Mariely Sanchez spent the last school year using generative artificial intelligence nearly every day in her classroom.

The Miami fourth-grade teacher began each morning by asking a chatbot — teachers in Miami-Dade have access not only to ChatGPT, but to Google’s Gemini and Microsoft’s Co-Pilot — to comb through Florida state standards and create reading passages for students. She’d also ask the AI to produce multiple-choice and short-response quizzes to test how well students understood the reading. 

The assignments, she said, weren’t easy for students. She built them by using “difficult standards that students need more practice with” and prompting the AI to create materials.

Sanchez is spending her summer break learning more about AI, including its ethics, and helping colleagues do the same, warning:

That effort got a big boost earlier last month, when the American Federation of Teachers that it would open an AI training center for educators in New York City, with $23 million in funding from OpenAI, Anthropic and Microsoft, three of the leading players in the generative AI marketplace.

AFT says it’ll open the National Academy for AI Instruction in Manhattan this fall, offering hands-on workshops for teachers. Over five years, it said, the academy will train 400,000 educators, or one in 10 U.S. teachers, effectively reaching the more than 7.2 million students they teach. 

When she announced the academy in early July, AFT President Randi Weingarten said teachers face “huge challenges,” including navigating AI wisely, ethically and safely. “The question was whether we would be chasing it — or whether we would be trying to harness it.”

‘It’s the Wild West’

AFT, the nation’s second largest teachers’ union, envisions the academy working much like those that train carpenters, electricians and construction workers,“where the companies, where the corporations actually come to the union to create the kind of standards that are needed” for success, Weingarten said. 

Microsoft, for example, has said it plans to give more than $4 billion in cash and technology services to train millions of people to use AI, underwriting efforts at schools, community colleges, technical colleges and nonprofits. The tech giant already boasts an AI to train members of the larger AFL-CIO labor union, of which AFT is a member. And it’s creating a new training program, , to help 20 million people earn certificates in AI.

Rob Weil — AFT’s director of research, policy and field programs — said the new academy will bring high-quality training to a profession that so far has seen uneven opportunity for it.

“It’s the Wild West,” he said in an interview during a training session at the union’s annual conference in July. “It’s all over the place. You have some school districts that are out front, and they’re doing a lot of pretty good work.” But others are banning AI or simply ignoring it, he said, leaving teachers to fend for themselves at a time when students need them perhaps more than ever.

“We have to make our instruction better. We have to be better on engagement. We have a crisis of engagement in our schools, and these tools can help with that.”

AFT’s move has been met with equal parts cautious optimism and weary skepticism.

Writing in her , ed-tech critic and AI skeptic Audrey Watters called  AFT’s partnership with the tech companies “a gigantic public experiment that no one has asked for.”

Unions, she wrote, “should be one of the ways in which workers resist, rather than acquiesce to … the tech industry’s vision of the future.” By joining forces with big tech, she said, AFT is implicitly endorsing its products. “Teaching teachers how to use a suite of Microsoft tools does not help students as much as it helps Microsoft. Teaching teachers how to use a suite of Microsoft tools is not so much an ‘academy’ as a storefront.”

Benjamin Riley, who has also about generative AI in education, said observers should “100% worry” that the new partnerships represent a play for market share. 

“It’s very obvious from a product standpoint that they see education as one of, if not the primary, place to go with their product,” said Riley. “And the fact that AFT is willing to say, ‘Cool, let’s get some of that money and we’ll build a training center to help teachers use it,’ I can see why OpenAI would jump all over that.”

But he questioned whether AI training is what AFT members really want. He suggested instead that the union should recommit to helping teachers more deeply understand how learning works. “They haven’t been opposed to it,” he said, noting that it has long run an “” column in the magazine it mails to members. “But in reality it just hasn’t been a priority. Improving pedagogy hasn’t really been, to my eyes, a union priority for a long time.”

Riley, who in 2024 founded the think tank to explore AI issues, said an organization like AFT should ideally be thinking about whether embracing AI will lead to better outcomes for children — or whether it could “potentially erode and devalue the work of human teaching” while opening up schools as customers for AI companies. 

Representatives of OpenAI and Anthropic did not immediately respond to requests for comment, but in an email, Microsoft’s Naria Santa Lucia said, “This isn’t about Microsoft’s technology, our focus is on making AI broadly accessible, so everyone has a fair shot at the future. If we collectively get this right, AI becomes a bridge to opportunity — not a barrier.”

During the academy’s unveiling, Chris Lehane, OpenAI’s chief global affairs officer, said AI technology “is coming — it is going to drive productivity gains. Can we ensure that those productivity gains are democratized so as many people as possible participate in them? And there is no better place to begin that work than in the classroom.”

OpenAI has noted that many of its users are students. In February, it said that of college-aged young adults in the U.S. use ChatGPT, with one in four of their queries related to learning and school work.

While a few observers said the tech giants are making a play for market share among the nation’s K-12 students, they noted that the companies are also filling an important role. 

“It’s welcome news that technology companies are bidding against each other — to outdo each other — to invest in public education,” said Zarek Drozda, executive director of , a coalition of groups advancing data science education. “I think that’s exciting at a time when federal investment in education is uncertain. Seeing industry step up is quite meaningful.”

But he said he’s concerned that the training might stop short after teaching teachers — and by extension students — simply how to use AI. “Training needs to go beyond use,” he said. “If we want to train a generation of students to be AI-ready, internationally competitive, they have to understand how these tools work under the hood, when and why the tool might be wrong, and how they can customize LLMs [Large Language Models] or other models for their own pursuits, versus simply taking what’s given.”

