Prompt coaching tool raises user awareness of bias in generative AI systems

Penn State

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The inclusive prompt coaching tool developed by a team of Penn State-led researchers warns users about bias in AI systems and suggests a prompt to generate more inclusive content.

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Credit: Penn State

UNIVERSITY PARK, Pa. — A coaching tool built into artificial intelligence (AI)-powered systems may raise user awareness of bias in AI algorithms and help individuals better prompt generative AI tools to produce more inclusive content, according to researchers at Penn State and Oregon State University.

The researchers developed a new text-to-image generative AI application intended to provide immediate media literacy interventions — methods designed to make users pause and reflect on the inclusiveness of their prompt design before image generation. As users enter prompts into the application, the “inclusive prompt coaching” tool issues warnings about biases in generative AI systems and offers suggestions for making their prompts more inclusive. The team presented their research today (April 16) at the 2026 Association of Computing Machinery Computer-Human Interaction Conference on Human Factors in Computing Systems in Barcelona, Spain. The paper received an honorable mention from the conference’s awards committee.

In the study, the researchers found that the inclusive prompt coaching intervention increased users’ awareness of algorithmic bias, or its tendency to produce stereotypical content. It also boosted their confidence in writing inclusive prompts to produce less biased outputs. The intervention also increased users’ perceived trust calibration, or their capability to adjust their trust levels to better reflect the systems’ actual trustworthiness. But the intervention led to a less satisfactory user experience, according to the researchers.

“Oftentimes, media literacy interventions like those for social media occur outside of the medium, informing or warning users about the dangers of social media before or after they’ve interacted with it,” said study co-author S. Shyam Sundar, Evan Pugh University Professor and the James P. Jimirro Professor of Media Effects at Penn State. “Here we are using the medium itself — AI text-to-image generators — to educate users about how to better use the medium while they’re interacting with it. It’s a newer twist on the media literacy approach to address the problem of lack of inclusiveness in generative AI.”

To see if prompt coaching can serve as an effective media literacy intervention, the researchers recruited 344 study participants from an online survey platform. They randomly assigned the participants to one of three study conditions: an inclusive prompt coaching condition; a detailed prompt coaching condition; and no coaching condition. The latter two served as control conditions. The researchers asked participants to use the system to generate an image of any character and then answer questions about their experience using the AI system, such as how much control they felt they had over the tool, their awareness of algorithmic bias and their confidence in their ability to craft effective prompts.

Participants in the inclusive prompt coaching condition received feedback on their prompts as soon as they wrote them. If a participant asked the tool to generate an image of beautiful girls in the forest, it would draw their attention to potential bias by explaining that the prompt reinforces the bias that female beauty is primarily defined by physical appearance, running the risk of objectifying the characters. It would then suggest a more inclusive wording, such as “enchanting individuals in a forest.”

Those who went through this intervention reported higher awareness of algorithmic bias compared to those in the no coaching condition. They also reported a higher perception of being able to craft effective prompts compared to those in the other two conditions. Yet participants in the inclusive and detailed prompt coaching conditions reported a more frustrating user experience compared to those in the no coaching condition.

“We found a positive effect of this new approach on improving peoples’ awareness of algorithmic bias and increasing their confidence in creating effective prompts to reduce bias in AI images,” said first author Cheng “Chris” Chen, assistant professor of emerging media and technology at Oregon State University who completed her doctorate with Sundar at Penn State. “The downside of the current version is that participants perceived it as less helpful and more frustrating compared to the control conditions, but we can address this in future design iterations.”

Participant feedback suggested that there was resentment among users that the AI system was giving them “a slap on the wrist” for not being inclusive, or that it was identifying potential biases in prompts but then generating images with biased components, the researchers explained. They pointed to one example where the system issued a warning and offered a suggestion for an innocent prompt asking for an image of “a cute toad.”

“To address these complaints, we can make the system more context aware and more specifically tailor it to user prompts, because some prompts may be more innocent than others,” Chen said. “More tailored interventions may be able to reduce negative perceptions regarding the user experience, reduce frustrations with the design and improve perceived helpfulness.”

