Aurelia Butler

With over 75% of professionals using AI in their daily work, writing and editing messages with tools like ChatGPT, Gemini, Copilot or Claude has become a commonplace practice. While generative AI tools are seen to make writing easier, are they effective for communicating between managers and employees?
A new study of 1,100 professionals reveals a critical paradox in workplace communications: AI tools can make managers’ emails more professional, but regular use can undermine trust between them and their employees.
“We see a tension between perceptions of message quality and perceptions of the sender,” said Anthony Coman, Ph.D., a researcher at the University of Florida’s Warrington College of Business and study co-author. “Despite positive impressions of professionalism in AI-assisted writing, managers who use AI for routine communication tasks put their trustworthiness at risk when using medium- to high-levels of AI assistance.”
In the study published in the International Journal of Business Communication, Coman and his co-author, Peter Cardon, Ph.D., of the University of Southern California, surveyed professionals about how they viewed emails that they were told were written with low, medium and high AI assistance. Survey participants were asked to evaluate different AI-written versions of a congratulatory message on both their perception of the message content and their perception of the sender.
While AI-assisted writing was generally seen as efficient, effective, and professional, Coman and Cardon found a “perception gap” in messages that were written by managers versus those written by employees.
“When people evaluate their own use of AI, they tend to rate their use similarly across low, medium and high levels of assistance,” Coman explained. “However, when rating other’s use, magnitude becomes important. Overall, professionals view their own AI use leniently, yet they are more skeptical of the same levels of assistance when used by supervisors.”
While low levels of AI help, like grammar or editing, were generally acceptable, higher levels of assistance triggered negative perceptions. The perception gap is especially significant when employees perceive higher levels of AI writing, bringing into question the authorship, integrity, caring and competency of their manager.

The impact on trust was substantial: Only 40% to 52% of employees viewed supervisors as sincere when they used high levels of AI, compared to 83% for low-assistance messages. Similarly, while 95% found low-AI supervisor messages professional, this dropped to 69-73% when supervisors relied heavily on AI tools.
The findings reveal employees can often detect AI-generated content and interpret its use as laziness or lack of caring. When supervisors rely heavily on AI for messages like team congratulations or motivational communications, employees perceive them as less sincere and question their leadership abilities.
“In some cases, AI-assisted writing can undermine perceptions of traits linked to a supervisor’s trustworthiness,” Coman noted, specifically citing impacts on perceived ability and integrity, both key components of cognitive-based trust.
The study suggests managers should carefully consider message type, level of AI assistance and relational context before using AI in their writing. While AI may be appropriate and professionally received for informational or routine communications, like meeting reminders or factual announcements, relationship-oriented messages requiring empathy, praise, congratulations, motivation or personal feedback are better handled with minimal technological intervention. More

The efficiency of quantum computers, sensors and other applications often relies on the properties of electrons, including how they are spinning. One of the most accurate systems for high performance quantum applications relies on tapping into the spin properties of electrons of atoms trapped in a gas, but these systems are difficult to scale up for use in larger quantum devices like quantum computers. Now, a team of researchers from Penn State and Colorado State has demonstrated how a gold cluster can mimic these gaseous, trapped atoms, allowing scientists to take advantage of these spin properties in a system that can be easily scaled up.
“For the first time, we show that gold nanoclusters have the same key spin properties as the current state-of-the-art methods for quantum information systems,” said Ken Knappenberger, department head and professor of chemistry in the Penn State Eberly College of Science and leader of the research team. “Excitingly, we can also manipulate an important property called spin polarization in these clusters, which is usually fixed in a material. These clusters can be easily synthesized in relatively large quantities, making this work a promising proof-of-concept that gold clusters could be used to support a variety of quantum applications.”
Two papers describing the gold clusters and confirming their spin properties appeared in ACS Central Science, ACS Central Science and The Journal of Physical Chemistry Letters.
“An electron’s spin not only influences important chemical reactions, but also quantum applications like computation and sensing,” said Nate Smith, graduate student in chemistry in the Penn State Eberly College of Science and first author of one of the papers. “The direction an electron spins and its alignment with respect to other electrons in the system can directly impact the accuracy and longevity of quantum information systems.”
Much like the Earth spins around its axis, which is tilted with respect to the sun, an electron can spin around its axis, which can be tilted with respect to its nucleus. But unlike Earth, an electron can spin clockwise or counterclockwise. When many electrons in a material are spinning in the same direction and their tilts are aligned, the electrons are considered correlated, and the material is said to have a high degree of spin polarization.
“Materials with electrons that are highly correlated, with a high degree of spin polarization, can maintain this correlation for a much longer time, and thus remain accurate for much longer,” Smith said.
The current state-of-the-art system for high accuracy and low error in quantum information systems involve trapped atomic ions — atoms with an electric charge — in a gaseous state. This system allows electrons to be excited to different energy levels, called Rydberg states, which have very specific spin polarizations that can last for a long period of time. It also allows for the superposition of electrons, with electrons existing in multiple states simultaneously until they are measured, which is a key property for quantum systems.