He’s also concerned that the AFT has laid out a vision spanning just five years. “We want there to be a deep investment in upskilling teachers for the skills that they will need to adapt to, not just AI, but what is the AI model five years from now?” he said. “What is the next emerging technology that the field should be ready to adapt to?”

More than just a commitment to training, Drozda said, the union and its partners should commit to a long-term sustainability plan for teacher training to attract new, young career professionals to the field.

Alex Kotran, founder and CEO of the , agreed that investing in teacher training is worthwhile. “That’s a very big rock that needs to be moved.” But the reported $23 million commitment from the three tech giants “is a bit of a drop in the bucket” considering their valuations, “symbolic at best.”

That said, AFT’s involvement could make the training more palatable for many school district leaders, he noted, since one of the uncertainties in training efforts typically is whether unions will allow members to attend under contract rules. By taking the lead in developing the training academy, “the unions have planted a flag and said, ‘PD [professional development] is important.’”

All the same, tech companies are in the business of selling their products, making them imperfect messengers for AI literacy, he said. “They’re deeply incentivized on one side, and it isn’t necessarily for the benefit of students.” 

Other industry watchers fear the partnership could be viewed as a high-profile bid for market share at a critical time in the AI industry’s history. 

“This is a land-grab moment,” said Alex Sarlin, co-host of the podcast. “I mean, this technology is only three years old. There are already three or four major players in it, if you don’t count China, and they all want to be the one left standing.”

For its part, Google has said its suite of Gemini educational AI tools would for free to all educators with Google Workspace for Education accounts.

While it was the only major player not included in the AFT announcement, Sarlin said Google is, in some ways, “playing the incumbent in this because in K-12, they’re already there.” Given the dominance of Chromebook laptops, the management tool and its programs, the search giant is “embedded in K-12,” he said. “Open AI and Anthropic, they’re basically consumer products that are being used by teachers.”

‘Oh yeah, what could go wrong?’

Matt Miller, an Indiana high school Spanish teacher, educational consultant and for teachers, said his colleagues are hungry for high-quality, classroom-tested training, but that what they often get from AI companies is over-the-top talk about “how much the world is going to change and how we’re revolutionizing education,” with promises to help teachers work more efficiently.

Trainings typically skim over the fact that most students are simply using generative AI for “cognitive offloading,” Miller said, avoiding critical thinking and skill development  “and letting AI do it for them.” Many teachers, meanwhile, are searching for ways to “AI-proof” their classrooms. 

The sessions typically all end the same way, he said: “It all sort of funnels back to their product.” 

Miller, whose latest book, in 2023, was , said the AFT/OpenAI/Anthropic partnership “scares the crap out of me.”

“Whenever you get that marriage between an organization and big companies, we just keep asking ourselves, ‘Oh, yeah, what could go wrong?’”

Money means influence, Miller said, so will the curriculum be “tool-agnostic? Is it going to be about the technology? Is it going to be about pedagogy? Or is it going to be a customized tutorial of how you can use our tool to do X, Y and Z?”

AFT’s Weil said those concerns are understandable but short-sighted. AI developers, he said, “don’t get to engage with us if you’re not going to be agnostic about the tools.” The academy’s directors talk openly to the developers “about how we have to have a practical, real relationship. This can’t be about product selling.”

More broadly, the partnerships are a way to exert influence upon how AI operates in schools and classrooms.

During the academy’s unveiling, Weingarten said its lessons will be “as open-source as possible,” not just for the union’s 1.8 million members but more broadly through its free platform.

For his part, Weil said AI is “not going to go away. Nobody’s going to put AI back in the bottle. It’s here. The young people, for them to be successful in their jobs in the future, are going to have to know how to effectively and efficiently and safely use these tools. So why wouldn’t the education system help with that process?”

That’s likely the message that union leaders have been getting from members, said Sarlin, the podcast co-host. “There was probably a moment a couple years ago where they were sort of teetering, where they could have gone anti-AI,” he said. “But I think at this point that’s not where the puck is headed.”

More than 400,000 K-12 educators across the country will get free training in AI through a $23 million partnership between a major teachers union and leading tech companies that is designed to close gaps in the use of technology and provide a national model for AI-integrated curriculum.

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The new National Academy for AI Instruction will be based in the downtown Manhattan headquarters of the United Federation of Teachers, the New York City affiliate of the American Federation of Teachers, and provide workshops, online courses, and hands-on training sessions. This hub-based model of teacher training was inspired by work of unions like the United Brotherhood of Carpenters that have created similar training centers with industry partners, according to AFT President Randi Weingarten.

“Teachers are facing huge challenges, which include navigating AI wisely, ethically and safely,” Weingarten said at a press conference Tuesday announcing the initiative. “The question was whether we would be chasing it or whether we would be trying to harness it.”

The initiative involves the AFT, UFT, OpenAI, Microsoft, and Anthropic.

The Trump administration . More than 50 companies to provide grants, education materials, and technology to invest in AI education.

In the wake of and , Weingarten sees this partnership with private tech companies as a crucial investment in teacher preparation.

“We are actually ensuring that kids have, that teachers have, what they need to deal with the economy of today and tomorrow,” Weingarten said.

The academy will be based in a city where the school system , claiming it would interfere with the development of critical thinking skills. A few months later, then-New York City schools Chancellor David Banks , pledging to help schools smartly incorporate the technology. He said New York City schools would embrace the potential of AI to drive individualized learning. But concrete plans have been limited.

The AFT, meanwhile, has tried to position itself as a leader in the field. Last year, the union and funded pilot programs around the country.

Vincent Plato, New York City Public Schools K-8 educator and UFT Teacher Center director, said the advent of AI reminds him of when teachers first started using word processors.

