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Researchers explore how AI can strengthen, not replace, human collaboration

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Researchers explore how AI can strengthen, not replace, human collaboration


Ph.D. student Allen Brown is among the Tepper School of Business researchers investigating how AI can be most useful in a team dynamic. Credit: Carnegie Mellon University

Researchers from Carnegie Mellon University’s Tepper School of Business are learning how AI can be used to support teamwork rather than replace teammates.

Anita Williams Woolley is a professor of organizational behavior. She researches , or how well teams perform together, and how artificial intelligence could change workforce dynamics. Now, Woolley and her colleagues are helping to figure out exactly where and how AI can play a positive role.

“I’m always interested in technology that can help us become a better version of ourselves individually,” Woolley said, “but also collectively, how can we change the way we think about and structure work to be more effective?”

Woolley collaborated with technologists and others in her field to develop Collective HUman-MAchine INtelligence (COHUMAIN), a framework that seeks to understand where AI fits within the established boundaries of organizational social psychology.

The researchers behind the 2023 publication of COHUMAIN caution against treating AI like any other teammate. Instead, they see it as a partner that works under human direction, with the potential to strengthen existing capabilities or relationships. “AI agents could create the glue that is missing because of how our work environments have changed, and ultimately improve our relationships with one another,” Woolley said.

The research that makes up the COHUMAIN architecture emphasizes that while AI integration into the workplace may take shape in ways we don’t yet understand, it won’t change the fundamental principles behind organizational intelligence, and likely can’t fill in all of the same roles as humans.

For instance, while AI might be great at summarizing a meeting, it’s still up to people to sense the mood in the room or pick up on the wider context of the discussion.

Organizations have the same needs as before, including a structure that allows them to tap into each human team member’s unique expertise. Woolley said that may best serve in “partnership” or facilitation roles rather than managerial ones, like a tool that can nudge peers to check in with each other, or provide the user with an alternate perspective..

Safety and risk

With so much collaboration happening through screens, AI tools might help teams strengthen connections between coworkers. But those same tools also raise questions about what’s being recorded and why.

“People have a lot of sensitivity, rightly so, around privacy. Often you have to give something up to get something, and that is true here,” Wooley said.

The level of risk that users feel, both socially and professionally, can change depending on how they interact with AI, according to Allen Brown, a Ph.D. student who works closely with Woolley. Brown is exploring where this tension shows up and how teams can work through it. His research focuses on how comfortable people feel taking risks or speaking up in a group.

Brown said that, in the best case, AI could help people feel more comfortable speaking up and sharing new ideas that might not be heard otherwise. “In a classroom, we can imagine someone saying, “Oh, I’m a little worried. I don’t know enough for my professor, or how my peers are going to judge my question,” or, “I think this is a good idea, but maybe it isn’t.” We don’t know until we put it out there.”

Since AI relies on a digital record that might or might not be kept permanently, one concern is that a human might not know which interactions with an AI will be used for evaluation.

“In our increasingly digitally mediated workspaces, so much of what we do is being tracked and documented,” Brown said. “There’s a digital record of things, and if I’m made aware that, ‘Oh, all of a sudden our conversation might be used for evaluation,’ we actually see this significant difference in interaction.”

Even when they thought their comments might be monitored or professionally judged, people still felt relatively secure talking to another human being. “We’re talking together. We’re working through something together, but we’re both people. There’s kind of this mutual assumption of risk,” he explained.

The study found that people felt more vulnerable when they thought an AI system was evaluating them. Brown wants to understand how AI can be used to create the opposite effect—one that builds confidence and trust.

“What are those contexts in which AI could be a partner, could be part of this conversational communicative practice within a pair of individuals at work, like a supervisor-supervisee relationship, or maybe within a team where they’re working through some topic that might have task conflict or relationship conflict?” Brown said. “How does AI help resolve the decision-making process or enhance the resolution so that people actually feel increased psychological safety?”

Creating a more trustworthy AI

At the individual level, Tepper researchers are also learning how the way in which AI explains its reasoning affects how people use and trust it. Zhaohui (Zoey) Jiang and Linda Argote are studying how people react to different kinds of AI systems—specifically, ones that explain their reasoning (transparent AI) versus ones that don’t explain how they make decisions (black box AI).

“We see a lot of people advocating for transparent AI,” Jiang said, “but our research reveals an advantage of keeping the AI a black box, especially for a high ability participant.”

One of the reasons for this, she explained, is overconfidence and distrust in skilled decision-makers.

“For a participant who is already doing a good job independently at the task, they are more prone to the well-documented tendency of AI aversion. They will penalize the AI’s mistake far more than the humans making the same mistake, including themselves,” Jiang said. “We find that this tendency is more salient if you tell them the inner workings of the AI, such as its logic or decision rules.”

People who struggle with decision-making actually improve their outcomes when using transparent AI models that show off a moderate amount of complexity in their . “We find that telling them how the AI is thinking about this problem is actually better for less-skilled users, because they can learn from AI decision-making rules to help improve their own future independent decision-making.”

