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Nikon revokes first prize in Small World in Motion video competition over AI use
The winner of a prestigious scientific photography competition has been disqualified after organizers concluded that his use of generative AI broke the rules.
Contest-Winning Microscope Thrown Out for Using Generative AI
Ning Xu's winning entry to Nikon Instruments' Small World in Motion competition was ineligible due to AI, a spokesperson for the contest told Gizmodo.
Nikon microscopic video competition winner disqualified for using generative AI
Nikon says it’s revisiting its competition rules after the original winner’s video was too good to be true.
Rice Business Wisdom marks 10 years of bringing faculty research to wider audience
The anniversary issue examines a technology reshaping how people work, learn and make decisions. Featured stories explore how AI and machine learning influence household financial decisions, what drives data center location decisions across the United States and whether generative AI can help organizations sustain creativity over time.
Claims that genAI speeds up PC ports of classic games are either "false" or missing the point, says Banjo Kazooie: Recompiled developer
A Banjo Kazooie: Recompiled developer has spoken out against the idea that generative AI allows for faster PC ports and, therefore, better preservation.
Here's What Capcom Said About Using Generative AI In The RE Engine: 'AI Is Not A Replacement For Humans'
Capcom want to evolve RE Engine into an engine for the AI generation, but not turn it into an engine powered by generative AI over humans
Jagex responds to use of generative AI in RuneScape trailer made by "trusted external partner"
Developer removes promotional material as it investigates situation, says it highlights "an issue with our own processes which we must address"
Integral Ad Science to Provide Brand Safety and Suitability Measurement in ChatGPT Ads
NEW YORK, October 05, 2026--As artificial intelligence rapidly reshapes digital advertising, marketers face a critical new challenge: ensuring brand safety and suitability within dynamic, generative AI-native environments. Without independent verification, advertising in conversational channels risks creating a blind spot for enterprise brands seeking reliable media quality standards.
Bishop’s computer science chair says AI is eliminating ‘grunt work’ and reshaping digital jobs
Dr. Russell Butler, chair of Bishop’s University’s Department of Computer Science, says artificial intelligence is increasingly taking over routine digital “grunt work,” changing the skills students and workers may need in the years ahead. Photo courtesy of Bishop’s University. Click here to read our platform! Get local news like this every morning. Subscribe free below. Subscribe Pulse Newsroom Artificial intelligence is already taking over some of the routine digital work once performed by entry-level employees, according to Bishop’s University Computer Science chair Dr. Russell Butler — a shift he believes will make expertise, judgement and the ability to evaluate AI-generated work increasingly important. Butler described the change as automation reaching what he calls the “bottom of the cognitive pyramid” during an interview with The Pulse about AI, university education and the future of digital work. His argument is not that humans are disappearing from the workplace. Instead, he sees their role changing as AI becomes capable of handling more of the repetitive tasks involved in computer-based work. “Everything’s converging on just AI basically doing all the grunt work,” Butler said. The bottom of the cognitive pyramid Butler is from Lennoxville, completed his undergraduate studies at Bishop’s and later earned his PhD at the Université de Sherbrooke. He joined Bishop’s in 2019 and now chairs its Department of Computer Science. He uses AI in research, teaching and other creative work, and said the technology is increasingly capable of handling routine digital tasks that once required substantial human time. “You’ve got the grunt work, like moving things around in Excel, doing basic programming tasks,” Butler said. “That’s like the bottom grunt work that the entry-level worker would have done two or three years ago.” Butler went further, saying in his view that much of this type of work has already been absorbed by AI tools. He connected that change to a shift he sees taking place in computer science, where entry-level roles have declined while experienced workers can use AI to increase what they can produce. “A senior developer now has access to essentially an unlimited amount of junior developers on demand,” Butler said. He was describing AI systems metaphorically, not literal employees. His point was that one experienced developer can now ask AI tools to produce code or other technical work that might previously have been assigned to more junior workers. That raises a broader question for universities and employers. If some of the simpler work traditionally given to newcomers can now be done by machines, how do people gain the experience needed to become senior workers themselves? Students doing work that once required years of programming Butler said he is already seeing the change inside his classroom. He created a Bishop’s course called CS208, Coding in Plain English, to show students — including those without traditional programming backgrounds — what they can accomplish using AI. Some come from disciplines such as psychology or neuroscience with no previous programming experience. “What I’m finding is that students who have zero programming experience, they come in from another discipline like psychology or neuroscience or something, they are now able to get up and running with real data sets,” Butler said. Butler’s own doctoral work involved neuroimaging, and he said he has assigned students work he considers comparable to the kinds of analysis he performed during his PhD. He described giving students a real dataset, an expected result and instructions to use AI to complete the analysis. Butler said those students have been able to carry out work at a level he associates with tasks he once performed after years of programming experience. That does not mean a student using AI instantly acquires the same knowledge as an experienced computer scientist. But Butler sees it as evidence that AI can dramatically lower the technical barrier between having a problem to solve and producing a working result. The role of the person using the system then changes. They need to know what to ask for, understand enough about the subject to judge the answer and take responsibility for what is ultimately produced. What about AI hallucinations? One persistent concern surrounding generative AI is hallucination — when a system produces information that sounds convincing but is false or unsupported. Butler said that problem has improved substantially in newer systems and is not as severe as it was with earlier models. He pointed in particular to newer AI systems’ ability to search the web, consult scientific databases and return source links rather than simply generating a citation from their internal model. Butler nevertheless said users should verify what AI produces. “You should verify,” he said while discussing citations generated with AI. His position is that hallucinations have become less common in the systems he uses, not that incorrect AI output is impossible. Human checking remains part of the process. Hours of work compressed Butler offered another example from his administrative work at Bishop’s. The university has been comparing CEGEP courses with first-year Bishop’s courses to determine where students may qualify for advanced standing. Traditionally, Butler said, that means reviewing two sets of course descriptions and manually matching one institution’s courses with another’s. As department chair, that could require hours of reading and comparison. He said AI can now be given both sets of material and asked to generate an initial mapping automatically. “It saves me hours and hours of work,” Butler said. Butler said the AI-generated mapping can also produce a better result than he would produce himself. He sees similar opportunities in businesses. A company may receive specifications, drawings, emails or other digital material from customers and then have employees convert that information into an internal format before anything can be manufactured or delivered. AI can increasingly perform parts of that intermediate processing. In Butler’s view, the employee does not necessarily disappear. Instead, the job becomes more about checking the result. “The human is still there,” he said. Judgement could become more valuable That change is central to Butler’s view of where digital work may be headed. If AI can produce a first draft, write basic code, compare documents or process large amounts of information, he argues that knowledge and judgement become increasingly important. “The real scarce resource going forward is going to be domain knowledge, expertise, and… credentials, authority, the ability to work with other people,” Butler said. He is therefore encouraging students not only to learn AI tools but also to broaden their education. He mentioned acting, fine art and photography as examples of courses that can help develop what he described as taste and intuition — the ability to recognize what is good, what is not and what should be changed. “And that’s the skill that they need now because the grunt work has been automated and now it’s about evaluating what the AI produces and telling it how to improve or expand the output,” Butler said. That does not remove the need for technical knowledge. Butler’s argument is that the emphasis may shift away from manually completing every step of a task and toward directing, checking and improving work produced with AI assistance. He also stressed that humans remain responsible for final decisions. “At the end of the day, the human has to make the final call,” Butler said, pointing to the question of accountability. Physical work may be different Butler draws a distinction between digital work and jobs requiring people to manipulate the physical world. He expects AI to continue advancing quickly in tasks performed almost entirely on computers. He is more cautious about claims that humanoid robots will soon be able to replace workers such as plumbers or electricians. Butler said those trades would not be replaced “anytime soon” in his view and described some current robotics demonstrations as overhyped. He described the situation as counterintuitive. “It’s almost like we solved the highest level first,” he said, contrasting advances in digital AI with the harder problem of building robots capable of operating reliably in the physical world. Butler’s argument is that some digital occupations could face automation sooner than trades requiring complex physical work. The wider AI shift in the Townships Butler’s comments come as local institutions are increasingly grappling with how AI should be used. The federal government recently announced up to $162 million over five years for 10,000 AI-related placements through Mitacs. The Université de Sherbrooke told The Pulse that the number of its collaborative research and innovation projects supported through Mitacs has approximately doubled since 2018-19, while the number of placements has approximately tripled. UdeS also said it already has projects involving both AI adoption and the application of AI to other fields. At Bishop’s, Butler said part of his role involves building the Computer Science department’s local presence, connecting students with regional partners and strengthening relationships with the Sherbrooke technology ecosystem. Those developments put universities in a difficult position. They have to prepare students to use the tools employers increasingly have available while also making sure graduates understand enough to recognize when those tools are wrong, incomplete or being applied to the wrong problem. The risk of losing human skills Butler does not see AI as risk-free. Later in the interview, he raised a separate concern: as AI becomes better at reading, writing, programming and other cognitive tasks, people could lose some of the underlying skills that historically helped produce new ideas. “The other danger is that we’re going to lose the human skills,” Butler said. He specifically mentioned reading and writing and argued that people could lose some of the lower-level understanding that contributes to breakthroughs. Butler said AI systems are based on existing human knowledge and argued that they become much more powerful when paired with a capable person. That tension runs through his view of the technology. AI can remove hours of routine work. It can allow beginners to perform tasks that once required substantial technical training. It can give experienced workers significant leverage. But the more capable the technology becomes, the more important it may be for people to develop the judgement needed to decide what should be done in the first place. For Butler, that is where education may have to change. Students still need to understand their field. They still need to know when something is wrong. And they still need to be able to make the final decision. But if AI increasingly handles the bottom of the cognitive pyramid, the value of a worker may depend less on how quickly they can perform the grunt work and more on whether they understand what the work is supposed to accomplish. Don’t miss the next story that affects your community. Join thousands of readers getting The Pulse every morning—plus breaking news alerts when it matters most. If you value this kind of local journalism, consider supporting it. Subscribe, share and like! Subscribe Share
Audible's new features let you explore book worlds — and use AI to talk to characters
Audible is rolling out new features that help listeners keep track of characters, explore places and imagery mentioned in books, and even interact with characters using generative AI.
