On Saturday, President Donald Trump called for the creation of an “AI Force” led by an AI “Czar,” although it is unclear what the proposed force or its head would do. Unlike the United States Space Force, which was created during the first Trump administration as the sixth and newest branch of the United States military, the AI Force would be a government initiative to monitor the artificial intelligence industry. The call for such a new organization comes as leaders of several AI firms have warned that AI development is advancing too quickly. The White House has suggested an AI Force could support the fast-moving industry rather than slow down innovation with strict new rules.
Trump compared the proposed AI Force to the U.S. Space Force, suggesting it would watch for “bad actors” and wrongdoing. It would rely on existing civil and criminal laws instead of creating the new guardrails that some in the AI industry have pushed for.
The White House has yet to clarify where such an AI force would sit in the federal government, what legal authority it could have, or whether it would require approval from Congress.
Forcing the Issue
It isn’t just lawmakers who seem unclear on what the AI Force’s responsibilities should be; cybersecurity experts warn it shouldn’t be only to drive innovation without creating some form of guardrails.
“Let’s not overcomplicate the question of AI regulation. In every other sector of the economy, we hold manufacturers accountable for the safety of what they build: toys, houses, cars, etc.,” explained Doc McConnell, head of Policy and Compliance at cybersecurity provider Finite State.
McConnell told ClearanceJobs that AI should not be an exception when it comes to regulation and accountability.
“Today, what clouds the debate over accountability is that there are multiple actors: the frontier labs that train the models, the companies that deploy them, and the users who prompt them and act on the outputs,” McConnell suggested. “That gives everyone a reasonable-sounding excuse. The lab claims that a deployer failed to sandbox the agent, the deployer blames a reckless user, and the user says the underlying model was flawed.”
Workable Regulation
AI innovation needs to continue, but it shouldn’t be without any regulation.
“Workable regulation is whatever survives an administration that doesn’t want to regulate, and that narrows it fast to two things: mandatory incident disclosure and clear liability for real-world harm,” suggested Denis Calderone, CTO at cybersecurity provider Suzu Labs.
However, Calderone warned that AI Force shouldn’t allow the industry to police itself. It should serve as a regulatory body as much as a driver of innovation and advancement.
“Self-reporting fails for the same reason the SEC has mandatory disclosure, and OSHA runs inspections instead of waiting for companies to mail in hazard reports, because the organization with the most to lose is the worst one to decide what the public hears,” Calderone told ClearanceJobs.
“Put people with real security experience in the room,” he added. “The people who’ve actually built, broken, and hardened production systems, who’ve worked a breach and had to explain to a customer what happened to their data, should be designing these tests and reviewing the findings.”
Meaningful Liability
There may need to be incentives for development and winning the AI race, but also consequences for when things go wrong. AI models have already been seen to carry out hacks on rival companies, something that would land living humans in legal trouble and likely in jail!
AI isn’t being punished, and so far neither are the developers.
“To ensure that these models are fundamentally safe, there must be meaningful liability for the frontier labs. This liability should apply to the doomsday scenarios we’re hearing about today, like biological agents or cyber attacks against real-world infrastructure,” said McConnell.
This isn’t just about a “Terminator” -style scenario either. AI’s actions aren’t limited to ending civilization.
“It should also apply to the harms that we’ve already seen play out: the creation of child sexual abuse material, or the contributions of chatbots to self-harm and suicide,” added McConnell. “The liability must be strong enough to counterbalance the enormous commercial incentive for labs to build faster, more responsive, more autonomous models.”
Moreover, there should be no compromise on what AI is allowed to do that a human isn’t.
“AI is a tool, used by people,” McConnell continued. “Those people must remain accountable for the fair and equitable outcomes of their work, no matter what tools they choose to use.”