“We are watching educators transform the way people use technology for work in real time, but with AI it’s on another unbelievable level because it’s just so much more powerful,” he said in a press release announcing the new partnership. “It can be a thought partner when they’re working by themselves, whether that’s late-night lesson planning, looking at student data or filing any types of reports — a tool that’s going to be transformative for teachers and students alike.”

Teachers who frequently use AI tools report saving 5.9 hours a week, according to . These tools are most likely to be used to support instructional planning, such as creating worksheets or modifying material to meet students’ needs. Half of the teachers surveyed stated that they believe AI will reduce teacher workloads.

“Teachers are not only gaining back valuable time, they are also reporting that AI is helping to strengthen the quality of their work,” Stephanie Marken, senior partner for U.S. research at Gallup, said in a press release. “However, a clear gap in AI adoption remains. Schools need to provide the tools, training, and support to make effective AI use possible for every teacher.”

While nearly half of school districts surveyed by the research corporation RAND have reported training teachers in utilizing AI-powered tools by fall 2024, . District leaders across the nation report a scarcity of external experts and resources to provide quality AI training to teachers.

OpenAI, a founding partner of the National Academy for AI Instruction, will contribute $10 million over the next five years. The tech company will provide educators and course developers with technical support to integrate AI into classrooms as well as software applications to build custom, classroom-specific tools.

Tech companies would benefit from this partnership by “co-creating” and improving their products based on feedback and insights from educators, said Gerry Petrella, Microsoft general manager, U.S. public policy, who hopes the initiative will align the needs of educators with the work of developers.

In a sense, the teachers are training AI products just as much as they are being trained, according to Kathleen Day, a lecturer at Johns Hopkins Carey Business School. Day emphasized that through this partnership, AI companies would gain access to constant input from educators so they could continually strengthen their models and products.

“Who’s training who?” Day said. “They’re basically saying, we’ll show you how this technology works, and you tell us how you would use it. When you tell us how you would use it, that is a wealth of information.”

Many educators and policymakers are also concerned that introducing AI into the classroom could endanger . Racial bias in grading could also be reinforced by AI programs, according to research by The Learning Agency.

Additionally, Trevor Griffey, a lecturer in labor studies at the University of California Los Angeles, that tech firms could use these deals to market AI tools to students and expand their customer base.

This initiative to expand AI access and training for educators was likened to New Deal efforts in the 1930s to expand equal access to electricity by Chris Lehane, OpenAI’s chief global affairs officer. By working with teachers and expanding AI training, Lehane hopes the initiative will “democratize” access to AI.

“There’s no better place to do that work than in the classroom,” he said at the Tuesday press conference.

This story was originally published by Chalkbeat. Chalkbeat is a nonprofit news site covering educational change in public schools. Sign up for their newsletters at .

In the annals of artificial intelligence, Feb. 16, 2011, was a watershed moment.

That day, IBM’s Watson supercomputer finished off a three-game shellacking of Jeopardy! champions Ken Jennings and Brad Rutter. Trailing by over $30,000, Jennings, now the show’s host, wrote out his Final Jeopardy answer in mock resignation: “I, for one, welcome our computer overlords.”

A lark to some, the experience galvanized Satya Nitta, a longtime computer researcher at IBM’s Watson Research Center in Yorktown Heights, New York. Tasked with figuring out how to apply the supercomputer’s powers to education, he soon envisioned tackling ed tech’s most sought-after challenge: the world’s first tutoring system driven by artificial intelligence. It would offer truly personalized instruction to any child with a laptop — no human required.

“I felt that they’re ready to do something very grand in the space,” he said in an interview. 

Nitta persuaded his bosses to throw more than $100 million at the effort, bringing together 130 technologists, including 30 to 40 Ph.D.s, across research labs on four continents. 

But by 2017, the tutoring moonshot was essentially dead, and Nitta had concluded that effective, long-term, one-on-one tutoring is “a terrible use of AI — and that remains today.”

For all its jaw-dropping power, Watson the computer overlord was a weak teacher. It couldn’t engage or motivate kids, inspire them to reach new heights or even keep them focused on the material — all qualities of the best mentors.

It’s a finding with some resonance to our current moment of AI-inspired doomscrolling about the future of humanity in a world of ascendant machines. “There are some things AI is actually very good for,” Nitta said, “but it’s not great as a replacement for humans.”

His five-year journey to essentially a dead-end could also prove instructive as ChatGPT and other programs like it fuel a renewed, multimillion-dollar experiment to, in essence, prove him wrong.

Some of the leading lights of ed tech, from to , are trying to pick up where Watson left off, offering AI tools that promise to help teach students. Sal Khan, founder of Khan Academy, last year said AI has the potential to bring “probably the ” that education has ever seen. He wants to give “every student on the planet an artificially intelligent but amazing personal tutor.”

A 25-year journey

To be sure, research on high-dosage, one-on-one, in-person tutoring is : It’s interventions available, offering significant improvement in students’ academic performance, particularly in subjects like math, reading and writing.  

But traditional tutoring is also “breathtakingly expensive and hard to scale,” said Paige Johnson, a vice president of education at Microsoft. One school district in West Texas, for example, recently spent in federal pandemic relief funds to tutor 6,000 students. The expense, Johnson said, puts it out of reach for most parents and school districts. 

For IBM, the opportunity to rebalance the equation in kids’ favor was hard to resist. 

The Watson lab is legendary in the computer science field, with and six Turing Award winners among its ranks. It’s where modern was invented, and home to countless other innovations such as barcodes and the magnetic stripes on credit cards that make . It’s also where, in 1997, Deep Blue beat Garry Kasparov, essentially inventing the notion that AI could “think” like a person.

The heady atmosphere, Nitta recalled, inspired “a very deep responsibility to do something significant and not something trivial.”