Global Health & WASH: October 2026 Funding Opportunities (26 new opportunities)
41 opportunities on the Global Health & WASH page this cycle, 26 of them new. The health money on this page is mostly research money, and much of it is aimed at people early in their careers. Funder after funder, from the TANGO2 Research Foundation’s Research Pathways grants to the South African Medical Research Council’s Early Investigators Programme to the National Ataxia Foundation and Alex’s Lemonade Stand Foundation, is funding early-career investigators and the institutions that host them, with a clear tilt toward researchers based in or from the Global South, from AMBSO in Uganda to Kenya’s CONNECT-VAX network to Ersilia’s AI Incubator for African drug discovery. The money is organized by disease as much as by need: narrow foundations, the Parkinson’s Foundation, NTAP for neurofibromatosis, the RUNX1 Research Program for an inherited blood disorder, each run their own grant, so the question for an applicant is less which health problem you work on than which foundation owns your disease. The largest European cheques go to consortia only, with the European Innovation Council putting up to EUR €4 million behind a single healthy-ageing project and UNITE up to EUR €1 million behind each cross-border digital health team. Water sits apart, almost entirely in applied utility research: the Water Research Foundation’s cluster of USD $250,000 to $500,000 projects, each built around a utility problem from sewer laterals to reuse treatment. And the biggest single pot is public: HRSA is renewing community health center service areas with awards of up to USD $10 million each. This post is for paid subscribers. This helps support the time and effort it takes to curate and organize these opportunities. Subscribe To keep this accessible to everyone who needs it, we’re happy to offer pay what you can rates. You can find more details here. Open Opportunities 2027 Building the Field of Health Advocacy Grant, Georgia Health Initiative. *New!* *Closing soon!* Georgia Health Initiative, a nonprofit private foundation focused on health equity, is opening its 2027 Building the Field of Health Advocacy Grant to strengthen the organizations that push for healthier systems across the state. The Initiative treats advocacy as infrastructure, backing one-year projects that range from urgent responses to shifting federal policy to longer arc campaigns on housing, behavioral health, care access, and food security. It wants coalitions that elevate community voice, apply an equity lens, and arrive ready to deploy concrete strategies, and it deliberately seeks variety in issues, communities, and organizational size. The optional webinar and required lobbying training signal a funder investing in a durable field, not one grant cycle. The strongest fits are Georgia nonprofits and public agencies ready to turn advocacy readiness into systems change. Geographies: United States. Who can apply: Tax-exempt 501(c)(3) public charities, state or local government agencies, or coalitions/collaboratives using a 501(c)(3) fiscal sponsor, that work in Georgia on behalf of Georgians and align with the mission, vision, and values of Georgia Health Initiative. Only one application per organization, though an organization may be listed as a partner or subcontractor on multiple applications. Funding amount: Organizations can apply for up to USD $80,000 per project; the Initiative anticipates investing a total of USD $1.36 million. Targeted Sectors / SDGs: Governance, Policy & Advocacy · SDG3; SDG10. Deadline: October 2, 2026. Learn more and apply here. TDD Research Pathways Grant, TANGO2 Research Foundation. *New!* *Closing soon!* The TANGO2 Research Foundation, working with a founding gift from Tango2UK, is opening its TDD Research Pathways Grant to fund early-career investigators anywhere in the world who study TANGO2 Deficiency Disorder. The foundation is using this money to seed pilot work and to build a research community around a rare disorder that few labs currently study. It wants to back emerging scientists, clinicians, and trainees who will stay with this field, not one-off projects, which is why it requires a committed mentor and real institutional support and asks each applicant for a plan for future contributions. The design rewards promise and persistence over track record. The strongest fits are students, residents, postdoctoral fellows, and new investigators ready to commit to TANGO2 research. Geographies: Global. Who can apply: Early-career investigators worldwide, including undergraduate, graduate, and medical trainees, postdoctoral fellows, residents, and clinical or research fellows. Early-career investigators must hold a PhD, MD, or equivalent doctoral degree and be within 10 years of that degree or within 5 years of initiating rare disease research, engaged in postdoctoral research at an academic institution, teaching hospital, or nonprofit research institute. Currently enrolled trainees and transitional PhD candidates beginning a postdoctoral appointment at a nonprofit institution by July 1, 2026 are also eligible. All applicants must identify a qualified mentor with relevant TDD or rare disease research experience and demonstrate institutional support. Funding amount: Up to USD $15,000. Targeted Sectors / SDGs: Innovation, Science & Technology. Deadline: October 2, 2026. Learn more and apply here. Call for Expression of Interest (EOI): AMBSO Impact Research Initiative, Africa Medical and Behavioral Sciences Organization (AMBSO). *Closing soon!* The Africa Medical and Behavioral Sciences Organization is inviting expressions of interest for its Impact Research Initiative, which funds early-stage pilot studies and proof of concept work on priority health challenges. AMBSO is a Ugandan research organization backing bold ideas that can grow into larger studies, and its tracks span antimicrobial resistance, epidemic preparedness, artificial intelligence for diagnostics, HIV prevention, climate and health, cancer, maternal and child health, and non-communicable diseases. The small award size and direct-cost-only rule point to a funder that wants evidence rather than overhead, and that favors projects able to attract follow-on money or use AMBSO’s own research infrastructure. Eligibility runs worldwide, welcoming researchers and institutions inside and outside Africa. The strongest fits are researchers with a feasible pilot that generates policy-ready evidence. Geographies: Global. Who can apply: Open worldwide to researchers, academic institutions, and research organizations whose work aligns with generating high-impact health evidence. Independent researchers are eligible if affiliated with an academic or research institution. Doctoral students are encouraged to apply as part of a research team led by a faculty Principal Investigator. Community-based organizations and other eligible entities may apply. Projects may be implemented inside or outside Uganda. Funding amount: Up to USD $10,000 per project, with no minimum funding threshold. Targeted Sectors / SDGs: SDG3. Deadline: October 2, 2026. Learn more and apply here. Entrepreneurs for Resilience 2027 (E4R27), Swiss Re Foundation. *Closing soon!* Swiss Re Foundation is opening the tenth edition of Entrepreneurs for Resilience, which backs healthcare social enterprises expanding affordable, quality primary care for low-income communities across low- and middle-income countries. The Foundation is using catalytic, blended funding plus multi-year advisory to take risk out of scaling, helping proven models reach more people sustainably rather than stay stuck at pilot size. It looks to back brick-and-click enterprises that pair physical care with digital tools and build affordability through savings, payments, or microinsurance, ideally integrated with public health systems. Requiring earned revenue, real customer scale, and gender-inclusive teams signals that this is growth capital for commercially serious ventures, not seed money. The strongest fits are established, revenue-generating healthcare enterprises ready to scale access for underserved populations. Geographies: Global. Who can apply: For-profit and hybrid healthcare social enterprises serving low-income and underserved populations in low- and middle-income countries, using combined physical and digital (brick-and-click) healthcare delivery models. Applicants must demonstrate measurable social impact, generate at least 50% of income through earned revenue, have been established no later than December 2023, already serve at least 50,000 people with potential to scale, and have at least 30% low-income customers. Preference for gender-inclusive enterprises with at least one female founder or at least 30% women in management. Funding amount: Pilot funding of up to USD $45,000 for the 6-8 shortlisted social enterprises; up to USD $1 million in blended funding (up to USD $600,000 unconditional plus up to USD $400,000 conditional) shared among 3-4 finalists over a two-year implementation period; total programme funding approximately USD $1.3 million. Targeted Sectors / SDGs: Innovation, Science & Technology · SDG3; SDG5. Deadline: October 4, 2026. Learn more and apply here. Horizon HealthTech 2026, IIITD Innovation & Incubation Center. *Closing soon!* IIITD Innovation and Incubation Center is opening Horizon HealthTech 2026, a nine-month MedTech incubation cohort run under the aegis of BIRAC EDGE for founders building medical devices, diagnostics, surgical and interventional tools, or remote monitoring. The center is backing teams that already hold a validated proof of concept and want to reach a tested prototype, pairing each founder with a named expert and clinical validation through a hospital partner. What they seek to back is Indian health technology that can survive real clinical scrutiny and regulatory review, not slideware. The structure, with lab access, CDSCO guidance, IP support, and investor connects, signals a program built to make startups ready for follow-on capital. The strongest fits are early-stage MedTech teams with defensible IP and a working path from bench to bedside. Geographies: India. Who can apply: Early-stage teams/startups with a validated idea/proof of concept (TRL 3 onwards) working on medical devices, diagnostics, surgical/interventional technologies, or remote monitoring, holding IP or with potential to generate IP. Funding amount: No cash award amount is stated on the official program page. Benefits are in-kind: prototyping lab and equipment access, clinical/hospital validation (Max Healthcare), expert mentorship, CDSCO regulatory guidance, IP filing support, workspace, cloud credits and tools, and investor connects. Run under the aegis of BIRAC EDGE and builds a path to follow-on Government/VC/Angel funding. Targeted Sectors / SDGs: Innovation, Science & Technology · SDG3; SDG9. Deadline: October 5, 2026. Learn more and apply here. OpenAI AI and Teen Development Research Grant Program, OpenAI. *New!* *Closing soon!* OpenAI is opening its AI and Teen Development Research Grant Program to fund independent studies of how generative AI shapes the lives of young people ages 13 to 17. OpenAI wants a stronger evidence base on how teens actually use these tools and what that use does to their social and emotional development, so that product teams, policymakers, and regulators can act on findings rather than assumptions. It seeks work on emotion regulation, relationships, belonging, and the safeguards that keep teens safer, welcoming interdisciplinary teams and any methodology. That it will fund research whose conclusions may not favor AI providers, and prioritizes studies touching ChatGPT, signals a genuine appetite for credible outside scrutiny. The strongest fits are research groups grounded in adolescent development, well-being, and AI safety. Geographies: Global. Who can apply: Researchers aged 18 or older who are affiliated with a research institution or organization, and/or have significant experience relevant to child or adolescent development, well-being, human-computer interaction, AI impacts, or a closely related field. Multiple institutions may collaborate. OpenAI is seeking to fund research rather than for-profit initiatives and will not prioritize for-profit organizations. Funding amount: Individual research grants up to USD $1 million, totaling up to USD $5 million; maximum 10% of each grant for overhead or indirect costs. Targeted Sectors / SDGs: Social Inclusion & Community Wellbeing; Innovation, Science & Technology. Deadline: October 6, 2026. Learn more and apply here.
