AI-Curious with Jeff Wilser

• How San Jose is Harnessing AI (and What We Can Learn From It), w/ Mayor Matt Mahan

  Can a city use AI to cut red tape, fill potholes faster, and shave minutes off commutes—without sliding into surveillance? We sit down with San José’s mayor, Matt Mahan, to unpack how a highly regulated public institution can adopt AI pragmatically and responsibly. In this episode, we dig into the playbook: pilots that become policy, guardrails that build trust, and workforce upskilling that actually moves the needle.We cover how bus routes now hit fewer red lights, why real-time translation boosts civic inclusion, what “privacy by design” looks like for license-plate readers, and how a 10-week AI curriculum is turning city staff into hands-on builders. We also press on the risks—bias, privacy, and transparency—and explore where city AI is headed next: transit, permitting, and procurement.HighlightsFrom pilots to scale: Bus route optimization with Light AI cut red-light hits by 50%+ and reduced travel time by 20%+, now rolling out citywide.Inclusion by default: Real-time multilingual access (e.g., Wordly) and improved translations informed by San José’s deep Vietnamese-language data.Eyes on the street, not faces: No facial recognition, strict retention, no third-party data sharing, and tightly controlled access to ALPR data.Upskilling at scale: A 10-week AI curriculum (plus a data track) with San José State; staff build custom GPTs (including a budget-analysis GPT) to speed analysis.Culture that ships: A “coalition of the willing,” clear problem statements, and a Mayor’s Office of Technology & Innovation to operationalize change.Road ahead: Smarter mass transit, faster permitting, and streamlined procurement—practical abundance without new tax dollars.If you’re new here, we’d love your support—subscribe on Apple, Spotify, or YouTube, and consider leaving a quick rating or sharing this episode with a colleague who’s wrestling with real-world AI adoption.

  --------  

  35:08

  --------

  35:08
• The Complicated Intersection of AI and Creativity, w/ Dr. Maya Ackerman

  Does AI make us more creative—or quietly replace us?In this episode of AI-Curious, we sit down with Dr. Maya Ackerman—author of Creative Machines: AI, Art, and Us—to probe where human creativity ends and machine creativity begins, and how incentives in Big Tech and venture capital shape the tools we all use. We explore why today’s dominant systems skew “convergent” (safe, samey, oracle-like) instead of “divergent” (surprising, generative), what that means for artists, and how to design AI that actually elevates human imagination rather than displacing it.Why listenWe wrestle with uncomfortable truths: bias mirrored back at us, investor pressure to “replace” vs. “augment,” and the risk of a cultural sea of slop. We also map a constructive path forward—collaborative systems, richer human–AI interfaces, and a 10-year horizon where AI expands human creative range.GuestDr. Maya Ackerman — AI researcher, entrepreneur, and author of Creative Machines: AI, Art, and Us. TakeawaysAI reflects us. Bias in → bias out; representation fixes are not enough without cultural understanding.Incentives matter. Many well-funded tools are architected to replace creators; augmentation tools are underfunded.Creativity ≠ autocomplete. Today’s LLMs are optimized for correctness and convergence, not genuine divergence.Better interfaces beat bigger models. Beyond “text-to-X,” human-centred, interactive tools can coach, not usurp.A hopeful arc. With the right design, collaborative AI can measurably raise human creative ability—and stick.Dr. Ackerman's new book: Creative Machineshttps://www.amazon.com/Creative-Machines-Future-Human-Creativity/dp/1394316267

  --------  

  39:22

  --------

  39:22
• LinkedIn's Chief AI Officer, Deepak Agarwal, on AI Agents, Building Responsible AI, and the Future of Work

  What does hiring look like when AI is embedded into the world’s largest professional network—and how should leaders, recruiters, and job-seekers adapt?We sit down with Deepak Agarwal, LinkedIn’s Chief AI Officer, for a practical playbook on AI at work: production-grade AI agents for hiring, how semantic job search changes discovery, why “relevance” is the antidote to spammy outreach, and how to build a culture of responsible AI that scales. We unpack where humans stay firmly in the loop—and how AI can reduce friction, close information asymmetries, and free more time for real human connection.Highlights•LinkedIn’s AI agents (incl. Hiring Assistant) are in market with paying customers; routine sourcing drops from ~40 hours to a few, while humans focus on candidate fit and relationship-building.•Semantic job search moves beyond keywords to plain-English intent and better matching across people, jobs, and knowledge.•Responsible AI is baked in: bias detection/mitigation, rigorous pre-launch testing, and governance—treated as a must-have, not an afterthought.•“Relevance is the key currency”: better matching reduces spray-and-pray outreach and AI-to-AI noise.•Guidance for leaders: embrace discomfort, start from the problem (not the tool), choose the right autonomy level, and rethink testing for non-deterministic systems.•Guidance for job-seekers: be authentic, upskill, and optimize for the next five years—not the next five months.•Future of work: AI shrinks the 80% “prep” to expand the 20% creative/strategic work; humans remain in control.If you’re curious about our AI & Leadership event, The Drawing Room at The Explorers Club in NYC, learn more at TheDrawingRoom.ai. If you found this useful, follow the show, rate/review, and share with a hiring leader or job-seeker who needs a clear view of what’s coming.LinkedInAI-Curious

