Artificial Intelligence

NSF CAREER award will support teen autonomy in age of AI

Nathan Kahl — Tue, 09 Jun 2026 15:45:38 +0000

NSF CAREER award will support teen autonomy in age of AI Nathan Kahl Tue, 06/09/2026 - 11:45

Adolescence has always been a time of figuring out who you are. Increasingly, that process unfolds alongside social media feeds, recommendation algorithms, and AI chatbots. 91��’s Nora McDonald received a prestigious National Science Foundation (NSF) CAREER award for $748,000 to better understand how adolescents experience and are shaped by these artificial intelligence (AI) and other personalized digital environments, and how they can develop the skills and capacities necessary to maintain their sense of self, autonomy, and agency within them.

McDonald, an assistant professor in the Department of Information Sciences and Technology, has spent several years studying a growing reality of adolescent life, and one increasingly shaped by personalized AI technologies. Her research has found that social media recommendation systems and AI chatbots can serve as spaces where young people reflect on themselves, experiment with identity, and seek feedback about who they are.

McDonald's work will give teens tools to properly engage with digital technologies. iStock photo.

“Much of the public conversation has been about how algorithms influence what kids see and how we go down rabbit holes,” McDonald said. “I’m interested in a different question: How do algorithms shape self-understanding and how do teens make sense of themselves in environments that are increasingly personalized and shaped by algorithms and AI?”

McDonald’s previous research suggests that even while teenagers often view AI chatbots and recommendation systems as practical tools, those systems can become important spaces for self-exploration and self-presentation.

“Over time, teens might come to expect these systems to reflect aspects of who they are,” McDonald said. “They use them not just for help with homework or entertainment, but also to explore and understand themselves.”

Those findings raise broader questions about identity development during adolescence. If recommendation systems continually influence what young people see, what feedback they receive, and what content captures their attention, how will that affect how they see themselves?

McDonalds's CAREER project will investigate that question through what she calls a resilience framework that examines how adolescents recognize, interpret, and respond to algorithmic influence and how it relates to the coherence of their sense of self.

The research combines interviews, diary studies, surveys, and participatory design activities to better understand how adolescents interpret and respond to algorithmic systems. McDonald will recruit teenagers from across the country, beginning with qualitative studies and eventually expanding to a national survey designed to generate broader statistical insights.

One major outcome of the project will be the development of practical resources and activities designed with teenagers to help them navigate personalized digital environments.

The effort differs from traditional digital literacy initiatives that focus primarily on explaining how algorithms work. “It helps them reflect on algorithmic influence and develop strategies that are really rooted in managing attention and maintaining perspective on who they are outside of digital experiences,” McDonald said.

The CAREER award also supports substantial educational activities. McDonald plans to develop a new undergraduate course focused on algorithmic self-defense from a human-computer interaction perspective. The project will also support a youth summer institute for high school students helping young people to critically engage with AI personalized digital technologies that increasingly shape their everyday experiences.

Learn about Artificial Intelligence at George Mason

In This Story

Nora McDonald

Topics

information sciences and technology

social media intervention

Teens

Artificial Intelligence

Research

National Science Foundation

Why did the AI agent cross the road?

tdonnel — Mon, 08 Jun 2026 18:31:17 +0000

Why did the AI agent cross the road? tdonnel Mon, 06/08/2026 - 14:31

Workshopping, an iterative process where creators share ideas, test what works, and refine what doesn’t through collective feedback, is at the heart of any writers’ group. This collaborative dynamic inspired 91�� PhD students Shiwei Hong to explore whether artificial intelligence (AI) could benefit from a similar approach.

Hong developed a novel multi-agent system that simulates a collaborative comedy writing environment in which AI agents generate, critique, and refine humorous content together. Her research, recently accepted to the prestigious 64th Annual Meeting of the Association for Computational Linguistics, investigates how structured interaction among AI agents can improve creative output.

Shiwei Hong. Photo provided.

Humor remains challenging for artificial intelligence. “Generating a joke or something that is very funny is actually a very tricky question, because it requires a lot of how humans interpret the generated piece,” said Hong, who is working on a degree in computer science.

She created a “sandbox” environment to mirror real-world creative collaboration, populated by 35 AI agents assigned distinct roles and personalities powered by GPT-4.

“Five agents acted as performers. The rest acted as critics or audience members,” said Hong.

Designing 35 unique agent personas required imagination as well as technical expertise. Drawing on her interest in writing fiction, Hong created characters with varied social and cultural backgrounds, adding depth to the simulated interactions.

In one experimental environment, the performer agents generated two scripts in sequence without feedback; in another, they engaged the audience members in critique and discussion between the rounds of generation. The difference was significant.

Human evaluators compared outputs across multiple criteria, such as humor, coherence, and social tone. In more than 70 percent of cases, evaluators preferred scripts produced in the second round of the discussion-based environment.

The improvement appears to stem from collective learning. As agents interact, they build on shared insights, identifying patterns in audience preferences and refining their outputs accordingly. Technically, this process is supported by a shared conversational memory stored in a vector database, allowing agents to retrieve relevant past exchanges and incorporate them into new content. The result is an iterative, emergent form of creativity that begins to resemble human collaboration.

Looking ahead, Hong and her advisor, Assistant Professor Zhicong Lu, aim to expand the system by incorporating human participants and richer modes of interaction. Future directions include integrating voice, gestures, and immersive technologies such as virtual and augmented reality to better capture the nuances of live performance.

“In real comedy, we have faces, gestures, and real voices,” she said. “We hope to bring more of that into the system.”

By demonstrating that workshopping can significantly enhance machine-generated humor, Hong’s work suggests the future of artificial intelligence may lie not only in more advanced individual models, but also in communities of agents learning, creating, and perhaps even laughing together.

This week in AI

CIO Charmaine Madison honored with Change Champion Award

Charmaine Madison, vice president for information technology and chief information officer, has been honored by Cloudforce with a Change Champion Award for leading transformative change at George Mason in the realm of AI, inspiring teams, and challenging the status quo to adopt new ways of working.

Learn how Madison champions the adoption of generative AI across the university.

Explore Research at George Mason

Topics

Human Computer Interaction

computer science

College of Engineering and Computing

Artificial Intelligence

doctoral students

Research

Public health meets the AI moment

Mary Cunningham — Fri, 05 Jun 2026 14:08:44 +0000

Public health meets the AI moment Mary Cunningham Fri, 06/05/2026 - 10:08

Key Takeaways

91��’s College of Public Health convened academics, practitioners, industry leaders, and students from across the country to examine how public health can adapt to AI while keeping equity, ethics, and human judgment at the center
The inaugural AI in Public Health Summit centered on what generative AI could mean for the future of research, education, and practice.
Five main themes emerged from the event: (1) We must lead or risk being left behind. (2) AI can assist, but humans still decide. (3) AI is a new social determinant of health. (4) Classrooms are adapting in real time. (5) Bridge-builders, translators, and critical thinkers are in demand.

Topics

Artificial Intelligence

Public Health

College of Public Health

Machine Learning

Social Determinants of Health

Campus News

In This Story

Melissa J. Perry, Sc.D., MHS, MBA

Robert M. Weiler, PhD, MPH

91��’s AI in Public Health Summit examined what artificial intelligence (AI) could mean for health equity, education, and the future workforce.