September Monthly Review: Health MCP Guy?
For all the time I spend talking about APIs and data exchange, this newsletter has had embarrassingly little interoperability of its own. It’s old-school SaaS, baby - UI or bust. Not all of that is my fault! Substack, for all its popularity, is (as mentioned before) really frustrating as my system of record. The primary user it optimizes towards is the reader, whose attention feeds the app, the Notes feed, and the recommendation network that Substack is actually selling. Health API Guy is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe They’re falling into the same trap that Medium once sprinted into, albeit at a much more glacial speed. Younger generations may not remember (or never knew) it, but Medium once lured publications like The Ringer and Signal v. Noise onto its platform, only to lose them as it rebuilt itself around a paywall and an algorithmic feed. Substack’s original pitch circa 2020 was the antidote (you own your list), but every new feed feature chips away at it. I get it: writers are generic supply in the eyes of the Substack product team. Generic supply follows demand, so the consistent pressure on the PMs is to generate demand, which leads to every product cycle going toward discovery (Notes, recommendations, the app, live video). The end result lackluster author tools (laggy and broken analytics are truly crippling) all despite the premium price point. The archive is where it crosses from authorial gripes to actual reader impact, though. Across Substack and LinkedIn, I’ve published 1,218 posts and nearly 900,000 words since 2018. Substack’s native search can see only the 464 posts that live on Substack, and even there it’s woefully inadequate at surfacing relevant content (even for the guy who wrote it)! Readers have the same problem, writ large. Ask the Archive Fixing search (for both my readers and my own use) turned out to be extremely non-trivial, unfortunately: There’s no public API for readers to access content RSS exists for new content notification, but it only carries the 20 most recent posts and cuts paid ones off at the preview The only Substack MCP is an admin tool for analytics The export exists for authors, but it’s painfully awkward and slow. So I built something to work around that: the Health API Guy MCP. It’s a private MCP server holding the full text of everything I’ve written across Substack and LinkedIn. Add it to Claude or ChatGPT as a connector and you can ask things like: It pairs keyword search (for acronyms and case names, of which we have many) with semantic search. Every post is also labeled by topic, form, and court case, so you can pull a lawsuit’s (or multiple cases’) entire docket across Substack and LinkedIn in one query: Hail, Healthapiguyhydra This is also a bit of me eating my own cooking. I’ve spent the year arguing that headless healthcare is arriving and that developers want primitives over abstractions. Last week in Hail, Benihydra, I watched Salesforce plug its platform into Claude and bet that the records underneath outlive whatever interface sits on top: Salesforce must believe that the Hydra’s immortal head is the records, permissions, and business logic (in that they will survive whatever happens to the interface). It felt a bit hypocritical to keep my own archive behind a Substack search bar. The archive is the body. Substack is one head, and now whatever tool you might use is another. Will the EHRs follow my lead? Probably not imminently, but one can hope! Why Founding Members Only The MCP is available to Founding Member subscribers. A few reasons: It costs money and time to run. Hosting, the database, Clerk usage and AI compute for search and labeling are significant operational costs (that increase with usage). Substack gives me no way to automate access. There’s no API to check whether someone is a paid subscriber, so every user is manual operations for now. It’s a beta. We’ll need to improve things and parts will break. I’d rather they break for a small group of dedicated readers who will tell me about it. The Founding tier deserved a real benefit. Until now it was mostly a generous tip. Now it comes with something. If you’re already a Founding Member, reply to this email with the address you’d like provisioned. If you’re not and want in, upgrade here. Larger teams (such as companies) can get access too: group subscriptions at the Founding tier come with the group discount. The admin for the subscription can reply with the list of addresses to provision. Get 20% off a group subscription Pricing Founding membership is now a flat $200 a year, replacing the old suggested $150 that readers could adjust. Existing Founding Members will have access grandfathered in at their previous rate. Month in Review Articles Published Make Networks Dumb Again (Sep 11): AI is making old analog networks cheaper to use and flooding them with machine traffic in the process. A plea for agent-native rails with the intelligence at the endpoints, and for Washington to drag them to ubiquity. Interoperability, Unbuttoned (Sep 29): Interoperability is a series of workflows in a trenchcoat, and this post finally takes the trenchcoat off. A color-coded map shows which provider workflows went digital, which are fragmented, and which still run on fax. Video Content Antitrust’s System of Record Problem (Sep 3): The FTC’s investigation into Epic prompted a ninety-minute webinar, now posted with chapters and a smoothed transcript. We get into why market definition, missing B2B share data, and the SSNIP test leave antitrust poorly suited to systems of record, plus why information blocking may be doing more than any pending lawsuit. The Information Exchange: Cerner Milking Edition (Sep 18): This was so fucking fun. Ryan Tucker, Ryan Brickner, Brad Thorson, and I try an Around the Horn format, complete with points, penalties, and a mute button. We debate whether Oracle Health is dead, who would actually buy Cerner (IBM enters the chat), p(Doom), and why the front desk still hands you a clipboard. Regulatory Ask Not What Your Network Can Do (Sep 23): CDC’s RFI on public health data intermediaries lists use cases already served, unevenly, by eCR, lab reporting, IZ Gateway, and syndromic surveillance. The real opportunity sits in one question about AI: a network that can handle the next emergency without another interface project. Court cases Particle v. Epic: The Naughty Schoolteacher (Sep 4): After a summer-long vigil, the answer on Epic’s early summary judgment bid is two paragraphs and a remedial assignment. Particle advances to the next grade, and market definition gets another year of discovery. The Epic Discovery Files (Sep 8): Texas’s motions to compel arrive with a 251-page appendix of requests, objections, and meet-and-confer letters with Cravath. Inside: Epic using generative AI for document review, denied interoperability requests in scope, and Noerr-Pennington raised against lobbying discovery. Epic v. Health Gorilla: “Working as Designed” (Sep 9): Epic wants nothing to do with the data breach MDL, and explaining why puts fresh discovery on the public docket. The spiciest allegation: Health Gorilla told GuardDog to scrub its law firm business from its website instead of cutting off access. Veeva v. Epic: Legal Bypass Surgery (Sep 15): Veeva asks the Wisconsin Supreme Court to skip the Court of Appeals, while law professors and three policy groups line up as amici. Meanwhile, Epic’s lawyers apologize for another round of citation errors, including a quote that never existed. Texas v. Epic: Behind the Black Bars (Sep 17): The