Within a few years of Watson’s victory, Nitta, who had arrived in 2000 as a chip technologist, rose to become IBM Research’s global head of AI solutions for learning. For the Watson project, he said, “I was just given a very open-ended responsibility: Take Watson and do something with it in education.”

Nitta spent a year simply reading up on how learning works. He studied cognitive science, neuroscience and the decades-long history of “intelligent tutoring systems” in academia. Foremost in his reading list was the research of Stanford neuroscientist Vinod Menon, who’d put elementary schoolers through a 12-week math tutoring session, collecting before-and-after scans of their brains using an MRI. Tutoring, he found, produced nothing less than an increase in neural connectivity. 

Nitta returned to his bosses with the idea of an AI-powered cognitive tutor. “There’s something I can do here that’s very compelling,” he recalled saying, “that can broadly transform learning itself. But it’s a 25-year journey. It’s not a two-, three-, four-year journey.”

IBM drafted two of the highest-profile partners possible in education: the children’s media powerhouse Sesame Workshop and Pearson, the international publisher.

One product envisioned was a voice-activated Elmo doll that would serve as a kind of digital tutoring companion, interacting fully with children. Through brief conversations, it would assess their skills and provide spoken responses to help kids advance.

Meanwhile, Pearson promised that it could soon allow college students to “dialogue with Watson in real time.”

Nitta’s team began designing lessons and putting them in front of students — both in classrooms and in the lab. In order to nurture a back-and-forth between student and machine, they didn’t simply present kids with multiple-choice questions, instead asking them to write responses in their own words.

It didn’t go well.

Some students engaged with the chatbot, Nitta said. “Other students were just saying, ‘IDK’ [I don’t know]. So they simply weren’t responding.” Even those who did began giving shorter and shorter answers. 

Nitta and his team concluded that a cold reality lay at the heart of the problem: For all its power, Watson was not very engaging. Perhaps as a result, it also showed “little to no discernible impact” on learning. It wasn’t just dull; it was ineffective.

“Human conversation is very rich,” he said. “In the back and forth between two people, I’m watching the evolution of your own worldview.” The tutor influences the student — and vice versa. “There’s this very shared understanding of the evolution of discourse that’s very profound, actually. I just don’t know how you can do that with a soulless bot. And I’m a guy who works in AI.”

When students’ usage time dropped, “we had to be very honest about that,” Nitta said. “And so we basically started saying, ‘OK, I don’t think this is actually correct. I don’t think this idea — that an intelligent tutoring system will tutor all kids, everywhere, all the time — is correct.”

‘We missed something important’

IBM soon switched gears, debuting another crowd-pleasing Watson variation — this time, a touching throwback: It engaged in . In a televised demonstration in 2019, it went up against debate champ Harish Natarajan on the topic “Should we subsidize preschools?” Among its arguments for funding, the supercomputer offered, without a whiff of irony, that good preschools can prevent “future crime.” Its current iteration, , focuses on helping businesses build AI applications like “intelligent customer care.” 

Nitta left IBM, eventually taking several colleagues with him to create a startup called . It uses voice-activated AI to safely help teachers do workaday tasks such as updating digital gradebooks, opening PowerPoint presentations and emailing students and parents. 

Thirteen years after Watson’s stratospheric Jeopardy! victory and more than one year into the Age of ChatGPT, Nitta’s expectations about AI couldn’t be more down-to-earth: His AI powers what’s basically “a carefully designed assistant” to fit into the flow of a teacher’s day. 

To be sure, AI can do sophisticated things such as generating quizzes from a class reading and editing student writing. But the idea that a machine or a chatbot can actually teach as a human can, he said, represents “a profound misunderstanding of what AI is actually capable of.” 

Nitta, who still holds deep respect for the Watson lab, admits, “We missed something important. At the heart of education, at the heart of any learning, is engagement. And that’s kind of the Holy Grail.”

These notions aren’t news to those who do tutoring for a living. , which offers live and online tutoring in 500 school districts, relies on AI to power a lesson plan creator that helps personalize instruction. But when it comes to the actual tutoring, humans deliver it, said , chief institution officer at , which operates Varsity.

”The AI isn’t far enough along yet to do things like facial recognition and understanding of student focus,” said Salcito, who spent 15 years at Microsoft, most of them as vice president of worldwide education. “One of the things that we hear from teachers is that the students love their tutors. I’m not sure we’re at a point where students are going to love an AI agent.”

The No. 1 factor in a student’s tutoring success is consistently, research suggests. As smart and efficient as an AI chatbot might be, it’s an open question whether most students, especially struggling ones, would show up for an inanimate agent or develop a sense of respect for its time.

When Salcito thinks about what AI bots now do in education, he’s not impressed. Most, he said, “aren’t going far enough to really rethink how learning can take place.” They end up simply as fast, spiffed-up search engines. 

In most cases, he said, the power of one-on-one, in-person tutoring often emerges as students begin to develop more honesty about their abilities, advocate for themselves and, in a word, demand more of school. “In the classroom, a student may say they understand a problem. But they come clean to the tutor, where they expose, ‘Hey, I need help.’”

Cognitive science suggests that for students who aren’t motivated or who are uncertain about a topic, only will help. That requires a focused, caring human, watching carefully, asking tons of questions and reading students’ cues. 

Jeremy Roschelle, a learning scientist and an executive director of Digital Promise, a federally funded research center, said usage with most ed tech products tends to drop off. “Kids get a little bored with it. It’s not unique to tutors. There’s a newness factor for students. They want the next new thing.” 