The Future of Public Health in an AI-Enabled World with Dean Melissa Perry and Easan Selvan, National Director, Academic Medicine and Public Health, Microsoft. Photo by Heather Carroll/CPH

For a field built to prevent and respond to disruptions, public health now faces a defining new challenge: harnessing the rapidly evolving power of artificial intelligence.

“There are moments in every profession when it becomes clear that change is not simply coming, that it has already arrived,” said Robert Weiler, senior associate dean for academic affairs at the George Mason College of Public Health.

That urgency carried through George Mason’s inaugural AI in Public Health Summit, where conversations centered on what generative AI, machine learning, and large language models could mean for the future of research, education, and practice.

“Today’s meeting is not about AI,” said College of Public Health Dean Melissa Perry. “It’s about the future of public health.” The challenge, she argued, is not simply grasping AI, but preparing future public health professionals to leverage it in ways that benefit humanity.

To achieve that goal, the College of Public Health convened a brain trust of academics, practitioners, industry leaders, and students from across the country. Helping anchor the discussion was the Association of Schools and Programs of Public Health (ASPPH), whose AI task force is helping shape national conversations around responsible AI adoption in higher education and practice. According to ASPPH representatives, George Mason is “leading in this space” among its 150 member institutions.

Several themes emerged across the day:

We must lead or risk being left behind.

Keeping Public Health at the Center of AI: Reflections on the Association of Schools and Programs of Public Health Task Force Report. Photo by Heather Carroll/CPH

At this point, the debate has shifted from whether AI belongs in public health to how to use it responsibly and effectively.

“There’s no escaping it,” said Eduardo Ruiz, chief information officer for ASPPH, pointing to rapid adoption across health care systems, public health agencies, and higher education.

Arman Latif, chief information officer at the Virginia Department of Health, framed AI as “less of a tool, and more of a shift in mindset” for public health. While ethical, environmental, equity, and philosophical concerns abound, he argued that the field can't ignore a technology with such potential to improve operations and strengthen how agencies serve the public. “To not do it, in itself, is unethical,” he suggested.

In a field focused on prevention and “upstream thinking,” speakers pointed to the promise of AI to anticipate problems instead of reacting to them: forecasting outbreaks, detecting overdose trends earlier, identifying food insecurity patterns, and uncovering insights buried in massive datasets.

AI can assist, but humans still decide.

AI in Public Health Summit hosted by the College of Public Health at FUSE at Mason Square. Photo by Mary Cunningham/CPH

The summit’s optimism around AI came with a consistent caveat: the technology may support public health work, but it will never replace the people making decisions and serving communities.

Jamie Atchison, senior director of innovation and strategy at ASPPH, pointed to one of her group’s core recommendations: keep AI human-centered, using it as a tool for decision-makers rather than a replacement for human judgment.

In disease surveillance, for example, AI may help detect patterns and flag emerging outbreaks, but people still need to interpret findings and take action. AI may also help tailor public health messaging to specific populations, but humans remain responsible for judgment, nuance, and building trust.

“AI is a non-moral technology,” said Easan Selvan, national director of academic medicine and public health at Microsoft. “Whether or not we decide to use it for good … is incumbent upon” people and institutions, he said.

AI is a new social determinant of health.

Preparing the Public Health Workforce for an AI-Enabled Future: Practitioners' Perspectives panel with representatives from ICF, Virginia Department of Health, Fairfax County Health Department, and Association of State and Territory Health Officials. Photo by Heather Carroll/CPH

If public health gets AI right, speakers argued, the technology could help narrow longstanding health inequities. Get it wrong, and those gaps could deepen.

“The risks [are] that AI can be an inequity multiplier if we’re not careful, but in fact that is up to us,” Perry said.

AI is already influencing many drivers of health, from information access to employment and health services. “We’re really thinking of AI as a determinant of health,” Ruiz said.

Speakers repeatedly returned to one concern: AI systems reflect the data behind them. So, if that data excludes or underrepresents specific populations, the resulting tools risk reinforcing existing disparities.

AI could also improve equity, from identifying vulnerable populations earlier to helping smaller health departments and community organizations access tools and data once limited to better-funded institutions.

Classrooms are adapting in real time.

Banning AI outright in the classroom has become unrealistic, George Mason faculty and students emphasized during the summit’s student panel.

“People are going to be using it either way,” said biology major Anika Tahsin Siddiqui, arguing that faculty should set clearer expectations and encourage open conversation around AI use to reduce stigma.

Students described using AI to learn coding languages, organize notes, create visualizations and presentations, and study for exams. But they pushed back against AI as a substitute for learning itself.

Bridge-builders, translators, and critical thinkers are in demand.

Student Panel: Teach Us What We Need to Know: Student Voices on AI Skills for Public Health Practice. Photo by Heather Carroll/CPH

While AI literacy is quickly becoming nonnegotiable in public health roles, panelists repeatedly argued that deep technical mastery is not the end goal. Instead, they described a growing demand for “bridge professionals” who can move between worlds: understanding community needs, public health practice, and data systems well enough to connect them.

“The translator is really key,” said Tabatha Offutt-Powell, vice president for public health data modernization and informatics at the Association of State and Territorial Health Officials.

“Those who are early to understand, early to use, early to adapt will be the best prepared,” Ruiz said.

Stay tuned to the College of Public Health for deeper insights from specific panels, as well as recordings of the sessions.

CIO Charmaine Madison honored by Cloudforce with Change Champion Award

lclarkg — Wed, 03 Jun 2026 14:36:32 +0000

CIO Charmaine Madison honored by Cloudforce with Change Champion Award lclarkg Wed, 06/03/2026 - 10:36

Charmaine Madison, 91�� vice president for information technology and chief information officer, has been honored by Cloudforce with a Change Champion Award. Cloudforce’s Frontier Awards recognize individuals who are driving impact with artificial intelligence (AI), embedding AI into operations, transforming how work gets done, and delivering outcomes at scale.

Charmaine Madison, vice president for information technology and chief information officer. Photo by Ron Aira/Office of University Branding

The Change Champion Award recognizes Madison for leading transformative change at George Mason in the realm of AI, inspiring teams, and challenging the status quo to adopt new ways of working

“When we talk about 'Integrate' in the context of AI, we’re not just referring to adopting new tools—we’re talking about rethinking how we work, teach, and serve,” Madison said. “AI is no longer optional; it’s a transformative force that’s already reshaping higher education. The challenge before us isn’t whether to use AI, but how to integrate it thoughtfully and effectively into the fabric of our university. That means aligning AI with our mission, values, and strategic goals—enhancing human capabilities, not replacing them.”

Madison arrived at 91�� in 2024, bringing more than 30 years of federal government experience in information technology, including more than a decade with the Central Intelligence Agency. She retired from the U.S. Air Force as a cyber operations officer.

At George Mason, Madison leads Information Technology Services and the university’s integration of the emerging AI ecosystem into teaching, learning, and campus operations. She has been a champion for the potential of generative AI and its adoption across faculty, staff, and students.

The launch of PatriotAI, a suite of specialized and secure AI tools, has provided university-managed access to large language models that aid academic work, studies, and student life. PatriotAI daily usage has tripled since its launch in 2025 to 2026.

