The theme of the Artificiality Summit 2026 is Unknowing. We start with five speakers—David Wolpert, Caleb Scharf, Wakanyi Macharia-Hoffman, Gašper Beguš, and Nina Beguš—whose work converges on a single finding: the uncertainty surrounding AI is permanent, not a phase.
We are dedicated to unraveling the profound impact of AI on our society, communities, workplaces, and personal lives. To truly grasp this transformation, our approach is rooted in engaging with core concepts such as critical thinking, logical analysis, and the scrutiny of underlying assumptions, principles that are essential in the realm of philosophical inquiry.
The future of the extended mind is not a fixed destination but an ongoing journey that requires our active participation and reflection as we redefine what it means to be human in an age of artificial intelligence.
Complex change recognizes that change is non-linear, emergent, and deeply interconnected with the system in which it occurs. This is even more important as we adapt to the complexity of generative AI.
AI's potential is vast but many applications remain incremental, simply grafting AI onto outdated frameworks. This is why we embrace complexity. We think about designing incentives, understanding self-organization and distributed control, and planning for emergence and adaptation.
I agree with the government that antitrust is important. That said, I would hate to see data privacy and security diminished just as we are trying to take advantage of AI’s power to be a personalized digital partner.
ChatGPT and similar tools can significantly alter workflows by changing how we match tasks with skills. Think of a two-by-two matrix: on one axis, you have the skill needed for a task; on the other, the worker's proficiency level.
Sensemaking is going to change. AI will allow us to find story-less, a-narrative yet meaningful correlations. Our minds will have to be open to a new kind of awe: that which a machine can make sense of that we cannot.
It appears that there is one effect many researchers are finding across multiple fields: generative AI has a significant impact on lower skilled and less experienced people. However, if we automate difficult tasks we cut ourselves off from the essential components for achieving mastery like flow.
Working with AI requires seeing beyond automation to amplification. If society chooses to complement strengths between humans and machines, more dynamic partnerships become possible.
Current AI resembles left-brained reasoning - optimized, logical but decontextualized. Humans play the right-brained role anchored in real world connections.
