When writing program code, software developers often work in pairs—a practice that reduces errors and encourages knowledge sharing. Increasingly, AI assistants are now being used for this role.

But this shift in working practice isn’t without its drawbacks, as a new empirical study by computer scientists in Saarbrücken reveals. Developers tend to scrutinize AI-generated code less critically and they learn less from it. These findings will be presented at the 40th IEEE/ACM International Conference on Automated Software Engineering (ASE 2025) in Seoul.

When two software developers collaborate on a programming project—known in technical circles as pair programming—it tends to yield a significant improvement in the quality of the resulting software.

“Developers can often inspire one another and help avoid problematic solutions. They can also share their expertise, thus ensuring that more people in their organization are familiar with the codebase,” explains Sven Apel, professor of computer science at Saarland University.

Together with his team, Apel has examined whether this collaborative approach works equally well when one of the partners is an AI assistant. In the study, 19 students with programming experience were divided into pairs: Six worked with a human partner, while seven collaborated with an AI assistant. The methodology for measuring knowledge transfer was developed by Niklas Schneider as part of his bachelor’s thesis.

For the study, the researchers used GitHub Copilot, an AI-powered coding assistant introduced by Microsoft in 2021, which—like similar products from other companies—has now been widely adopted by software developers. These tools have significantly changed how software is written.

“It enables faster development and the generation of large volumes of code in a short time. But this also makes it easier for mistakes to creep in unnoticed, with consequences that may only surface later on,” says Apel. The team wanted to understand which aspects of human collaboration enhance programming and whether these can be replicated in human-AI pairings. Participants were tasked with developing algorithms and integrating them into a shared project environment.

“Knowledge transfer is a key part of pair programming,” Apel explains. “Developers will continuously discuss current problems and work together to find solutions. This does not involve simply asking and answering questions, it also means that the developers share effective programming strategies and volunteer their own insights.”

According to the study, such exchanges also occurred in the AI-assisted teams—but the interactions were less intense and covered a narrower range of topics.

“In many cases, the focus was solely on the code,” says Apel. “By contrast, human programmers working together were more likely to digress and engage in broader discussions and were less focused on the immediate task.”

One finding particularly surprised the research team: “The programmers who were working with an AI assistant were more likely to accept AI-generated suggestions without critical evaluation. They assumed the code would work as intended,” says Apel. “The human pairs, in contrast, were much more likely to ask critical questions and were more inclined to carefully examine each other’s contributions.”

He believes this tendency to trust AI more readily than human colleagues may extend to other domains as well, stating, “I think it has to do with a certain degree of complacency—a tendency to assume the AI’s output is probably good enough, even though we know AI assistants can also make mistakes.

Apel warns that this uncritical reliance on AI could lead to the accumulation of “technical debt,” which can be thought of as the hidden costs of the future work needed to correct these mistakes, thereby complicating the future development of the software.

For Apel, the study highlights the fact that AI assistants are not yet capable of replicating the richness of human collaboration in software development.

“They are certainly useful for simple, repetitive tasks,” says Apel. “But for more complex problems, knowledge exchange is essential—and that currently works best between humans, possibly with AI assistants as supporting tools.”

Apel emphasizes the need for further research into how humans and AI can collaborate effectively while still retaining the kind of critical eye that characterizes human collaboration.

A fermentation byproduct might help to solve two major global challenges: world hunger and the environmental impact of fast fashion. The leftover yeast from brewing beer, wine or even to make some pharmaceuticals can be repurposed to produce high-performance fibers stronger than natural fibers with significantly less environmental impact, according to a new study led by researchers at Penn State and published in the Proceedings of the National Academy of Sciences.

The yeast biomass—composed of proteins, fatty molecules called lipids and sugars—left over from alcohol and pharmaceutical production is regarded as waste, but lead author Melik Demirel, Pearce Professor of Engineering and Huck Chair in Biomimetic Materials at Penn State, said his team realized they could repurpose the material to make fibers using a previously developed process.