Learn more about AI at 91��.

More about AI at George Mason

Topics

Information Technology Services

Artificial Intelligence

Faculty and Staff News

Chaos theory finds its voice

Nathan Kahl — Tue, 19 May 2026 15:42:55 +0000

Chaos theory finds its voice Nathan Kahl Tue, 05/19/2026 - 11:42

Talk may be cheap, but it is still rich with data, and George Mason's Anomadarshi Barua is using artificial intelligence (AI) and a new approach to chaos theory to rebuild missing pieces of speech with incredible accuracy.

"When we talk, our voices have a frequency component from zero kilohertz (kHz) to around 8 kHz," said Barua, an assistant professor in the Department of Cyber Security Engineering. "Capturing all those frequencies normally requires devices to collect and process large amounts of data, which consumes power, storage, and computing resources."

He will present a paper he coauthored on this topic at the Association for Computational Linguistics (ACL) annual meeting later this summer. ACL is one of the world's leading conferences in natural language processing and speech technologies, and the paper was accepted in the top 15 percent of accepted submissions at a conference with a 19 percent acceptance rate overall.

Smaller devices and sensors operating with limited battery life or bandwidth have difficulty capturing an entire signal, and so record a smaller slice, attempting to reconstruct the missing frequencies later. Barua says this is known as bandwidth extension or bandwidth reconstruction.

Imagine listening to a song through a wall and trying to mentally fill in the muffled higher notes. Barua's research teaches AI systems to do something similar, but with far greater mathematical precision. The team's major breakthrough came from incorporating a concept not often associated with speech: chaos theory.

"Our speech is actually a chaotic signal," Barua said. "'Chaos' does not mean completely random."

Instead, he describes speech as "deterministically random," meaning sounds and phonemes are strongly connected to one another in predictable ways. "You can actually determine what could be the next phoneme if you have the sufficient information from the previous phoneme," he said.

To capture those hidden relationships, the researchers developed what Barua calls a "chaotic discriminator" inside a machine-learning framework known as a generative adversarial network, or GAN. In simple terms, one part of the AI system generates reconstructed speech while another checks whether the recreated speech preserves the natural chaotic patterns found in human voices.

The approach significantly improved reconstruction quality compared to previous methods. "We are getting more improved results compared to the previous baseline," Barua said, "because of the incorporation of the chaotic properties."

By integrating chaos-informed modeling, the team dramatically reduced the size of the AI system needed for reconstruction. "We actually reduce the size of the discriminator by 14 times," Barua said. Smaller models require less memory and computing power, making them more practical for real-world devices.

For Barua, whose earlier work focused primarily on cybersecurity before expanding into speech and natural language processing, the ACL conference's acceptance marks an important milestone. "This is my first paper in natural language processing," he said.

While the current paper focuses on speech, Barua sees much broader possibilities ahead. The same reconstruction techniques could eventually be applied to electrical signals, sonar, lidar, and other sensing technologies. "This concept is not only limited to speech," he said. "We are trying to open up a larger branch in different signal modality."

And that message comes through loud and clear.

In This Story

Anomadarshi Barua

Explore Cybersecurity at George Mason

Powering Artificial Intelligence

Topics

Cybersecurity

Department of Cyber Security Engineering

natural language processing

large language models

Artificial Intelligence

Research

College of Engineering and Computing

A future doctor finds a wider path with public health

Mary Cunningham — Mon, 11 May 2026 17:52:05 +0000

A future doctor finds a wider path with public health Mary Cunningham Mon, 05/11/2026 - 13:52

Emaan Emir, Bachelor of Science in Community Health graduate in May '26. Photo provided.

Emaan Amir started at George Mason on a straightforward trajectory toward medical school, studying forensic science. Within weeks, she knew she wanted to expand that path, turning to public health to better understand the forces that influence care.

“I realized early on that medicine extends far beyond the clinical setting,” she said. “So many structural factors affect health. I really appreciated how the College of Public Health helped me better understand how policy, access to care, and broader social factors shape health outcomes and patient experiences.”

Her early shift set the tone for her four years. An Honors College student, Amir majored in community health, pairing it with a clinical science concentration that keeps her on track for medical school while also honing experience in research and clinical settings.

She’s working toward a career that knits all these pieces together, in the clinic and beyond.

Public health, applied

One experience in particular was a turning point: her work with George Mason’s Learning Lab for Community Health through Mason and Partners Clinics' Empowered Communities.

The project began as a case challenge focused on chronic absenteeism in Virginia schools. Amir and her team were tasked with designing a solution with a hypothetical $1 million budget, presenting it to a panel of community leaders.

Their concept won.

“I think our team stood out because we approached the issue from a more holistic perspective,” Amir said. “We didn’t view physical health, mental health, and social support as separate issues.”

That project also led to an atypical opportunity for an undergraduate. Amir contacted her mentor in the case challenge, Lisa Gring-Pemble, associate professor in the Costello College of Business, about a graduate research assistant role connected to the Learning Lab, and Gring-Pemble welcomed Amir into the role.

Amir has worked on a case study examining Afghan refugees’ access to health care and services in Northern Virginia. The project identified gaps in insurance, housing, employment, and legal support, then translated that into a practical resource toolkit.

“One of the most meaningful aspects of the project was turning research into something practical and community-centered,” Emaan said. “We wanted the final product to be actionable and informed directly by the needs we identified through interviews with health providers and community organizations.”

Holistic prep for medical school

Alongside her pre-med requirements in biology and chemistry, Amir rounded out her public health education with classes that examine how social and historical forces shape medical care.

Outside the classroom, she’s gained hands-on experience through volunteering with pediatric patients and working as a medical assistant in urgent care settings.

The clinical work has affirmed what she sees in her research. “Seeing firsthand how financial and insurance limitations impact patients’ ability to access basic care has reinforced many of the inequities I studied in public health,” she said.

Looking ahead

This summer, Amir heads to the Mayo Clinic Summer Research Program, where she’ll study how voice-based artificial intelligence can be used to detect reflux disease.

Building on that line of interest, she next plans to complete the graduate certificate in AI and health care at George Mason while applying for medical schools.

The throughline is consistent: Amir is not choosing between public health and medicine, but blending the two.

“I hope to contribute not only through patient care, but also through research, policy, and innovation that improve health outcomes on a broader scale,” she said.

Learn more about the bachelor of science in community health.

Key Takeaways

• Graduating senior Emaan Amir combined a pre-med track with public health to better understand how policy, access, and social conditions impact patient care.

• Through George Mason’s Learning Lab for Community Health, Amir worked on projects involving chronic absenteeism in Virginia schools and barriers facing Afghan refugees.

• Amir will join the Mayo Clinic to study artificial intelligence tools for detecting disease before pursuing graduate training in AI and health care and applying to medical school.

Topics

bachelor of science in community health

Artificial Intelligence

Learning experience design course helps students dive head-first into client consulting

sholla4 — Wed, 06 May 2026 17:26:55 +0000

Learning experience design course helps students dive head-first into client consulting sholla4 Wed, 05/06/2026 - 13:26

Learning doesn’t stop when you finish school. Whenever you start a new job or a new program, you learn new rules, new strategies, and new systems. And just like classroom education, there’s science behind how that learning can be best supported.

