Artificiality: Being with AI – Détails, épisodes et analyse

We enjoyed giving a virtual keynote for the Autonomous Summit on December 4, 2025, titled Becoming Synthetic: What AI Is Doing To Us, Not Just For Us.

We talked about our research on how to maintain human agency & cognitive sovereignty, the philosophical question of what it means to be human, and our new(ish) approach to create better AI tools called unDesign.

unDesign is not the absence of design nor is it anti-design. It's design oriented differently. The history of design has been a project of reducing uncertainty. Making things legible. Signaling affordances. Good design means you never have to wonder what to do.

Undesign inverts this and uses "uns" as design material. The unknown. The unpredictable. The unplanned. These aren't bugs. They're the medium where value actually lives. Because uncertainty is the condition of genuine encounter.

unDesign doesn't design outcomes—it designs the space where outcomes can emerge.

You can watch the full keynote below. Check it out!

In this conversation recorded on the 1,000th day since ChatGPT's launch, we explore education, creativity, and transformation with Tess Posner, founding CEO of AI4ALL. For nearly a decade—long before the current AI surge—Tess has led efforts to broaden access to AI education, starting from a 2016 summer camp at Stanford that demonstrated how exposure to hands-on AI projects could inspire high school students, particularly young women, to pursue careers in the field.

What began as exposing students to "the magic" of AI possibilities has evolved into something more complex: helping young people navigate a moment of radical uncertainty while developing both technical capabilities and critical thinking about implications. As Tess observes, we're recording at a time when universities are simultaneously banning ChatGPT and embracing it, when the job market for graduates is sobering, and when the entire structure of work is being "reinvented from the ground up."

Key themes we explore:

• Living the Questions: How Tess's team adopted Rilke's concept of "living the questions" as their guiding principle for navigating unprecedented change—recognizing that answers won't come easily and that cultivating wisdom matters more than chasing certainty
• The Diverse Pain Point: Why students from varied backgrounds gravitate toward different AI applications—from predicting droughts for farm worker families to detecting Alzheimer's based on personal experience—and how this diversity of lived experience shapes what problems get attention
• Project-Based Learning as Anchor: How hands-on making and building creates the kind of applied learning that both reveals AI's possibilities and exposes its limitations, while fostering the critical thinking skills that pure consumption of AI outputs cannot develop
• The Educational Reckoning: Why this moment is forcing fundamental questions about the purpose of schooling—moving beyond detection tools and honor codes toward reimagining how learning happens when instant answers are always available
• The Worst Job Market in Decades: Sobering realities facing graduates alongside surprising opportunities—some companies doubling down on "AI native" early career talent while others fundamentally restructure work around managing AI agents rather than doing tasks directly
• Music and the Soul Question: Tess's personal wrestling with AI-generated music that can mimic human emotional expression so convincingly it gets stuck in your head—forcing questions about whether something deeper than output quality matters in art

The conversation reveals someone committed to equity and access while refusing easy optimism about technology's trajectory. Tess acknowledges that "nobody really knows" what the future of work looks like or how education should adapt, yet maintains that the response cannot be paralysis. Instead, AI4ALL's approach emphasizes building community, developing genuine technical skills, and threading ethical considerations through every project—equipping students not with certainty but with agency.

About Tess Posner: Tess Posner is founding and interim CEO of AI4ALL, a nonprofit working to increase diversity and inclusion in AI education, research, development, and policy. Since 2017, she has led the organization's expansion from a single summer program at Stanford to a nationwide initiative serving students from over 150 universities. A graduate of St. John's College with its Great Books curriculum, Tess is also an accomplished musician who brings both technical expertise and humanistic perspective to questions about AI's role in creativity and human flourishing.

Our Theme Music:

• Solid State (Reprise)
• Written & performed by Jonathan Coulton
• License: Perpetual, worldwide licence for podcast theme usage granted to Artificiality Institute by songwriter and publisher

At the Artificiality Summit 2024, Jamer Hunt, professor at the Parsons School of Design and author of Not to Scale, catalyzed our opening discussion on the concept of scale. This session explored how different scales—whether individual, organizational, community, societal, or even temporal—shape our perspectives and influence the design of AI systems. By examining the impact of scale on context and constraints, Jamer guided us to a clearer understanding of the appropriate levels at which we can envision and build a hopeful future with AI. This interactive session set the stage for a thought-provoking conference.