Giving users the option of toggling the system on and off could also address the user experience issues, added Sundar, who is also the director of the Penn State Center for Socially Responsible Artificial Intelligence (CSRAI).

“When you’re asking an AI system to generate an image of a toad, the system should not bother trying to automatically correct your lack of inclusiveness,” he said. “But when you’re dealing with a topic much more in the world of human affairs, the system should realize that you might need help, and that you might appreciate assistance with regard to prompt coaching for inclusiveness.”

The prompt coaching approach could help technology companies make their AI tools more ethical and responsible, which could promote appropriate trust among their users, Chen said.

“For everyday users, the inclusive prompt coaching intervention could provide a moment to pause and reflect on how inclusive their prompt is to elicit the best output from AI,” she said. “We found that the increased thinking, or elaboration, in users’ prompt design led to greater trust and improved perceptions of trust calibration.”

In addition to Sundar and Chen, other study co-authors were Mengqi Liao, assistant professor at the University of Georgia who received her doctorate from Penn State; Penn State master’s students Aditya Anand Phadnis and Yao Li; Andrew High, professor of communication arts and sciences at Penn State; and Saeed Abdullah, associate professor of information sciences and technology at Penn State.

 

A team led by Penn State researchers developed an inclusive prompt coaching tool that helped study participants identify bias in AI systems and better prompt generative AI tools to produce more inclusive content. This AI-generated image of a radiant Black woman resulted from a prompt suggested by the tool.

Credit

Penn State

DOI

10.1145/3772318.3791542 

Article Title

Prompt Coaching for Inclusiveness: A Media Literacy Approach to Increase Users’ Awareness of Algorithmic Bias and Prompting Efficacy

Article Publication Date

16-Apr-2026

A student-led experiment sets new limits in the search for axions

A study published in JCAP shows how, with limited resources and support from a large experiment, students built an axion detector and helped narrow down the properties of dark matter

Sissa Medialab

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The experimental apparatus built and used by students at the University of Hamburg

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Credit: Nabil Salama and Agit Akgümüs

In the era of precision cosmology, research often means big science: large observatories, highly complex instruments, international collaborations and substantial funding. Yet even in such an advanced field, progress is still possible — including in the search for elusive dark matter — through more agile approaches, driven by small teams and young researchers, supported by institutions and a good dose of ingenuity.

In a paper just published in the Journal of Cosmology and Astroparticle Physics (JCAP), a group of then-undergraduate students from the University of Hamburg built a cavity detector to search for axions — among the most promising candidates for dark matter — and set new experimental limits on their properties. The result was achieved with relatively limited resources, showing that even small-scale experiments can make a meaningful contribution to one of the most open challenges in modern physics.

Funding for students

The project was made possible through a student research grant provided by the University of Hamburg via the Hub for Crossdisciplinary Learning, which supports independent research initiatives.

“We were kind of embedded in the research group of the MADMAX dark matter experiment,” explains Nabil Salama, one of the authors of the study, currently pursuing an M.Sc. in Physics at the University of Hamburg. “MADMAX carries out a similar experiment on a much larger and more complex scale, and we benefited from their expertise and support.”
“We are very grateful for this help,” he adds, “and also to the University of Hamburg and the Quantum Universe Cluster of Excellence, which provided funding, access to key equipment such as the magnet, and invaluable support from researchers.”

Searching for dark matter

“The benefit of working with dark matter, or axions, is that we expect it to be present everywhere in our galaxy,” says Agit Akgümüs, first author of the study with Salama, currently pursuing an M.Sc. in Mathematical Physics at the University of Hamburg. “So essentially, no matter where you perform the experiment, you have some dark matter on your hand you can do experiments with.”

The funding was first used to build the experimental setup, starting with a resonant cavity made from highly conductive materials, along with the necessary electronics, cabling, supports and measurement instruments. “The detector we built is essentially the simplest version of a cavity detector for dark matter,” says Salama.
The team did not work entirely from scratch: in addition to the funding, they relied on existing infrastructure and equipment provided by the university and collaborating research groups.
The experiment was then tested, calibrated and operated to collect data for analysis.