Lisa Giacumo. Photo provided.

“Large multinational or national organizations need people with knowledge of how people learn and how to create systems and supports for learning and development,” explained Lisa Giacumo, associate professor of learning design and technology in 91��’s College of Education and Human Development (CEHD).

Learning experience design (LXD) and user experience (UX) research are two key pillars of the CEHD’s learning design and technology master’s program. Giacumo has spent her faculty career developing courses on accessible workplace learning, needs assessment, and evaluation, that merge theory with hands-on application to give students a “nuanced” understanding of real-world use cases. The research and design courses (i.e., EDIT 732 and EDIT 752) she leads currently pair students with live clients to develop solutions for LXD problems or new opportunities.

“The recursive loop of asking for input, getting feedback, professional reflection, and making revisions is an important part of the process that is hard to conceptualize from textbook alone,” said Giacumo. “With live clients, students get a chance to see how things might work outside of a textbook while learning how to communicate as a consultant.”

This semester, students worked with two startups: EMK Learning Solutions LLC and Research Sphere.

“Working with a live client and a team really made the whole experience feel more like a UX job. You have deadlines, you have limitations, you have to make decisions and iterate. It feels very realistic,” said George Mason alumna Georgiana Patrichi-Abarca, BA Conflict Analysis and Resolution ’15, a current student in the learning design and technology master’s program. She’s been able to apply what she’s learned in class to her full-time job with the U.S. Department of State, developing training for a new piece of software.

Master’s student Tyler Girvan came into the learning design and technology program with a background in video game design and graphic design. “Getting that practical experience from research inception to executing a prototype was the stand-out element of the course for me,” said Girvan. “It helped me understand where I can feed my past skills through these new filters.”

Girvan continued, “You have to balance meeting the needs of the user while negotiating the ideas and goals of the client, and that’s a skill we were able to develop working with real clients as opposed to simulations."

“The closer you connect what you do in the learning environment to what you need done in the performance environment, the easier it is for learners to transfer what they learned into desired performance on the job,” said Giacumo.

Maurine Kwende, MEd Curriculum and Instruction ’15, CERG Learning Technologies ’15, and PhD Education ’23, is the founder and CEO of EMK Learning Solutions LLC, one of the participating businesses for the course. Her business works with companies to help improve their training and leadership capabilities, leveraging Kwende’s own expertise in learning systems and design. This semester, students worked on developing a professional development chatbot for EMK Learning Solutions that could coach employees when a human coach and trainer isn’t available or isn’t an option. The bot will also be a thinking and brainstorming partner for new employees to get a head start on ideas prior to meeting with their supervisors or stakeholders.

Kwende found the commitment of the students in the course commendable. “They’re dedicated and passionate about our field,” she said. “In the beginning, it felt like a mentoring process ,which was very exciting. Then it became a two-way process: I mentored them as a consultant, and they reverse-mentored me in the areas of technology. In the end, the students helped expand my thinking and showed me the potential of the product. They grew a seed into a full tree.”

“George Mason attracts many very talented, smart, and driven individuals,” said Giacumo. “These students contribute to these organizations’ success stories. And after the classes are over, my students build their own success stories by landing their next job or promotion and continue developing their consulting practices on a solid foundation.”

Learn more about the College of Education and Human Development

Topics

Artificial Intelligence

College of Education and Human Development

Podcast: AI is a clinician’s newest diagnostic partner

sholla4 — Tue, 28 Apr 2026 14:09:11 +0000

Podcast: AI is a clinician’s newest diagnostic partner sholla4 Tue, 04/28/2026 - 10:09

Depending who you talk to, AI – artificial intelligence – is either the cutting edge of technology that can usher in a golden age of efficiency, precision, and capability that will allow humans to shake off the shackles of drudgery and guesswork, or it’s a resources-devouring shadow that’s going to strip us of our humanity, creativity, and connectedness.

On today’s episode of Access to Excellence, College of Public Health professor of health informatics Farrokh Alemi joins President Gregory Washington to discuss the unique juncture of health care, industrial engineering, and now, artificial intelligence; specifically, what AI can do for educators and clinicians.

Intelligent tutors don't give the advice of how to solve a problem. They ask questions from the students of how they want to solve it and evaluate that and give feedback to the student. So the student has to be actively engaged in thinking through things. It's not a copy/paste thing. Without the intelligent tutor, the student can go to an AI system, AI open AI system, and just copy, paste their response to an assignment. But with intelligent tutors that, especially the one that we have on Patriot AI, the student has to go in and interact and answer questions... it gives them an ability to interact at every step very slowly through their assignment." - Farrokh Alemi

Read the transcript

Intro (00:04):

Trailblazers in research, innovators in technology, and those who simply have a good story: all make up the fabric that is 91��, where taking on the grand challenges that face our students and graduates in higher education is our mission and our passion. Hosted by Mason President Gregory Washington, this is the Access to Excellence podcast.

Gregory Washington (00:27):

Is there any term in popular culture right now that is more misunderstood than AI? It's used by so many people for different purposes to mean different things. Depending on who you talk to, AI, or artificial intelligence, is either the cutting edge of technology that can usher in a golden age of efficiency, precision, and capability that will allow humans to take off the shackles of drudgery and guesswork. Or it's a resources-devouring shadow that's going to strip us of our humanity, creativity ,and connectedness. To help us wade through all of this is Dr. Farrokh Alemi, professor of health informatics at George Mason's College of Public Health. Dr. Alemi has spent his career studying how humans, particularly doctors, engineers, and health policy makers, collect and interpret data--that's gonna be very important for later on. And then how they use that data to make crucial decisions from disease diagnoses and prescription choices to predictive analyses of public health needs. His research and teaching have put him at the unique juncture of healthcare, industrial engineering, and now artificial intelligence. Dr. Alemi, welcome to the show.

Farrokh Alemi (02:01):

Thank you so much.

Gregory Washington (02:02):

So now your background is really interesting, right? Because you have a, uh, industrial engineering and operations background, which I know all too well. And you're teaching in the School of Public Health. How did this come about? How are these entities related?

Farrokh Alemi (02:19):

So, industrial engineers, uh, about one third of industrial engineers were work in the healthcare industry. They go work in the hospitals. They, they examine efficiency. They, a lot of things that we go through, like when should we screen for cancer? When anything that's happening between visits is done by industrial engineers. There is a lot of contributions of industrial engineers to healthcare.

Gregory Washington (02:44):

That makes some sense actually. You know, if you want to make something more efficient, you call in an industrial engineer.

Farrokh Alemi (02:51):

<laugh>. That's true.

Gregory Washington (02:52):

So is there an engineering mindset that changes or benefits the way in which you look at a patient's journey through the healthcare system?

Farrokh Alemi (03:01):

As an engineer, sometimes I look at healthcare and I don't understand the way we are healthcare. For example, in depression, we prescribe antidepressants to patients, and the first time we try it, only 40% of time it works. So the majority of the patients don't benefit from our first prescription of antidepressant. Doctors go through trial and errors to improve this to around 60%, 70%. And for 30% of the patients, we don't do anything. So I look at healthcare and I scratch my head. Why are we so inefficient in understanding what works, what's effective, and why are we wasting so many resources in making wrong prescriptions? I can also say the other thing that bothers me a great deal is this kind of cascade of medications where a patient is given one medication and for the side effect they're given a different medication. And on the third one, they're given a something to control what the second one had caused. So in the end, you become polypharmacy and for what? To control something that sometimes is not fatal, and it might be just as well endured and our lives could be so much better with- without some medications.

