Watch for Legal Risks in Everyday AI Use

When AI outputs results are either misused or misapplied — most notably without human oversight — the risks and consequences can be outsized.
In the current federal regulatory environment, where regulatory protections and structures are often deemed as burdensome and impediments to business, it’s not difficult to understand why federal AI regulation has gone virtually nowhere. In fairness, it also must be noted that getting federal legislation drafted and passed is a monumental task in and of itself, and in the current environment, it’s even more difficult. However, the need for additional guardrails on how AI was used has become increasingly obvious, and where Congress has failed—or been unable—to act, the states have stepped up. In some cases, they’ve followed the roadmap laid by international bodies like the executive body of the European Union, the European Commission, and in others, some states have followed the lead(s) of others. This has led to a crazy quilt of differing regulations and approaches to regulation.

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AI Tools Demonstrate Hidden Risks of Imperfect Outputs

As AI use grows, so does the need for disclaimers, vetting AI-generated results, and avoiding expensive errors.
When it comes to deployment of AI, some deployers are listening to their lawyers. Many documents that are created with AI now contain disclaimers like this one which I found at the bottom of a document reviewed in legal community platform Justia: “Some case metadata and case summaries were written with the help of AI, which can produce inaccuracies. You should read the full case before relying on it for legal research purposes.” At least, this entity has the courage to announce and warn about its use of AI. At least this entity has the courage to announce and warn about its use of AI. Many documents and entities are not, including a radio station with which I’m familiar, which uses AI to produce weather reports, signed off by “staff meteorologists” who are not real. The AI-generated forecasts are close to accurate, which I view as positive but not determinative, but the named staff meteorologists who provide the forecasts are identified as real people, which they are not.

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Bad News For Net Neutrality

Perhaps there will be new ways for the federal government to tackle the issues that net neutrality sought to address – but here’s a reminder of what those issues are.
In what seems to me to be an opinion that’s as politically charged as any I can recall, the U.S Court of Appeals for the Sixth Circuit threw out the Biden Administration’s attempt to restore network neutrality. Given the upcoming change of administration, and the current balance on the U.S. Supreme Court, it is extremely unlikely that the FCC will choose to appeal this decision one more time in an effort to restore what many—including me—believe a fair and equitable way to treat the internet as it should be treated, i.e. as the utility that it has become.  However, rather than cry over spilled milk, I would suggest that while many argue that regulation stifles innovation, I think that regulation only inspires it, especially since it establishes frameworks that offer unexpected and smaller players to compete with new ideas and implementations. However, in the absence of this sort of innovation-encouraging structure, perhaps there will be new ways for the federal government to tackle the issues that net neutrality sought to address head-on.

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A Potentially Shifting Regulatory Agenda in 2025

Expect an increased focus on AI and cybersecurity issues, the ability of the FCC to make and enforce policy top the list of likely changes in the new year.
Between the Supreme Court’s decision in Loper Bright and the presence of a new administration, priorities will shift. But the need for reliable communications, irrespective of underlying technologies, particularly as impacts public safety and security, remains essential.

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AI Needs to Reduce Errors – Or Everyone Will Pay the Price

As litigators begin to go after AI systems and those that deploy them, every human in the technology-deployment chain must carefully consider how much an AI-sponsored error is worth.
I have yet to meet anyone who enjoys being in direct communication with an AI tool. AI-augmented CX systems may provide some efficiencies, but those efficiencies often translate into high levels of customer dissatisfaction. With this in mind, and studies of various flavors indicating that AI is a low trust technology, it’s important for anyone considering the deployment of highly advanced and seemingly sophisticated AI-based products and services to consider the downside(s). A systematic deep dive in the cost-benefit analysis is a wise idea, particularly given the fact that the AI bar is just revving up.

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