  --------  

  48:43

  --------

  48:43
• Why GEO is the New SEO--And How Businesses Must Adapt--w/ Curtis Sparrer, co-founder of Bospar

  Will GEO replace SEO? (Spoiler alert: Probably!) We dig into how generative engines are reshaping discovery, why executives are already making decisions from AI answers, and what brands should do now to show up accurately and credibly in AI results.In this episode of AI-Curious, we sit down with Curtis Sparrer, co-founder and principal at Bospar PR (and president of the San Francisco Press Club). Curtis has been experimenting across models, building a GEO toolkit (“Audit-E”), and advising companies on how to fix AI-age brand visibility—especially when models get facts wrong or elevate low-quality sources.What we coverGEO vs. AEO vs. classic SEO—clear definitions and where each mattersHow AI engines weigh sources (and why third-party, reputable coverage now carries outsized influence)The “AI content gold rush”: press releases, FAQs, and AI-first site architecture (schemas, structured info)Case study: correcting a widely propagated falsehood about a client (“not dead yet”) and the steps that workedPractical GEO hygiene: what to keep from the SEO playbook; what to adapt for AI reasoningPitching in the AI era: why templated, “robotic” outreach backfires and how to use AI for ideation and structure, not the final draftWinners & losers: PR-skeptics vs. teams that proactively feed reputable signals to modelsNear-term predictions: from “AI ethics” to emerging AI manners—what will be considered rude or acceptable AI use in commsGuestCurtis Sparrer — Co-founder & Principal, Bospar PR; President, San Francisco Press Club.Bospar:https://bospar.com/Forbes coverage of Audit-E launchhttps://www.forbes.com/sites/digital-assets/2025/09/25/whats-in-your-search-why-generative-ai-is-the-new-front-door/If you’re new here, subscribe on Apple, Spotify, or YouTube, drop a five-star rating, and share with a friend who’s wrestling with search-to-answer disruption.

  --------  

  40:10

  --------

  40:10
• Space Robots Are Here *Now*, w/ Icarus Robotics cofounders Ethan Barajas and Jamie Palmer

  What happens when “space robots” stop being sci-fi set dressing and start punching a clock? We dig into a new breed of microgravity robots that do the unglamorous work—so astronauts can do more science.In this episode of AI-Curious, we talk with Ethan Barajas (CEO) and Jamie Palmer (CTO), co-founders of Icarus Robots, fresh out of stealth with a $6M raise. Their pitch is simple and radical: put agile, teleoperated robots insidespacecraft like the ISS to handle cargo, inspections, and maintenance—then use the resulting microgravity manipulation data to unlock partial (and eventually full) autonomy. We cover the tech, the economics (why astronaut time is so expensive), the AI roadmap, and a pragmatic path from today’s chores to tomorrow’s orbital factories and lunar bases.What we coverWhy astronaut hours are precious—and how robots can “augment” rather than replace themThe form factor: free-flying, drone-like bodies with dual arms optimized for zero-G dexterityInside first, outside later: a deployment strategy that lowers safety hurdles and accelerates learningData advantage: building the first large microgravity manipulation dataset via continuous teleopAI’s role: from human-in-the-loop control to primitives to scalable dexterous manipulationCommunications and latency: S-band today, laser links tomorrow; what “real-time” actually meansThe “orbital factory” thesis: pharma, semiconductors, fiber optics—and servicing orbital data centersLong-horizon forecasts: humans living and working in space; physical labor increasingly done by robotsGuestsEthan Barajas — Co-founder & CEO, Icarus RobotsJamie Palmer — Co-founder & CTO, Icarus RobotsWhy this mattersIf half of Earth’s GDP is labor, the space economy scales only when on-orbit labor scales. Teleoperated robots that learn from expert demonstrations—then graduate to safe autonomy—are a credible bridge from today’s stations to tomorrow’s factories, data centers, and off-world bases.https://www.icarusrobotics.com/

  --------  

  41:51

  --------

  41:51

More Technology podcasts

Trending Technology podcasts

About AI-Curious with Jeff Wilser

AI-Curious with Jeff Wilser: Podcasts in Family