Author: cxdig

University assistant predoctoral on “Self-Fulfilling Prophecies” project – Universität Klagenfurt

The University of Klagenfurt is pleased to announce the following open position at the Department of Business Management at the Faculty of Management, Economics & Law with a negotiable starting date, commencing on March 3, 2025, at the latest:
University assistant predoctoral (all genders welcome)
Level of employment: 75 % (30 hours/week)
Minimum salary: € 37,577.40 per annum (gross); classification according to collective agreement: B1
Contract duration: 3.5 years
Application deadline: January 8, 2025

Area of responsibility
* Research in a project for studying Self-Fulfilling Prophecies from the perspective of complex systems and management control, emphasizing the impact of digital technologies
* Independent scientific work with the aim to submit a dissertation and acquire a Doctoral degree
* Teaching and student supervision in the domain of the project
* Engagement in networking and science communication

Apply at: jobs.aau.at

The Election and Complexity Science Webinar


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The results of the 2024 U.S. Presidential Election will send shockwaves through political, social, and economic systems, impacting and exposing deep vulnerabilities in society and governance structures worldwide. What does Complexity Science reveal about the dynamics driving these outcomes, their causes, and broader implications?

Join Dr. Yaneer Bar-Yam, founder of the New England Complex Systems Institute (NECSI) and co-founder of the World Health Network (WHN), who will analyze the election through the lens of complexity science, offering critical insights into the systemic issues underlying today’s governance challenges. 

Read the full article at: www.youtube.com

Large language models (LLMs) as agents for augmented democracy

Jairo F. Gudiño , Umberto Grandi and César Hidalgo

Roy Soc Phil Trans A Volume 382I ssue 2285

We explore an augmented democracy system built on off-the-shelf large language models (LLMs) fine-tuned to augment data on citizens’ preferences elicited over policies extracted from the government programmes of the two main candidates of Brazil’s 2022 presidential election. We use a train-test cross-validation set-up to estimate the accuracy with which the LLMs predict both: a subject’s individual political choices and the aggregate preferences of the full sample of participants. At the individual level, we find that LLMs predict out of sample preferences more accurately than a ‘bundle rule’, which would assume that citizens always vote for the proposals of the candidate aligned with their self-reported political orientation. At the population level, we show that a probabilistic sample augmented by an LLM provides a more accurate estimate of the aggregate preferences of a population than the non-augmented probabilistic sample alone. Together, these results indicate that policy preference data augmented using LLMs can capture nuances that transcend party lines and represents a promising avenue of research for data augmentation.

Read the full article at: royalsocietypublishing.org

Human Superintelligence: How you can develop it using recursive self-improvement, by John Stewart

There are many books and articles that outline the findings made by existing complexity science. But there are almost none that identify how you can develop the thinking that was used to produce those findings. None show how individuals can develop the higher cognition that will be necessary if they are to contribute to the emergence of a genuine science of complexity.

In contrast, this book sets out specifically to provide methods and practices for developing higher cognition.

The book argues that the ability to construct and utilize mental models of complex phenomena is essential if humanity is to overcome the existential challenges that currently threaten the survival of human civilization on Earth. Furthermore, it argues that this metasystemic cognition is essential for the development of a genuine science of complexity – the book makes the case that the analytical/rational cognition that underpins current mainstream science is largely limited to generating only mechanistic reductions of complex phenomena.

The book recognises that most potential readers are likely to be highly skeptical about its claims to enable the scaffolding of metasystemic cognition. The website for the book attempts to dispel this skepticism by making the first chapter of the book freely available. This chapter is designed to evoke the realization that the methods detailed by the book are plausible, and that currently almost no one uses the methods systematically, despite their enormous potential.

The website for the book is HumanSuperIntelligenceBook.com