“We reduced very complex experiments to their essential components,” says Salama. “The result is a less sensitive setup, limited to a small search window, but still capable of producing new scientific data.”

No signal found, new limits set

“The search for axions involves exploring a wide range of possible parameters,” adds Akgümüs. “Our experiment covers only a small region, with limited sensitivity, but it still helps narrow down the possibilities. To actually find the particle, we need either much larger experiments or many different ones, each probing a specific region.”
At the end of the data-taking phase, the team did not observe any signal attributable to axions. Rather than a failure, this is a meaningful scientific result: it allows researchers to exclude the presence of axions with certain properties within the explored mass range, particularly those with stronger interactions with photons. In this way, the study helps narrow the parameter space and guide future searches.

“I think the point of our experiment is that things can be done on a smaller scale,” says Salama. Akgümüs adds: “Our results are naturally more limited than those of larger experiments. Performance scales with resources and complexity. However, we have shown that it is possible to reduce these setups to a much smaller scale — even to projects developed almost independently by students — while still producing real scientific data.”

During the peer-review process of the paper, a referee made a particularly notable comment, Salama recalls. According to the referee, once the axion is discovered and its properties — especially its mass — are known, experiments of this kind could become far more accessible, potentially even suitable for teaching laboratories. “We were told that setups like ours could one day become standard student lab experiments,” says Salama. “In a way, we may have anticipated that future, showing that it is already possible to build and operate such an experiment on a small scale.”

The paper “A New Limit for Axion Dark Matter with SPACE” by M. A. Akgümüs, N. Salama, J. Egge, E. Garutti, M. Maroudas, L. H. Nguyen, and D. Leppla-Weber has been published in the Journal of Cosmology and Astroparticle Physics (JCAP).

Salama (left) and Akgümüs (right) with the experimental apparatus

Credit

Nabil Salama and Agit Akgümüs

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Journal

Journal of Cosmology and Astroparticle Physics

Method of Research

Experimental study

Article Title

A new Limit for Axion Dark Matter with SPACE

 

“Can we hear lost voices again?” Restoring ‘my voice’ by reading light and reviving with AI

Pohang University of Science & Technology (POSTECH)

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Schematic diagram illustrating the difference between communication using conventional voice-based methods and the developed silent speech interface.

 

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Credit: POSTECH

Hearing words even when spoken in silence—a new technology has been developed that reads the subtle movements of neck muscles using light and employs AI to restore them into actual voices.

 

A research team led by Professor Sung-Min Park (Department of IT Convergence Engineering, Mechanical Engineering, Electrical Engineering, and the Graduate School of Convergence) and Dr. Sunguk Hong (Department of Mechanical Engineering) at POSTECH (Pohang University of Science and Technology) conducted this study. The findings were published in the online edition of Cyborg and Bionic Systems, a Science Partner Journal in the field of biomedical engineering.

 

The research began with tiny changes that occur around the neck when a person speaks. It is not just the vocal cords that create sound. Whenever we speak, the muscles and skin around the neck move together, drawing an invisible "movement map" on the skin. The research team focused on the fact that these microscopic movements contain information about what the person intends to say.

 

To capture this information, the research team developed a ‘Multiaxial Strain Mapping Sensor.’ This sensor, which combines a miniature camera with small reference markers on a soft silicone material, can be conveniently worn on the neck and detects even the most minute skin movements. The wearing position and tightness can be adjusted for the individual, and an algorithm automatically corrects errors that may occur when the device is reattached, allowing it to operate stably in daily environments.

 

The strain patterns collected by the sensor are analyzed by AI. It estimates the words or sentences the user intends to say and combines them with voice synthesis technology trained on the individual's vocal characteristics to reproduce the actual voice. Even without producing sound, it "reads" the speech and converts it into a voice.