Even now, Nitta points out, research shows that big commercial AI applications don’t seem to hold users’ attention as well as top entertainment and social media sites like YouTube, Instagram and TikTok. dubbed the user engagement of sites like ChatGPT “lackluster,” finding that the proportion of monthly active users who engage with them in a single day was only about 14%, suggesting that such sites aren’t very “sticky” for most users.

For social media sites, by contrast, it’s between 60% and 65%. 

One notable AI exception: , an app that allows users to create companions of their own among figures from history and fiction and chat with the likes of Socrates and Bart Simpson. It has a stickiness score of 41%.

As startups like offer “your child’s superhuman tutor,” starting at $29 per month, and publicly tests its popular Khanmigo AI tool, Nitta maintains that there’s little evidence from learning science that, absent a strong outside motivation, people will spend enough time with a chatbot to master a topic.

“We are a very deeply social species,” said Nitta, “and we learn from each other.”

IBM declined to comment on its work in AI and education, as did Sesame Workshop. A Pearson spokesman said that since last fall it has been ​​beta-testing AI study tools keyed to its e-textbooks, among other efforts, with plans this spring to expand the number of titles covered. 

Getting ‘unstuck’

IBM’s experiences notwithstanding, the search for an AI tutor has continued apace, this time with more players than just a legacy research lab in suburban New York. Using the latest affordances of so-called large language models, or LLMs, technologists at Khan Academy believe they are finally making the first halting steps in the direction of an effective AI tutor. 

Kristen DiCerbo remembers the moment her mind began to change about AI. 

It was September 2022, and she’d only been at Khan Academy for a year-and-a-half when she and founder Khan got access to a beta version of ChatGPT. Open AI, ChatGPT’s creator, had asked Microsoft co-founder Bill Gates for more funding, but he told them not to come back until the chatbot could pass an Advanced Placement biology exam.

So Open AI queried Khan for sample AP biology questions. He and DiCerbo said they’d help in exchange for a peek at the bot — and a chance to work with the startup. They were among the first people outside of Open AI to get their hands on GPT-4, the LLM that powers the upgraded version of ChatGPT. They were able to test out the AI and, in the process, become amateur AI before anyone had even heard of the term. 

Like many users typing in queries in those first heady days, the pair initially just marveled at the sophistication of the tool and its ability to return what felt, for all the world, like personalized answers. With DiCerbo working from her home in Phoenix and Khan from the nonprofit’s Silicon Valley office, they traded messages via Slack.

“We spent a couple of days just going back and forth, Sal and I, going, ‘Oh my gosh, look what we did! Oh my gosh, look what it’s saying — this is crazy!’” she told an audience during a recent at the University of Notre Dame. 

She recounted asking the AI to help write a mystery story in which shoes go missing in an apartment complex. In the back of her mind, DiCerbo said, she planned to make a dog the shoe thief, but didn’t reveal that to ChatGPT. “I started writing it, and it did the reveal,” she recalled. “It knew that I was thinking it was going to be a dog that did this, from just the little clues I was planting along the way.”

More tellingly, it seemed to do something Watson never could: have engaging conversations with students.

DiCerbo recounted talking to a high school student they were working with who told them about an interaction she’d had with ChatGPT around The Great Gatsby. She asked it about F. Scott Fitzgerald’s famous , which scholars have long interpreted as symbolizing Jay Gatsby’s out-of-reach hopes and dreams.

“It comes back to her and asks, ‘Do you have hopes and dreams just out of reach?’” DiCerbo recalled. “It had this whole conversation” with the student.

The pair soon tore up their 2023 plans for Khan Academy. 

It was a stunning turn of events for DiCerbo, a Ph.D. educational psychologist and former senior Pearson research scientist who had spent more than a year on the failed Watson project. In 2016, Pearson that Watson would soon be able to chat with college students in real time to guide them in their studies. But it was DiCerbo’s teammates, about 20 colleagues, who had to actually train the supercomputer on thousands of student-generated answers to questions from textbooks — and tempt instructors to rate those answers. 

Like Nitta, DiCerbo recalled that at first things went well. They found a natural science textbook with a large user base and set Watson to work. “You would ask it a couple of questions and it would seem like it was doing what we wanted to,” answering student questions via text.

But invariably if a student’s question strayed from what the computer expected, she said, “it wouldn’t know how to answer that. It had no ability to freeform-answer questions, or it would do so in ways that didn’t make any sense.” 

After more than a year of labor, she realized, “I had never seen the ‘OK, this is going to work’ version” of the hoped-for tutor. “I was always at the ‘OK, I hope the next version’s better.’”

But when she got a taste of ChatGPT, DiCerbo immediately saw that, even in beta form, the new bot was different. Using software that quickly predicted the most likely next word in any conversation, ChatGPT was able to engage with its human counterpart in what seemed like a personal way.

Since its debut in March 2023, Khanmigo has turned heads with what many users say is a helpful, easy-to-use, natural language interface, though a few users have pointed out that it sometimes .

Surprisingly, DiCerbo doesn’t consider the popular chatbot a full-time tutor. As sophisticated as AI might now be in motivating students to, for instance, try again when they make a mistake, “It’s not a human,” she said. “It’s also not their friend.”

Khan Academy’s shows their tool is effective with as little as 30 minutes of practice and feedback per week. But even as many startups promise the equivalent of a one-on-one human tutor, DiCerbo cautions that 30 minutes is not going to produce miracles. Khanmigo, she said, “is not a solution that’s going to replace a human in your life,” she said. “It’s a tool in your toolbox that can help you get unstuck.”

‘A couple of million years of human evolution’

For his part, Nitta says that for all the progress in AI, he’s not persuaded that we’re any closer to a real-live tutor that would offer long-term help to most students. If anything, Khanmigo and probabilistic tools like it may prove to be effective “homework helpers.” But that’s where he draws the line. 