court portal served up Epic’s unredacted filings, revealing a $5 million document review budget and the AI workflow behind it. Also inside: the 200-plus company names Texas wants searched, and one very expensive Zoom invitation. OpenEvidence v. Doximity: Consequences Will Follow (Sep 25): OpenEvidence tells the court it will not comply with a discovery order, and its own lawyers at Quinn Emanuel say they won’t defend the choice. Add years of Slack reported unrecoverable, and Rule 37 sanctions come into view. Health Tech Keeps Choosing Violence (Sep 28): Doximity moves to end OpenEvidence’s case, Epic asks Texas to show its work, and a sleepy Audacious Inquiry patent fight sprouts antitrust and information blocking counterclaims. The main event is a long-sealed Cognizant v. Infosys ruling that hints where system of record antitrust claims can survive. EHRs One Verb for Oracle Health (Sep 14): Oracle’s earnings call quantifies every data center to the decimal point, while Oracle Health gets a single verb: “accelerate.” Panning the few healthcare mentions turns up an agentic care management system, a research-to-care ledger play, and the question of whether healthcare gets Larry’s patience. Epic’s Forretress Under Siege (Sep 30): Judy Faulkner tells a panel Epic paused hundreds of projects to harden its software and calls it a “shame,” while a spokesperson insists the roadmap hasn’t changed. Project Glasswing, a Pokémon-branded QAN sprint, and a trove of Jodel grievances reconcile the two Epics and preview the Jevons paradox coming for all software. Industry Analysis Scanning for a Network (Sep 1): Scan.com raises $220M to build the imaging network labs never got, speedrunning Zocdoc’s consumer-to-B2B pivot. Its wedge to network density may be the most American one available: personal injury litigation. The Front Desk Wants the Damn Whole Building (Sep 16): Hello Patient buys Converse Health, pushing its AI front desk into referrals, chart work, and prior auth. The copilot categories keep blurring, and your distribution partner is still your final boss. Cross-industry Comparisons A Different Patchwork Quilt (Sep 10): Healthcare loves to envy open banking, but the US version has no mandate, a toll booth at Chase, and data quality problems of its own. The grass isn’t greener; it’s another American patchwork quilt, and perhaps a worse one. Hail, Benihydra (Sep 21): Salesforce brings its platform into Claude, Slack, and its own agent, inviting the interfaces that might replace it. Cut off one head and more grow back, so long as the records underneath stay put. Living on A Trade Secret Prayer (Sep 22): Six credit unions are suing Fiserv, the Epic of core banking, by claiming their own member records as trade secrets. Banking has no Cures Act, so its lawyers reach for legal alchemy that healthcare has already tried. Other News None this month External Media Nabla Accelerate NYC: I kicked off fall conference season at Nabla’s Accelerate event in New York, where Delphine Groll opened by asking the room to picture the company it wants to become and the one it doesn’t. I liked her framework of bureaucracy, fear, and ego as the blockers. I also love vendor conferences/events in general - different vibe than industry biggies. Healthcare 101 with Nikhil Krishnan: I briefly guest lectured Out-Of-Pocket’s Healthcare 101 class. Appreciated Nikhil’s takeaways cover whether AI doctors can query HIEs, why healthcare’s data-liberation rules beat most industries’, and the hi-res graphic is in the comments. HCN: Epic Probed by the FTC: I joined the HCN guys to talk through the FTC’s investigation into Epic. Cedric’s new hairdo was an unexpected plot twist. The episode also covers MFN drug pricing, healthcare M&A and Eli Lilly’s acquisition streak. Fall Conferences: At eHealth Exchange’s Annual Meeting in Austin on Oct 27, I’ll moderate a panel on the tensions between AI, HIEs, and timely patient access with Jean Ross (Primary Record), Therasa Bell (Kno2), Byron Crowe (Doctronic), and Michael Marchant (Freenome). Here’s the rest of my schedule if you want to meet up: CommonWell (Redwood Shores, CA): Oct 13-14 Will be participating in a fun Jeopardy event Open@Epic (Madison, WI): Oct 20-23 Will be enjoying Verona, Willy Street, and other local adventures eHealth Exchange and Sequoia Project (Austin, TX): Oct 27-29 Yeehaw HLTH (Vegas): Nov 15-18 Groundhog Day, Venetian Edition RSNA (Chicago): Nov 30-Dec 2 See me at “Governing AI in Breast Imaging: What Health Systems Are Actually Doing” Digital Health Counsel 2026 AI Summit (Seattle): December 2-3 Will likely be speaking to a bunch of lawyers about information blocking Posts I Liked ChatGPT’s Epic integration: game changer or nothing burger?: Joshua Liu, MD offers five thoughts on OpenAI’s Epic launch, starting from the point that it rides the same open APIs available to anyone. He argues read-only access leaves ordering to Art and the ambient startups, and asks why HCA is piloting it alongside Commure. He’s sorta a must-follow at this point - consistently excellent, thought-provoking takes. Epic, Lilly, and the Discovery pass: Seth Chaney reads Epic’s first major Discovery deal (with Eli Lilly), as well as its revised developer terms on commercial displays, as the pipe finally opening between EHRs and pharma. Life sciences and health continue to collide. Scott Rossignol on EHR payer platforms and ePA fees: Scott argues the top ambulatory EHR vendors are turning the prior auth mandate into a per-member-per-year toll on payers, for an API whose operating cost has nothing to do with covered lives. His fix is two lines of regulatory text: put the CRD/DTR/PAS certification criteria in the Base EHR definition, and bring payer-facing ePA connectivity under § 170.404’s cost-based fee rules. It’s a good solution. Health API Guy is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe
Can law schools learn from computer science programs in the debate on generative AI?
In many university computer science programs, students are not only allowed to use artificial intelligence during exams, they are encouraged to learn about the
AI Agents Are Moving into the Small Business Mainstream - Small Business & Entrepreneurship Council
By Karen Kerrigan – Artificial intelligence is entering another important phase for small businesses. Over the past several years, entrepreneurs have rapidly embraced generative AI to write content, conduct research, create images, analyze data, improve customer service and perform dozens of other tasks. Now, AI is moving from simply helping business owners do the work […]
Ubisoft's calling its next push into gen-AI game development Motherbrain
Ubisoft has been quite enthusiastic about generative AI's use in game development, and a new trademark might sound familiar to Nintendo and Metroid fans.
The Cost of Overlooking Generative AI in Entertainment -
By Sirius McDonell Writer/Reporter As the years go by, generative AI, or Gen AI, has started to become a staple in online spaces. You can ask it to write an essay for you, have it figure out a recipe from ingredients you have on hand or even talk to it as if it were your […]
From AI Users to AI Leaders: How Businesses Can Navigate Generative AI | Elmhurst University Elmhurst University Blog
Artificial intelligence is rapidly becoming part of how organizations operate, compete and make decisions. Businesses not only need more AI programmers and data scientists; they also need managers, analysts and business leaders who understand what AI can do, where it can create value and how to use AI responsibly in a changing business environment.