“These trapped gaseous ions are by nature dilute, which makes them very difficult to scale up,” Knappenberger said. “The condensed phase required for a solid material, by definition, packs atoms together, losing that dilute nature. So, scaling up provides all the right electronic ingredients, but these systems become very sensitive to interference from the environment. The environment basically scrambles all the information that you encoded into the system, so the rate of error becomes very high. In this study, we found that gold clusters can mimic all the best properties of the trapped gaseous ions with the benefit of scalability.”
Scientists have heavily studied gold nanostructures for their potential use in optical technology, sensing, therapeutics and to speed up chemical reactions, but less is known about their magnetic and spin-dependent properties. In the current studies, the researchers specifically explored monolayer-protected clusters, which have a core of gold and are surrounded by other molecules called ligands. The researchers can precisely control the construction of these clusters and can synthesize relatively large amounts at one time.
“These clusters are referred to as super atoms, because their electronic character is like that of an atom, and now we know their spin properties are also similar,” Smith said. “We identified 19 distinguishable and unique Rydberg-like spin-polarized states that mimic the super-positions that we could do in the trapped, gas-phase dilute ions. This means the clusters have the key properties needed to carry out spin-based operations.”
The researchers determined the spin polarization of the gold clusters using a similar method used with traditional atoms. While one type of gold cluster had 7% spin polarization, a cluster with different a ligand approached 40% spin polarization, which Knappenberger said is competitive with some of the leading two-dimensional quantum materials.
“This tells us that the spin properties of the electron are intimately related to the vibrations of the ligands,” Knappenberger said. “Traditionally, quantum materials have a fixed value of spin polarization that cannot be significantly changed, but our results suggest we can modify the ligand of these gold clusters to tune this property widely.”
The research team plans to explore how different structures within the ligands impact spin polarization and how they could be manipulated to fine tune spin properties.
“The quantum field is generally dominated by researchers in physics and materials science, and here we see the opportunity for chemists to use our synthesis skills to design materials with tunable results,” Knappenberger said. “This is a new frontier in quantum information science.”
In addition to Smith and Knappenberger, the research team includes Juniper Foxley, graduate student in chemistry at Penn State; Patrick Herbert, who earned a doctoral degree in chemistry at Penn State in 2019; Jane Knappenberger, researcher in the Penn State Eberly College of Science; as well as Marcus Tofanelli and Christopher Ackerson at Colorado State
Funding from the Air Force Office of Scientific Research and the U.S. National Science Foundation supported this research. More

