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Meet the AI expert who says we should stop using AI so much

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The Download:  biased AI warnings, and experimental CRISPR therapies


Broussard has also recently recovered from breast cancer, and after reading the fine print of her electronic medical records, she realized that an AI had played a part in her diagnosis—something that is increasingly common. That discovery led her to run her own experiment to learn more about how good AI was at cancer diagnostics.

We sat down to talk about what she discovered, as well as the problems with the use of technology by police, the limits of “AI fairness,” and the solutions she sees for some of the challenges AI is posing. The conversation has been edited for clarity and length.

I was struck by a personal story you share in the book about AI as part of your own cancer diagnosis. Can you tell our readers what you did and what you learned from that experience?

At the beginning of the pandemic, I was diagnosed with breast cancer. I was not only stuck inside because the world was shut down; I was also stuck inside because I had major surgery. As I was poking through my chart one day, I noticed that one of my scans said, This scan was read by an AI. I thought, Why did an AI read my mammogram? Nobody had mentioned this to me. It was just in some obscure part of my electronic medical record. I got really curious about the state of the art in AI-based cancer detection, so I devised an experiment to see if I could replicate my results. I took my own mammograms and ran them through an open-source AI in order to see if it would detect my cancer. What I discovered was that I had a lot of misconceptions about how AI in cancer diagnosis works, which I explore in the book.

[Once Broussard got the code working, AI did ultimately predict that her own mammogram showed cancer. Her surgeon, however, said the use of the technology was entirely unnecessary for her diagnosis, since human doctors already had a clear and precise reading of her images.]

One of the things I realized, as a cancer patient, was that the doctors and nurses and health-care workers who supported me in my diagnosis and recovery were so amazing and so crucial. I don’t want a kind of sterile, computational future where you go and get your mammogram done and then a little red box will say This is probably cancer. That’s not actually a future anybody wants when we’re talking about a life-threatening illness, but there aren’t that many AI researchers out there who have their own mammograms. 

You sometimes hear that once AI bias is sufficiently “fixed,” the technology can be much more ubiquitous. You write that this argument is problematic. Why? 

One of the big issues I have with this argument is this idea that somehow AI is going to reach its full potential, and that that’s the goal that everybody should strive for. AI is just math. I don’t think that everything in the world should be governed by math. Computers are really good at solving mathematical issues. But they are not very good at solving social issues, yet they are being applied to social problems. This kind of imagined endgame of Oh, we’re just going to use AI for everything is not a future that I cosign on.

You also write about facial recognition. I recently heard an argument that the movement to ban facial recognition (especially in policing) discourages efforts to make the technology more fair or more accurate. What do you think about that?

I definitely fall in the camp of people who do not support using facial recognition in policing. I understand that’s discouraging to people who really want to use it, but one of the things that I did while researching the book is a deep dive into the history of technology in policing, and what I found was not encouraging. 

I started with the excellent book Black Software by [NYU professor of Media, Culture, and Communication] Charlton McIlwain, and he writes about IBM wanting to sell a lot of their new computers at the same time that we had the so-called War on Poverty in the 1960s. We had people who really wanted to sell machines looking around for a problem to apply them to, but they didn’t understand the social problem. Fast-forward to today—we’re still living with the disastrous consequences of the decisions that were made back then. 

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The Download: AI films, and the threat of microplastics

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Welcome to the new surreal. How AI-generated video is changing film.


The Frost nails its uncanny, disconcerting vibe in its first few shots. Vast icy mountains, a makeshift camp of military-style tents, a group of people huddled around a fire, barking dogs. It’s familiar stuff, yet weird enough to plant a growing seed of dread. There’s something wrong here.

Welcome to the unsettling world of AI moviemaking. The Frost is a 12-minute movie from Detroit-based video creation company Waymark in which every shot is generated by an image-making AI. It’s one of the most impressive—and bizarre—examples yet of this strange new genre. Read the full story, and take an exclusive look at the movie.

—Will Douglas Heaven

Microplastics are everywhere. What does that mean for our immune systems?

Microplastics are pretty much everywhere you look. These tiny pieces of plastic pollution, less than five millimeters across, have been found in human blood, breast milk, and placentas. They’re even in our drinking water and the air we breathe.

Given their ubiquity, it’s worth considering what we know about microplastics. What are they doing to us? 

