Skip to content
Search

Latest Stories

Top Stories

The end of privacy?

person hacking a website
Bill Hinton/Getty Images

Frazier is an assistant professor at the Crump College of Law at St. Thomas University and a Tarbell fellow.

Americans have become accustomed to leaving bread crumbs of personal information scattered across the internet. Our scrolls are tracked. Our website histories are logged. Our searches are analyzed. For a long time, the practice of ignoring this data collection seemed sensible. Who would bother to pick up and reconfigure those crumbs?

In the off chance someone did manage to hoover up some important information about you, the costs seemed manageable. Haven’t we all been notified that our password is insecure or our email has been leaked? The sky didn’t fall for most of us, so we persisted with admittedly lazy but defensible internet behavior.


Artificial intelligence has made what was once defensible a threat to our personal autonomy. Our indifference to data collection now exposes us to long-lasting and significant harms. We now live in the “inference economy,” according to professor Alicia Solow-Niederman. Information that used to be swept up in the tumult of the Internet can now be scrapped, aggregated and exploited to decipher sensitive information about you. As Solow-Niederman explains, “seemingly innocuous or irrelevant data can generate machine learning insights, making it impossible for an individual to anticipate what kinds of data warrant protection.”

Our legal system does not seem ready to protect us. Privacy laws enacted in the early years of the internet reflect a bygone era. They protect bits and pieces of sensitive information but they do not create the sort of broad shield that’s required in an inference economy.

The shortcomings of our current system don’t end there. AI allows a broader set of bad actors to engage in fraudulent and deceptive practices. The fault in this case isn’t the substance of the law — such practices have long been illegal — but rather enforcement of those laws. As more actors learn how to exploit AI, it will become harder and harder for law enforcement to keep pace.

Privacy has been a regulatory weak point for the United States. A federal data privacy law has been discussed for decades and kicked down the road for just as long. This trend must come to an end.

The speed, scale and severity of privacy risks posed by AI require a significant update to our privacy laws and enforcement agencies. Rather than attempt to outline each of those updates, I’ll focus on two key actions.

First, enact a data minimization requirement. In other words, mandate that companies collect and retain only essential information to whatever service they provide to a consumer. Relatedly, companies should delete that information once the service has been rendered. This straightforward provision would reduce the total number of bread crumbs and, consequently, reduce the odds of a bad actor gathering personal and important information about you.

Second, invest in the Office of Technology at the Federal Trade Commission. The FTC plays a key role in identifying emerging unfair and deceptive practices. Whether the agency can perform that important role turns on its expertise and resources. Chair Lina Khan recognized as much when she initially created the office. Congress is now debating how much funding to provide to this essential part of privacy regulation and enforcement. Lawmakers should follow the guidance of a bipartisan group of FTC commissioners and ensure that office can recruit and retain leading experts as well as obtain new technological resources.

It took decades after the introduction of the automobile for the American public to support seat belt requirements. Only after folks like Ralph Nader thoroughly documented that we were unsafe at any speed did popular support squarely come to the side of additional protections. Let’s not wait for decades of privacy catastrophes to realize that we’re currently unsafe upon any scroll. Now’s the time for robust and sustained action to further consumer privacy.

Read More

An illustration of AI chat boxes.

An illustration of AI chat boxes.

Getty Images, Andriy Onufriyenko

In Defense of ‘AI Mark’

Earlier this week, a member of the UK Parliament—Mark Sewards—released an AI tool (named “AI Mark”) to assist with constituent inquiries. The public response was rapid and rage-filled. Some people demanded that the member of Parliament (MP) forfeit part of his salary—he's doing less work, right? Others called for his resignation—they didn't vote for AI; they voted for him! Many more simply questioned his thinking—why on earth did he think outsourcing such sensitive tasks to AI would be greeted with applause?

He's not the only elected official under fire for AI use. The Prime Minister of Sweden, Ulf Kristersson, recently admitted to using AI to study various proposals before casting votes. Swedes, like the Brits, have bombarded Kristersson with howls of outrage.

Keep ReadingShow less
shallow focus photography of computer codes
Shahadat Rahman on Unsplash

When Rules Can Be Code, They Should Be!

Ninety years ago this month, the Federal Register Act was signed into law in a bid to shine a light on the rules driving President Franklin Roosevelt’s New Deal—using the best tools of the time to make government more transparent and accountable. But what began as a bold step toward clarity has since collapsed under its own weight: over 100,000 pages, a million rules, and a public lost in a regulatory haystack. Today, the Trump administration’s sweeping push to cut red tape—including using AI to hunt obsolete rules—raises a deeper challenge: how do we prevent bureaucracy from rebuilding itself?

What’s needed is a new approach: rewriting the rule book itself as machine-executable code that can be analyzed, implemented, or streamlined at scale. Businesses could simply download and execute the latest regulations on their systems, with no need for costly legal analysis and compliance work. Individuals could use apps or online tools to quickly figure out how rules affect them.

Keep ReadingShow less
Microchip labeled "AI"
Preparing for an inevitable AI emergency
Eugene Mymrin/Getty Images

Nvidia and AMD’s China Chip Deal Sets Dangerous Precedent in U.S. Industrial Policy

This morning’s announcement that Nvidia and AMD will resume selling AI chips to China on the condition that they surrender 15% of their revenue from those sales to the U.S. government marks a jarring inflection point in American industrial policy.

This is not just a transaction workaround for a particular situation. This is a major philosophical government policy shift.

Keep ReadingShow less
Doctor using AI technology
Akarapong Chairean/Getty Images

Generative AI Can Save Lives: Two Diverging Paths In Medicine

Generative AI is advancing at breakneck speed. Already, it’s outperforming doctors on national medical exams and in making difficult diagnoses. Microsoft recently reported that its latest AI system correctly diagnosed complex medical cases 85.5% of the time, compared to just 20% for physicians. OpenAI’s newly released GPT-5 model goes further still, delivering its most accurate and responsive performance yet on health-related queries.

As GenAI tools double in power annually, two distinct approaches are emerging for how they might help patients.

Keep ReadingShow less