While transparency is proving to have its own use cases and benefits, Jiang said the most surprising findings are around how people perceive black box models. “When we’re not telling these participants how the model arrived at its answer, participants judge the model as the most complex. Opacity seems to inflate the sense of sophistication, whereas transparency can make the very same system seem simpler and less ‘magical,'” she said.

Both kinds of models vary in their use cases. While it isn’t yet cost‑effective to tailor an AI to each human partner, future systems may be able to self-adapt their representation to help people make better decisions, she said.

“It can be dynamic in a way that it can recognize the decision-making inefficiencies of that particular individual that it is assigned to collaborate with, and maybe tweak itself so that it can help complement and offset some of the decision-making inefficiencies.”

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Just in Time for Spring, Don’t Miss These Electric Scooter Deals

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Just in Time for Spring, Don’t Miss These Electric Scooter Deals


The snow is melting, the days are getting longer, and I can almost smell the springtime ahead. Soon, we’ll be cruising around town on ebikes and electric scooters instead of burning fossil fuels. For now, the weather hasn’t quite caught up, which is great for markdowns. Many of the best electric scooters are still seeing significant discounts. If you’ve been thinking about buying one, now’s the best time: prices are low, and sunny commuting days are just ahead.

Gear editor Julian Chokkattu has spent five years testing more than 45 electric scooters. These are his top picks that are also on sale right now.

Apollo Go for $849 ($450 Off)

Photograph: Julian Chokkattu

This is Gear editor Julian Chokkattu’s favorite scooter. The riding experience is powerful and smooth, thanks to its dual 350-watt motors and solid front and rear suspensions. The speed maxes out at 28 miles per hour (mph), which doesn’t make it the fastest scooter on the market, but it has a good range. (Chokkattu is a very tall man and was able to travel 15 miles on a single charge at 15 mph.) Other Apollo features he appreciates: turn signals, a dot display, a bell, along with a headlight and an LED strip for extra visibility.

Apollo Phantom 2.0 for $2099 ($900 Off)

  • Photograph: Julian Chokkattu

  • Photograph: Julian Chokkattu

  • Photograph: Julian Chokkattu

The Apollo Phantom 2.0 maxes out at 44 mph, with plenty of power from its dual 1,750-watt motors. It’s a gorgeous scooter, designed with 11-inch self-healing tubeless tires and a dual-spring suspension system for a smooth riding experience. But with great power comes great weight. At 102 pounds, the Phantom 2.0 is the heaviest electric scooter Chokkattu has tested, so I would only recommend this purchase if you don’t live in a walkup and/or have a garage.

More Discounted Electric Scooters

Segway

Max G3

This is the best commuter scooter, with more power and range than the Apollo Go and a fast 3.5-hour recharge time.

Segway

Ninebot F3 Electric Scooter

The Segway F3 is designed with turn signals, a bell, a bright display, and a feature-rich app experience.

Niu KQi 300X

This is the best all-terrain scooter, with reliable suspension, dual disc brakes, and thick 10.5-inch tubeless tires.

Segway

E2 Pro

This is the best budget scooter, designed with a decent 350-watt motor, a max speed of 15 mph, a front drum brake, and a rear electronic brake.



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What’s an E-Bike? California Wants You to Know

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What’s an E-Bike? California Wants You to Know


A few months ago, a family came into Pasadena Cyclery in Pasadena, California, for a repair on what they thought was their teenager’s e-bike. “I can’t fix that here,’ Daniel Purnell, a store manager and technician, remembers telling them. “That’s a motorcycle.” The mother got upset. She didn’t realize that what she thought was an e-bike could go much faster, perhaps up to 55 miles per hour.

“There’s definitely an education problem,” Purnell says. In California, bike advocates are pushing a new bill designed to clear up that confusion around what counts as an electric bicycle—and what doesn’t.

It’s a tricky balance. On one hand, backers want to allow riders access to new, faster, and more affordable non-car transportation options, ones that don’t require licenses and are emission-free. On the other hand, people, and especially kids, seem to be getting hurt. E-bike-related injuries jumped more than 1,020 percent nationwide between 2020 and 2024, according to hospital data, though it’s not clear if the stats-keepers can routinely distinguish between e-bikes and their faster, “e-moto” cousins. (Moped and powered-assisted cycle injuries jumped 67 percent in that same period.)

“We’re overdue to have better e-bike regulation,” says California state senator Catherine Blakespear, a Democrat who sponsored the bill and represents parts of North County in San Diego. “This has been an ongoing and growing issue for years.”

Senate Bill 1167 would make it illegal for retailers to label higher-powered, electric-powered vehicles as e-bikes. It would clarify that e-bikes have fully operative pedals and electric motors that don’t exceed 750 watts, enough to hit top speeds between 20 and 28 mph.

“We’re not against these devices,” says Kendra Ramsey, the executive director of the California Bicycle Coalition, which represents riders and is promoting the legislation. “People think they’re e-bikes and they’re not really e-bikes.”

