All told, 85 students plus faculty members traveled together over March break to learn and grow.
One group explored Andean culture in the Secret Valley of Peru while another headed to the nation’s capital to learn about programs that address poverty, food access, housing and homelessness. In Alabama, a group studied civil rights, justice and the ongoing legacy of slavery. Latin and Greek students visited the ancient cities, temples, amphitheaters and markets of Sicily and Campania where the primary Latin and ancient Greek authors they study lived or worked.
But the most vocal group of Exonians of them all was the Concert Choir. Thirty-nine students and Music Instructor Kris Johnson made a weeklong trek through Northern Italy. Stopping in Florence, Verona, Mantua and Venice, the group performed in stunning venues along the way — all while exploring both historic and contemporary Italian art, cuisine and culture. Hear their voices and see more behind the scenes from the trip on their Instagram – @PEA_Choir_Italy.
In total, five groups traveled to Washington, D.C., Montgomery, Alabama, Northern Italy, Sicily and Campania and Machu Picchu, Peru. Swipe through to see photos from the trips.
This article was originally published in the spring 2025 edition of The Exeter Bulletin.
“New England winters are tough,” says Lauren Josef, chair of the Theater and Dance Department. “We need joy. We need weird.” Exeter’s performance of The 25th Annual Putnam County Spelling Bee brought all that and more to The David E. and Stacey L. Goel Center for Theater and Dance. The fast-paced and riotous musical featured six “middle schoolers” and audience participants who spelled their way through vexing vocabulary while sharing hilarious and poignant personal stories.
“I think one of the reasons this show has felt so special is because early on we said, ‘This is not going to be a traditional show,’ ” says Josef, the production’s director. “We told the students: ‘You’re going to be interacting with the audience. You might be throwing things. You’re going to be in character preshow and bringing everybody into this environment.”
Delivering such an immersive experience took creativity and collaboration. Here’s a behind-the-scenes look at the way the show took shape.
Student actors interact with the live audience.
Instructors in Theater Lauren Josef and Anthony Reed stand in the lighting and sound booth.
hours to paint a gym floor onstage
cast and crew members
body microphones
lighting cues
minutes running time
You would forgive Meg Foley if at some point during the next academic year she started her workday by walking to the northeast corner of the Academy Building — and into somebody else’s classroom. That kind of muscle memory develops from teaching in the same space for nearly two and a half decades.
But in July, Foley will transition to a new role, dean of faculty, and away from her corner room with the views into two quads. “I’ve had the chance to switch rooms over time, but I’ve always stuck with this room because I love the classic features,” she says. “And I love the vantage point. As people are leaving the building, especially after assembly, students or colleagues from other departments will pop in to chat. I’ll really miss that.”
Foley says she’ll also miss those moments of connection around the Harkness table, where — for 50 minutes each class — everything outside Room 030 fades away and meaningful discussion takes over.
“There are various tributes to my home state of Minnesota sprinkled around the room. I’ve got the ‘Purple Rain’ cover of The New Yorker from when Prince died, the Minnesota Twins Homer Hanky and Boundary Waters prayer flags.”
“These maps are so old; this one is from 1954. The country borders have changed, of course, but when you’re teaching history, that can be useful! They’re so fragile, I’m always worried that they’re going to rip.”
“I like to have a few little toys out that kids will sometimes play with or just hold while they’re talking or at the table. I started the course Why Are Poor Nations Poor? and a student who lived in Bangladesh came back from winter break and brought me this tiny rickshaw. She told me all about the marketplace where she bought it and the artisan who had made and sold it to her. So much of her story aligned with themes in the course.”
“These are document readers for two courses, one from 1998 and one from this year. With our teaching, there’s kind of a lineage to it. You start by working with somebody off of their syllabus and then you make changes and adjustments and slowly it becomes your own. Or maybe you make a radical break and it becomes your own suddenly. Then someone else starts teaching the course and you share your syllabus with them and they make their additions and you add some of their additions to your own. When you look back at these readers, you can see that lineage.”
Skulls, crossed bones, swords and smoke — these are just some of the iconic symbols that represented Exeter’s early secret societies, or fraternities. Their origins trace back to 1818, when the Golden Branch Literary Society emerged as a secret organization. The first fraternity, Pi Kappa Delta, was started about 1870, but not until the 1890s did a growing number of these groups begin to stir intrigue, mystery and controversy.
