THE CREATIVE FORCE Harvard's Center for Digital Thriving named this week's problem: "AI is making student learning invisible to teachers." Offering Maryland undergraduates an AI tutor pulled them away from their own courses. Our defenses shrink the work further; as Jennifer Taback writes, "we have narrowed assessment to what we can proctor." But mathematics is a creative act you can only judge if you can see it: a question posed and lived with, the way young mathematicians took four papers to crack Graham's 1971 conjecture. So by June, where will the math we grade actually happen? THE FIVE 1. [Research] EdWorkingPapers: The Effects of Course-Integrated AI Tutoring on Student Performance and Engagement: A Randomized University Trial In a University of Maryland randomized trial, sections given a university-provided tutor built on OpenAI's GPT-4o earned final grades 0.37 standard deviations below other sections of the same course, though only about 15% of students ever used it (working paper, not yet peer-reviewed). Before any AI rollout in math, ask what it will replace. 2. [Report] Harvard's Center for Digital Thriving: An AI Policy Isn't a Playbook Among teachers who had faced an AI dilemma, 74% described something about cheating, and the side effect is perverse: "Some students deliberately underperform to avoid being flagged." In math, suspicion teaches students to hide exactly the thinking we're trying to grow. 3. [Essay] Terence Tao's blog: What does the advent of powerful AI models mean for mathematicians like me? Bowdoin's Jennifer Taback resents AI for pushing her assessments into timed classrooms, since without graduate student help, oral exams are "impractical at the scale of my teaching." Yet AI is also the research colleague her small department can't provide: a double bind teaching-heavy departments will recognize. 4. [Policy] CalMatters: Student math scores are abysmal. A new California law requires early testing for skill SB 1067 will screen every California K–2 student on counting, quantities, and number recognition starting in 2028, with no new money attached. The state's largest teachers union opposed it, arguing teachers already know who is struggling; the real test is whether screening changes what happens next. 5. [News] Quanta: Mathematicians Harness Randomness To Crack a 55-Year-Old Conjecture Ronald Graham asked in 1971 whether any set of nonzero numbers on a prime-hour clock can be ordered so every running total is different; four papers by young mathematicians now prove it for every large enough prime. Noah Kravitz's motive, "it's embarrassing for humanity that we don't know this," is the creative force no proctored test measures.

New format: five reads and one question we answer together. Vote, tell us why, and next week's Dispatch opens with how you voted and the top comment. Research mathematics just ran into a problem every math teacher knows. OpenAI's Navier–Stokes proof appears to be correct, but experts say it "doesn't teach us much." The first 3D "Einstein" tile was, in its finder's words, "found by Astra, not me." Every teacher has graded that paper: the right answer, with nobody home behind it. Harvard's PhD summit reaches for the teacher's fix: have students defend it out loud. The Khanmigo study shows the catch: students walk away when the tutor asks them to think. THE FIVE [Radio · 4 min] NPR: AI solved one of math's hardest problems. Humanity learned nothing (so far) OpenAI's 166-page Navier–Stokes proof passes a computer check, yet the mathematicians reading it say they can't learn much: "The paper is not written for humans." It's the clearest case yet that a proof and an explanation are different things. [News] Quanta: Software developer finds first 3D "einstein" tile An Athens software developer used OpenAI's GPT-6 Astra to find Chair44, a single shape that fills space but never repeats. He says he understands the intuition, "not the mathematics of it." Amateur discovery changed the meaning, and so did checking: an expert had to cut the 61-page paper to eight pages so others could follow it. [Report] Harvard CMSA: Recommendations of the Summit on PhD Math Education in the Age of AI Twenty-four senior mathematicians propose that a PhD "should not be awarded primarily on the basis of the text of the dissertation," but on a defense that demands complete mastery. Read "dissertation" as "homework," and it's a blueprint for assessment in any math classroom. It's a first draft, and they want feedback.

A Hobbyist, a Chatbot, and an 80-Year-Old Problem News Feature — Source: ‘It is incredible’: How AI is transforming mathematics — Nature Liam Price has no formal mathematical training and hasn’t yet attended university — but working from home in southwest England, he used ChatGPT to break new ground on Erdős problem #1196, one of more than a thousand puzzles the Hungarian mathematician Paul Erdős collected over his lifetime. What unsettled specialists wasn’t just the answer but the route: where human solvers had reached for the language of probability theory, the model worked in the problem’s original framing and, in doing so, implicitly built a bridge between numbers and probability. The piece sits against a broader backdrop — AI also cracking a separate 80-year-old challenge — and captures a field watching its own methods shift under its feet. CREATIVE FORCE: When a result can come from someone outside the credentialing system entirely, the question stops being “can AI do mathematics?” and becomes “who gets to be a mathematician, and what counts as doing the work?” That’s a question math educators will be answering for their students very soon. ‘The Job Description Is Changing’: Terence Tao on the Rise of AI Interview — Source: ‘The job description is changing’: mathematician Terence Tao on the rise of AI — Nature If the Price story was interesting for you, this interview could be considered the sequel as it answerthe questions in the CREATIVE FORCE line. The Fields medalist pushes back on the loudest framing — a wave of coverage has suggested mathematics is being fundamentally overturned, and Tao notes that AI’s real capabilities are often hyped, and that it’s premature to declare the profession dead. But he doesn’t dismiss the shift either: by his account, in just the past year AI has moved from secondary-school-level problems to being genuinely useful in working mathematicians’ daily research. His through-line is collaboration, not replacement — a recalibration of what the day-to-day of the discipline looks like rather than its obituary.

Hello my name is Emmanuel azeko a final mathematics major student at the University of Ghana passionate about machine learning, AI and robotics i hope to contribute value and support to this community thank you all.

If you get a chance, I wrote an article last week that I think you'll find interesting. Feedback and thoughts are always encouraged and welcome! https://open.substack.com/pub/drkevinberkopes/p/the-teachers-twinge-why-faculty-confidence?r=2pvimo&utm_campaign=post-expanded-share&utm_medium=web