Whether you like it or not, celebrities have an impact on politics
The global groundswell of support for Macklemore’s pro-Palestinian advocacy serves to remind us that maybe celebrity activism really is that deep after all, writes Cheek’s Varsha Yajman. Subscribe In the last week, publications, podcasts, and influencers that have either rarely or never spoken about Israel’s genocide in Palestine have flooded my social feed. And it was all because singer Ed Sheeran and his team dropped Macklemore as his opener for saying “Free Palestine” on stage. Millions raised, millions speaking up in support of Palestine - all of this confirming my view that, whether I like it or not, celebrities do have an impact on political outcomes. And this is interesting when much of the time celebrity activism can induce an eye roll - I love to see Charli XCX pointing out a Palestinian flag in the crowd, but it’s hardly the bold symbol of allyship that some fans would make it out to be. But there’s a line between healthy scepticism and outright dismissal - and I’d argue that the latter lets the rich and powerful off far too easily. For instance, actress Jennifer Lawrence, once outspoken about her political views, last year told The Times she no longer believes celebrities have a role to play: “Celebrities do not make a difference whatsoever on who people vote for. So then what am I doing? I’m just sharing my opinion on something that’s going to add fuel to a fire that’s ripping the country apart.” While it’s a narrative she might find comfort in, it simply is not true. Grassroots movements often garner worldwide attention when celebrities and other high-profile spokespeople bring a mainstream platform to their causes. And this frustrates me. We have had three years of a live-streamed genocide. Macklemore himself has been calling for a Free Palestine long before he booked the Sheeran concert. Yet it’s the high-profile fallout of the last week that finally seems to have made saying “Free Palestine” socially acceptable in the mainstream. It feels like the collective mood has shifted, where calling out censorship is now the obvious response - not just the business of ‘radical’ activists. To recap, Sheeran’s decision followed an ultimatum from billionaire Robert Kraft, owner of Gillette Stadium, one of the venues Sheeran was scheduled to perform at: either drop Macklemore as your opener after only two of the eight scheduled shows, or you do not play at any stadiums. Sheeran’s disappointing decision to stand on the side of billionaire-led censorship has ultimately seen a surge in support for Free Palestine. It began when all his openers and his backing band pulled out of Sheeran’s tour, in solidarity with Macklemore and with the Palestinian cause. It was met with an uproar of support from those who had never or barely touched politics before: influencers lip-syncing to Macklemore’s music, singers like Jack Antonoff singing “Free Palestine,” and publications and podcasts standing with Macklemore. And finally, we saw material support: Macklemore donated $1 million in profits from his two nights opening for Sheeran’s tour to several Palestinian aid groups and called for Sheeran and Kraft to match it, which they have since promised to do. We’ve also seen children’s entertainer Ms Rachel follow suit with a $1 million donation to Palestinian aid, and publication PopBase has donated $10,000. Anera, a humanitarian aid group working in Palestine, Lebanon, and Jordan, said donations since Macklemore’s announcement were more than triple this month’s daily average. The group’s Instagram page has also gained 8,000 followers. Macklemore far from the first celebrity to speak and participate in politics in the Western World. In 1924, singer Al Jolson supported Republican candidate Warren G. Harding for president, and decades later, celebrities such as Harry Belafonte, Lena Horne, and Aretha Franklin voiced their public support for the Civil Rights movement. More recently, in the lead-up to the 2024 US election, ‘The Daily Show with Trevor Noah partnered with the organisation Power the Polls to recruit poll workers to address shortages- a problem disproportionately affecting voters of colour. The campaign saw 170,000 new sign-ups - 35,000 of which came directly through the TV show’s link - resulting in the recruitment of 713,000 total poll workers that year, an almost three-fold increase on the organisation’s goal. Alongside recruiting workers, celebrities in the US (where voting in elections is not compulsory) have made a huge difference by calling for people to register to vote. Taylor Swift’s endorsement of Kamala Harris in 2024 saw over 400,000 visitors on the voter registration site within 24 hours of her Instagram post. In 2023, Swift had urged her fans to register, resulting in 35,000 new voter registrations. Similarly, Ariana Grande promoted voter registration in 2019 by setting up booths at concerts on the American leg of her tour, resulting in over 33,000 voters registering. And the same thing is happening closer to home. This year, musician Jack River successfully called for government action to ensure creatives in Australia do not have their work scraped by generative AI companies. Celebrity as the mediator between the punter and the politician Celebrity activism isn’t just a feel-good news story - research tells us it actually makes a difference. By directing attention to issues affecting the average person, like voting inaccessibility or a lack of action on a genocide, researchers Alfred Archer and Amanda Cawston state that “celebrities can play a useful bridging role between political elites and the people they represent”. Alternatively, in a world where talking about politics is “not cool,” or where people lack exposure or knowledge to engage with politics, celebrities can act as an educational resource or an entry point into the political world - when they speak up about an issue, their audience gets exposed to it. Olivia Rodrigo’s Daisy Chain Fields festival is a perfect example. Rodrigo partnered with twelve organisations focused on women’s issues, such as reproductive rights. These organisations had stalls at the festival for people to meet them and were also featured heavily on social media, giving their issues global attention and raising $20 million for the organisations. We have also seen celebrities at award shows such as the Emmys wearing F*CK ICE pins, referring to the U.S. Immigration and Customs Enforcement’s treatment and detainment of people - generally people of colour. When celebrities speak up about political issues in public forums, they put the issue at the forefront of mainstream media, rally their supporters, and make it clear that, however much they disagree, the government cannot simply ignore it. Our over-reliance on celebrities versus our politicians As much as I love seeing my favourite celebrity use their platform for a good cause, there is an important question to ask: not whether celebrity activism is good or bad, but whether we should have to rely on celebrities. And the answer would, in an ideal world, be no. In an ideal world, or merely a just world, action on Palestine would’ve happened decades ago, climate change would be taken seriously, and most importantly, people would understand their democratic rights. However, that is not our reality. Only around 28 per cent of Australian Year 10 students reach proficiency in civics and citizenship. In the US, almost two-thirds of people under 30 say high school civics education didn’t prepare them to understand voting deadlines, how to research candidates, or how to vote by mail. When civics education is weak, our trust in these institutions and our understanding of change-making processes also decline. This is where celebrity steps in and becomes our main source of reliance. As Mary R. Connelly notes in _The Tartan, “_Celebrities will always be involved in campaigns in one form or another, but their presence is not what causes people to vote blindly. The lack of political engagement and literacy is what allows celebrities to wield their influence on the political sphere so impactfully.” About the author Varsha Yajman is the Digital Content Producer at Cheek Media. She is a youth advocate and lawyer with a background in climate litigation and is passionate about looking at the intersection between race, climate justice, and mental health. Thanks for reading Cheek Media Co. ! This post is public so feel free to share it. Share
Wolverine developer Insomniac denies using generative AI after fans spot strange restroom sign
Insomniac denies using generative AI on Marvel's Wolverine after fans spotted a strange bathroom sign, blaming a "UV map bug" instead.
Insomniac Says Marvel's Wolverine Uses No Generative AI After Fans Spot Strange Signs in-Game
Insomniac Games has stepped in to confirm Marvel's Wolverine contains no generative AI after a few bizarre in-game signs raised eyebrows on social media.
From Python and Statistics to Agentic AI: 5 Data Science Certificate Programs in 2026
Python and statistics still sit at the center of data science, but the work surrounding them has expanded. Professionals now move from cleaning data and testing hypotheses into predictive modeling, recommendation systems, deep learning, Generative AI, and applications that can retrieve information or act through external tools. That progression matters when comparing programs. A curriculum […]
Can researchers trust that AI models won’t leak their ideas?
Research funders are asking how they can stop confidential scientific ideas in grant proposals from leaking out through large language models (LLMs), for example if reviewers use AI to help them judge applications. Last week, a row erupted in mathematics after OpenAI announced it had solved a notoriously difficult problem, only for another mathematician to demand answers over whether the company had used ideas he had fed into its models. The spat, and the broader issue of idea leakage through AI models, was discussed by funders at an R&D policy conference held in Paris on September 14. At worst, it threatens to undermine the correct attribution of breakthroughs, one of the foundations of modern science. The mathematics dispute around OpenAI is “certainly something we're looking at” Jason Gallo, head of the newly established Office of Metascience at the US National Science Foundation (NSF), told the Blue Sky Forum, hosted by the Organisation for Economic Co-operation and Development. The controversy started on September 8, when OpenAI announced it had cracked a mathematical problem that had gone unsolved for 90 years. Using a swarm of AI agents, millions of dollars’ worth of computing power and a new internal model, the company said it had finally proved that a long-used formula for modelling fluid dynamics breaks down under certain conditions. However, Tristan Buckmaster, a New York University mathematician who had been independently working with collaborators on the same problem using OpenAI’s Codex tool, hit back with a statement questioning whether the company had snooped on his Codex sessions to gain an advantage. OpenAI has always denied it looked up the “specific user data” of Buckmaster and colleagues. However, the company initially admitted that “while unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models,” although its proofs “differ significantly” from Buckmaster’s. The firm later said that, following an investigation, it concluded that Buckmaster’s Codex prompts “could not have influenced the [OpenAI] system in any way, including through training.”Funder concernYet OpenAI’s initial admission that its model might have ingested Buckmaster’s ideas, then spat them out to its own mathematicians, has scientistsworriedthat their work could leak out if shared with AI. Some AI tools give users an opt-out option to stop their sessions from training the model. If such guarantees can be trusted, this gives scientists some confidence they can use an LLM to develop an idea without the risk of it leaking out.But there’s a bigger potential vulnerability. To win money to investigate ideas, scientists have to share them with funding bodies. These grant proposals are normally kept strictly confidential, to prevent other scientists from scooping them, or to protect commercially valuable intellectual property. To preserve this confidentiality, when the NSF uses AI models, “we have to be sure that it's not making server calls out to an external party, leaking that data,” said Gallo to delegates in Paris. Leaks through reviewersHowever, funders normally use external academic reviewers to assess proposals. And there are growing worries that these reviewers are feeding grant ideas into AI models to help them make a judgement. Research funders have noticed that peer review reports and funding recommendations have “suddenly become much longer, more detailed and complex,” said Diogo Machado, head of the data science unit at Technopolis, a science and technology-focused consultancy. “The sense is that reviewers are increasingly using generative AI in their review work, even where guidelines sometimes forbid it,” he told Science|Business. “This is very difficult for funders to control or prove.” Happening at scaleThis sharing of confidential proposals with AI models is “happening at scale already,” said James Wilson, executive director of the Research on Research Institute, based at University College London, during the debate in Paris. In response, Gallo said the NSF had “strict guidance” around the uploading of proposals to AI models. But he added the NSF was mulling new types of assessment to make sure applicants were truly the originators of their ideas, such as following a short-form proposal with an oral presentation, which would allow the foundation to “really interrogate the investigator on their intellectual contribution.” Related articlesHow can Europe cope with a flood of AI-assisted research grant proposals?The risks and benefits of AI in screening research grant proposals Viewpoint: AI could make scientific overload worse“For us as funders, a lot of the ways to ensure that the application remains the applicant's own intellectual contribution, those ways are quite regressive,” Peter Clifford, head of strategy at Research Ireland, told delegates. “They're maybe ten or 15 or 20 years old, and they don't scale particularly well.” Disputes over the origin of ideas are as old as modern science. Isaac Newton and Gottfried Wilhelm Leibniz spent more than a decade arguing over who invented calculus, for example. And long before LLMs emerged, academics would agonise over how much of their early work to reveal at conferences, in case their colleagues scooped them, Jack Leahy, a senior metascience advisor to the UK government, told delegates. But AI was “accelerating” the “problems of the system,” he said.
