We only find open-ended evolution (OEE) in the development of human technology or in the evolution of life itself. The research on OEE at ALIFE aims to discover a mechanism that generates OEE automatically in a computer or machine. A potential mechanism and the conditions required have been discussed in three previous workshops. In this study, we propose and discuss man–machine interaction experiments as a new OEE mechanism. The pertinent definition of OEE here is whether we can continue to create new movements that are distinguishable to us. We consider the development of body movement patterns generated when Alter3 androids imitate each other and when Alter3 androids and humans imitate each other. We use UMAP contraction and transfer entropy to measure these changes and demonstrate that man–machine communication is far more dynamic and complex than the machine–machine interaction. We discuss how human subjects can engender OEE via communication with the android.

Watch at: www.youtube.com

In 1984 computer scientist Aaron Sloman published a paper called “The structure of the space of possible minds.” It called for systematic thinking about the vague yet intuitive notion of mind, which was capable of admitting into the conversation what we had then learnt about animal cognition and artificial intelligence. Almost four decades later, we are in a fair better position to examine Sloman’s proposal: to consider what kinds of minds can exist within the laws of physics, to compare those we already recognize (including the diversity of human minds), and to speculate about the possibilities for artificial “mind design”. In this talk I will explore this question, looking at our current understanding of the functions and capabilities of biological minds, what this might imply for efforts to create artificial “minds”, and what the implications are for ideas about consciousness, agency and free will.

Speaker Bio: Philip Ball is a freelance writer and author, and worked for many years as an editor of Nature. His many books include Critical Mass (which won the 2005 Aventis Science Books prize), Beyond Weird and How to Grow a Human. His next book, The Book of Minds, will be published in early 2022.

Watch at: youtu.be

Economies in the modern world are incredibly complex systems. But when we sit down to think about them in quantitative ways, it’s natural to keep things simple at first. We look for reliable relations between small numbers of variables, seek equilibrium configurations, and so forth. But those approaches don’t always work in complex systems, and sometimes we have to use methods that are specifically adapted to the challenges of complexity. That’s the perspective of W. Brian Arthur, a pioneer in the field of complexity economics, according to which economies are typically not in equilibrium, not made of homogeneous agents, and are being constantly updated. We talk about the basic ideas of complexity economics, how it differs from more standard approaches, and what it teaches us about the operation of real economies.

Listen at: www.preposterousuniverse.com

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The Complexity in the Social World series of interviews (and YouTube Playlist) follows on from the seminar we organised in March 2021. The aim of this series is to capture some of the foundational thinkers in conversation around how to apply complexity thinking to the social world, the world of managers, economists, change agents and societies. In this way, some of these foundational thinkers, many starting their work in the 1980s, are represented and their differing perspectives and different foci of application are available in one place.

Watch at: www.youtube.com

The popular conception of ants is that “anatomy is destiny”: an ant’s body type determines its role in the colony, for once and ever. But this is not the case; rather than forming rigid castes, ants act like a distributed computer in which tasks are re-allocated as the situation changes. “Division of labor” implies a constant “assembly line” environment, not fluid adaptation to evolving conditions. But ants do not just “graduate” from one task to another as they age; they pivot to accept the work required by their colony in any given moment. In this “agile” and dynamic process, ants act more like verbs than nouns — light on specialization and identity, heavy on collaboration and responsiveness.

What can we learn from ants about the strategies for thriving in times of uncertainty and turbulence?What are the algorithms that ants use to navigate environmental change, and how might they inform the ways that we design technologies? How might they teach us to invest more wisely, to explore more thoughtfully?

Listen at: complexity.simplecast.com