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Digital Technology and the Regulatory State | Podcast Highlights

Blog Post | Communications

Digital Technology and the Regulatory State | Podcast Highlights

Chelsea Follett interviews Jennifer Huddleston about the benefits of digital technologies as well as how we should think about the risks and problems they pose.

Read the full transcript or listen to the podcast here.

We hear so much about the risks and downsides of technology. What are some areas where you believe digital technologies have improved our lives?

There are so many areas that we’ve seen transformed by technology over the last decade. Think about when we were faced with the COVID-19 pandemic, and so much of our lives shifted to our homes. Now imagine if that same thing had happened in 2010. How different would that have been? How much more limited would the options have been to stay connected to friends and family, entertain yourself at home, and continue your education and job?

Because the US has maintained a light-touch regulatory approach to the technology sector, we empowered entrepreneurs to create products that benefit consumers, sometimes in ways that we never could have imagined. I still remember the days when you had to have atlases in your car. And I remember when MapQuest seemed like such a huge deal. Now, if you’re going somewhere new, you often don’t even look it up in advance.

I’m hearing a lot of calls for more regulation of digital technologies. President Biden is saying we need to clamp down on AI, while Nikki Haley has said we must deanonymize social media. What are some of the dangers of over-regulating these technologies?

I’m going to start by asking you a question. How often do you think you use AI?

When it comes to ChatGPT, every few days. But I’m sure that what you’re hinting at is that AI is incorporated into far more than we’re even aware of.

Exactly. Most of us have been using AI for much longer than we realize. Search engines and navigation apps use AI. If you’ve ever tried to do a return and interacted with a chatbot, some of that is possible because of advances in AI. We’ve also benefited from AI in indirect ways. For example, AI can be used to help predict forest fires and to assist in medical research. Because AI is such a general-purpose technology, a lot of the calls for regulation may lead to fewer of those beneficial applications and could even make it harder to use many of the applications we’re already used to.

Oftentimes, people just don’t think about the consequences of regulation. When we think about an issue like anonymous speech, many people immediately jump to their negative experiences with anonymous trolls online. But we should also think about the costs of deanonymizing speech. Think about dissidents trying to communicate with journalists or people trying to alert each other to social problems in authoritarian regimes. Anonymous speech is incredibly valuable to those people, and we have a long-standing tradition of protecting that kind of speech in the US. When we look at creating backdoors or deanonymizing things, that’s not just going to be used for going after the bad guys. It’s also going to be exploited by a whole range of bad actors.

And this country was arguably founded on a tradition of pseudonymous and anonymous speech; think of the Federalist Papers.

Right.

What do you think is driving this distrust of new technologies?

Disruptive new technologies like social media and artificial intelligence are naturally going to make us uncomfortable. They create new ways of doing things and force societal norms to evolve. This is something that happened in the past, for example, with the camera. We’re now used to having cameras everywhere, but we had to develop norms around when, where, and how we can take pictures. With AI, we’re watching that process happen in real-time.

The good news is that we’re adapting to new technologies faster than ever. When you look at the level of adoption of technologies like ChatGPT and the comfort level that younger people have with them, innovations seem to be becoming socially acceptable at a much quicker pace than in the past.

The current technology panics are also not unique to the present. We’ve seen a lot of concern about young people and social media recently, but before that, it was young people and video games, and before that, it was magazines and comic books. We even have articles from back in the day of people complaining that young people were reading too many novels.

There’s also this fear of tech companies having too much market share. Can you walk us through that concern and provide your take on it?

I’m sure you’re talking about Myspace’s natural monopoly on social media. Or maybe you’re talking about how Yahoo won the search wars. These were very real headlines 20 years ago with a different set of technology giants. So, my first point is that innovation is our best competition policy.

My second point is that before we implement competition policy, we need to figure out why big companies are popular. If a company is popular because it’s serving its consumers well, that’s not a problem; that’s something we should be applauding. When we think about incredibly popular products like Amazon’s Prime program, people choose to engage with it because they find it beneficial.