The researchers successfully achieved pilot-scale production of the fiber—producing more than 1,000 pounds—in a factory in Germany, with continuous and batch production for more than 100 hours per run of fiber spinning.

They also used data collected during this production for a lifecycle assessment, which assessed the needs and impact of the product from obtaining the raw fermentation byproduct through its life to disposal and its cost, and to evaluate the economic viability of the technology. The analysis predicted the cost, water use, production output, greenhouse gas emissions and more at every stage.

Ultimately, the researchers found that the commercial-scale production of the fermentation-based fiber could compete with wool and other fibers at scale but with considerably fewer resources, including far less land—even when accounting for the land needed to grow the crops used in the fermentation processes that eventually produce the yeast biomass.

“Just as hunter-gatherers domesticated sheep for wool 11,000 years ago, we’re domesticating yeast for a fiber that could shift the agricultural lens to focus far more resources to food crops,” said Demirel, who is also affiliated with the Materials Research Institute and the Institute of Energy and the Environment, both at Penn State.

“We successfully demonstrated that this material can be made cheaply—for $6 or less per kilogram, which is about 2.2 pounds, compared to wool’s $10 to $12 per kilogram—with significantly less water and land but improved performance compared to any other natural or processed fibers, while also nearly eliminating greenhouse gas emissions. The saved resources could be applied elsewhere, like repurposing land to grow food crops.”

Waste not, want not

Demirel’s team has spent over a decade developing a process to produce a fiber from proteins. Inspired by nature, the fiber is durable and free of the chemicals other fibers can leave in the environment for years.

“We can pull the proteins as an aggregate—mimicking naturally occurring protein accumulations called amyloids—from the yeast, dissolve the resulting pulp in a solution, and push that through a device called a spinneret that uses tiny spigots to make continuous fibers,” Demirel said, explaining the fibers are then washed, dried and spun into yarn that can then be woven into fabric for clothes.

He also noted that the fibers are biodegradable, meaning they would break down after disposal, unlike the millions of tons of polyester clothing discarded every year that pollutes the planet.

“The key is the solution used to dissolve the pulp. This solvent is the same one used to produce Lyocell, the fiber derived from cellulose, or wood pulp. We can recover 99.6% of the solvent used to reuse it in future production cycles.”

The idea of using proteins to make fiber is not new, according to Demirel, who pointed to Lanital as an example. The material was developed in the 1930s from milk protein, but it fell out of fashion due to low strength with the advent of polyester.

“The issue has always been performance and cost,” Demirel said, noting the mid-20th century also saw the invention of fibers made from peanut proteins and from corn proteins before cheap and stronger polyester ultimately reigned.

Freeing land from fiber to produce food

Beyond producing a quality fiber, Demirel said, the study also indicated the fiber’s potential on a commercial scale. The models rolled their pilot-scale findings into simulated scenarios of commercial production. For comparison, about 55,000 pounds of cotton are produced globally every year and just 2.2 pounds—about what it takes to make one T-shirt and one pair of jeans—requires up to 2,642 gallons of water. Raw cotton is relatively cheap, Demirel said, but the environmental cost is staggering.

“Cotton crops also use about 88 million acres, of farmable land around the world—just under 40% of that is in India, which ranks as ‘serious’ on the Global Hunger Index,” Demirel said.

“Imagine if instead of growing cotton, that land, water, resources and energy could be used to produce crops that could feed people. It’s not quite as simple as that, but this analysis demonstrated that biomanufactured fibers require significantly less land, water and other resources to produce, so it’s feasible to picture how shifting from crop-based fibers could free up a significant amount of land for food production.”

In 2024, 733 million people—about one in 12—around the world faced food insecurity, a continued trend that has led the United Nations to declare a goal of Zero Hunger to eliminate this issue by 2030. One potential solution may be to free land currently used to grow fiber crops to produce more food crops, according to Demirel.

