allow AI to do will be a more potent brake on progress than technological limitations, as seen with unions protecting dockworker jobs.

Roles requiring accountability will persist despite AI's capabilities. An LLM can't be a lawyer because it can't be disbarred; it can't be held responsible. This principle highlights that the need for human validation and liability will protect many professions.

AI could theoretically provide world-class legal, medical, or educational advice. However, it cannot disrupt these fields because it can't get licensed, admitted to the bar, or receive insurance reimbursements. These regulatory moats will keep these professions untouched by AI's capabilities for the foreseeable future.

The legal guild's primary defense against disruption is the 'Unauthorized Practice of Law' (UPL) statute in each state, which prevents non-lawyers (and thus, AI tools) from giving legal advice. These statutes are the central battleground for consumer-facing legal AI.

Forbidding existing companies from replacing workers with AI will backfire. New, more efficient companies will be founded using AI from the start, avoiding the need to fire anyone. These new firms will outcompete and replace the old ones, ultimately leading to the same job displacement the law sought to prevent.

As AI systems become infinitely scalable and more capable, humans will become the weakest link in any cognitive team. The high risk of human error and incorrect conclusions means that, from a purely economic perspective, human cognitive input will eventually detract from, rather than add to, value creation.