The short answer is: we don’t really know. But scientists have begun to build a picture of their potential effects from early studies in animals and clumps of cells, and new research suggests that they could affect not only the health of our body tissues, but our immune systems more generally. Read the full story.

—Jessica Hamzelou

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Microplastics are everywhere. What does that mean for our immune systems?

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Microplastics are everywhere. What does that mean for our immune systems?


Here, bits of plastic can end up collecting various types of bacteria, which cling to their surfaces. Seabirds that ingest them not only end up with a stomach full of plastic—which can end up starving them—but also get introduced to types of bacteria that they wouldn’t encounter otherwise. It seems to disturb their gut microbiomes.

There are similar concerns for humans. These tiny bits of plastic, floating and flying all over the world, could act as a “Trojan horse,” introducing harmful drug-resistant bacteria and their genes, as some researchers put it.

It’s a deeply unsettling thought. As research plows on, hopefully we’ll learn not only what microplastics are doing to us, but how we might tackle the problem.

Read more from Tech Review’s archive

It is too simplistic to say we should ban all plastic. But we could do with revolutionizing the way we recycle it, as my colleague Casey Crownhart pointed out in an article published last year. 

We can use sewage to track the rise of antimicrobial-resistant bacteria, as I wrote in a previous edition of the Checkup. At this point, we need all the help we can get …

… which is partly why scientists are also exploring the possibility of using tiny viruses to treat drug-resistant bacterial infections. Phages were discovered around 100 years ago and are due a comeback!

Our immune systems are incredibly complicated. And sex matters: there are important differences between the immune systems of men and women, as Sandeep Ravindran wrote in this feature, which ran in our magazine issue on gender.

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Welcome to the new surreal. How AI-generated video is changing film.

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Welcome to the new surreal. How AI-generated video is changing film.


Fast and cheap

Artists are often the first to experiment with new technology. But the immediate future of generative video is being shaped by the advertising industry. Waymark made The Frost to explore how generative AI could be built into its products. The company makes video creation tools for businesses looking for a fast and cheap way to make commercials. Waymark is one of several startups, alongside firms such as Softcube and Vedia AI, that offer bespoke video ads for clients with just a few clicks.

Waymark’s current tech, launched at the start of the year, pulls together several different AI techniques, including large language models, image recognition, and speech synthesis, to generate a video ad on the fly. Waymark also drew on its large data set of non-AI-generated commercials created for previous customers. “We have hundreds of thousands of videos,” says CEO Alex Persky-Stern. “We’ve pulled the best of those and trained it on what a good video looks like.”

To use Waymark’s tool, which it offers as part of a tiered subscription service starting at $25 a month, users supply the web address or social media accounts for their business, and it goes off and gathers all the text and images it can find. It then uses that data to generate a commercial, using OpenAI’s GPT-3 to write a script that is read aloud by a synthesized voice over selected images that highlight the business. A slick minute-long commercial can be generated in seconds. Users can edit the result if they wish, tweaking the script, editing images, choosing a different voice, and so on. Waymark says that more than 100,000 people have used its tool so far.

The trouble is that not every business has a website or images to draw from, says Parker. “An accountant or a therapist might have no assets at all,” he says. 

Waymark’s next idea is to use generative AI to create images and video for businesses that don’t yet have any—or don’t want to use the ones they have. “That’s the thrust behind making The Frost,” says Parker. “Create a world, a vibe.”

The Frost has a vibe, for sure. But it is also janky. “It’s not a perfect medium yet by any means,” says Rubin. “It was a bit of a struggle to get certain things from DALL-E, like emotional responses in faces. But at other times, it delighted us. We’d be like, ‘Oh my God, this is magic happening before our eyes.’”

This hit-and-miss process will improve as the technology gets better. DALL-E 2, which Waymark used to make The Frost, was released just a year ago. Video generation tools that generate short clips have only been around for a few months.  

The most revolutionary aspect of the technology is being able to generate new shots whenever you want them, says Rubin: “With 15 minutes of trial and error, you get that shot you wanted that fits perfectly into a sequence.” He remembers cutting the film together and needing particular shots, like a close-up of a boot on a mountainside. With DALL-E, he could just call it up. “It’s mind-blowing,” he says. “That’s when it started to be a real eye-opening experience as a filmmaker.”

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