Month: September 2021

Can Mutual Imitation Generate Open-Ended Evolution? Takashi Ikegami University Tokio

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.

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The Space of Possible Minds – Philip Ball

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.

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Neutral bots probe political bias on social media

Wen Chen, Diogo Pacheco, Kai-Cheng Yang & Filippo Menczer
Nature Communications volume 12, Article number: 5580 (2021)

Social media platforms attempting to curb abuse and misinformation have been accused of political bias. We deploy neutral social bots who start following different news sources on Twitter, and track them to probe distinct biases emerging from platform mechanisms versus user interactions. We find no strong or consistent evidence of political bias in the news feed. Despite this, the news and information to which U.S. Twitter users are exposed depend strongly on the political leaning of their early connections. The interactions of conservative accounts are skewed toward the right, whereas liberal accounts are exposed to moderate content shifting their experience toward the political center. Partisan accounts, especially conservative ones, tend to receive more followers and follow more automated accounts. Conservative accounts also find themselves in denser communities and are exposed to more low-credibility content. 

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