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It was a stranger who first brought home for me how big this year’s vibe shift was going to be. As we waited for a stuck elevator together in March, she told me she had just used ChatGPT to help her write a report for her marketing job. She hated writing reports because she didn’t think she was very good at it. But this time her manager had praised her. Did it feel like cheating? Hell no, she said. You do what you can to keep up.

That stranger’s experience of generative AI is one among millions. People in the street (and in elevators) are now figuring out what this radical new technology is for and wondering what it can do for them. In many ways the buzz around generative AI right now recalls the early days of the internet: there’s a sense of excitement and expectancy—and a feeling that we’re making it up as we go.

That is to say, we’re in the dot-com boom, circa 2000. Many companies will go bust. It may take years before we see this era’s Facebook (now Meta), Twitter (now X), or TikTok emerge. “People are reluctant to imagine what could be the future in 10 years, because no one wants to look foolish,” says Alison Smith, head of generative AI at Booz Allen Hamilton, a technology consulting firm. “But I think it’s going to be something wildly beyond our expectations.”

“Here’s the catch: it is impossible to know all the ways a technology will be misused until it is used.”

The internet changed everything—how we work and play, how we spend time with friends and family, how we learn, how we consume, how we fall in love, and so much more. But it also brought us cyber-­bullying, revenge porn, and troll factories. It facilitated genocide, fueled mental-health crises, and made surveillance capitalism—with its addictive algorithms and predatory advertising—the dominant market force of our time. These downsides became clear only when people started using it in vast numbers and killer apps like social media arrived.

Generative AI is likely to be the same. With the infrastructure in place—the base generative models from OpenAI, Google, Meta, and a handful of others—people other than the ones who built it will start using and misusing it in ways its makers never dreamed of. “We’re not going to fully understand the potential and the risks without having individual users really play around with it,” says Smith.

Generative AI was trained on the internet and so has inherited many of its unsolved issues, including those related to bias, misinformation, copyright infringement, human rights abuses, and all-round economic upheaval. But we’re not going in blind.

Here are six unresolved questions to bear in mind as we watch the generative-AI revolution unfold. This time around, we have a chance to do better.

1

Will we ever mitigate the bias problem?

Bias has become a byword for AI-related harms, for good reason. Real-world data, especially text and images scraped from the internet, is riddled with it, from gender stereotypes to racial discrimination. Models trained on that data encode those biases and then reinforce them wherever they are used.

Chatbots and image generators tend to portray engineers as white and male and nurses as white and female. Black people risk being misidentified by police departments’ facial recognition programs, leading to wrongful arrest. Hiring algorithms favor men over women, entrenching a bias they were sometimes brought in to address.

Without new data sets or a new way to train models (both of which could take years of work), the root cause of the bias problem is here to stay. But that hasn’t stopped it from being a hot topic of research. OpenAI has worked to make its large language models less biased using techniques such as reinforcement learning from human feedback (RLHF). This steers the output of a model toward the kind of text that human testers say they prefer.

8bit pixel art of a brown-skinned person's head in profile
SELMAN DESIGN

Other techniques involve using synthetic data sets. For example, Runway, a

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By: Will Douglas Heaven
Title: These six questions will dictate the future of generative AI
Sourced From: www.technologyreview.com/2023/12/19/1084505/generative-ai-artificial-intelligence-bias-jobs-copyright-misinformation/
Published Date: Tue, 19 Dec 2023 10:00:00 +0000

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Is this the end of animal testing?

In a clean room in his lab, Sean Moore peers through a microscope at a bit of intestine, its dark squiggles and rounded structures standing out against a light gray background. This sample is not part of an actual intestine; rather, it’s human intestinal cells on a tiny plastic rectangle, one of 24 so-called “organs on chips” his lab bought three years ago.

Moore, a pediatric gastroenterologist at the University of Virginia School of Medicine, hopes the chips will offer answers to a particularly thorny research problem. He studies rotavirus, a common infection that causes severe diarrhea, vomiting, dehydration, and even death in young children. In the US and other rich nations, up to 98% of the children who are vaccinated against rotavirus develop lifelong immunity. But in low-income countries, only about a third of vaccinated children become immune. Moore wants to know why.

His lab uses mice for some protocols, but animal studies are notoriously bad at identifying human treatments. Around 95% of the drugs developed through animal research fail in people. Researchers have documented this translation gap since at least 1962. “All these pharmaceutical companies know the animal models stink,” says Don Ingber, founder of the Wyss Institute for Biologically Inspired Engineering at Harvard and a leading advocate for organs on chips. “The FDA knows they stink.”

But until recently there was no other option. Research questions like Moore’s can’t ethically or practically be addressed with a randomized, double-blinded study in humans. Now these organs on chips, also known as microphysiological systems, may offer a truly viable alternative. They look remarkably prosaic: flexible polymer rectangles about the size of a thumb drive. In reality they’re triumphs of bioengineering, intricate constructions furrowed with tiny channels that are lined with living human tissues. These tissues expand and contract with the flow of fluid and air, mimicking key organ functions like breathing, blood flow, and peristalsis, the muscular contractions of the digestive system.

