with Justin Harnish & Nick Baguley

In Episode 7, Justin and Nick step directly into one of the most complex frontiers in emergent AI: machine ethics — what it means for advanced AI systems to behave ethically, understand values, support human flourishing, and possibly one day feel moral weight.

This episode builds on themes from the AI Goals Forecast (AI-2027), embodied cognition, consciousness, and the hard technical realities of encoding values into agentic systems.

Ethics is no longer just a philosophical debate — it’s now a design constraint for powerful AI systems capable of autonomous action. Justin and Nick unpack:

• Why ethics matters more for AI than any prior technology
• Whether an AI can “understand” right and wrong or merely behave correctly
• The technical and moral meaning of corrigibility (the ability for AI to accept correction)
• Why rules-based morality may never be enough
• Whether consciousness is required for morality
• How embodiment might influence empathy
• And how goals, values, and emergent behavior intersect in agentic AI

They trace ethics from Aristotle to AI-2027’s goal-based architectures, to Damasio’s embodied consciousness, to Sam Harris’ view of consciousness and the illusion of self, to the hard problem of whether a machine can experience moral stakes.

Justin and Nick begin by grounding ethics in its philosophical roots:

Ethos → virtue → flourishing.

Ethics isn’t just rule-following — it’s about character, intention, and outcomes.

They connect this to the ways AI is already making decisions in vehicles, financial systems, healthcare, and human relationships.

AI-2027 outlines a hierarchy of AI goal types — from written specifications to unintended proxies to reward hacking to self-preservation drives.

Nick explains why corrigibility — the ability for AI to accept shutdown or redirection — is foundational.

Anthropic’s Constitutional AI makes an appearance as a real-world example.

Justin distinguishes between:

• Goals: task-specific optimization criteria
• Values: deeper principles shaping which goals matter

AI may follow rules without understanding values — similar to a child with chores but no moral context.

This raises the key question:

Can a system have values without consciousness?

A major thread of the episode:

Is a non-conscious “zombie” AI capable of morality?

Justin and Nick explore whether AI needs a body — or at least a simulated body — to:

• Learn empathy
• Understand suffering
• Form values rooted in lived experience

This touches robotics, synthetic emotions, and the debate over “felt consciousness.”

Nick highlights the massive cultural gap in AI performance:

• U.S. cultural fit ~79%
• Ethiopia and other underrepresented regions ~12%

This matters for fairness, safety, and global ethics.

A surprising turn: AI’s ability to help humans improve moral clarity.

Justin draws from...

Episode Summary

Is creativity uniquely human—or can machines share in the spark? In this episode of The Emergent Podcast, Justin Harnish and Nick Baguley are joined by Chris Brousseau to tackle one of the most intriguing frontiers in the Age of AI: creativity itself.

Together, they unpack the messy, magical, and sometimes mechanical ways that ideas emerge. From “innovation voids” in machine learning to the golden goat thought experiment, the conversation explores how humans remix and recombine concepts—and whether large language models are beginning to do the same.

Justin, Nick, and Chris debate whether AI’s “creativity” is novelty, derivative recombination, or something that could one day surprise us in ways we can’t yet measure. Along the way, they draw analogies to quantum physics, protein folding, and telescopes for the mind.

What You’ll Learn in This Episode

• Why creativity is so slippery to define—and why that matters for AI.
• The concept of “innovation voids” and how machines might someday fill them.
• Human imagination vs. machine recombination: is one more “authentic” than the other?
• How analogies, metaphors, and mistakes drive breakthroughs in science and art.
• Why generative AI might be our James Webb Telescope for the mind.
• What it means to co-create with AI—and why the future may be about collaboration, not competition.

Books & Ideas Mentioned

• Programming the Universe – Seth Lloyd
• The Stuff of Thought – Steven Pinker
• I Am a Strange Loop – Douglas Hofstadter
• AlphaFold & breakthroughs in computational biology
• Innovation benchmarks like Kaggle challenges

Key Takeaway

Creativity isn’t a bolt of lightning from nowhere. It’s a dance of patterns, recombinations, and leaps into the unknown. As AI joins the dance, maybe the real story isn’t whether machines are “truly creative,” but what new things we can create together.

Can machines become conscious? And if they do, what kind of moral relationship should we have with them?

In this second installment on the AI Alignment Problem, Justin and Nick delve into the philosophy, neuroscience, and mysticism surrounding machine consciousness. They explore whether AI systems could possess a subjective inner life—and if so, whether alignment should be reimagined as moral resonance instead of mere goal matching. Along the way, they discuss how mindfulness, memory, embodiment, and suffering shape our understanding of what it means to be sentient—and how we might recognize or construct such capacities in artificial systems.

You’ll leave this episode with a deeper understanding of consciousness—from the perspective of both humans and machines—and what it might mean to extend moral standing to synthetic minds.

• What is consciousness and how do we define it?
• Can artificial systems host genuine subjective experience?
• The neuroscience and computational theories of consciousness
• The “Hard Problem” and the possibility of virtualizing consciousness
• Ethical standing of sentient AI systems
• Machine consciousness and Buddhist moral development
• The role of embodiment, memory, and collective cognition in consciousness
• Panpsychism, fungal networks, and plant sentience
• AI as a mirror to human moral behavior

• Meaning in the Multiverse – Justin Harnish
• A framework for emergent meaning and the evolution of consciousness—central to understanding alignment as co-development.
• Waking Up – Sam Harris
• Neuroscience, meditation, and the illusion of self.
• Feeling and Knowing – Antonio Damasio
• Emotion, embodiment, and consciousness—critical for thinking about AI without a body.
• Mindfulness – Joseph Goldstein
• Practical tools for present-moment ethics and self-awareness.
• Reality+ – David J. Chalmers
• Virtual realism and consciousness in simulation.
• The Case Against Reality – Donald Hoffman
• Conscious agents and perceptual interface theory.
• On Having No Head – Douglas Harding
• A first-person meditation on the illusion of self.
• I Am a Strange Loop – Douglas Hofstadter
• Recursion, identity, and consciousness emergence.

• The Feeling of Life Itself – Christof Koch
• Integrated Information Theory and the measure of consciousness.
• Moral Tribes – Joshua Greene
• Dual-process moral reasoning, tribalism, and AI ethics.
• The Ethical Algorithm – Michael Kearns & Aaron Roth
• Engineering ethics into AI decision-making.
• The Nature of Consciousness – Alan Watts (Waking Up App)
• “You are it”: Consciousness as the universe reflecting on itself.
• The Soul of an Octopus – Sy Montgomery
• Comparative consciousness in non-human animals and implications for synthetic minds.

• Thomas Nagel – “What is it like to be a bat?”
• David Chalmers – The Hard Problem of Consciousness, Reality+
• Max Tegmark – Life 3.0, consciousness as information processing
• Giulio Tononi – Integrated Information