As a 1935 article in The Exonian described, the secret societies distressed some faculty and the administration: “They openly opposed faculty authority. The initiations were held late at night, and in some cases, all night, and the candidates were injured both mentally and physically, so that their class work began to drop.”
The initiation ceremonies, as chronicled in the article, were both eerie and humiliating. One society, for instance, took initiates to an old burial vault lit only by candles. Other societies, it recounted, were notorious for their physical tests, including branding candidates with a cigar and requiring candidates to appear in “fantastic and almost no clothes at classes, sell peanuts to the faculty and townspeople, and make speeches from a soap box at what is now the town bandstand.”
The 2012-13 Exeter boys basketball team was riding high when it returned from the holiday break. The team was7-0 as it prepared for a game at Kimball Union to tip off the second half of the season.
“Sure enough, we got our brains beatin and we were brought back down to earth,” Harry Rafferty ’13 recalls. “The loss reminded us that we were a special group, but we still had to get off the bus and compete. We had to hold true to the principle sour coach had laid out for us.”
In case anyone had forgotten one of those principles, coach Jay Tilton had T-shirts printed to remind them: HUMBLE PIE. EAT IT.
“It was not a fancy font or anything like that,” Rafferty says, laughing. “True to Jay form, it was black font on a white shirt; as basic as it gets.”
Exeter didn’t lose another game the rest of the season, going 25-1 and capturing the first NEPSAC Class A title in program history. The Big Red went on to win four more titles during Tilton’s tenure as coach.
But his 210-96 career record and seven championship game appearances are just part of the legacy he leaves behind as he retires from coaching to become regional director of major gifts in the school’s Office of Institutional Advancement.
“Coach T could always see the bigger picture,” Emmett Shell ’18 says. “He left a lot of us with life lessons that have been invaluable. He got me to see a way of approaching not just basketball, but life with a little more toughness, a little more consistency, and a little more energy, which I think can make all the difference.”
Tilton began leading the program in 2009 after nine seasons as an assistant coach under Malcolm Wesselink. Tilton’s father, Mark, coached for 21 years at New Hampton School, where the basketball court is named in his honor. “I grew up watching the modeling of coaches and student-athletes, so that has always been in my blood,” says Tilton, 56, who was born in Berlin, New Hampshire, and spent four years as an assistant at Dartmouth College.
“Life lessons were taught through athletics, and my greatest mentors in my life were coaches, but they were also educators.”
When Tilton was considering the move to Exeter, his peers told him he couldn’t win there because of the Academy’s academic standards. He took that as a challenge — one he passed on to his team.
“Coach T was really good at making sure everyone was producing and contributing at their highest capacity,” says Shell, who was a co-captain his senior year. “He pushed me in ways that I never thought I could be pushed.”
Tilton describes himself as an emotional coach, but Rafferty says that emotion never turned negative. “He has this Ted Lasso-like sensibility or optimism that makes guys really want to play for him,” Rafferty says.“Aside from him being a great coach, he’s genuine and he has every one of his players’ backs, long after they played for him.”
Tilton began pondering retirement a couple of years ago. He felt he had accomplished all he could, and he wanted to spend more time with his wife, Darcy, and his son, Cameron. They had sacrificed so much, he says, because of the demands of coaching. When Rafferty joined his staff as an assistant coach this season, a succession plan was in place.
“I knew I was on the back nine,” Tilton says. “I just wasn’t sure if I was on 16, 17 or 18. When Harry told me was getting out of the college coaching world and coming back to the area, I was like: ‘Wow. What are the odds this is happening right now?”
“Harry Rafferty was the best teammate I’ve ever coached because he really understood people, he is an exceptional motivator and, of course, he really knows how to coach. The program will be in good hands.”
Before the team boarded the bus to head to the 2025 NEPSAC title game in March, Tilton spent a quiet and poignant moment in the gym. It took him back to the 2012-13 season when, just before his team claimed its first title and altered the trajectory of the program, he sat in the gym by himself and thought, “We’ve arrived.”
“This time around, I knew it was going to be my last bus ride with the team,” he says. “It was an emotional moment because it was a reflection of everybody that’s been through that journey with me. I remember the big wins and the trophies, but the highs and lows that you share with a group of young men who are committed to working together — whether you achieved or you fell just short — those are the things that I will remember the most. I feel so incredibly grateful to have had those moments with these young men, these Exonians.”