More than 60 companies now produce organs on chips commercially, focusing on five major organs: liver, kidney, lung, intestines, and brain. They’re already being used to understand diseases, discover and test new drugs, and explore personalized approaches to treatment.

As they continue to be refined, they could solve one of the biggest problems in medicine today. “You need to do three things when you’re making a drug,” says Lorna Ewart, a pharmacologist and chief scientific officer of Emulate, a biotech company based in Boston. “You need to show it’s safe. You need to show it works. You need to be able to make it.”

All new compounds have to pass through a preclinical phase, where they’re tested for safety and effectiveness before moving to clinical trials in humans. Until recently, those tests had to run in at least two animal species—usually rats and dogs—before the drugs were tried on people.

But in December 2022, President Biden signed the FDA Modernization Act, which amended the original FDA Act of 1938. With a few small word changes, the act opened the door for non-animal-based testing in preclinical trials. Anything that makes it faster and easier for pharmaceutical companies to identify safe and effective drugs means better, potentially cheaper treatments for all of us.

Moore, for one, is banking on it, hoping the chips help him and his colleagues shed light on the rotavirus vaccine responses that confound them. “If you could figure out the answer,” he says, “you could save a lot of kids’ lives.”

While many teams have worked on organ chips over the last 30 years, the OG in the field is generally acknowledged to be Michael Shuler, a professor emeritus of chemical engineering at Cornell. In the 1980s, Shuler was a math and engineering guy who imagined an “animal on a chip,” a cell culture base seeded with a variety of human cells that could be used for testing drugs. He wanted to position a handful of different organ cells on the same chip, linked to one another, which could mimic the chemical communication between organs and the way drugs move through the body. “This was science fiction,” says Gordana Vunjak-Novakovic, a professor of biomedical engineering at Columbia University whose lab works with cardiac tissue on chips. “There was no body on a chip. There is still no body on a chip. God knows if there will ever be a body on a chip.”

Shuler had hoped to develop a computer model of a multi-organ system, but there were too many unknowns. The living cell culture system he dreamed up was his bid to fill in the blanks. For a while he played with the concept, but the materials simply weren’t good enough to build what he imagined.

“You can force mice to menstruate, but it’s not really menstruation. You need the human being.”

Linda Griffith, founding

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By: Harriet Brown
Title: Is this the end of animal testing?
Sourced From: www.technologyreview.com/2024/06/21/1093419/animal-testing-organ-on-chip-research/
Published Date: Fri, 21 Jun 2024 09:00:00 +0000

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The Download: replacing animal testing, and underwater drones

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This is today’s edition of The Download our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

Is this the end of animal testing?

Animal studies are notoriously bad at identifying human treatments. Around 95% of the drugs developed through animal research fail in people, but until recently there was no other option.

Now organs on chips, also known as microphysiological systems, may offer a truly viable alternative. They’re triumphs of bioengineering, intricate constructions furrowed with tiny channels that are lined with living human tissues that expand and contract with the flow of fluid and air, mimicking key organ functions like breathing, blood flow, and peristalsis, the muscular contractions of the digestive system.

It’s only early days, but if they work as hoped, organs on chips could solve one of the biggest problems in medicine today. Read the full story.

—Harriet Brown

This story is from the forthcoming print issue of MIT Technology Review, which explores the theme of Play. It’s set to go live on Wednesday June 26, so if you don’t already, subscribe now to get a copy when it lands.

How underwater drones could shape a potential Taiwan-China conflict

A potential future conflict between Taiwan and China would be shaped by novel methods of drone warfare involving advanced underwater drones and increased levels of autonomy, according to a new war-gaming experiment by the think tank Center for a New American Security (CNAS).

Since Russia invaded Ukraine in 2022, drones have been aiding in what military experts describe as the first three steps of the “kill chain”—finding, targeting, and tracking a target—as well as in delivering explosives. Drones like these would be far less useful in a possible invasion of Taiwan. Instead, a conflict with Taiwan would likely make use of undersea and maritime drones to scout for submarines. Read the full story.

—James O’Donnell

Should social media come with a health warning?

Earlier this week, the US surgeon general, also known as the “nation’s doctor,” authored an article making the case that health warnings should accompany social media. The goal: to protect teenagers from its harmful effects.

But the relationship between this technology and health isn’t black and white. Social media can affect users in different ways—often positively. So let’s take a closer look at the concerns, the evidence behind them, and how best to tackle them. Read the full story.