Oracle Health extends clinical AI agent to inpatient nurses
Oracle Health is building out its generative AI capabilities for inpatient nursing workflows. The company announced the U.S. | The clinical AI agent, embedded directly within the Oracle Health Foundation EHR, combines voice-driven chart navigation and search, acute nursing summaries and voice-enabled discrete charting.
50 New Things Your iPhone Can Do in iOS 27
Apple released iOS 27 this week, and despite the company's focus this year on refining its flagship operating system and nixing bugs, there are still many additional features to explore, not least of which is Apple's new context-aware Siri, re-tooled for the generative AI era. Which iPhones Support Every iOS 27 Feature? This year's major iPhone software update isn't all about AI, though, as the following feature list testifies.
'Cognitive stunting' and the potential threat generative AI poses for children's brains
As LAUSD starts moratorium, there's not much data on what AI does to kids. The little information that is available doesn't look good
Professor Layton studio Level-5's CEO admits using AI to make its digital showcase "more spectacular"
Level-5 CEO Akihiro Hino has confirmed the studio used generative AI in its recent Yo-Kai Watch and Professor Layton showcase, and apologised to fans.
Level 5 boss admits using AI for Professor Layton, Yo-Kai Watch reveals
CEO apologises for using generative AI for recent Level 5 showcase…
Level-5 Boss Addresses AI Backlash After Fans Hit Out at Game Reveal Showcase
Developer Level-5 has apologized for and explained its use of generative AI after fans spotted 'AI slop' in footage of games like Professor Layton and the Curious Village, DecaPolice, and more.
Chandigarh University's Computer Science Engineering Students Develop AI-Powered Platform to Detect Fraudulent Apps
Chandigarh University's Computer Science Engineering (CSE) students have once again proven their brilliance on the national stage by securing second position in the national-level CyberShield Hackathon, organized by Bank of India in collaboration with IIT Hyderabad to solve AI, cybersecurity and banking-fraud challenges, winning a prize of Rs 3 lakh by providing innovative solution for harnessing Generative AI for automated reverse engineering, static and dynamic analysis and risk scoring of fra
MIPCOM 2026 expands creator economy programming, embraces vertical content and generative AI
The worlds of legacy entertainment and creator content are becoming ever more intertwined--and MIPCOM wants to be the nexus where they meet. Lucy Smith, "We don't see the creator economy and mainstream media as two separate worlds anymore. They are increasingly part of the same entertainment business," Smith says. "Creators are building audiences, businesses and valuable IP. Studios and platforms are looking for new talent and new ways to reach audiences. Brands are becoming content partners and investors."
Blizzard union workers ratify contract covering 1,900 employees
Union members have secured guardrails around generative AI usage, layoff protections, remote and hybrid work benefits, and more.
School students who use AI chatbots score lower in OECD science test
Students who use generative AI for specific tasks score lower in science than those who don’t, according to an OECD report.
FDA pilot offers generative AI medical devices a path to patients before they are authorized
AI products from Cadence and Limbic are among four devices recently accepted into the FDA’s TEMPO pilot that will allow digital health companies to release products without marketing authorization.
Google Pics is like Canva, but with even more AI
By more, we mean it’s all generative AI.
Together, GLP-1s And GenAI Can Solve Healthcare’s Affordability Crisis
Two innovations offer a new path to healthcare affordability: GLP-1 medications and generative AI. Here's how to two could radically improve medicine and lower costs.
UCSB Researchers Unveil 10 Rules for Generative AI in Science
UC Santa Barbara's NCEAS has released a 10-rule framework in PLOS Computational Biology to guide environmental scientists using generative AI for coding.
A field guide for the Wild West of AI-assisted science
Researchers at UCSB's National Center for Ecological Analysis and Synthesis develop a set of practice guidelines for environmental data scientists who use generative AI
FDA promises new AI guidance, and what happened at Epic's UGM
In this edition of STAT Health Tech: FDA's plans for regulating generative AI-powered devices, and updates from EPIC's UGM.
Delivering Business Outcomes in the AI Era: Ricoh's Process-First Approach to AX | Stories | Global
Many organizations are investing in digital transformation (DX) and generative AI, yet few are achieving the business outcomes they expected. According to Takashi Asaka, Head of DX Division, Ricoh Company, Ltd., the challenge often lies not in AI itself, but in business processes that were never designed with AI in mind.
Family entertainment company WildBrain acquires Personality AI
TORONTO — Family entertainment company WildBrain Ltd. has acquired Personality AI, which uses technology to create interactive characters using generative AI.
FDA plans to regulate generative AI
New clues to RFK Jr.'s vaccine plans, a bottleneck for nurse practitioners, and more health news from Morning Rounds
FDA digital health leader promises generative AI regulatory guidance is coming
FDA expects to issue guidance on policies regarding generative AI devices, according to Rick Abramson, the agency’s head of digital health policy.
Jason Arday and the new politics of plagiarism
The resignation and death of the Cambridge professor is the latest chapter in a centuries-old struggle over originality and intellectual ownership – one intensified by the rise of generative AI.
Following accusations, James Pond Legacy devs say no generative AI was used in creating artwork
Out of their depth
FDA wants feedback on how to regulate generative AI in medicine
“Generative AI-enabled medical devices are poised to reshape the health technology landscape, and the FDA has an important responsibility to provide thoughtful leadership for this new era,” says radiologist Rick Abramson, MD.
AI Helps Researchers Win NIH Grants. Will Science Suffer?
A new analysis of thousands of NSF and NIH grant applications—including some confidential rejected submissions—illuminates new patterns in generative AI’s relationship with federally funded research.
30 New Things Your iPhone Can Do in iOS 27
Apple will release iOS 27 in September, and despite the company's focus this year on refining its flagship operating system and nixing bugs, there are still many additional features on the way, not least of which is Apple's new context-aware Siri, re-tooled for the generative AI era. This year's major iPhone software update isn't all about AI, though, as the following feature list testifies.
Twitch Is Now Using Your Content To Train Amazon AI Models And Has Hidden The Option To Opt Out
For now at least, you can stop Amazon from using your streams and chat to train its generative AI tools
Shopify Inc. (SHOP) Soars as Jim Cramer Applauds AI-Driven Business Formation
Software platforms faced selling pressure due to concerns that generative AI tools would replace traditional software architectures. However, Shopify Inc. (NASDAQ:SHOP) broke away from sector headwinds after second-quarter financial results showed AI tools driving business formation rather than displacing its e-commerce infrastructure. Because Shopify serves small and medium-sized businesses requiring turnkey checkout, payment processing, and […]
Twitch is Mining Peoples' Streams to Train Amazon's AI
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Nature Medicine Just Published the AI Mental Health Audit Framework the FDA Hasn’t Written Yet
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The creatures born from code: Generative AI threatens to upend citizen science records
You need to tread carefully among the leaf litter of the Indonesian scrubland and its tropical rainforests. The dead leaves might seem caught in a gentle breeze, but there's more here than meets the eye. ...
Commentary: AI-obsessed filmmakers are making a crucial miscalculation
Established filmmakers haven’t minced words about their opposition to AI: Guillermo del Toro said he’d “rather die” than use generative AI, while James Cameron has called AI actors “horrifying.” Industry
Nvidia GPUs see yet another price hike of up to 30 percent, as the generative AI hardware crisis worsens
In response Samsung announced another price increase across DRAM as the personal computing nightmare deepens.
AI Tokenomics Explained: What Every Business Leader Needs To Know
AI tokens determine how generative AI systems process information, calculate usage and generate costs, making tokenomics essential for effective AI budgeting.
All The Video Game Studios That Refuse To Use Generative AI
People made games before it existed, and they'll keep doing so long after its gone
Game AI Expert on Where AI Actually Belongs in Game Development
Luke Dicken has been researching AI technology for gaming for decades, and he joined us to share his perspective on the history of AI in games, modern generative AI, game development, production pipelines, player personalization, and why the industry's biggest opportunity doesn't lie in replacing human talent.