— Craig Morgan
This article was originally published in spring edition 2025 edition of The Exeter
In 1994, Jimmy Lin ’97 predicted that artificial intelligence, or AI, would become a reality during his lifetime. He was 15 and competing against a small group of engineers and computer scientists for the Loebner Prize, awarded to the person who creates the most human-like computer program. Lin’s program was designed to recognize and respond to familiar key words in human speech. “I hesitate to call it artificial intelligence,” he told reporters at the time. “I like to refer to it as a bag of tricks.”
Although Lin didn’t win the prize, his comment that his “bag of tricks” was a precursor to something bigger was prescient. “In the late 1990s, chatbots were weird,” Lin says. “Now, chatbots are just chatbots and of course we can talk to machines.”
Computer programming has been part of Lin’s life since he was a child. “Among my earliest memories are sitting on my dad’s lap in front of an Apple II computer, and that was back when you had to hook the phone line up to a modem,” he says.
Ahn and his brother, Daniel, run Delfi, what Ahn calls “the first AI investment bank.” The AI financial “copilot” they developed enables Delfi to deliver balance sheet hedging strategies and analytics for banks, credit unions and asset managers. “AI and machine learning risk management algorithms makes this type of analysis available to everyone, enabling them to make better investment decisions,” Ahn says. “Our business model wouldn’t exist without AI.” Currently, he says, 50% of the world’s GDP does not engage in capital markets. “That’s a missed opportunity,” he adds. “We can expand that up to at least 75%.”
The U.S. Department of Defense (DOD) started researching AI in 1958, when it formed the Defense Advanced Research Projects Agency (known now as DARPA). In the 1990s, the U.S. military used an AI program called DART (Dynamic Analysis and Replanning Tool) to solve logistical challenges like moving supplies or personnel and saving millions of dollars. The military has also funded research into the development of autonomous cars as well as robots, and has used autonomous weapons like mines, torpedoes and heat-guided missiles in warfare.
When Sofiya Goncharova’25 noticed how immersed her peers and teachers were in AI, she decided to demystify the technology for others. For her senior project, she created Co[de]pendent: Living Alongside AI, a podcast she describes as a place “where we explore the quirks, questions and quiet revolutions of living in a world that’s not just human anymore.”
Goncharova’s interest in AI stemmed from research she did over the summer at Yale University’s Social Robotics Lab. Working on a study about human responses toward robots, she learned how manipulative AI technology can be. “We wanted to understand how people adjust their feedback based on how competent they think the robot is,” she says. “People’s sentiment about the robot would change depending upon the robot’s behavior. That got me thinking about AI and how it impacts us.”
An example of AI’s manipulative power are the algorithms used on platforms like YouTube and TikTok, she says, and how they shape what users see. “They actively steer our behavior by amplifying content that boosts engagement often in subtle or emotional ways,” Goncharova says. “I see that kind of influence in how quickly narratives or trends catch on with my peers, often without them realizing it. That deeply impacted how I view AI and inspired me to create the podcast.”
Goncharova’s podcasts, developed in consultation with Computer Science Instructor El Kaplan and Religion, Ethics and Philosophy Chair Tom Simpson, address timely AI topics. She examines the effect of AI on art with photographer and artist Derin Korman, a photography teacher at the Commonwealth School in Boston. Korman trained a machine learning model to compare his original work with the AI-generated work. “The takeaway is that you need to know your intention with using AI and acknowledge that it’s part of your work,” Goncharova says.
In other episodes, she tackles the influence of AI on politics (“The EU is much further ahead of the U.S. in terms of legal controls on AI,” she says) and has a conversation with Director of Studies Jeanette Lovett on AI’s effects on education and the workforce. “My goal is not to lead to conclusions,” Goncharova says. “I just want to inform people about the concepts.”
“I’m excited about how we can use AI to advance scientific discovery and enable personalized, effective health care,” says Ayush Noori ’20, a Harvard University senior and Rhodes scholar, who is developing AI tools to personalize diagnostics for people with neurological disorders and participated in the Exeter panel. “AI will better help us understand disease pathobiology and work towards novel diagnostic and therapeutic options.”