“I have no problem calling it that, but don’t call it a tutor,” he said. “You’re trying to endow it with human-like capabilities when there are none.”  

Unlike humans, who will typically do their best to respond genuinely to a question, the way AI bots work —by digesting pre-existing texts and other information to come up with responses that seem human — is akin to a “statistical illusion,” writes Harvard Business School Professor . “They’ve just been well-trained by humans to respond to humans.”

Largely because of this, Nitta said, there’s little evidence that a chatbot will continuously engage people as a good human tutor would.

What would change his mind? Several years of research by an independent third party showing that tools like Khanmigo actually make a difference on a large scale — something that doesn’t exist yet.

DiCerbo also maintains her hard-won skepticism. She knows all about the halting early decades of computers a century ago, when experimental, punch-card operated “teaching machines” guided students through rudimentary multiple-choice lessons, often with simple rewards at the end. 

In her talks, DiCerbo urges caution about AI revolutionizing education. As much as anyone, she is aware of the expensive failures that have come before. 

In her recent talk at Notre Dame, she did her best to manage expectations of the new AI, which seems so limitless. In one-to-one teaching, she said, there’s an element of humanity “that we have not been able to — and probably should not try — to replicate in artificial intelligence.” In that respect, she’s in agreement with Nitta: Human relationships are key to learning. In the talk, she noted that students who have a person in school who cares about their learning have higher graduation rates. 

But still.

ChatGPT now has 100 million weekly users, according to . That record-fast uptake makes her think “there’s something interesting and sticky about this for people that we haven’t seen in other places.”

Being able to engineer prompts in plain English opens the door for more people, not just engineers, to create tools quickly and iterate on what works, she said. That democratization could mean the difference between another failed undertaking and agile tools that actually deliver at least a version of Watson’s promise.��

Seven years after he left IBM to start his new endeavor, Nitta is philosophical about the effort. He takes virtually full responsibility for the failure of the Watson moonshot. In retrospect, even his 25-year timeline for success may have been naive.

“What I didn’t appreciate is, I actually was stepping into a couple of million years of human evolution,” he said. “That’s the thing I didn’t appreciate at the time, which I do in the fullness of time: Mistakes happen at various levels, but this was an important one.”

Our struggles teaching the subject — whether evidenced by our middling performance against peer nations or the striking even by young children — are a stumbling block from reaching their goals, he has argued. And the obstacle has only grown since the generational setback of COVID-19, which triggered the greatest learning crisis in history. Scores on the latest iteration of the National Assessment of Educational Progress sank to levels last seen in the early 2000s.

That’s part of the reason why the Bill & Melinda Gates Foundation announced last fall that it would make math “the cornerstone of our K–12 education program strategy” over the next decade. Powered by $1.1 billion in new investments, the philanthropic giant will work with its partners to devise better curricular materials, improve teacher training and professional development, and fund research and development breakthroughs that hold the potential to transform the classroom experience. 

The agenda partially reflects Gates’s personal fascination with mathematics, which dates back to his years as a student. Before embarking on perhaps the most consequential career in the history of software, the future Microsoft founder blazed through Harvard’s , only focusing exclusively on computer science because he considered it unlikely that he would become one of the world’s greatest mathematicians. Distinguishing himself even in the rare air of tech founders, he that settled the delicious-sounding question of “pancake sorting” for decades.

In a broader sense, the huge bet on math also builds on the Foundation’s existing work in the K–12 sphere. Gates has proven one of the most influential actors in American education over the first part of this century, fostering a movement toward small schools and promoting the adoption of the Common Core State Standards. Even when some efforts didn’t bear fruit — such as a failed seven-year campaign to strengthen teacher evaluation — Gates’s deep pockets and commitment to experimentation have helped make the weather in education policy for the last two decades.

Other priorities are expected to take a backseat through 2026, while math programming will grow from 40 percent of the organization’s education budget to 100 percent. It’s a commitment that dovetails with the public’s own concerns, Gates says: According to a poll released this week by the Foundation, large majorities of adults believe that math instruction needs an overhaul to become more relevant and engaging.

In a discussion with ����Ӱ��’s Kevin Mahnken at the 2023 ASU+GSV summit — an educational technology conference that draws thousands of educators, investors, and entrepreneurs annually — Gates talked about America’s post-pandemic math deficits and what it will take to climb out of them. He also touched on the potential rewards to helping kids overcome their anxiety and fall in love with math.

“There is a gigantic upside in improving our public education system, both economically and in terms of equity,” Gates said. “But the country’s not falling apart as much as you might think.”

This conversation has been edited for length and clarity. 

����Ӱ��: What is the extent of the math learning crisis that’s followed COVID? And can it be compared to the aftermath of other society-level emergencies, like the financial crisis of 2007?

Bill Gates: Even pre-pandemic, what the U.S. had was very disappointing. Math is a basic skill for many areas, and your attitude and success with regard to math is very predictive of whether you graduate high school or go on to higher education.

In our K–12 strategy, the Gates Foundation has shifted to math as our biggest priority by quite a bit. It’s a decision we made around the year before the pandemic started. It’s fair to say that the pandemic worsened math scores more than any other scores. Math is kind of a specialized skill in that your exposure can drop to near zero if you’re out of school, whereas your exposure to reading — and maybe, to some degree, writing — may not drop as dramatically. So it’s not that surprising, and we also see that math decay over the summer is dramatically higher than reading decay and writing decay.