The Science Behind the AI Panic Is Shakier Than You Think
A column by Sascha Lobo Is AI making us dumb? So asked DER SPIEGEL on its cover a while ago. After a few weeks of recovery and a therapeutic intervention with the help of my AI, I feel able to respond. That’s a bit unfair, of course; the article itself is more nuanced than the loud cover, the image of a schoolkid with dull prompt questions, or the subtitle: “AI is conquering the schools, and educators fear a disaster.” The short answer to “Is AI making us dumb?” is: no. The long answer is more interesting, and even carries a preliminary glimmer of the spectacular. Unfortunately, it requires a detour into the sphere of artificial intelligence, into the mogul-field terrain of technology assessment, the attention economy, and the destructive virus of cultural pessimism. Along with narrowing the scope to AI’s effects on education and work rather than on intelligence. Because the honest version of the question would be: Does AI help us learn and work, or not? Generative AI, which set off the still-ongoing hype with ChatGPT, has only existed in relevant distribution since late 2022, early 2023. For a technology-driven transformation of people and society, that is extremely short. For that reason alone, research is still in its infancy. And technology assessment is not a fast discipline anyway. Prominent voices from Elizabeth Eisenstein to RAND to Tom Wheeler say we still cannot conclusively judge the consequences of the printing press. Its invention is a mere 580 years back, and some scholars would rather not circulate assessments that might have to be retracted in two or three hundred years. We’re Going Through Growing Pains A phenomenon that already caused upheaval in social media research makes serious assessment of AI’s consequences even harder: the “moving target” problem of LLM-ology, as the linguist Sean Trott called it in 2025. AI develops so quickly and so unpredictably that researchers often end up studying snapshots of the past. There are concepts, from morphological analysis to anticipatory governance, for keeping research, planning, and regulation halfway meaningful anyway. But even with those, universally valid statements are rare. DER SPIEGEL - The German View is a reader-supported publication. To receive new posts and support our work, consider becoming a free or paid subscriber. Subscribe We should therefore treat findings about the interplay between humans and AI as far more procedural and situational. Unfortunately, this challenge comes at the worst possible time. We are going through growing pains: AI’s everyday impact has grown very large very fast, and with it the longing for guidance. Annoyingly, the body of solid knowledge has not exploded along with it. Experts cannot be moved to broad consensus on even banal statements about AI. Sascha Lobo, born in 1975, is an author and strategy consultant focusing on the internet and digital technologies. Together with Jule Lobo, he explores the debates of the day in the podcast “Feel the News – Was Deutschland bewegt” (”What Moves Germany”). Nvidia CEO Jensen Huang says software developers are dying out. Bill Gates considers coders one of only three professions that will survive the AI tsunami. Top tech economists find virtually irrefutable arguments both for and against an AI bubble. The same naturally applies to the structurally youth-hostile debate over whether AI is good or bad for young people. The gap between the demand for insight and the supply of solid knowledge creates an orientation vacuum. This vacuum of AI cluelessness is filled, as the attention economy described by Georg Franck in 1998 would have it, with half-knowledge (funnily enough, often AI-generated), marketing, and self-marketing. After all, infinite money is at stake, along with academia’s best current shot at global fame. But this iridescent froth of interpretation operates more by the algorithmic principles of the digital public sphere than by seriously earned insight. That is why dramatized, fear-feeding claims about AI are so promising. It tempts parts of academia into distorted drivel, and parts of the media then sensationalize the published drivel once more. Was the Research Aimed at a Desired Result? How badly this can influence academia and public perception is demonstrated by one of the most-discussed studies on AI’s effects: “Your Brain on ChatGPT.” The MIT study by Nataliya Kosmyna also gets plenty of space in the SPIEGEL cover story. What was measured and interpreted: lower brain activity in people who write with AI assistance, compared to people who only google or write without any tools. As is common with preprints, the study has not yet been peer-reviewed, and it contains substantial weaknesses that experts have sharply criticized. The first round had 54 participants in three groups, the second only 18, who reportedly also came from MIT’s own orbit. There was no preregistration (committing in advance to what you want to find out with which data). In their analysis, Stanković et al. even discovered an opposite effect that the study does not further explain. Some measurement data has not (yet) been published. And the EEG analysis method used is considered too imprecise to support such far-reaching conclusions. The biggest criticism, though, is the suspicion of an activism-driven study. In an interview with Time, lead author Kosmyna said she published the study immediately, rather than after full peer review, because she feared politicians might otherwise decide to put ChatGPT in kindergartens. She considers that absolutely harmful. It is legitimate to hold such a view. It just seems unscientific to approach a study with it, and then to design the setup so that the chance of a fitting desired result remains as high as possible. Ideologies Collide It is not easy to separate genuine AI insights from studies that trivialize and weaken well-founded AI criticism. The same goes for the opposing, AI-enthusiastic narratives, because the pro-AI side works against it with billions in resources. Ideologies collide, fed by egos, PR strategies, moral posturing, and once-in-a-lifetime opportunities. Doomsday marketing makes the search even harder: AI companies can profit from warnings about the dangers of AI, whether through the notoriety of apocalypse narratives or because, in some target groups, danger translates into power. Some seemingly negative findings are therefore quite welcome in the AI industry. If you try to get at the findings presumably less influenced by interest groups, the picture in education seems relatively clear: AI can improve educational outcomes when the right AI is used the right way, namely pedagogically. Simply dumping an AI chatbot into a classroom, by contrast, accomplishes little. Huge surprise. But something else is also obvious: whether they are allowed to or not, kids use AI for school, which is why the controlled integration of AI tools into education is, in the medium term, entirely without alternative. In the world of work, the landscape of findings is more complex and requires more differentiation. A series of serious studies points to an AI effect that suits neither the alarmists, regulation fetishists, and AI opponents, nor the trillion-dollar corporations with their armada of paid scientists, PR professionals, and ecosystems: working with AI helps the inexperienced (at least for now) considerably more than it helps the pros, in certain fields of work, and provided they know how to use it correctly. Missing Domain Knowledge Among the experienced, the professionals, and the high flyers, by contrast, despite frequent time savings, partially negative effects and new problems are emerging. Take the jagged frontier problem: AI solves task A brilliantly and fails completely at task B, even though both look similar even to professionals. Or the verification-cost problem, in which AI’s greater productivity gets eaten up by the enormous effort of checking its output. Or the illusion of competence, because AI makes new domains seem easily penetrable, until you painfully discover that deep domain knowledge is missing. Taken as a whole, the effects of working with AI do lean positive. But the promise that AI works as a turbocharger for everyone and boosts practically everything simply refuses to materialize. The AI magic the world has been feeling since ChatGPT arrived in late 2022 has so far barely shown up in most companies’ numbers. The consulting firm McKinsey has coined a term for this, the “gen AI paradox,” and believes that work processes and corporate structures would have to be rebuilt quite fundamentally to realize AI’s benefits at scale. Reuters just reported that only 3.3 percent of Microsoft’s customers have subscribed to the AI package Copilot. That may be down to the product; in other areas we continue to see soaring successes and new AI triumphs. But after the first quarter of 2026, disillusionment is the word for all too many AI projects at traditional companies: because the promised revolution of AI agents has so far failed to arrive or been postponed, and because of the leveling effect that many of the studies cited here suggest. Against Inequality The societal effects, on the other hand, appear rather encouraging. Many previous technologies operated on the Matthew principle, named for the Gospel verse about giving to those who already have: they tended to reward the more competent and more privileged. AI, however, seems more often to have an equalizing effect once a threshold of access and education is crossed. Some anecdotal insights point in this direction, for example, how an unemployed man in Leipzig successfully defended himself in court in 2025 against fraud accusations from Germany’s federal employment agency — without a lawyer, armed only with ChatGPT. The AI made mistakes and cited invented court rulings, but in the end the man walked away unpunished. And a key capability of artificial intelligence is its capacity to learn: set up correctly and fed with data, it can keep getting better. It is a question of time, or more precisely of AI innovations and training data, until even free AI chatbots write better legal briefs than law graduates with perfect exam scores. Whether that will make anyone dumb is something the world’s press will surely inform us of in due time. Subscribe Leave a comment
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‘The reality, for better or worse’: Columbia comp sci students and faculty grapple with AI’s disruption of the field
‘The reality, for better or worse’: Columbia comp sci students and faculty grapple with AI’s disruption of the field ‘The reality, for better or worse’: Columbia comp sci students and faculty grapple with AI’s disruption of the field A field that once seemed like a direct path to stable, lucrative work is becoming less certain under AI, students and faculty told Spectator. By Ria Vasishtha and Arjun Menon May 3, 2026 Shanying Liu / Deputy Illustrations Editor Asia Genawi, SEAS ’29, first encountered artificial intelligence during her sophomore year at her high school in Indiana. Back in 2023, policies on AI varied widely—even within the same district—and some schools had no guidance at all. As Genawi began to see the effects of AI trickle into her classroom, she turned to guidance from her home state’s Department of Education, which she said she found “outdated and inaccessible.” Genawi spent the rest of her high school career dedicated to the issue, including writing a 15-page memo exploring varying AI policies across Indiana schools, which she sent to every Indiana state senator and representative whose contact information she was able to find. She later helped draft a bill that would have required public high schools to establish and share their own AI policies with students in an accessible format. But with so many other bills already awaiting referral, hers never made it to committee. When Genawi arrived at Columbia to study computer science, she found that the gaps she had spent years trying to address in Indiana had followed her there. Many students and professors were also grappling with what AI meant for the field. Across Columbia’s undergraduate schools, computer science has become the most popular major—accounting for around 11 percent of degrees awarded in Columbia College, 32 percent in the School of Engineering and Applied Science, and 12 percent in the School of General Studies in 2024. While the number of computer science majors in SEAS grew from 166 to 173 during the 2024-25 academic year, the total number across the three schools fell around 4.5 percent from 393 to 375, driven by