Anatomy of an AI-powered malicious social botnet

Yang, K., & Menczer, F. (2024).

Journal of Quantitative Description: Digital Media 4

Large language models (LLMs) exhibit impressive capabilities in generating realistic text across diverse subjects. Concerns have been raised that they could be utilized to produce fake content with a deceptive intention, although evidence thus far remains anecdotal. This paper presents a case study about a Twitter botnet that appears to employ ChatGPT to generate human-like content. Through heuristics, we identify 1,140 accounts and validate them via manual annotation. These accounts form a dense cluster of fake personas that exhibit similar behaviors, including posting machine-generated content and stolen images, and engage with each other through replies and retweets. ChatGPT-generated content promotes suspicious websites and spreads harmful comments. While the accounts in the AI botnet can be detected through their coordination patterns, current state-of-the-art LLM content classifiers fail to discriminate between them and human accounts in the wild. These findings highlight the threats posed by AI-enabled social bots.

Read the full article at: journalqd.org

Is the Emergence of Life an Expected Phase Transition in the Evolving Universe?

Stuart Kauffman and Andrea Roli

We propose a novel definition of life in terms of which its emergence in the universe is expected, and its ever-creative open-ended evolution is entailed by no law. Living organisms are Kantian Wholes that achieve Catalytic Closure, Constraint Closure, and Spatial Closure. We here unite for the first time two established mathematical theories, namely Collectively Autocatalytic Sets and the Theory of the Adjacent Possible. The former establishes that a first-order phase transition to molecular reproduction is expected in the chemical evolution of the universe where the diversity and complexity of molecules increases; the latter posits that, under loose hypotheses, if the system starts with a small number of beginning molecules, each of which can combine with copies of itself or other molecules to make new molecules, over time the number of kinds of molecules increases slowly but then explodes upward hyperbolically. Together these theories imply that life is expected as a phase transition in the evolving universe. The familiar distinction between software and hardware loses its meaning in living cells. We propose new ways to study the phylogeny of metabolisms, new astronomical ways to search for life on exoplanets, new experiments to seek the emergence of the most rudimentary life, and the hint of a coherent testable pathway to prokaryotes with template replication and coding.

Read the full article at: osf.io

Self-Improvising Memory: A Perspective on Memories as Agential, Dynamically Reinterpreting Cognitive Glue

Michael Levin

Entropy 2024, 26(6), 481

Many studies on memory emphasize the material substrate and mechanisms by which data can be stored and reliably read out. Here, I focus on complementary aspects: the need for agents to dynamically reinterpret and modify memories to suit their ever-changing selves and environment. Using examples from developmental biology, evolution, and synthetic bioengineering, in addition to neuroscience, I propose that a perspective on memory as preserving salience, not fidelity, is applicable to many phenomena on scales from cells to societies. Continuous commitment to creative, adaptive confabulation, from the molecular to the behavioral levels, is the answer to the persistence paradox as it applies to individuals and whole lineages. I also speculate that a substrate-independent, processual view of life and mind suggests that memories, as patterns in the excitable medium of cognitive systems, could be seen as active agents in the sense-making process. I explore a view of life as a diverse set of embodied perspectives—nested agents who interpret each other’s and their own past messages and actions as best as they can (polycomputation). This synthesis suggests unifying symmetries across scales and disciplines, which is of relevance to research programs in Diverse Intelligence and the engineering of novel embodied minds.

Read the full article at: www.mdpi.com

Antifragility of stochastic transport on networks with damage

L. K. Eraso-Hernandez, A. P. Riascos

A system is called antifragile when damage acts as a constructive element improving the performance of a global function. In this letter, we analyze the emergence of antifragility in the movement of random walkers on networks with modular structures or communities. The random walker hops considering the capacity of transport of each link, whereas the links are susceptible to random damage that accumulates over time. We show that in networks with communities and high modularity, the localization of damage in specific groups of nodes leads to a global antifragile response of the system improving the capacity of stochastic transport to more easily reach the nodes of a network. Our findings give evidence of the mechanisms behind antifragile response in complex systems and pave the way for their quantitative exploration in different fields.

Read the full article at: arxiv.org

On the Unexpected Abilities of Large Language Models

Stefano Nolfi

Adaptive Behavior

Large Language Models (LLMs) are capable of displaying a wide range of abilities that are not directly connected with the task for which they are trained: predicting the next words of human-written texts. In this article, I review recent research investigating the cognitive abilities developed by LLMs and their relation to human cognition. I discuss the nature of the indirect process that leads to the acquisition of these cognitive abilities, their relation to other indirect processes, and the implications for the acquisition of integrated abilities. Moreover, I propose the factors that enable the development of abilities that are related only very indirectly to the proximal objective of the training task. Finally, I discuss whether the full set of capabilities that LLMs could possibly develop is predictable.

Read the full article at: journals.sagepub.com