—Jessica Hamzelou

This story is from The Checkup, our weekly health and biotech newsletter. Sign up to receive it in your inbox every Thursday.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 The US government is banning Kaspersky’s antivirus software  
Officials claim the firm’s ties with Russia mean it poses a major security risk. (Reuters)
It’ll ban sales of software from 20 July, and updates from 29 September. (TechCrunch)
The ban follows a two-year probe into Kaspersky. (The Verge)

2 Americans are paying way too much for prescription drugs
And shadowy pharmacy benefit managers are partly to blame. (NYT $)
The UK has been hit by a drug shortage, too. (The Guardian)

3 How a secretive ocean alkalinity project in the UK spiraled into disaster
It raises important questions: who gets to decide where trials can take place? (Hakai Magazine)
This town’s mining battle reveals the contentious path to a cleaner future. (MIT Technology Review)

4 Car dealers have been locked out of their selling systems
Businesses have had to resort to paper and pen to close their sales. (WSJ $)
It’s unlikely to be resolved before the weekend. (Bloomberg $)

5 Make way for much less large language models
They’re a fraction of the size, but just as effective. (IEEE Spectrum)
Large language models can do jaw-dropping things. But nobody knows exactly why. (MIT Technology Review)

6 Inside the growing cottage industry of wildfire mitigation
In Boulder, Colorado, the solutions are increasingly experimental. (Bloomberg $)+ The quest to build wildfire-resistant homes. (MIT Technology Review)

7 Zimbabwe’s traditional healers are peddling financial advice on TikTok
But spirituality and tech are uneasy bedfellows. (Rest of World)

8 How to avoid falling for scams on Amazon
Read those product reviews super carefully. (Wired $)

9 Tech companies are still interested in making smart glasses
👓
Despite Meta being the sole big player. (The Information $)

10 The internet looked very different 30 years ago
A whole lot more

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By: Rhiannon Williams
Title: The Download: replacing animal testing, and underwater drones
Sourced From: www.technologyreview.com/2024/06/21/1094135/the-download-replacing-animal-testing-and-underwater-drones/
Published Date: Fri, 21 Jun 2024 12:10:00 +0000

Did you miss our previous article…
https://mansbrand.com/how-generative-ai-could-reinvent-what-it-means-to-play/

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How generative AI could reinvent what it means to play

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First, a confession. I only got into playing video games a little over a year ago (I know, I know). A Christmas gift of an Xbox Series S “for the kids” dragged me—pretty easily, it turns out—into the world of late-night gaming sessions. I was immediately attracted to open-world games, in which you’re free to explore a vast simulated world and choose what challenges to accept. Red Dead Redemption 2 (RDR2), an open-world game set in the Wild West, blew my mind. I rode my horse through sleepy towns, drank in the saloon, visited a vaudeville theater, and fought off bounty hunters. One day I simply set up camp on a remote hilltop to make coffee and gaze down at the misty valley below me.

To make them feel alive, open-world games are inhabited by vast crowds of computer-controlled characters. These animated people—called NPCs, for “nonplayer characters”—populate the bars, city streets, or space ports of games. They make these virtual worlds feel lived in and full. Often—but not always—you can talk to them.

a man leads his horse through mountainous terrain toward a sunrise in Red Dead Redemption 2

a scene of gunfighters in Red Dead Redemption 2
In open-world games like Red Dead Redemption 2, players can choose diverse interactions within the same simulated experience.

After a while, however, the repetitive chitchat (or threats) of a passing stranger forces you to bump up against the truth: This is just a game. It’s still fun—I had a whale of a time, honestly, looting stagecoaches, fighting in bar brawls, and stalking deer through rainy woods—but the illusion starts to weaken when you poke at it. It’s only natural. Video games are carefully crafted objects, part of a multibillion-dollar industry, that are designed to be consumed. You play them, you loot a few stagecoaches, you finish, you move on.

It may not always be like that. Just as it is upending other industries, generative AI is opening the door to entirely new kinds of in-game interactions that are open-ended, creative, and unexpected. The game may not always have to end.

Startups employing generative-AI models, like ChatGPT, are using them to create characters that don’t rely on scripts but, instead, converse with you freely. Others are experimenting with NPCs who appear to have entire interior worlds, and who can continue to play even when you, the player, are not around to watch. Eventually, generative AI could create game experiences that are infinitely detailed, twisting and changing every time you experience them.

The field is still very new, but it’s extremely hot. In 2022 the venture firm Andreessen Horowitz launched Games Fund, a $600 million fund dedicated to gaming startups. A huge number of these are planning to use AI in gaming. And the firm, also known as A16Z, has now invested in two studios that are aiming to create their own versions of AI NPCs. A second $600 million round was announced in April 2024.

Early experimental demos of these experiences are already popping up, and it may not be long before they appear in full games like RDR2. But some in the industry believe this development will not just make future open-world games incredibly immersive; it could change what kinds of game worlds or experiences are even possible. Ultimately, it could change what it means to play.

“What comes after the video game? You know what I mean?” says Frank Lantz, a game designer and director of the NYU Game Center. “Maybe we’re on the threshold of a new kind of game.”

These guys just won’t shut up

The way video games are made hasn’t changed much over the years.

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By: Niall Firth
Title: How generative AI could reinvent what it means to play
Sourced From: www.technologyreview.com/2024/06/20/1093428/generative-ai-reinventing-video-games-immersive-npcs/
Published Date: Thu, 20 Jun 2024 09:00:00 +0000

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