Gregory Washington (04:30):

You have been dealing with AI for some time. You, you worked on it and the management of depression as you highlighted. But you know, at least in the early phases, AI has a risk of hallucinations, right. And in and in this business, that's a, that could be a difficult set of outcomes. So, so talk about how you're managing the risk of hallucinations in this work.

Farrokh Alemi (04:58):

So I should mention that we have been funded by Robert Wood Johnson Foundation, by the state of Virginia, and by the Patient Centered Outcome Research group to look at depression management and the use of AI. So we have been at this for some years. Hallucinations, uh, happen and we have been testing creating systems to reduce hallucinations. And the main way we you reduce hallucinations is to giving a prompt to the AI system that restricts its use. So it's, we tell to AI, don't talk about this, don't talk about that, just talk about this conversation here. We limit the AI a great deal. And that kind of prompting helps AI stay accurate. The other way we do reduce hallucination is to just get away from internet and go down to the medical record side and actually tell AI to analyze data and base its judgment on the finding from the data, not from comments that people have made on the internet that could be quite inappropriate in clinical management of a patient.

Gregory Washington (06:15):

So what evidence do you have that AI can manage depression better than clinicians?

Farrokh Alemi (06:20):

This is a very interesting evidence. What we do know is in two studies we have shown that the patients of AI concordant clinicians, those are clinicians that follow AI's advice, are more likely to have remission of their symptoms than patients of AI discordant clinicians. Now, that's about 17% in one study and 11% in another study. To give you perspective when average clinician on the first prescription of antidepressant is accurate, around 40%. So we improve this to reach around 57% in one study and in another study to around 50%. So we crossed that borderline of getting the majority of patients to benefit. Right now, only minority of patients are benefiting and we want to get it at least to 60% so that we can have more reliance on these medications when they are appropriate. Of course, we don't always prescribe antidepressants, we also give advice on doing psychotherapy. And for some mild depression we prescribe they that they should not use any antidepressant. So we, we go through a lot of different kinds of advice that we provide. I have to be clear about this thing because I, I use the word prescribe. We don't prescribe, our systems only provide advice. And then later on, the clinician decides to prescribe or not to follow that advice or not follow that advice.

Gregory Washington (08:03):

So the algorithm, the, the AI basically provides input to the clinician.

Farrokh Alemi (08:11):

The AI does not decide, the AI only provides input. But the interesting thing is that we don't collect the information about the patient from the patient in the clinic. We collect the information directly at the patient's home. We advertise on the internet, and we recruit patients that are depressed, some of whom are not seeing any clinician. And we give them the advice and we refer them to a clinic for them to adjust their medications if, if that's necessary.

Gregory Washington (08:43):

And so tell me how it's working. How well does the AI accomplish this task?

Farrokh Alemi (08:48):

So we don't know yet. We are, on April 15th, we are starting with the first randomly selected patient. So we will start and we expect by September 15th to recruit 45 depressed patients and then for the next year to go on to 130 patients. And at that point we will be able to say whether they benefited, whether their clinicians followed their advice, and whether the clinicians who didn't follow their advice, what would have happened if they had followed.

Gregory Washington (09:21):

Do you also have to teach patients how to best use AI? Doesn't the accuracy of the AI depend on the prompt engineering piece that the patient enters?

Farrokh Alemi (09:33):

So in our systems, the patient doesn't enter the prompt. We enter it through a chain of thought, through a long series of prompts that we give to the system. But yes, in general, the quality of the prompt matters a great deal. And currently we are working on a research project in which we are looking at how do you improve that quality of the prompt. So just to give you a sense, for example, when you first come into the system, and if you say, I took citalopram and I didn't get any remission of my symptoms, the AI system currently, if you go to open AI system or Claude or other systems, it will try to engage you and will give you some advice, but that's not the correct behavior in our redesign of the system. It will say, wait a second, I can't give you any advice until I know a little bit more about you.

Farrokh Alemi (10:33):

And that way we get to ask questions about the patient that matter in terms of which advice we give them. The questions we ask from the patient take around five to 10 minutes of interaction. So it's a long visit with the AI, it's not a short question and answer. So you are sitting there, you are talking to AI, AI is asking for your complete medical history, your current medication, anything you tried in the past, what symptoms you have. It's almost like a visit to a clinician. And then at the end we can give some advice and that advice is then taken to your own clinician. So in the end, I think going back to your earlier question, yes, it's really matters that you train whoever is interacting with the AI to ask the right question

Gregory Washington (11:27):

And ask it the right way.

Farrokh Alemi (11:29):

And ask it the right way.

Gregory Washington (11:31):

You have that two facets of your work, right? One is all of the work in depression and uh, psychiatry and the like. And then you have this other aspect of your work, which is this AI as a classroom teacher, which, you know, that's how I actually came across your name. It was a YouTube video. I was looking at other videos on AI, and you know how you'll see in the queue videos that, that it's recommending based on what you're searching and what you're doing. And I see a video from you. Yes. So then I watch it and, uh, I was blown away by by what you're doing. So, so let's, let's talk about it a little bit. Can you highlight what you are doing in the classroom? A course has a number of components. You have the class notes that's usually developed by the instructor that's actually taught to the students, right? You have a mechanism of testing, right? To test students on how well they're learning the material that they're being taught. You have grading, right? And then you have this whole area of assessment where you assessing as part of the grading mechanism, but also kind of part of a modification of the teaching, right? You are, you are looking at how students are learning and then you adjust your teaching in order to increase the depth of knowledge or add stuff that people are missing in this process. And you have managed to take AI and use it in a number of these areas. So can you go through what you've done, what's working, what's not working, and the like, so, so start, just start at the top.

Farrokh Alemi (13:23):

Alright. But first let me go back to why you were able to see my YouTube: because my courses are all open. So one of the YouTube videos that you saw was one of the hundreds of lecture that we have openly available on the web. So there is a, this wealth of knowledge that we have on YouTube that we provide to the world, to everybody in the community. So how are we using AI in the course? Before I go there, let me just say a few things about the type of course that I was teaching.

Gregory Washington (13:56):

Sure.

Farrokh Alemi (13:57):

So there are, I think AI has different roles in different courses. At George Mason, we have a series of courses that are taught online asynchronously.

Gregory Washington (14:09):

Yes.

Farrokh Alemi (14:10):

AI can transform these, these kind of courses to something that's extraordinary interactive.

Gregory Washington (14:17):

Okay.

Farrokh Alemi (14:18):

So that's one type of course. Then you have on the other end experiential courses, which AI can't really do anything for because you have to get there, you have to show skills, you have to do, you have to dance or something like that. Or in healthcare you have to see a patient interact with the patient. These things AI can do less of. In between, there are didactic courses. These didactic courses, AI can make a difference there. So what did I do? I use AI videos to provide my lectures. So those lectures used to be 10 minutes, 15 minutes long and boring. So I asked AI to do what I was doing, and in very, very short time, it did a better job than I did.