You’ve got this huge loss, but there are some viewpoints that we’re starting to see some meaningful rebound. There was on that a few months ago. Then again, because our progress in math over the last 20 years has been so modest, the scores have hardly gone up at all. They’ve gone up a little bit. I’m only saying this to note, okay, we’re back where we were 10 years ago. But that’s partly a statement about the size of the loss, and it’s partly a statement about the very, very slow nature of the gains that we’ve had in math. The U.S. is doing quite poorly compared to other rich countries, even though the amount we spend on it is higher than any other, by substantial amounts.

The losses are tragic, though there are different ways of looking at them in terms of how much is in the inner city and inequitable. Some reports show learning loss as pretty much across-the-board; others show it much more in their inner city. If you abstract out how long your classroom was closed or what degree of online access you had, that is pretty predictive of lower performance.

And sadly, that does correlate with the lower income, minority-serving schools being worse off because their ability to do online learning, to get internet access, to get a device — almost every element that has to come together for good online learning — is less present in an inner-city public school than, to take the extreme, a suburban private school. And in the U.S., we had our schools closed longer than any other country. 

What are the big-picture costs of poor math learning on America’s competitiveness as both an economic and a geopolitical force?

The shortcomings of the U.S. education system are clear in terms of the inequity you end up with: the kind of jobs, salaries, mobility you’d like to see in society. Education is the great enabler of mobility, and we’re falling short on that. In fact, the U.S. economy has done relatively well because there are so many factors that enter into it, including the ability of the U.S. to draw very talented people from the entire world. But I think the predictions that this is going to hurt us in the long run are true, and we’d be further ahead if we were running our education system as well as we’d like to. 

This is why the Gates Foundation basically has two big things we do. The global work, which is centered on health and some things related to health, is the biggest thing for us because the vacuum of resources and thinking for and childhood was mind-blowing. In some of those areas, the Foundation is almost alone.

Research and philanthropy related to education should be a lot larger than it is, but we’re not alone there. There are a lot of players, and by some measures we’re one of the biggest players. There is a gigantic upside in improving our public education system, both economically and in terms of equity. But the country’s not falling apart as much as you might think. We make up for it by having universities that are the strongest in the world, and we do get some intellectual capacity because we’re an attractive place. Almost no other country in the world has this: When people say, “Hey, China’s strong,” they’re not saying that all great scholars in the world are flocking to China or India or Japan. Other than a few other English-speaking countries, the U.S. is truly unique in that respect.

It sounds like you’re saying that America isn’t so much falling behind the rest of the world as it is falling behind its own potential. That reminds me of research from Harvard’s Tom Kane, which found that we could lose almost a trillion dollars in future wages if eighth-grade math deficits aren’t significantly mitigated.

We’re going to be paying a price for a long time in areas that are hard to measure. We’ve seen this in terms of mental health problems, which obviously interact with young people’s persistence in education. The isolation that came out of the pandemic was a huge setback. How you map that onto economic figures — okay, there are a lot of assumptions in those numbers — but we’ve got a lot of making up to do. 

And most of the resources that help with that make-up are only going to be around for a couple of years. We will not have remedied our NAEP deficit — even to get back to where we were before the pandemic, which wasn’t an ideal situation — during the time that the ESSER money is still available. You also have shrinking school districts in many places, and scaling down while maintaining quality can be a very difficult thing. So U.S. education is a challenged space.

Switching gears a bit, you’ve previously compared the emergence of ChatGPT with the development of the microprocessor. I’m wondering how you contextualize it alongside other civilizational breakthroughs, like the Green Revolution or the emergence of vaccines.

The Holy Grail of computer science from the first time anybody did computation was how its abilities could compare with human capabilities. The so-called was formulated before I was born, and throughout my history of using computers, there were things like or obscure things like , which sort of tried to be a dialogue machine. Almost everybody who starts writing programs will do some random sentence generator where you have various grammatical patterns and sets of words and generate blather. It’s funny because sometimes it almost seems to make sense. 

We’ve been making progress in human sensory things, like matching visual recognition and speech recognition of humans. When I worked on AI stuff in the ‘70s and ‘80s, we weren’t making that much progress, but then there was the combination of scaling and new techniques — so-called machine learning techniques. It didn’t bother people that much that it could listen better than us or that, in a sense, it could see better than us, but there was no ability to read or write.

What we’ve got now is pretty amazing. It’s got huge limitations in terms of its accuracy and how you can train it. But given the scale of the industry and the promise — the amount of activity and the pace of innovation to take the current limitations and make it more effective — it’s pretty mind-blowing.

Its reading and writing capability has got everyone saying, “Wow.” When you sit at the computer creating models or taking a document or making a presentation, its ability to help you be more productive on those things is really phenomenal. And we’ve gone from no ability to do that to a pretty substantial ability just in this calendar year.

You mentioned your twin interests of public health and public education. Do you think the Gates Foundation’s successes in the former sphere — perhaps measured in the huge decline of malaria deaths in this century — are greater than those in the latter? And if so, why might that be?

The progress on public health, because it was so ignored, is really unbelievably dramatic. I’m not sure most people are aware of it, but if you gave a report card to humanity of what we’ve done well since the year 2000, at the top of that report card would be from over 10 million to under 5 million. Now, most of those deaths were in poor countries, and so the visibility to most Americans of that miracle is extremely low even though some American government aid was part of that; certainly, mass amounts of government science were part of that. And our Foundation played a fairly central role, if not a solo role. We have a lot of partners, including the U.S. government. 

There’s no equivalent in education. The equivalent would have been if the dropout rate from high schools was cut in half, that the dropout rate from college was cut in half, that U.S. math scores went up 30 percent, that we’re at the top of the lead tables. 

No such miracle took place.