AI is here and it’s changing everything we do, including how we bank, interact with our doctors and shop. (The use of AI in retail is predicted to grow to $54.92 billion by 2033 from $11.83 billion in 2024). As with any disruptive societal change, the technology raises questions about inaccuracy, biases, privacy, copyright and more. “What happens if generative artificial intelligence improves things across the board but creates a gap in access, for example, between men and women?” says Trustee Christine Robson Weaver ’99, a data product lead at Google who was a panelist. “You have to set a higher bar for the technology.”
Most of the leading companies creating AI technologies — including Google, Microsoft and OpenAI — have developed mission statements that outline their goals for using AI. Weaver was on an internal Google team that developed the firm’s AI principles based on improving the user experience while protecting their safety. “There is so much science fiction around AI and so many issues that people think about,” she says. “I favor AI safety decisions that are tactical, like AI alignment. Does the model do what I say it’s going to do most of the time? I’m interested in how it interacts with users.”
She favors the use of policy “layers” that define safety at different levels, both at the corporate level and through individual product policies. Those layers act as a final check before exposing the product to end users. “Having access to quality data is important for the development of AI models,” Weaver says. “Having compliant-safe data and the right tools to work with that data and track what’s being done is critical.”
Karl Cobbe ’09, a research scientist at Open AI, which created ChatGPT, shares Weaver’s concerns about the data that feeds the AI models and the validity of what the models churn out. “A big issue with large learning models are hallucinations: They make up facts,” Cobbe says. “We’re trying to make the models better at reasoning.”
AI development also taxes natural resources. According to the Allen Institute for AI, one query to ChatGPT uses approximately as much electricity as one lightbulb for 20 minutes. Each question a chatbot receives is routed to a data center, which uses a lot of energy and contributes to greenhouse emissions. Google and other tech companies are still engaging with that problem.
1796
Jonathan Swift’s satiric novel, Gulliver’s Travels, refers to the Engine, a large contraption used by scholars to generate new ideas, sentences and books.
1950
British mathematician Alan Turing publishes an academic paper addressing whether machines can think. He developed the Turing Test, a way to measure machine intelligence by assessing its ability to mimic human conversation and behavior. (The Loebner Prize competition is based on the Turing Test.)
1956
Dartmouth College mathematics professor John McCarthy coins the term “artificial intelligence” during the Dartmouth Summer Research Project on Artificial Intelligence, a conference exploring how machines could simulate human intelligence.
1958
Perceptron, the first artificial neural network, is developed by American psychologist Frank Rosenblatt. The program makes decisions in a way similar to the human brain. It can distinguish between punch cards marked on the left and right and is described by its creator as the first machine capable of having an original idea.
1960
Adaline (Adaptive Linear Neuron), a single-layer artificial neural network, is developed by Stanford University professor Bernard Widrow and his student Marcian Hoff. It’s an adaptive system for pattern recognition and the foundation for future advances in neural network and machine learning.
1997
Deep Blue, developed by IBM, is the first computer system to defeat a reigning world chess champion, Garry Kasparov. The computer’s underlying technology advances the ability of supercomputers to tackle complex calculations to perform tasks like uncovering patterns in databases.
2012
AlexNet, a deep learning neural network with eight layers, is a breakthrough in image recognition, identifying images of dogs and cars at a level similar to humans.
2017
Google Research develops Transformer, a neural network architecture that can train a computer to recognize the next word in a chain of words.
2019
OpenAI’s Generative Pretrained Transformer 2 (or GPT-2) demonstrates the power of natural language processing. GPT-2 is able to predict the next item in a sequence, perform tasks such as summarizing and translating text. GPT-3, introduced in 2020, is able to produce text often indistinguishable from human writing.
2021
DALL-E, a neural network that creates pictures from language prompts is introduced by Open AI.
2022
ChatGPT, Open AI’s chatbot, built on a large language model, introduces generative AI, which can create new content based on existing data. It can produce text, images, videos, audio and more.
2023
Google Labs releases Notebook LM, which summarizes up to 50 sources, including documents, videos and books.
2024
Using Google’s AI algorithms, Google Research and Harvard publish the first synaptic resolution of the human brain. Open AI releases Sora, an AI tool that creates videos from text, images and other video.
Debbie Kane is a longtime contributor to The Exeter Bulletin. Her work has also appeared in AIA NH Forum, New Hampshire Home and NewHampshire Magazine.
This article was originally published in the spring 2025 edition of The Exeter Bulletin.