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exhibit-ai

Exhibit A(I): Three AI Legal Cases That Draw the Real Line

Three recent AI legal developments point to the same rule: AI can assist, but the human still owns authorship, accountability, and final judgment.

Exhibit A(I): Three AI Legal Cases That Draw the Real Line

The useful legal question is no longer whether AI shows up in the system.

It does.

The useful question is where the law is drawing the boundary between assistance and authority. Three recent developments point to the same answer: AI can help, draft, summarize, and recommend. The human still owns authorship, accountability, and final judgment.

The fact pattern

Start with the easiest case.

A US appeals court fined lawyers $30,000 over an AI-related filing failure. That is not an abstract ethics debate. That is a court turning sloppy reliance into a bill.

Then move to copyright. The US Supreme Court declined to hear the fight over whether AI-generated material can receive copyright protection without human authorship. That leaves the lower-court result standing and reinforces the same basic rule: machine generation alone does not magically create a human-rights wrapper around output.

Then look at the operational side. Courts in Los Angeles are piloting AI to help judges with drafting and backlog management, but the reporting still centers human oversight. Not because everyone suddenly became cautious. Because the institution already understands where the legal risk lands.

Three very different settings. Same line.

The line the law is actually drawing

Here is the pattern I care about.

AI is being accepted as a support tool.

AI is not being accepted as a liability sink.

That distinction matters because companies keep trying to market around it. "The model drafted it" is not a defense. "The system generated it" is not authorship. "The tool suggested it" does not remove the human duty to verify, decide, and own the result.

In court filings, that means lawyers still have to stand behind every citation and representation.

In copyright disputes, that means human creative contribution remains the legal hinge.

In courtroom pilots, that means judges can use AI to speed process, but the institution still has to preserve human responsibility for the ruling.

What the sanctions case really means

The sanctions story is not just about hallucinations. It is about professional duty.

Courts are telling lawyers that AI mistakes are still lawyer mistakes once they enter the filing. The duty to verify does not shrink because the draft came faster.

That is the first line.

If you deploy AI into a regulated professional workflow, the regulated professional keeps the duty.

That principle will not stay confined to lawyers. It maps cleanly onto compliance teams, clinicians, security operators, and anyone else trying to use AI inside a role that already carries a standard of care.

The copyright dispute makes the second line clearer.

You do not get to erase the human from authorship and then keep the legal privileges that depend on human authorship.

That matters beyond artists and copyright theorists. It shapes product claims, IP strategy, and how companies position AI-generated work product. If your business model quietly assumes that raw machine output will be treated like human-authored property, that assumption is getting weaker, not stronger.

The legal system is not saying AI output is worthless.

It is saying authorship still has a human threshold.

What the courtroom pilots really mean

The Los Angeles court pilot is the third line.

Institutions want the operational upside. Faster drafting. Better sorting. Less backlog.

But even in a setting under pressure to move faster, the model is still assistive. Human decision-makers remain the accountable layer.

That is not just administrative caution. It is design wisdom.

The more consequential the setting, the less appetite there is for handing final authority to a probabilistic system with no legal personhood, no duty of care, and no assets to sue.

The operator takeaway

If you build, buy, or deploy AI into legal or quasi-legal workflows, stop asking whether the tool is impressive.

Ask where the human duty survives.

That is where your policy, audit, and liability design should start.

Use this checklist:

  1. Identify who still owns the final verification duty.
  2. Record where human review is mandatory, not optional.
  3. Preserve evidence of what the AI generated versus what the human changed or approved.
  4. Avoid product language that implies the machine absorbs professional or authorship risk.

The law is giving us the pattern in plain view.

AI may assist.

The human still signs, owns, and answers for the outcome.

Sources

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