Gregory Washington (15:07):

What is your AI of choice?

Farrokh Alemi (15:09):

For the AI videos? I use a software called HeyGen. HeyGen is AI video with avatars. And these avatars go and teach specific concept that I have. So you go to the avatar and you say, I want to teach this topic, what should I say? And the avatar uses its knowledge of AI and says, here is what I think you should say. You examine that and you improve it. And then you say, okay, go ahead and teach this. And the avatar goes ahead, creates an entire video for that topic. Usually it took me a whole day to make a video lecture. And this is like five minutes and it can do the everything I used to do.

Gregory Washington (15:55):

What input do you give it? Like say...

Farrokh Alemi (15:57):

It gives me input. It says, if you are teaching this topic, these are the kinds of things you should talk about. And I say, well no, I don't want this one and I want this one. I, I edit it, its input. It's not that I tell it exactly what to do, I just say I wanna teach about, let's say regression, a statistical approach. And it says, okay, if you are teaching regression, you gotta, you gotta teach these things. And I said, well, no, I have already taught these items and these other items, all I want is this particular item. Then it goes in more depth and says, do you want this? And then, then it says, okay, do you want a display? What kind of display you want? And you have to create a storyboard. It creates the storyboard for you. You examine the storyboard and you say, okay, go ahead. And then within minutes you have the entire lecture. So that part I found extraordinarily helpful to me.

Gregory Washington (16:56):

Okay.

Farrokh Alemi (16:57):

The second part was, this course that I was teaching was a learning by example. You know, there are different paradigms of teaching. One is didactic teaching, the where you give a lecture. And the other one is learning by examples where you put the student through repeated practices of the concepts that you want them to learn. And learning by example is how AI work and they shine in those settings. So in that course, there were about 30 different assignments to the students. So imagine this is a, I think it was a 12 week summer course. So they had 30 assignments to do. So each one of these assignments is a separate AI system. And in each one the AI interacts with the student to finish the assignment properly. So we had 30 different AI tutors for 30 different assignments. The next thing part was that we did the grading. Because if, if the AI is doing the tutoring, it knows what is correct, what is wrong.

Gregory Washington (18:10):

Now you have this HeyGen that developed a video that's doing the teaching, right?

Farrokh Alemi (18:15):

HeyGen is doing the video, but everything else is Patriot AI. It's now we are in a different environment.

Gregory Washington (18:22):

So now you're using Patriot AI?

Farrokh Alemi (18:24):

Yeah. In the tutoring part. So the tutoring part works. Grading is very simple then because you tell the AI give a pass, fail grade, not in those words to the students. So the AI says, okay, let let your instructor know that everything is fine. And I know that message means that they have passed that assignment. I now remember they have exams to do also. There's 30 assignments and two exams in, in 12 weeks.

Gregory Washington (18:54):

So let's go back. HeyGen does the videos. Patriot AI does...

Farrokh Alemi (18:59):

Tutoring.

Gregory Washington (19:00):

Does the tutoring.

Farrokh Alemi (19:01):

And part of the tutoring is the grading.

Gregory Washington (19:04):

Now are you feeding in the videos into the tutoring? How does it know what subjects to tutor?

Farrokh Alemi (19:10):

Yes. I, I tell it what to tutor, because these are the assignments. The tutors are focused only on assignments. The students don't care on big ideas. They want to do the assignments and finish and get out of a class.

Gregory Washington (19:24):

You know that <laugh>.

Farrokh Alemi (19:26):

<laugh>. So we do that. Now, what happened was this, uh, last summer when I did all these things, I found I had very little to do. So I started looking for a role for myself. So then I started saying, okay, I call if a student is late in their assignment, I called. I talked to them.And then some students wanted career advising. I would talk to them about what, what's the career like. And then some students had bigger ideas and smaller I, it gave me better relationship with the students because

Gregory Washington (20:00):

Yeah, because you're not talking about the coursework then because the AI is doing that. You're getting, you're talking to them about broader subjects?

Farrokh Alemi (20:07):

Broader subjects. Yes. And I am available to them. By the way, in that course I was available on every text. So they could text me from 9:00 AM to 9:00 PM

Gregory Washington (20:17):

So, so how do you do the assessment?

Farrokh Alemi (20:20):

The assessment is done by the tutor. So the tutor, the tutor says, Hey, you're finished. Because everything you bring to the tutor, the tutor evaluates and says, this is correct. Go to the next step, go to the next step. And when you get to the final step, the tutor says everything is correct. Let your instructor know that everything is correct. So it's a pass/fail grade.

Gregory Washington (20:42):

What do you think that does to promote critical thinking amongst your students?

Farrokh Alemi (20:46):

I use AI in my teaching and we have intelligent tutors. These intelligent tutors provide advice to the students about an assignment that I have given them. And last summer I tried to see what impact AI has on my teaching and on my students. This was a class of 12 people. And in the 12 people, 10 people responded to a survey that I made for them. And of them, nine of them really liked intelligent tutors and one of them didn't, wanted more time with the instructor. So what does it do with critical thinking? So intelligent tutors don't give the advice of how to solve a problem. They ask questions from the students of how they want to solve it and evaluate that and give feedback to the student. So the student has to be actively engaged in thinking through things. It's not a copy/paste thing. Without the intelligent tutor, the student can go to an AI system, AI open AI system, and just copy, paste their response to an assignment. But with intelligent tutors that, especially the one that we have on Patriot AI, the student has to go in and interact and answer questions.

Gregory Washington (22:14):

Yeah. It's very different.

Farrokh Alemi (22:15):

Very different. They can copy paste and they, they like it more because it really engages them. So if you go to, for example, Claude and you put in here is an assignment, give me the response, it will do so, and students can do that, but they prefer to come to our Patriot AI because it doesn't just put pages and pages of things that you have to copy paste and you, and if there is an error, you don't know where the error is. So it, it gives them an ability to interact at every step very slowly through their assignment.

Farrokh Alemi (22:53):

Let me give you an example. So let's suppose this student has to do an essay. The first thing the intelligent tutor does says, Hey, you need to write this essay. What is your paragraph structure? What is the structure of this essay? Tell me how you were thinking about this. What is your ideas on this paragraph? What are your ideas on that paragraph? And gradually, gradually it gets it to a point that the student is ready to write the essay. So this is not copy paste at all. This is critical thinking at its best because a, a professor, including me, I can't spend this kind of time with students, but the intelligent tutor can spend the time with them and can help them think through the assignment in a way that's more productive.

Gregory Washington (23:44):

That is amazing. So let me put my president's hat on.

Farrokh Alemi (23:49):

Yes.

Gregory Washington (23:49):

So let's suppose for a minute, so you've tried this out in the class? Give me your assessment. How well did it work?

Farrokh Alemi (23:56):

It works very well, but it needs to be evaluated. In, in a large scale. So as I said, 90% of the students liked it in the survey of 10 students. But that's very small scale.

Gregory Washington (24:11):

Right. So you need to expand it to a larger class.

Farrokh Alemi (24:14):

Not only a larger class, other people have to do it. And we have to see that it's independent from me.