 

Existing voice restoration technologies used biological signals such as ‘EMG (electromyography)’ or ‘EEG (electroencephalography),’ but they had limitations in daily life due to complex equipment and uncomfortable wearability. The research team solved this problem with a wearable sensor and confirmed through experiments that speech could be reconstructed with high accuracy even in noisy environments such as factories.

 

The scope of application is also broad. It is expected to be used in various fields, such as communication assistance for patients who have lost their voices due to vocal cord diseases or laryngeal surgery, communication technology for industrial sites without microphones or radios, and even "silent communication" in libraries or conference rooms.

 

Professor Sung-Min Park, who led the study, said, "We hope this technology will accelerate the day when patients with speech disorders can reclaim their voices," adding, "It is a noteworthy technology because it has a wide range of potential applications, including assisting laryngectomized patients, communicating in noisy industrial environments, and even supporting silent conversations.“

 

Meanwhile, this research was conducted with support from Doctoral Course Research Grant Program and the Mid-career Researcher Program of the Ministry of Education, Bio&Medical Technology Development Program and the Pioneering Convergence Science and Technology Development Program of the Ministry of Science and ICT.

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Journal

Cyborg and Bionic Systems

DOI

10.34133/cbsystems.0536 

Article Title

Soft Multiaxial Strain Mapping Interface with AI-Driven Decoding for Silent Speech in Noise

 

E-cigarette devices expose users to toxic metals, UTS study finds

University of Technology Sydney

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Red and black vaping device

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Credit: Photo by Vaporesso on Unsplash

Vaping is largely believed to be a safer alternative to cigarettes, but new research shows that vaping devices can deliver toxic metals directly into lung tissue.

A study published in Analytical and Bioanalytical Chemistry by University of Technology Sydney (UTS) researchers showed that even short‑term vaping at exposure levels below typical daily human use resulted in measurable accumulation of toxic metals in lung tissue – including lead, copper and nickel.

Lead researcher Dr Dayanne Bordin, a lecturer in analytical chemistry, said the pre-clinical study provides the first evidence that e-cigarette aerosols include metal-containing (organometallic) species, including those associated with tin and mercury – forms that are often more bioavailable and biologically reactive than inorganic metals.

“From a risk perspective, the findings reveal under‑recognised hazards associated with vaping,” she said.  “Metal emissions and their biological effects are rarely incorporated into current safety assessments or public understanding. Unlike cigarettes, which are a relatively consistent products, e-cigarettes and devices are often manufactured with poor quality control involving materials and components with unknown toxicological relevance.

“The metal profiles observed are consistent with emissions from heating coils and electrical components, identifying the device itself as a critical source of exposure and highlighting important gaps in how vaping risks are evaluated.”

Dr Bordin explains this is important because many people believe vaping carries less risk than conventional cigarettes. This perceived reduction in harm, along with misleading marketing campaigns, has contributed to the rapid uptake of e-cigarettes globally, particularly among younger demographics. In Australia, for example, e-cigarette use among young adults increased from 5.3% in 2019 to over 21% in 2023, with a similar rise in adolescents.

“Our findings challenge the assumption that e-cigarettes are safer and shows how critical it is to review current vaping regulations, which should be expanded to include device-derived emissions, not just e-liquid composition,” she said.

“Vaping can deliver toxic metals directly into the lungs, even after short-term use. This information is important for anyone considering vaping, especially young people, because these metal exposures are largely invisible and rarely discussed.

“Specifically, there is a need for standards and routine testing of metal and organometallic emissions from e-cigarettes, particularly from heating coils and internal components,” said Dr Bordin.

“The results also support updating risk assessment frameworks and public health guidance to incorporate metal exposure and bioaccumulation and improving consumer awareness around these previously unrecognised risks.”

 

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Journal

Analytical and Bioanalytical Chemistry

DOI

10.1007/s00216-026-06487-1 

Method of Research

Observational study

Subject of Research

Animals

Article Title

Analytical investigation of metal distribution from e-cigarette aerosols to lung deposition using multi-platform mass spectrometry

Article Publication Date

16-Apr-2026

 

Hong Kong’s waters at risk from over-the-counter (OTC) drug pollution

KeAi Communications Co., Ltd.