Bio: Jamer Hunt collaboratively designs open and adaptable frameworks for participation that respond to emergent cultural conditions—in education, organizations, exhibitions, and for the public. He is the Vice Provost for Transdisciplinary Initiatives at The New School (2016-present), where he was founding director of the graduate program in Transdisciplinary Design at Parsons School of Design (2009-2015). He is the author of Not to Scale: How the Small Becomes Large, the Large Becomes Unthinkable, and the Unthinkable Becomes Possible (Grand Central Publishing, March 2020), a book that repositions scale as a practice-based framework for analyzing broken systems and navigating complexity. He has published over twenty articles on the poetics and politics of design, including for Fast Company and the Huffington Post, and he is co-author, with Meredith Davis, of Visual Communication Design (Bloomsbury, 2017).

In this episode, we open with an opinionated chat about Facebook’s new oversight board and then we have a great conversation with Ted Kwartler, VP of Trusted AI at DataRobot. We think DataRobot is a very interesting AI company and Ted’s role is key to helping their customers with ethical AI.

In this episode, I have a conversation with Arash Rahnama, Head of Applied AI Research at Modzy (@arashrahnamaphd, @getmodzy, www.modzy.com). We talk about techniques for providing explainability in AI, how to pair explainability with fairness to reduce bias, how AI goes wrong and how diverse teams can provide important prior knowledge to AI systems and help govern them in the wild.

In this episode, I have a conversation with Scott Stephenson, Co-founder and CEO of Deepgram, a company which has built an end-to-end deep learning speech recognition system. We talk about why end-to-end deep learning sets Deepgram apart from other speech recognition companies, how Deepgram handles accents and bias, how enterprise speech recognition differs from consumer and Deepgram’s goal of becoming a speech understanding company.

In this episode, I have the pleasure of talking with Will Griffin, Chief Ethics Officer of Hypergiant, an Austin Texas-based AI product and services company. We talk about how Hypergiant uses Immanuel Kant’s categorical imperative in its ethics framework, how Hypergiant applies its ethics process with clients and why Will thinks ethical processes are important in AI development.

In this episode, I have the pleasure of interviewing Chelsea Barabas a PhD candidate at MIT’s Media Lab. We talk about her work on bias in the criminal justice system as well as her most recent work applying the concept of “studying up” from anthropology to the data science world.

Here are some of the links we refer to in the episode:

http://www.chelsbar.com

https://cmsw.mit.edu/profile/chelsea-barabas/

https://medium.com/@chelsea_barabas

https://www.nytimes.com/2019/07/17/opinion/pretrial-ai.html

https://journal.culanth.org/index.php/ca/article/view/ca31.3.01/367

https://discardstudies.com/2016/08/08/ethnographic-refusal-a-how-to-guide/

https://science.sciencemag.org/content/366/6464/421/tab-article-info

In this episode, Dave interviews Helen about her recent article in Quartz, “Are AI ethicists making any difference?” Some of the topics we explore include:

* Why is there a rush to hire AI ethicists in the tech industry?

* What do AI ethicists do?

* Why are people skeptical and what is “ethics washing” and “ethics bashing?”

* What does Jacob Metcalf of Data & Society mean by saying that ethics is “the vessel which we use to hold our values?”

* What does Josh Lovejoy of Microsoft mean by saying that ethics need not be seen as a philosophical add-on “but as just good design?”

* What are AI checklists and why is their use good practice?

In this episode, we dive into the paradox of autonomy. Some of the topics we explore include:

* Why are there so many paradoxical observations in AI?

* What is the autonomy paradox?

* Is there any way that giving up more information can be autonomy-enhancing?

* What are principal reason and counter-factual explanations?

* How can we deal with the autonomy paradox through AI UX design?

For further reading, check out the most recent Artificiality article, the research paper we reference and the Buzzfeed article on Clearview AI.

Special thanks to our friend, Jonathan Coulton, for our theme music.