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 listen

We 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.

Guest

Dr. Maya Ackerman — AI researcher, entrepreneur, and author of Creative Machines: AI, Art, and Us.

Takeaways

• AI 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 Machines

https://www.amazon.com/Creative-Machines-Future-Human-Creativity/dp/1394316267

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.

LinkedIn

AI-Curious

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 cover

• GEO vs. AEO vs. classic SEO—clear definitions and where each matters
• How 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 worked
• Practical GEO hygiene: what to keep from the SEO playbook; what to adapt for AI reasoning
• Pitching in the AI era: why templated, “robotic” outreach backfires and how to use AI for ideation and structure, not the final draft
• Winners & losers: PR-skeptics vs. teams that proactively feed reputable signals to models
• Near-term predictions: from “AI ethics” to emerging AI manners—what will be considered rude or acceptable AI use in comms

Guest

Curtis Sparrer — Co-founder & Principal, Bospar PR; President, San Francisco Press Club.

Bospar:

https://bospar.com/

Forbes coverage of Audit-E launch

https://www.forbes.com/sites/digital-assets/2025/09/25/whats-in-your-search-why-generative-ai-is-the-new-front-door/

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