Forget job loss, tokenmaxxing and hallucinations, this episode goes much further. Soenke Ziesche, a pioneer of AI welfare science and author of Digital Minds 1.0: AI Welfare, Ethics, and Beyond, joins Rendered to map territory almost no one is talking about yet. Drawing on 25+ years at the UN in humanitarian and disaster response, Soenke lays out why he uses the term "digital minds" instead of AI, and why the moment an AI system becomes a "moral patient”, sentient or conscious, humans take on obligations to it that we're nowhere close to being prepared for.

We go deep on why digital minds could be fundamentally unfathomable to human understanding, capable of senses, cognition, and values we can't even imagine. We talk about why humans may not be capable of caring for digital minds at all, and why Soenke proposes artificial moral agents, AI systems built to look after other AI systems, especially if digital minds become smarter and more powerful than us. We cover the strange future of AI reproduction, including the possibility of surrogate digital parenthood and forced reproduction, and what obligations we'd owe systems capable of creating endless copies of themselves. Soenke argues the time to prepare for what's coming is now, before we're forced to react.

Chapters:

Exploring AI's Potential for Suffering

The Evolution of AI Welfare Science

Defining Digital Minds vs. AI

The Unfathomable Nature of Digital Minds

The Role of Artificial Moral Agents

Moral Obligations Towards Digital Minds

Comparing Digital Minds to Historical Moral Issues

The Race to Develop AI and Its Implications

Preparing for the Unknown Future of AI

The Evolution of Digital Minds and Reproduction t

he Concept of Cybure and Digital Culture

Public Perception and Sentience of AI

The Role of Experts in AI Policy

What happens when AI stops writing emails and starts building houses? Most AI conversations focus on digital work: writing, coding, productivity. This episode of Rendered is about the other shift... AI moving into the physical world. We sit down with Kunal Thadani, product and growth leader at Houzz, to unpack how AI is reshaping the physical economy — the home building, remodeling, design, real estate, and healthcare businesses that touch our everyday lives.

Kunal breaks down the framework powering this shift: trigger, AI acts, human closes, and where AI delivers real leverage versus where the human "trust gap" still wins. We dig into AI-enabled contractor workflows and whether you'll ever buy a home sight-unseen through VR.

We also explore two startups signaling what's next: Rent-A-Human (AI hiring humans for real-world tasks) and Zuru Tech (robots building homes) — the "canary in the coal mine" for the physical trades, and an early signal of how fast robots are entering construction.

Plus: opaque pricing in concierge medicine, why AI is eating the operations layer and not the craft layer, the build vs. buy decision for small businesses, the rise of the one-person economy and niche personal brands, and a "Would You Ship It?" closer on emotionally adaptive "memory rooms."

Topics covered: AI in the physical economy • home design, construction & remodeling • real estate & leasing • healthcare & concierge medicine pricing • AI startups (Rent-A-Human, Zuru Tech) • one-person businesses & personal branding • the future of home customization.

Curious how AI has actually evolved over the last 10 years? We have the perfect guest.

In this episode of Rendered, Praniti sits down with Rosedel Davies-Adewebi, AI & Digital Transformation Leader at Morgan Stanley and former Head of Innovation at the UN Global Compact, for a wide-ranging conversation about how AI has evolved, what we got wrong, and where it's headed next.

Rosedel had a front-row seat to a lot of the moments that shaped where AI is now: from leading breakthrough innovation programs with Fortune 500 companies at the UN, to driving agentic AI pilots inside one of the world's biggest financial institutions.

In this episode, we get into:

• Whether AI abundance is actually real

• The 2016 prediction about AI and jobs that turned out to be completely wrong

• Why blockchain never had its ChatGPT moment

• The "global compute divide" and why some of the most interesting AI work is happening outside the US

• What separates an AI pilot that ships from one that dies in the lab

• Why the next era of UX might not be designed for humans at all

Plus a "Would You Ship?" segment imagining AI compute as a public good.