In medicine and biotechnology, the ability to evolve proteins with new or improved functions is crucial, but current methods are often slow and laborious. Now, Scripps Research scientists have developed a synthetic biology platform that accelerates evolution itself — enabling researchers to evolve proteins with useful, new properties thousands of times faster than nature. The system, named T7-ORACLE, was described in Science on August 7, 2025, and represents a breakthrough in how researchers can engineer therapeutic proteins for cancer, neurodegeneration and essentially any other disease area.
“This is like giving evolution a fast-forward button,” says co-senior author Pete Schultz, the President and CEO of Scripps Research, where he also holds the L.S. “Sam” Skaggs Presidential Chair. “You can now evolve proteins continuously and precisely inside cells without damaging the cell’s genome or requiring labor-intensive steps.”
Directed evolution is a laboratory process that involves introducing mutations and selecting variants with improved function over multiple cycles. It’s used to tailor proteins with desired properties, such as highly selective, high-affinity antibodies, enzymes with new specificities or catalytic properties, or to investigate the emergence of resistance mutations in drug targets. However, traditional methods often require repeated rounds of DNA manipulation and testing with each round taking a week or more. Systems for continuous evolution — where proteins evolve inside living cells without manual intervention — aim to streamline this process by enabling simultaneous mutation and selection with each round of cell division (roughly 20 minutes for bacteria). But existing approaches have been limited by technical complexity or modest mutation rates.
T7-ORACLE circumvents these bottlenecks by engineering E. coli bacteria — a standard model organism in molecular biology — to host a second, artificial DNA replication system derived from bacteriophage T7, a virus that infects bacteria and has been widely studied for its simple, efficient replication system. T7-ORACLE enables continuous hypermutation and accelerated evolution of biomacromolecules, and is designed to be broadly applicable to many protein targets and biological challenges. Conceptually, T7-ORACLE builds on and extends efforts on existing orthogonal replication systems — meaning they operate separately from the cell’s own machinery — such as OrthoRep in Saccharomyces cerevisiae (baker’s yeast) and EcORep in E. coli. In comparison to these systems, T7-ORACLE benefits from the combination of high mutagenesis, fast growth, high transformation efficiency, and the ease with which both the E. coli host and the circular replicon plasmid can be integrated into standard molecular biology workflows.
The T-7 ORACLE orthogonal system targets only plasmid DNA (small, circular pieces of genetic material), leaving the cell’s host genome untouched. By engineering T7 DNA polymerase (a viral enzyme that replicates DNA) to be error-prone, the researchers introduced mutations into target genes at a rate 100,000 times higher than normal without damaging the host cells.
“This system represents a major advance in continuous evolution,” says co-senior author Christian Diercks, an assistant professor of chemistry at Scripps Research. “Instead of one round of evolution per week, you get a round each time the cell divides — so it really accelerates the process.”
To demonstrate the power of T7-ORACLE, the research team inserted a common antibiotic resistance gene, TEM-1 β-lactamase, into the system and exposed the E. coli cells to escalating doses of various antibiotics. In less than a week, the system evolved versions of the enzyme that could resist antibiotic levels up to 5,000 times higher than the original. This proof-of-concept demonstrated not only T7-ORACLE’s speed and precision, but also its real-world relevance by replicating how resistance develops in response to antibiotics.

“The surprising part was how closely the mutations we saw matched real-world resistance mutations found in clinical settings,” notes Diercks. “In some cases, we saw new combinations that worked even better than those you would see in a clinic.”
But Diercks emphasizes that the study isn’t focused on antibiotic resistance per se.
“This isn’t a paper about TEM-1 β-lactamase,” he explains. “That gene was just a well-characterized benchmark to show how the system works. What matters is that we can now evolve virtually any protein, like cancer drug targets and therapeutic enzymes, in days instead of months.”
The broader potential of T7-ORACLE lies in its adaptability as a platform for protein engineering. Although the system is built into E. coli, the bacterium serves primarily as a vessel for continuous evolution. Scientists can insert genes from humans, viruses or other sources into plasmids, which are then introduced into E. coli cells. T7-ORACLE mutates these genes, generating variant proteins that can be screened or selected for improved function. Because E. coli is easy to grow and widely used in labs, it provides a convenient, scalable system for evolving virtually any protein of interest.
This could help scientists more rapidly evolve antibodies to target specific cancers, evolve more effective therapeutic enzymes, and design proteases that target proteins involved in cancer and neurodegenerative disease.
“What’s exciting is that it’s not limited to one disease or one kind of protein,” says Diercks. “Because the system is customizable, you can drop in any gene and evolve it toward whatever function you need.”
Moreover, T7-ORACLE works with standard E. coli cultures and widely used lab workflows, avoiding the complex protocols required by other continuous evolution systems.

“The main thing that sets this apart is how easy it is to implement,” adds Diercks. “There’s no specialized equipment or expertise required. If you already work with E. coli, you can probably use this system with minimal adjustments.”
T7-ORACLE reflects Schultz’s broader goal: to rebuild key biological processes — such as DNA replication, RNA transcription and protein translation — so they function independently of the host cell. This separation allows scientists to reprogram these processes without disrupting normal cellular activity. By decoupling fundamental processes from the genome, tools like T7-ORACLE help advance synthetic biology.
“In the future, we’re interested in using this system to evolve polymerases that can replicate entirely unnatural nucleic acids: synthetic molecules that resemble DNA and RNA but with novel chemical properties,” says Diercks. “That would open up possibilities in synthetic genomics that we’re just beginning to explore.”
Currently, the research team is focused on evolving human-derived enzymes for therapeutic use, and on tailoring proteases to recognize specific cancer-related protein sequences.
“The T7-ORACLE approach merges the best of both worlds,” says Schultz. “We can now combine rational protein design with continuous evolution to discover functional molecules more efficiently than ever.”
In addition to Diercks and Schultz, authors of the study, “An orthogonal T7 replisome for continuous hypermutation and accelerated evolution in E. coli,” are Philipp Sondermann, Cynthia Rong, Thomas G. Gillis, Yahui Ban, Celine Wang and David A. Dik of Scripps Research.
This work was supported by funding from the National Institutes of Health (grant RGM145323A). More