Gregory Washington (24:20):

Right. So, so then let me ask this question. If I were to give you a group of faculty. Three, four, how fast, how much time will it take for you to take those three or four faculty and different subject areas than yours? You know, maybe there's, uh, somebody who is in social sciences and then maybe there's a chemist and then maybe there's somebody in, uh, another form of engineering. Right? How long do you think it would take for you to help those faculty to develop a similar like course?

Farrokh Alemi (25:01):

What kind of course they're teaching the same didactic course with assignments, learning from examples?

Gregory Washington (25:07):

Yeah.

Farrokh Alemi (25:08):

They're not teaching experiential courses.

Gregory Washington (25:10):

Nope. Didactic course learning from examples.

Farrokh Alemi (25:13):

Days. Within a week.

Gregory Washington (25:15):

Within a week, you can have them all going,

Farrokh Alemi (25:17):

All going.

Gregory Washington (25:19):

That's pretty good.

Farrokh Alemi (25:20):

If you wanna convince faculty at George Mason to change, I would advise you to do a study of this. A valid study that shows people, that students benefit that there is no copy pasting. That they learn critical thinking and that they are better off.

Gregory Washington (25:40):

No, that makes a lot of sense. Would you recommend this to faculty?

Farrokh Alemi (25:45):

Absolutely. Yeah. I think faculty will have better relationship with students if they do this. They, they will have a better time with teaching.

Gregory Washington (25:56):

So if you were to look out in your crystal ball and say, I've seen the way I've, I've seen I've done this, I've made it work. Could this be the next wave of teaching that we put in front of our students?

Farrokh Alemi (26:14):

Absolutely. This is the next wave. Whether we put it in front of our students or whether we don't. This is coming and you can do this the right way in which it, it enhances critical thinking. Versus you can do it the wrong way, which is, I don't want AI while the students are using it and you are preventing it. That doesn't work. I wanna say one other thing and brings us back to a earlier conversation about depression and AI. My goal is to create the first, uh, artificial psychiatrist. To me that, that will be groundbreaking change. Now this thing with teaching AI as kind of, it wasn't my goal at all. I was just trying to experiment with it. <laugh> And now it has become such a big part of it.

Gregory Washington (27:06):

Let's talk about this artificial psychiatrist. So tell me how it would work. So I, so let's say, you know, I, I wanna get evaluated. Would I come and sit at a little booth like we are today and the AI will be on the other side? And will it ask me questions or will I, tell me how, how this thing would work?

Farrokh Alemi (27:27):

Alright. First you're not in a clinic. You're at home, or at work or someplace. And you call and you say you want an appointment with the AI system. The AI system interviews you, uh, interacts with you, asks a lot of questions from you, takes around five to 10 minutes. And then it says, okay, now I'm ready to give you some advice. But before I give you advice, I have to know your clinician. Who are you gonna take this advice to? Where are you gonna go with it? Hmm. So at that point, we give you the advice, we send the information to your clinician, and we coordinate and hopefully the clinician agrees with us and helps you. So one of the things that we are doing, we have a proposal to Gates Foundation to do this in South Africa. We have a proposal that has been funded to do this in Virginia. Uh, so these are not pie in the sky because the only thing that makes this a pie in the sky is that all of our current work is on depression. And we need to expand it beyond depression to psychosis, to intimate partner violence, all mental health area, and that I call artificial psychiatrist.

Gregory Washington (28:53):

Oh, this is really, really interesting. Um, so let me ask you the hard questions. Let's say you're able to do this both on the instructor side and you'd say you develop the AI psychiatrist.

Farrokh Alemi (29:10):

Yes.

Gregory Washington (29:10):

Okay. Question number one. I'll ask it rapid fire. What's the role of the instructor in the AI uh, guided class?

Farrokh Alemi (29:18):

Oh, I, I that my class is a good example. The role of the instructor is to have a relationship.

Gregory Washington (29:23):

With the students.

Farrokh Alemi (29:24):

With the students to understand them, to figure them out, and to really be a role model for them and help them get there. All these things that take so much time grading in, doing assignments, doing lectures, take our time away from being with this student.

Gregory Washington (29:43):

You make a, you make a strong case, but then is AI replacing the instructor?

Farrokh Alemi (29:48):

Yes. And I, I know there is problem here. There is a, an intellectual problem. What's happening with jobs today. Let's take that.

Gregory Washington (29:58):

Okay.

Farrokh Alemi (29:59):

They are disappearing. Computer programmer jobs are disappearing. Sure. Social media jobs are disappearing. Sure. Why? And it's all AI. Is that good or bad? Of course, it's, you know, people should have work, but there is a transition period of what you do when the entire system is AI. We, we need to teach more about how AI can create jobs. There are new jobs here and our degrees and educations should focus on these new jobs and we haven't defined those things. And I think in part, I am part of the blame because I am kind of making these jobs disappear.

Gregory Washington (30:43):

But maybe there is a new type of professor.

Farrokh Alemi (30:47):

Yes. That, absolutely true. There is a new type of professor.

Gregory Washington (30:50):

And maybe there's this new way of teaching and if you have this mechanism, now the professor can do other things.

Farrokh Alemi (30:57):

Exactly.

Gregory Washington (30:58):

You can do other kinds of research. You can do...

Farrokh Alemi (31:00):

If, if, if

Gregory Washington (31:01):

Some jobs are right, because not because now you have more time. Right.

Farrokh Alemi (31:03):

Yes. If jobs are disappearing, maybe new jobs are coming. Right. But this is a maybe we don't know for sure.

Gregory Washington (31:10):

I agree with that. I agree with that. And, and so we need to be thinking about what does the human societal framework look like? Yeah. What happens to the relationship between instructor and student?

Farrokh Alemi (31:24):

Improves. This is the surprising part. Because now the, the instructor is more available and is more engaged with students that are at risk and can do things that previously the instructor didn't have time to do. So that part is good.

Gregory Washington (31:40):

So why is a large R1 public university like George Mason, the right place to do this kind of AI-guided classroom?

Farrokh Alemi (31:50):

Because this is our future. We are closer to the future because we are in this university and we know this future better and we are shaping it.

Gregory Washington (32:02):

That's a great answer to the question. How can we promote more and better use of AI in our classrooms?

Farrokh Alemi (32:11):

I think, uh, the university is doing a lot of things with the AI policies. It's doing a lot of things with, uh, operation.

Gregory Washington (32:20):

It's great that you're using the Patriot AI platform for your work.

Farrokh Alemi (32:23):

Yeah.That was helpful. And that's university supplied.

Gregory Washington (32:26):

Yes.

Farrokh Alemi (32:26):

Yeah. AI policies, everybody's doing AI policies. A lot of faculty are doing different kinds of, this is the first time that AI is actually teaching. At this university, or I think even some other universities.

Gregory Washington (32:42):

I agree with that.

Farrokh Alemi (32:43):

So that is an interesting thing. We need to absolutely evaluate this and it, and an evaluation that is rigorous and that people can point to and say what will happen if we do this. One thing that amazes me is that students like this, but I don't know if in the, in uh, market studies, whether students will prefer coming to an asynchronous course that is, that has AI or go to a asynchronous course by a different university that doesn't have AI. I think it will give us a marketing advantage too, but that has to be evaluated. We need, we, I don't know that. What is the advantage of doing all this work for attracting students and training people and getting them to work? What, what will happen?