Current production methods not only use significant resources, he said, but more than 66% of clothing produced annually in the U.S. alone ends up in landfills. Demirel’s approach offers a solution for both problems, he said.

“By leveraging biomanufacturing, we can produce sustainable, high-performance fibers that do not compete with food crops for land, water or nutrients,” Demirel said. “Adopting biomanufacturing-based protein fibers would mark a significant advancement towards a future where fiber needs are fulfilled without compromising the planet’s capacity to nourish its growing population. We can make significant strides towards achieving the Zero Hunger goal, ensuring everyone can access nutritious food while promoting sustainable development goals.”

Future of fiber

Demirel said the team plans to further investigate the viability of fermentation-based fibers at a commercial scale.

The team includes Benjamin Allen, chief technology officer, and Balijit Ghotra, Tandem Repeat Technologies, Inc., the spin-off company founded by Demirel and Allen based on this fiber production approach. The work has a patent pending, and the Penn State Office of Technology Transfer licensed the technology to Tandem Repeat Technologies. Other co-authors include Birgit Kosan, Philipp Köhler, Marcus Krieg, Christoph Kindler and Michael Sturm, all with the Thüringisches Institut für Textil- und Kunststoff-Forschung (TITK) e. V. in Germany.

“In my lab at Penn State, we demonstrated we could physically make the fiber,” Demirel said. “In this pilot production at the factory, together with Tandem and TITK, we demonstrated we could make the fiber a contender in the global fiber market. Sonachic, an online brand formed by Tandem Repeat, makes this a reality. Next, we will bring it to mass market.”

Changpeng Zhao, the multibillionaire founder of crypto exchange Binance, spent four months last year locked in a federal prison. After US president Donald Trump pardoned Zhao in October, the government has recast him as a martyr.

Zhao, who goes by CZ, pleaded guilty in November 2023 to failing to maintain an effective anti-money-laundering program at Binance. In parallel, Binance admitted to violating US sanctions and settled with financial regulators, which accused the company of failing to report suspicious transactions involving terror groups, child exploitation networks, and cybercriminals, among other violations. In a particularly incriminating exchange detailed in court documents, one Binance employee said to a colleague, “We see the bad, but we close 2 eyes.”

As part of their respective settlement deals, Zhao agreed to forfeit his role as Binance CEO, and Binance agreed to leave the US, accept supervision by a US-appointed compliance monitor, and pay a record $4.3 billion penalty.

Less than two years later, the narrative has flipped. On October 23, Trump struck the charges from Zhao’s criminal record. The Binance founder was a victim of the “Biden administration’s war on crypto,” a White House spokesperson declared.

The decision to pardon Zhao will reverberate throughout the US crypto exchange market, which Binance could seek to reenter, legal experts claim. It may also come with long-term political consequences for the crypto industry after Trump’s presidency ends.

Whether Zhao’s pardon was justified has been hotly disputed, particularly in light of connections between Binance and World Liberty Financial, a crypto business founded by Trump and his sons. (Through a corporate entity, the Trump family owns a 38 percent stake in World Liberty Financial’s parent company.) In May, Binance agreed to receive a $2 billion investment denominated in USD1, a coin issued by World Liberty Financial, which could earn tens of millions of dollars from the arrangement. In July, Bloomberg reported that Binance had developed the codebase for USD1.

Remarkably, Trump claims to know very little about Zhao. “OK, are you ready? I don’t know who he is,” Trump told 60 Minutes in an interview that aired on November 2. “I can only tell you this. My sons are into [crypto],” he said later in the interview.

Zhao’s legal representatives and industry allies have defended the pardon as a rightful corrective. “CZ is the first and only known first-time offender in US history to receive a prison sentence for this single, non-fraud-related charge,” wrote Teresa Goody Guillén, partner at law firm Baker & Hostetler, which represents Zhao, in a post on X.