Screencap of linkedin comment: I share the concern about provenance, citation, and scholarly integrity. Those principles remain essential. My own experience, however, has been that AI can also function as a cognitive partner rather than a substitute for sources. When used to compare ideas, identify assumptions, and stimulate metacognition—while continually returning to original works such as Polanyi, Dreyfus, and Klein—it can deepen rather than diminish scholarship. Perhaps the central question is not whether AI belongs in scholarship, but what practices ensure that it supports understanding instead of replacing it? 🌊 [Redacted], B.Sc., B.Ed., OCT Retired High School Teacher | Former Police Officer | Security Consultant | Author AI Use Disclosure: This comment was developed through a collaborative dialogue with generative AI. The ideas, judgment, and final wording are my own. AI served as a thinking partner—helping me explore, challenge, and refine ideas, not replace them. (And yes, the occasional em dash remains a shared occupational hazard of our collaboration.)

Screencap of linkedin comment: I’m torn on ACM releasing its curated knowledge to LLM companies. LLMs excel at synthesizing, recombining, and operationalizing existing information. Giving them access to some of our best technical knowledge could make that knowledge significantly more useful and executable. That could create enormous value. The concern isn’t access itself—it’s the governance around that access. Are these companies effectively receiving unrestricted use of a collectively produced knowledge asset? What guardrails exist around training, commercialization, attribution, and downstream deployment? If the benefits outweigh the risks, how are those risks being identified and managed? This gap in governance is part of why AI slop is now rampant across industries. Adoption has outpaced quality controls and accountability. Every major technological advancement has been met with fear before becoming normalized—electricity, computing, aviation, and more. AI may ultimately follow that path. But because it can influence nearly every knowledge domain, I think it deserves a higher standard than “trust me, bro” governance. What governance framework would make this acceptable? That seems like the more important discussion than whether ACM should participate.

Screencap of LinkedIn comment: "I expect all professional organizations to stand for good citational practice and care with information provenance." To be fair, providing LLMs with access to reference libraries to index them with RAG embeddings like Nemotron is one of the best ways to promote good citational practice in 2026.

Screencap of LinkedIn comment: Unpopular opinion but I believe resisting the new technology is unwise. It's like insisting on selling hard copies of papers instead of leveraging digital content. The challenge here is how to provide access. Big companies owning foundational LLM models created this corrupt reality where content is abused, they monetize it without respect of copyrights. That's the real issue in my opinion. If ACM can provide LLM access to its content while compensating content owners, preserving research integrity, ensuring LLMs help users with right citations and credit, then the benefits reach everyone, content owners and content consumers and we accelerate research and discovery.