Gregory Washington (33:39):

These are the kind of discussions that we need to have as universities, as faculty and the like. And, you know, this is why I brought you on this podcast. Right. This is the kind of thing that I think is exciting and the kind of thing that I believe starts to force us to start thinking about how this technology affects us on a daily basis in terms of what we do.

Farrokh Alemi (34:08):

I do thank you for doing that. And I also have been following what you have been saying about AI. And I really think that you are thinking right.

Gregory Washington (34:16):

Yeah. Well, I appreciate that. Well, look, we're gonna have to leave it there. Dr. Alemi, thank you for sharing your vision and your leadership with the educators of our future. I am George Mason, president Gregory Washington. Thanks for listening. And tune in next time for more conversations that show why we are all together different.

Outro (34:41):

If you like what you heard on this podcast, go to podcast.gmu.edu for more of Gregory Washington's conversations with the thought leaders, experts, and educators who take on the grand challenges facing our students, graduates, and higher education. That's podcast.gmu.edu.

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In This Story

Farrokh Alemi, PhD

Gregory Washington

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Schar School Students Turn Language Barriers into Award-Winning Entrepreneurial Opportunity

Andrew J Schappert — Mon, 20 Apr 2026 19:44:15 +0000

Schar School Students Turn Language Barriers into Award-Winning Entrepreneurial Opportunity Andrew J Schappert Mon, 04/20/2026 - 15:44

Schar School senior Jayden Banks, left, and sophomore Anthony Even-Vaca pose with ceremonial checks at the Baylor New Venture Competition. Photo provided

Two Schar School of Policy and Government undergraduates took third place and an honorable mention award during the 14th Annual Baylor New Venture Competition in March for pitching a prototype of their medical language translation platform.

The Doctors United DPT/91�� sign at the Baylor New Venture Competition

The cofounders “really felt like the underdogs,” said Anthony Even-Vaca, a 19-year-old sophomore in the Schar School’s International Security and Law degree program at 91��. “I definitely was the youngest there.”

The national competition held at Baylor University’s Paul L. Foster Campus for Business and Innovation in Waco, Texas, drew student entrepreneurs from around the country eager to pitch their startup business ideas to panels of judges for cash awards and sage advice. Many of the competitors were doctoral students affiliated with established ventures, Even-Vaca said, heightening the sense of being underdogs in a field of seasoned innovators.

He and graduating government and international politics senior Jayden Banks took the $1,500 honorable mention prize and $500 for placing third in the elevator pitch competition for their self-funded platform, Doctors United DPT.

The idea for the language translation platform stemmed from Banks’s experience working for the last two years at the Inova Fairfax Medical Campus as a clinical technician, assisting the medical staff in patient care. He began building the app, he said, about a year-and-a-half ago after witnessing firsthand the difficulties of language barriers in a medical environment and how they can complicate even routine interactions.

“I started testing the prototype on the nurses, my coworkers, and they were super supportive of it,” he said. “I interviewed doctors, neurosurgeons, cardiac surgeons, and asked them how language barriers affect them specifically to their specialty.“

Banks and Even-Vaca became friends after working together as coaches at a swim school and then sharing a room for a week during a Schar School study-abroad program to Switzerland. Eventually, Banks recruited Even-Vaca to the Doctors United DPT project “and he immediately had ideas for it, like bringing it to refugee camps. And so we started working on it together,” Banks said.

It was during a second Schar School study-abroad trip, this one to Israel, where the work they were doing in translating medical terminology became real.

“I got sick, I couldn’t get out of bed for a day,” Even-Vaca said. “I was wondering, am I going to have to go to a doctor? I don’t know Hebrew or Arabic, and I felt a little bit hopeless.” (It turned out to be a bad cold. Still, the plane ride home was miserable.)

The app uses AI to render instantaneous translations of some 200 languages, Banks said. It was Even-Vaca’s idea, he said, to add a “confidence meter” to override AI’s sometimes questionable reliability in translations. “The judges loved it,” he said.

The cofounders are actively seeking George Mason alumni and business professors for guidance in building out the award-winning business.

“We’re trying to make more connections, networking, and raising capital,” Banks said. “We see a big demand for interpreter services in other areas, such as international forums and institutions as well as immigration law. We want to implement it around the world and bridge cultural gaps, help people, make a difference. That’s our hope, our vision.”

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George Mason launches Einstein Labs to accelerate AI, in partnership with the Einstein family

ckearney — Wed, 15 Apr 2026 14:55:39 +0000

George Mason launches Einstein Labs to accelerate AI, in partnership with the Einstein family ckearney Wed, 04/15/2026 - 10:55

91�� is launching a new artificial intelligence (AI)-focused accelerator housed in Fuse at Mason Square called Einstein Labs. A partnership between the Einstein family and Mason Enterprise, the lab will develop dual-use technologies for commercial big tech and government, initially focusing on three high-impact sectors: health, quantum, and cybersecurity technologies.

From left, Tad Einstein, Farhad Chowdhury, and Steven Einstein. Photo provided

“Ten years ago, we set out with one dream: to create a place where the Department of War could meet Silicon Valley, and today, that dream is being realized with Mason Enterprise,” said Farhad Chowdhury, Mason Enterprise board member and founder of George Mason’s Entrepreneur in Residence program. “Einstein Labs brings together the best of established and emerging technology, and the government in one place, enabling the region to lead on high-impact collaborations.”

The initiative establishes a framework for academic collaboration, joint innovation, and workforce development. Mason Enterprise and Einstein Labs will also work together to expand interdisciplinary research and development opportunities, and create new curriculum offerings across George Mason’s schools and programs.

Two prominent leaders are joining the George Mason and Einstein Labs initiative:

Steven Einstein—a 30-year mergers-and-acquisitions veteran and retired partner at PricewaterhouseCoopers (PwC), now the newest board member of Mason Enterprise.
Tad Einstein—founder of Google Cloud's Explore platform and global head of immersive experiences, and now serving as George Mason’s newest Entrepreneur-in-Residence.

Tad Einstein referenced a quote often attributed to his ancestor, Albert Einstein, which describes the mission of Einstein Labs: "We cannot solve our problems with the same thinking we used when we created them."

He added, "Einstein Labs is anchored by the 'Innovation Diamond'—a strategic concentration of industry, academia, government, and capital within a single location. By uniting these four assets under one roof, the lab breaks down traditional silos to accelerate breakthroughs.”

“The Einstein family brings both deep industry experience and a strong track record of building scalable, market-driven solutions,” said Paula Sorrell, associate vice president of innovation and economic development at George Mason. “Fostering cross-sector collaborations is essential to responsible digital innovation.”

Mason Enterprise leads the university’s efforts to build an inclusive, high-functioning entrepreneurial ecosystem across the region. The division supports more than 30,000 startups, small businesses, researchers, and industry partners seeking to innovate and accelerate growth, with an annual audience of 58,000 event and workshop attendees and a $2.8 billion annual impact on the economy.

Einstein Labs is a for-profit accelerator dedicated to advancing breakthroughs in AI across quantum, cyber, and health sectors. With support from leaders in the U.S. government, big tech, and academia, the organization aims to build the nation’s premier dual-use AI innovation platform.

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