declines at Columbia College and General Studies. At Barnard, it has grown to become the second most popular major as of 2025, up from third the year prior. The number of degrees awarded have grown fivefold since 2016. Faculty members and students in the department told Spectator that the surge in the major’s popularity has been driven in large part by its apparent promise of a secure, well-paid career path. However, they noted that the recent rise of generative AI has compromised the sense of stability that once defined the field, even as interest in technical skills among students persists. According to data from the Federal Reserve Bank of New York in 2024, out of 74 majors tracked, computer science had the fifth highest unemployment rate among majors at 7 percent, while computer engineering had the second highest at 7.8 percent. “Anecdotally, people are moving away from CS as a major,” Daniel Bauer, a senior lecturer in the computer science department, said. “They’re still taking some of our classes, right, because they think they need that, but they’re instead majoring in other things.” Bauer described a field that had shifted from what he called a “nerdy outlier discipline” to one that “everyone needs,” a sign that technical skills have become a baseline expectation across industries with the emergence of AI. “A lot of people thought, ‘Oh, it’s a guaranteed path to a stable income. You get a six-figure job right out of your undergrad,’” Bauer said. Now, companies may see AI as a way to reduce demand for entry-level programmers, especially in what he calls “code monkey jobs,” roles where a large number of employees are “just writing out code nine-to-five.” Chris Murphy, a senior lecturer in the computer science department, described the current moment as the convergence of two forces: the downturn of the job market and generative AI coming onto the scene. “Things kind of started to really pick up in 2014, 16,” he said, recalling the years after the weaker 2010 market. Murphy added that this was also a period where “students were getting more experience outside of class than they were inside of class” through internships, jobs, and side projects. Murphy suggested that the earlier momentum helped make computer science feel like both an academic program and a reliable pathway into work. That feeling is harder to sustain now as the industry reconfigures, which is a shift that students are seeing firsthand. Rebecca Yu, SEAS ’27, said that during a recent internship in Big Tech, she saw that “every single tech company was racing to integrate” large language models. She added that her manager said her intern class was the first to complete their assigned projects, which she attributed to the increased efficiency that comes with AI. Frank Liu, SEAS ’29, said that with AI lowering the barrier to coding, companies now expect everyone to write code. “A lot of companies outright say if you’re not using coding in your job, you might get fired for not being productive enough,” Liu said. Yu similarly expressed that students increasingly have to accept AI being a part of industry workflow, adding that many also “make use of it to maximize their productivity.” Richard Li, CC ’28, described a “franticness” among his peers as the pace of change accelerates. He explained how “some new tool” is released regularly, noting that tools rise and fall in prominence within weeks. He has come to believe that he doesn’t need to “match that speed all the time” and keep up with every development. Li has learned that AI tools allow him to “take a breath” and “get back into the loop much easier than before” when he needs to. While some companies specifically target Columbia when hiring, sending representatives to campus career fairs and recruiting large numbers from Columbia, a computer science degree cannot be treated as a static credential, Yu described. “You can’t just get your degree and stop learning after that. You have to always be learning,” Yu said. “That is something you basically have to expect for your job.” AI has not only affected students’ decisions to major in computer science, but also reshaped how the subject is taught. Across departments, faculty members no longer treat work done outside the classroom as a reliable measure of understanding, shifting instead toward in-person exams, quizzes, and attendance checks. While homework once made up as much as 60 to 70 percent of a student’s grade in computer science classes, Murphy said that breakdown has since flipped, with exams and quizzes now accounting for the majority. “The assumption—especially among pessimists—is that they’re using it to do their homework,” Murphy said. “They take the homework assignment. They put it into generative AI. Out comes the solution. Submit solution. The end.” Murphy said that faculty members ranged in their responses from fully prohibiting AI use to actively teaching students how to effectively work with AI. He said he shifted his approach this year after his teaching assistants called his belief that students weren’t using the technology “naïve,” and now permits students to use AI on assignments. His surveys of students in his introductory classes have told a more complicated story than the one so-called pessimists offer: Around 60 to 70 percent of students who reported using AI said they used it to have concepts explained to them, to clarify assignment instructions, to generate test cases, or to create practice questions. “Those are all ways that you might have had a tutor in the past to do that, and now you have this AI essentially as your tutor,” he said. Bauer has taken a different approach, teaching students how to use AI productively without sacrificing the core principles of the discipline. “People who are trained to actually use AI tools productively, while being in charge of designing the overall project, will be very much in demand in the next couple of years,” he said. Over the past year, a working group of computer science faculty has been redesigning the introductory and intermediate programming sequence to integrate generative AI as both a subject and a tool, representatives from SEAS wrote in a statement to Spectator. The effort is “coordinated” across the department, “not course-by-course,” with a systematic assessment of how AI integration is affecting student outcomes underway to shape the next round of changes. The goal, the department explained, is for students to be able to “read, verify, and reason about code, whether they or a model wrote it.” Tony Dear, senior lecturer in the computer science department, is piloting individualized AI feedback in a discrete mathematics course, while a machine learning course is also testing a Socratic AI dialogue system designed to “guide inquiry rather than supply answers,” the statement reads. Beyond individual courses, SEAS funded seven cross-departmental faculty projects in generative AI this past academic year, spanning biomedical engineering, chemical engineering, industrial engineering, and computer science, according to the statement. This phenomenon extends beyond the computer science department. SEAS’ new AI minor, which it announced in November 2025, reflects the University’s attempt to adapt. The minor is specifically designed for noncomputer science majors and aims to provide “essential AI knowledge” while emphasizing practical and responsible use across disciplines, according to the SEAS website. At the center of the minor is AI in Context, a course taught by a team of faculty from the departments of computer science, applied mathematics, philosophy, music, literature, and the Writing Center, the representatives told Spectator. Bauer described it as targeted at students who want to bring AI into fields like economics or biology, rather than as a path into software engineering itself. At the graduate level, SEAS announced a new Master of Science in artificial intelligence in February, with the inaugural cohort starting in the fall. While recognizing how AI has helped them navigate coursework, students also described its rise as isolating, even among members of the Application Development Initiative, one of Columbia’s largest computer science clubs. “As people start to ask AI for questions that they would normally ask students and members, it starts to isolate people” Li said. Alexa Kafka, BC ’27, echoed Li’s sentiment, pointing out that computer science has always been a collaborative discipline with code reviews and pull requests, even as AI makes independent work easier. Despite this, Kafka noted that she hasn’t been to office hours “in at least a year.” Bauer added that faculty are exploring long-term solutions to the assessment problem. “One of the things that we’re trying to do at the department or school level is to maybe move towards computerized testing facilities,” Bauer said, referring to ideas in the department to revitalize computer labs as an alternative to pen-and-paper exams. “We have to accept that this is the reality, for better or worse.” But more exams, students say, does not mean better learning, nor does it reflect how computer science is actually done. “Code is so variable and can be approached in so many directions, there’s never just going to be one correct answer. There can be multiple optimal solutions,” Kafka said. Students also expressed concern that the shift toward exam-heavy grading pulls focus away from the applied, project-based work that better reflects both discipline and industry expectations. ADI has tried to respond more quickly than the curriculum can. Through a vibe coding workshop this past semester, club members said they wanted to help students understand not just that AI exists, but how to use it deliberately. “Vibe coding” refers to the practice of prompting AI to write code for a task or project, and has become widespread enough that ADI felt the gap in formal instruction was worth addressing, according to Sophia Huang, BC ’29. The workshop introduced students to the concept of context engineering, which Shaina Sahu, SEAS ’27, described as not just writing a prompt, but optimizing “the rest of the relevant information that you would feed into the model.” Without that, students said that AI-generated code can fail at scale or introduce difficult-to-detect bugs. Genawi said the shift toward AI has changed what it means to be good at computer science. “I think the shift has kind of gone towards what can you create and what can you do, instead of, what do you know,” she said. Indeed, during ADI DevFest, its annual hackathon, Li said more teams are trying to complete their projects than in years past. While sign-ups have historically outpaced submissions, Li said this is beginning to change because teams “have a tool that completes the vision for them.” While many students see AI as an equalizer that lowers the barrier to entry for coding and technical work, Murphy said it also creates new equity concerns inside the classroom around who can afford stronger tools and who already knows how to use them. “The equity issues I worry about are students who have access to paid versions of things versus free versions of things,” he said. Although popular AI models like ChatGPT and Claude have free versions available, both have paid models that can reach over $100 per month, which output different qualities of code. Murphy also pointed to differences in prior exposure to AI literacy itself. “Students who go to high schools or K-12 education, where they’re taught AI literacy, prompt engineering, context engineering, they understand how to do this, as opposed to students who go to schools who don’t teach that,” he said. “Then they come in, and then they’re somehow expected to know how to use these tools.” For Genawi, those disparities begin long before students arrive on campus. “It’s very interesting to consider how lucky you were geographically,” she said. “To be born where you were is influencing your ability to get access to these spaces.” Students like Yu, though broadly apprehensive about the future of computer science, are not without hope. “I’m optimistic, because I think if you’re truly passionate about CS, there will definitely be a place in the field to do something you want to do,” she said. Senior Staff Writer Ria Vasishtha can be contacted at ria.vasishtha@columbiaspectator.com. Follow Spectator on X @ColumbiaSpec. Staff Writer Arjun Menon can be contacted at arjun.menon@columbiaspectator.com. Follow Spectator on X @ColumbiaSpec. Want to keep up with breaking news? Subscribe to our email newsletter and like Spectator on Facebook. Produced with Spectate by Emily Ta
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