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A novel holistic paradigm for effective control of priority pharmaceuticals in complex river-estuary continuums. 

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Credit: City University of Hong Kong

A recent study of Hong Kong's river and estuary systems has uncovered an overlooked major source of water pollution: common over-the-counter (OTC) drugs. Researchers from City University of Hong Kong (CityUHK) found that accessible, everyday OTC drugs, such as painkillers, antihistamines, and caffeine, accounted for up to 85% of pharmaceutical pollution in these waters during the wet season—far outpacing prescription-only medicines.

The study was led by Professor Kenneth Mei-Yee Leung, Director of the State Key Laboratory of Marine Environmental Health (SKLMEH), Chair Professor of Environmental Toxicology and Chemistry, and Associate Dean of Science College at CityUHK, in collaboration with the Guangdong Research Institute of Water Resources and Hydropower at Guangzhou in China.

"We often assume that complex or restricted prescription medications pose the greatest environmental risk, but our findings shine a new light on everyday household medicines," says Professor Kenneth Leung. "Because OTC drugs are easily accessible and continuously consumed, they act as 'pseudo-persistent' pollutants. Even if they break down easily, our constant use means they are always present in our aquatic ecosystems."

Pharmaceuticals tend to be mobile in water due to their molecular properties, allowing them to transport through river networks and enter the ocean via estuaries, posing further threats to marine ecosystems. In fact, it is well known that pharmaceuticals are present in rivers, estuaries, and coastal waters worldwide.

"Pharmaceutical pollution is not a local pollution issue at a specific site. Hence, we should adopt a river-estuary-sea perspective to prioritize pollutants for control and management," Leung adds.

Notably, existing site-specific risk assessments lack a macroscopic perspective, making it difficult to distinguish widespread ecological threats from localized contamination. To address this concern, the research team introduced a newly developed paradigm that could advance the risk assessment.

"Our approach integrates the river/estuary-to-sea transport trajectory modeling with consideration of persistence, mobility, and toxicity (PMT) of the pharmaceutical pollutant and thus the results can better evaluate and prioritize pharmaceuticals for risk management," explains Leung.

They team found that 80% of the investigated pharmaceuticals met the criteria for being PMT pollutants in water environments. Caffeine, paracetamol, cetirizine, cimetidine, sitagliptin, and fexofenadine were identified as priority pollutants for control in the river-estuary system of Hong Kong, exhibiting a greater potential to harm sensitive marine habitats of the endangered Indo-Pacific humpback dolphin. Among those, the top four pharmaceuticals with the highest risks were all OTC drugs.

By pinpointing high-priority pharmaceuticals and the rivers that contribute most to their spread, the team suggests that targeted interventions, such as upgrading sewage treatment and installing stormwater retention tanks along major discharge rivers, could effectively reduce their emissions into the sea.

"Raising public awareness is also essential," says Leung. "Residents should return unwanted or expired medications for proper disposal rather than throwing them away or flushing them. Clearer government guidance on safe drug disposal is urgently needed."

 

Measurement of water quality parameters

Water sampling from Shing Mun River, Hong Kong

Credit

City University of Hong Kong

Contact the author: Kenneth Mei-Yee Leung, State Key Laboratory of Marine Environmental Health and Department of Chemistry, City University of Hong Kong, Hong Kong, China, kmyleung@cityu.edu.hk

The publisher KeAi was established by Elsevier and China Science Publishing & Media Ltd to unfold quality research globally. In 2013, our focus shifted to open access publishing. We now proudly publish more than 200 world-class, open access, English language journals, spanning all scientific disciplines. Many of these are titles we publish in partnership with prestigious societies and academic institutions, such as the National Natural Science Foundation of China (NSFC).

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Journal

Environmental Chemistry and Ecotoxicology

DOI

10.1016/j.enceco.2026.02.021 

Method of Research

Experimental study

Subject of Research

Not applicable

Article Title

Uncovering prevalence of environmentally mobile pharmaceuticals and their priority control strategies in river-estuary continuum of Hong Kong