We should really only want to see antitrust or competition policy used if anti-competitive behavior is harming consumers. We don’t want a competition policy that presumes big is bad. And we certainly don’t want to see competition policy that focuses on competitors rather than consumers. We don’t want a world where the government dictates that the Model T can’t put the horseshoe guys out of business.

People of all stripes want to restrict how private companies moderate content. People on the left are concerned about potential misinformation online, while those on the right worry about political bias in content moderation. What’s your take on this issue?

Online content moderation matters for a lot more than social media. We often think about this in the context of, “Did X take down a certain piece of content or leave up a certain piece of content?” But this is actually much bigger. Think about your favorite review site. If you travel and you’re going to a new place and looking for somewhere to stay or go to dinner, you’re probably going to go to your favorite review site rather than read what some famous travel reporter has said.

The review sites allow you to find reviewers with your same needs. Maybe you’re traveling with young children, or you have someone with dietary restrictions. This is something that only user-generated content can provide. But what about bad or unfair reviews? What happens when someone starts trying to get bad reviews taken down? We want these sites to be able to set rules that keep reviews honest, that keep the tool useful, where they’re not being overrun by spam, and they aren’t afraid of a lawsuit from someone who disagrees with a review.

This is one example of why we should be concerned about these online content moderation policies. When it comes to questions of misinformation, I think it’s important to take a step back and think, “Would I want the person I most disagree with to have the power to dictate what was said on this topic?” Because if we give the government the power to label misinformation and moderate content, the government will have that power whether or not the people you agree with are in charge. So not only do we have First Amendment concerns here in the US from a legal point of view, but we should also have some pretty big first principles concerns regarding some of these proposals.

That’s a good segue into another concern a lot of people have with new technology, which is its effect on young people. What do you make of those concerns?

Youth online safety can mean so many different things. Some people are concerned about how much time their child spends online. Some people are concerned about issues related to online predators. Others are just concerned about particular types of content that they don’t want their children exposed to. The good news is we’ve seen the market respond to a lot of these concerns, and there are a lot of tools and choices available to parents.

The first choice is just when you allow your child to use certain technology. That’s going to vary from family to family. But even once you’ve decided to allow your child to have access to a device, you can set time limits or systems that alert you to how the child is using the device. There, we have seen platforms, device makers, and civil society respond with a great deal of tools and resources for parents. To reduce harm to children, we should look to education rather than regulation. We need to empower people to make the choices that work best for them because this isn’t going to be a one-size-fits-all decision, and policy intervention will result in a one-size solution.

Many people are also concerned about privacy. Whenever there is a large gathering of data, that data can be leaked to the government or to bad actors. How should we think about data privacy?

When we talk about privacy, I think it’s important to distinguish between the government and private actors. We need very strong privacy protections against government surveillance, not only for consumers but also for the companies themselves, so that they can protect their consumers and keep the promises they’ve made to consumers regarding data privacy.

When it comes to individual companies, we need to think about the fact that there are a lot of choices when it comes to data privacy, some of which we don’t even think are data privacy choices.

One example is if you go to a website and sign up for a newsletter in order to get a ten percent off coupon, you’re technically exchanging a bit of data, such as your email address, for that 10 percent off coupon. You get a direct benefit in that moment. That’s a privacy choice you make. If we think about privacy as a choice, we start to see that we make these choices every day. Even where we choose to have a conversation is a data privacy choice.

The other element when it comes to data privacy is that an individual’s data, while we deeply care about it, is not actually that valuable. What’s been valuable is how data can be used in the aggregate to improve services. So, when we hear that we should just treat data like any other piece of property, it doesn’t necessarily work because data doesn’t act like other forms of property in many cases. Not only is the value of the data not tied to a single data point, but the data also is often not tied to a single user. This makes regulating data privacy very complicated. If you and I are in a picture together, whose data is that? Is it the person who took the picture’s or people in the picture’s? Or does it belong to the location we were in while taking the picture? Can you invoke a right to be forgotten that removes the picture? And if so, then what does that do to the person who took the picture’s speech rights? These are not easy questions, and they’re often better solved on an individual basis than with a one-size-fits-all approach.

