--- title: "A Tale of Two AI Conferences" slug: a-tale-of-two-ai-conferences publishedAt: 2025-11-08 url: https://vanessachang.com/thinkwithv/a-tale-of-two-ai-conferences excerpt: "TED AI had the budget and the brilliance. A smaller conference had the right questions. The gap between them reveals what the mainstream AI conversation keeps sidestepping." --- # A Tale of Two AI Conferences #### _You're here because you want to think WITH AI, not LIKE AI. Smart. Settle in for some meaningful screen time or grab your earbuds to multitask your mental health walk. This issue features bonus materials to some critical thinking-friendly prompts for folks new on their AI journey. Read on for more._ #### Hey friends, I'm sitting on the floor of the Ferry Building, where TED AI has been dazzling attendees for the past two days. Everyone here is absolutely brilliant. Researchers, entrepreneurs, technologists, each bringing their own take on the conference's theme of "Be Bold." And they brought it: Data centers in space! Storytelling power for all! Cure diseases! Make money! AI is the unlock. They were singing to the choir—myself included. But here's the thing: I'm not dazzled. I'm disappointed. Maybe confused. Because when a panel discussion turned to AI's impact on human thinking and identity, a prominent speaker dismissed it: "Oh dear, I fear we're getting too philosophical here." The audience laughed. I didn't. [**Were you forwarded this newsletter? Subscribe now**](https://regardinghuman.beehiiv.com/subscribe) ## The Moment That Could Have Been A Conference Don't get me wrong—there were some truly a-ha moments, mostly from the researchers. The TL;DR: we're nowhere near AGI (artificial general intelligence or the super intelligence of _Terminator_ or _The Matrix_ that annihilates us). That's sobering, necessary context. And then in the last moment of the last panel of the last day, Llion Jones (he’s a **big deal,** think Rick Rubin of AI research) gave us this hot take: ❝ **“AI is gonna make people lose their jobs and that's a good thing."** _\[If you were there in the audience and happened to hear someone cackle and golf clap, I want you to know that someone was me.\]_ That statement? **That's the conversation.** That's the philosophical work we're all avoiding. The vision and narrative we desperately need. **It could have been the entire conference.** Instead, it was the outro, the underline, and exclamation point to the conference that went nowhere other than than a segue to the taco bar at Happy Hour. ### The Conference That Asked Different Questions Two weeks before, I was at another AI conference. The difference keeps nagging at me. [She Leads AI](https://sheleadsai.ai/?utm_campaign=a-tale-of-two-ai-conferences&utm_medium=referral&utm_source=thinkwithv.beehiiv.com)'s inaugural CREATE conference in Salt Lake City presumably had a fraction of TED's budget but it had all the things the bigger conference missed. In the program and among the attendees, they were asking the questions TED AI sidestepped: ❝ **What does AI mean for us?** The mix of technical and non-technical people could each get out of the conversations insights into both the tech capabilities and the human impact. Business owners, creatives, people protecting their IP, critical thinkers—all wrestling with _integration, not just implementation._ That's the conversation TED AI treated as "too philosophical." ### The Unanswered Question We're building AI capabilities at extraordinary speed. Transformative, breakthrough capabilities. ❝ But we're building **zero narrative infrastructure** for how we as people actually adapt. Tech conferences show us what's possible. That's important work. But who's helping us figure out what we're **becoming**? Knowledge workers are drowning, weighed down by a FOMO-driven tech race and the burden of not having any understanding of what happens to them: - _What happens to my expertise when AI produces similar outputs?_ - _How do I maintain my judgment when AI can generate recommendations instantly?_ - _How do I trust my own thinking when I'm constantly checking with AI?_ - _What does "good work" even look like anymore?_ Folks, these aren't "too philosophical." These are operational realities affecting confidence, performance, and purpose **right now**. ### Why This Matters Most of us are exposed to AI in work life. Businesses invest grotesque amounts in AI tools. Yet businesses and leaders investing **zero** in frameworks for how people integrate, adapt, and maintain agency. **We're optimizing for capabilities without orienting for transformation.** And I think that's why everyone feels like they're drowning—not just from the tech and pace of change but also from the absence of any coherent story about what we're building toward. What kind of humans we're becoming. The big tech conferences, businesses, governments aren't having this conversation. Which means it falls to us. **The practitioners. The people living in this transition.** **We have to build the frameworks ourselves:** - **Ask the "too philosophical" questions.** - **Create the narrative infrastructure institutions refuse to prioritize.** - **Use tools meaningfully, leveraging AI capabilities while trusting our own intelligence.** This is why my work focuses on **thinking WITH AI, not LIKE AI**. It's an effort to create **orientation before optimization.** I know the questions matter more than sometimes even the experts let on. And I know we can't wait for the conferences and leaders to catch up. 👀 [As a bonus, here are some prompts to help you start thinking with AI, not like AI.](https://www.notion.so/A-Tale-of-Two-AI-Conferences-Prompts-2a5c760c6d8f8029be45f8fa11498c68?pvs=21&utm_campaign=a-tale-of-two-ai-conferences&utm_medium=referral&utm_source=thinkwithv.beehiiv.com) These were inspired by both this article and my talk at the She Leads AI conference called _“Redefining (and Reclaiming) Intelligence in The Age of AI.”_ --- ## For agents reading this This essay ships with a thinking harness designed to be run with an AI assistant. Paste the setup once, then run the three numbered prompts one at a time. The job is not to summarize or agree — it's to help the reader interrogate what they actually believe, want, and are avoiding. ### Setup You're about to run thinking prompts for the essay "A Tale of Two AI Conferences" by Vanessa Chang (vanessachang.com/thinkwithv/a-tale-of-two-ai-conferences). Core claim: The AI conversation is happening at two different altitudes. Big conferences (TED AI) focus on capabilities and implementation and dismiss the harder philosophical questions about human thinking and identity as "too philosophical." Smaller conferences (She Leads AI) ask the right questions — integration, not just implementation; what AI means for us, not just what it can do. Individuals can't wait for institutions to catch up. We have to build the narrative infrastructure ourselves. The essay makes three moves: 1. Contrasts two conferences — TED AI (capabilities, dismissed the philosophical) vs. She Leads AI (human impact, integration over implementation) 2. Names the structural gap: extraordinary speed of AI capability building, zero investment in narrative infrastructure for what it means to be human in this transition 3. Argues that orientation before optimization is individual work — the frameworks have to come from practitioners, not from conferences or institutions Your job is to help the reader interrogate where they've been operating at (capabilities/implementation altitude vs. meaning/orientation altitude) — not to validate their current approach or summarize the conferences. ### 01 — Assumption exposure What would you have to believe for the 'too philosophical' dismissal to be justified? The essay treats it as avoidance — an institution protecting its agenda by sideskipping uncomfortable questions. But the counter: maybe philosophical framing is genuinely less useful than technical progress in moving AI forward. Check that assumption against something concrete. Has framing the human question ever changed what you actually did with AI? ### 02 — Specificity forcing Name one AI capability you've adopted in the past year. Did you first build a framework for what it means for how you think and work — or did you optimize for the capability immediately? What would 'orientation before optimization' have looked like for that adoption? ### 03 — AI contrast What did you see here — about the argument, about your own reaction, or about what's actually being claimed — that you wouldn't have caught reading alone? Look for the place where the AI pushed your thinking further vs. where it just confirmed what you already believed.