Bill backers say they hope the fix, if it passes, makes a difference, especially for teenagers, who love the freedom that electric motors give them but can get into trouble if something goes wrong at higher speeds. Kids 17 and younger accounted for 20 percent of US e-bike injuries from 2020 to 2024, about in line with the share of the total population. But headlines—and the laws that follow them—have focused on teen injuries and even deaths.

There are no national laws governing e-bike riding. But bike backers spent years moving between states to pass laws that put e-bikes into three classes: Class 1, which have pedal-assist that only works when they’re actually pedaled, and goes up to 20 mph; Class 2, which have throttles that work without pedaling but still only reach 20 mph; and Class 3, which use pedal-assist to move up to 28 mph. Plenty of states and cities restrict the most powerful Class 3 bikes to people older than 16. (In a complicated twist, some e-bikes have different “modes,” allowing riders to toggle between Class 2 and Class 3.)

Last year, researchers visited 19 San Francisco Bay Area middle and high schools and found that 88 percent of the electric two-wheeled devices parked there were so high-powered and high-speed that they didn’t comply with the three-class system at all.

E-bikes have clearly struck a chord with state policymakers: At least 10 bills introduced this year deal with e-bikes, according to Ramsey.

Some bike advocates believe injuries have less to do with e-bikes than “e-motos,” a category that’s less likely to appear in retail stores or the sort of social media ads attracting teens to the tech. These have more powerful motors and can travel in excess of 30 mph. Vehicles, like the Surron Ultra Bee, which can hit top speeds of 55 mph, or Tuttio ICT, which can hit 50, are often marketed by retailers as “electric bikes.” Because so many sales happen online, it can be hard for people, and especially parents, to know what they’re getting into.



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OpenAI Fires an Employee for Prediction Market Insider Trading

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OpenAI Fires an Employee for Prediction Market Insider Trading


OpenAI has fired an employee following an investigation into their activity on prediction market platforms including Polymarket, WIRED has learned.

OpenAI CEO of Applications, Fidji Simo, disclosed the termination in an internal message to employees earlier this year. The employee, she said, “used confidential OpenAI information in connection with external prediction markets (e.g. Polymarket).”

“Our policies prohibit employees from using confidential OpenAI information for personal gain, including in prediction markets,” says spokesperson Kayla Wood. OpenAI has not revealed the name of the employee or the specifics of their trades.

Evidence suggests that this was not an isolated event. Polymarket runs on the Polygon blockchain network, so its trading ledger is pseudonymous but traceable. According to an analysis by the financial data platform Unusual Whales, there have been clusters of activities, which the service flagged as suspicious, around OpenAI-themed events since March 2023.

Unusual Whales flagged 77 positions in 60 wallet addresses as suspected insider trades, looking at the age of the account, trading history, and significance of investment, among other factors. Suspicious trades hinged on the release dates of products like Sora, GPT-5, and the ChatGPT Browser, as well as CEO Sam Altman’s employment status. In November 2023, two days after Altman was dramatically ousted from the company, a new wallet placed a significant bet that he would return, netting over $16,000 in profits. The account never placed another bet.

The behavior fits into patterns typical of insider trades. “The tell is the clustering. In the 40 hours before OpenAI launched its browser, 13 brand-new wallets with zero trading history appeared on the site for the first time to collectively bet $309,486 on the right outcome,” says Unusual Whales CEO Matt Saincome. “When you see that many fresh wallets making the same bet at the same time, it raises a real question about whether the secret is getting out.”

Prediction markets have exploded in popularity in recent years. These platforms allow customers to buy “event contracts” on the outcomes of future events ranging from the winner of the Super Bowl to the daily price of Bitcoin to whether the United States will go to war with Iran. There are a wide array of markets tied to events in the technology sector; you can trade on what Nvidia’s quarterly earnings will be, or when Tesla will launch a new car, or which AI companies will IPO in 2026.

As the platforms have grown, so have concerns that they allow traders to profit from insider knowledge. “This prediction market world makes the Wild West look tame in comparison,” says Jeff Edelstein, a senior analyst at the betting news site InGame. “If there’s a market that exists where the answer is known, somebody’s going to trade on it.”

Earlier this week, Kalshi announced that it had reported several suspicious insider trading cases to the Commodity Futures Trading Commission, the government agency overseeing these markets. In one instance, an employee of the popular YouTuber Mr. Beast was suspended for two years and fined $20,000 for making trades related to the streamer’s activities; in another, the far-right political candidate Kyle Langford was banned from the platform for making a trade on his own campaign. The company also announced a number of initiatives to prevent insider trading and market manipulation.

While Kalshi has heavily promoted its crackdown on insider trading, Polymarket has stayed silent on the matter. The company did not return requests for comments.

In the past, major trades on technology-themed markets have sparked speculation that there are Big Tech employees profiting by using their insider knowledge to gain an edge. One notorious example is the so-called “Google whale,” a pseudonymous account on Polymarket that made over $1 million trading on Google-related events, including a market on who the most-searched person of the year would be in 2025. (It was the singer D4vd, who is best known for his connection to an ongoing murder investigation after a young fan’s remains were found in a vehicle registered to him.)



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