UCL | Communications

UK Neuralink Patient Uses Thought to Control Computer

“A patient with motor neurone disease was able to control a computer just by using his thoughts following the UK’s first Neuralink implant surgery in a study led by UCL and UCLH clinical researchers.

The surgery is part of the GB-PRIME study evaluating the safety and functionality of Neuralink’s robotically implanted brain-computer interface (BCI), which aims to improve independence for people who are paralysed. 

The surgery, which took place at UCLH’s National Hospital for Neurology and Neurosurgery (NHNN) in October 2025, went as planned, and on the day following the procedure, the patient was able to begin using their BCI implant to move a computer cursor with their thoughts and to return home from the hospital.”

From UCL.

New York Times | Computing

Google’s Quantum Computer Makes a Big Technical Leap

“On Wednesday, Dr. Devoret and his colleagues at a Google lab near Santa Barbara, Calif., said their quantum computer had successfully run a new algorithm capable of accelerating advances in drug discovery, the design of new building materials and other fields.

Leveraging the counterintuitive powers of quantum mechanics, Google’s machine ran this algorithm 13,000 times as fast as a top supercomputer executing similar code in the realm of classical physics, according to a paper written by the Google researchers in the scientific journal Nature…

In another paper published on Wednesday on the research site arXiv, the company showed that its algorithm could help improve what is called nuclear magnetic resonance, or N.M.R., which is a technique used to understand the structure of tiny molecules and how they interact with one another.

N.M.R. is a vital part of effort to develop new medicines for fighting disease and new materials for building everything from cars to buildings. It can help understand Alzheimer’s disease or drive the creation of entirely new metals, said Ashok Ajoy, an assistant professor of chemistry at Berkeley who specializes in N.M.R. and worked with Google’s researchers on the new paper.”

From New York Times.

Nature | Science & Technology

OpenAI’s GPT-5 Hallucinates Less than Previous Models Do

“In one literature-review benchmark known as ScholarQA-CS, GPT-5 ‘performs well’ when it is allowed to access the web, says Akari Asai, an AI researcher at the Allen Institute for Artificial Intelligence, based in Seattle, Washington, who ran the tests for Nature. In producing answers to open-ended computer-science questions, for example, the model performed marginally better than human experts did, with a correctness score of 55% (based on measures such as how well its statements are supported by citations) compared with 54% for scientists, but just behind a version of institute’s own LLM-based system for literature review, OpenScholar, which achieved 57%.

However, GPT-5 suffered when the model was unable to get online, says Asai. The ability to cross-check with academic databases is a key feature of most AI-powered systems designed to help with literature reviews. Without Internet access, GPT-5 fabricated or muddled half the number of citations that one of its predecessors, GPT-4o, did. But it still got them wrong 39% of the time, she says.

On the LongFact benchmark, which tests accuracy in long-form responses to prompts, OpenAI reported that GPT-5 hallucinated 0.8% of claims in responses about people or places when it was allowed to browse the web, compared with 5.1% for OpenAI’s reasoning model o3. Performance dropped when browsing was not permitted, with GPT-5’s error rate climbing to 1.4% compared with 7.9% for o3. Both models showed worse performance than did the non-reasoning model GPT-4o, which had an error rate of 1.1% when offline.”

From Nature.

Wired | Science & Technology

OpenAI Just Released Its First Open-Weight Models Since GPT-2

“OpenAI just dropped its first open-weight models in over five years. The two language models, gpt-oss-120b and gpt-oss-20b, can run locally on consumer devices and be fine-tuned for specific purposes. For OpenAI, they represent a shift away from its recent strategy of focusing on proprietary releases, as the company moves towards a wider, and more open, group of AI models that are available for users…

What sets apart an open-weight model is the fact that its ‘weights’ are publicly available, meaning that anyone can peek at the internal parameters to get an idea of how it processes information. Rather than undercutting OpenAI’s proprietary models with a free option, cofounder Greg Brockman sees this release as ‘complementary’ to the company’s paid services, like the application programming interface currently used by many developers. ‘Open-weight models have a very different set of strengths,’ said Brockman in a briefing with reporters. Unlike ChatGPT, you can run a gpt-oss model without a connection to the internet and behind a firewall.”

From Wired.