With education, you do have trends that are tough. Very appropriately, the labor market gives capable women way more opportunities than it did in the past. But the education system cheated somewhat by having very talented women who weren’t given the opportunities they should have. So you have a little bit of adjustment in your teaching pool. And given where you have population growth, the average incomes of the kids going into the public school system is a bit lower, with more non-English-speaking households. That’s a little bit of a negative factor, but we’ve maintained and improved slightly. We’ve improved math scores slightly, racial equity slightly, high school graduation rates slightly.

It’s interesting. You can come to a conference like this or visit a really exemplary school and be reminded, “Wow, there are outliers!” There are microcosms where things are pretty fantastic, even at the school level. Certainly at the classroom level, you’ve always been able to go find the Stand and Deliver-style, unbelievable teacher. And whenever you find variance, you can say to yourself, “Hey, how come we can’t capture that best practice and get the average teacher to be close to that top teacher? What is it about training and understanding and incentives that makes that very difficult?”

We haven’t succeeded as much on that as we’d like. We have all this technology where, yes, you can look up YouTube videos and Wikipedia articles and sit there and do math questions for free on Khan Academy. And yet none of that — none of the seriousness about transferring best practices in terms of traditional teaching, and none of the new technology — has come in and really made that dramatic of a difference. Somebody could say, “Well, give up,” but not many people want to do that. We’re stubborn enough to believe that the improvements that have been made were worthwhile even though, compared on a per-dollar basis to what we’ve done in global health, it’s just not the same thing.

We save lives for $1,000 per life. And in education, [laughs] we haven’t done the equivalent of saving a life for $1,000. We feel like our work has been good, including helping the field find dead ends. In education, the R&D investment about “Why is that teacher good” or “Why should you insist on homework being done?” is way less than what it should be. And our foundation is one of many that’s tried to bring more understanding to what works and what doesn’t.

You probably saw the proposal to dramatically increase the reach of the Institute for Education Sciences and establish something like a “DARPA for education,” with the aim of accelerating the development of breakthrough technologies for learning. It seems like there might be a bigger role for the federal government to play in this field.

For all governments, all over the world; a lot of what we learn about education is pretty universal. But anyway, as a percentage of its size in the economy and the benefit of improving it, you could say there’s pretty dramatic underinvestment in K–12 research because the numbers are actually quite small. And if I said to you that the best math teacher was somebody 50 years ago, you could actually believe that. If somebody said that the best cancer doctor was some guy 50 years ago, you’d go, “What the hell are you talking about? That’s the silliest thing I’ve ever heard.”

So the field has changed and improved, but pretty modestly. Helping those researchers — that’s still worth investing in. I was at a middle school this morning called where — together with a partner, — we do some of our math instruction work. When you get into the classroom, it’s fascinating to see what works and what doesn’t. I have to say, when you see the teachers who are really engaged in trying to help other teachers do better, it often reminds you why this is an important field and that there really is promise.

When I think about the big K–12 reforms that were launched the last few decades by both Washington and institutions like the Gates Foundation, it seems like there’s now much less political will to pursue huge projects like those. I’m wondering if you are at all worried that really ambitious ventures — you could also include vaccine development and advocacy — are going to be a little harder to launch, harder to support.

Hmm. I’d say that, both under Bush and Obama, there was a real effort at the federal level to drive change in education. Of course, the federal level has the advantage that it affects all 50 states. It also has the disadvantage that you’re writing some rule about, “Please spend the money on this thing” in Washington, D.C., and then have many layers and diverse environments in the states.

For better or for worse, the amount of experimentation and top-down system reform that’s going to come from the federal government after the Obama period will be very modest. You can say that’s good or bad, but it’s just a fact that Democrats and Republicans in Congress are not thinking, “We’re going to change the way education is done.” The action has moved, you could say, to the state, district or classroom level, or these ed tech people, or the things that philanthropists fund. 

There isn’t one common theme. Charter schools continue to advance, although they’re a modest percentage of all students. Interestingly, there’s a huge shift such that charter schools are growing more in red states than blue states now. It’s complicated to characterize the results, but they’re largely good, and they are laboratories of learning. A lot of good ideas that should suffuse themselves into the broader public system come out of that charter experience.

I don’t think it’s that people are satisfied with our current education system. We did a survey about math recently where parents were very willing to say, “Hey, instruction should be different to drive the relevance and the engagement,” so there’s still open-mindedness that education can be better. Hopefully it’s not too politicized in that, if you show that a curriculum can get better results, people view that as helping kids and helping society.

I’m sure that if you get into some political topics in the curriculum, you may run into some sort of deadlock. But most educational things can stay away from those issues. The way we teach multiplication or algebra, we can do far better. That’s certainly a belief embedded in the priority we’re putting into math and math curriculum.

A lot of our readers might not be aware that you considered becoming an academic mathematician yourself. Are you still drawn to math? 

Yes! Math is fascinating. The way these new AI models work is extremely mathematical. If you learn all this new stuff, you’re drawing more on your math skills than your coding skills.

I initially did math, I was very good at math, and that helped me do coding. My framework for the world is very mathematical. And the boundaries of math have not moved all that much: We’ve proved the , we’ve proved . It’s fun to track where we’re making progress and where we’re not. But I enjoy math, and thank goodness, because otherwise I couldn’t be as engaged in the AI stuff as I am.

Even when I’m doing my global health work, or when we’re looking at the trends in these education developments, math is important. I like symbolic, complex math, but just data science — which we’re hoping to get into the curriculum and make the curriculum more interesting — that stuff is amazing now.��

See previous 74 Interviews: Sal Khan on COVID’s math toll; economist Tom Kane on the challenge of reversing learning loss; and education researcher Martin West on last fall’s NAEP results. The full archive is here.��

Disclosure: The Bill & Melinda Gates Foundation provides financial support to ����Ӱ��.