Month: December 2024

The use of knowledge in open-ended systems

Abigail Devereaux, Roger Koppl

Economists model knowledge use and acquisition as a cause-and-effect calculus associating observations made by a decision-maker about their world with possible underlying causes. Knowledge models are well-established for static contexts, but not for contexts of innovative and unbounded change. We develop a representation of knowledge use and acquisition in open-ended evolutionary systems and demonstrate its primary results, including that observers embedded in open-ended evolutionary systems can agree to disagree and that their ability to theorize about their systems is fundamentally local and constrained to their frame of reference what we call frame relativity. The results of our framework formalize local knowledge use, the many-selves interpretation of reasoning through time, and motivate the emergence of nonlogical modes of reasoning like institutional and aesthetic codes.

Read the full article at: arxiv.org

Real-time estimates of the emergence and dynamics of SARS-CoV-2 variants of concern: A modeling approach

Nicolò Gozzi, Matteo Chinazzi, Jessica T. Davis, Kunpeng Mu, Ana Pastore y Piontti, Marco Ajelli, Alessandro Vespignani, Nicola Perra

Epidemics Volume 49, December 2024, 100805

The emergence of SARS-CoV-2 variants of concern (VOCs) punctuated the dynamics of the COVID-19 pandemic in multiple occasions. The stages subsequent to their identification have been particularly challenging due to the hurdles associated with a prompt assessment of transmissibility and immune evasion characteristics of the newly emerged VOC. Here, we retrospectively analyze the performance of a modeling strategy developed to evaluate, in real-time, the risks posed by the Alpha and Omicron VOC soon after their emergence. Our approach utilized multi-strain, stochastic, compartmental models enriched with demographic information, age-specific contact patterns, the influence of non-pharmaceutical interventions, and the trajectory of vaccine distribution. The models’ preliminary assessment about Omicron’s transmissibility and immune evasion closely match later findings. Additionally, analyses based on data collected since our initial assessments demonstrate the retrospective accuracy of our real-time projections in capturing the emergence and subsequent dominance of the Alpha VOC in seven European countries and the Omicron VOC in South Africa. This study shows the value of relatively simple epidemic models in assessing the impact of emerging VOCs in real time, the importance of timely and accurate data, and the need for regular evaluation of these methodologies as we prepare for future global health crises.

Read the full article at: www.sciencedirect.com

Fact-checking information from large language models can decrease headline discernment

Matthew R. DeVerna, Harry Yaojun Yan, Kai-Cheng Yang, and Filippo Menczer
PNAS 121 (50) e2322823121

This study explores how large language models (LLMs) used for fact-checking affect the perception and dissemination of political news headlines. Despite the growing adoption of AI and tests of its ability to counter online misinformation, little is known about how people respond to LLM-driven fact-checking. This experiment reveals that even LLMs that accurately identify false headlines do not necessarily enhance users’ abilities to discern headline accuracy or promote accurate news sharing. LLM fact checks can actually reduce belief in true news wrongly labeled as false and increase belief in dubious headlines when the AI is unsure about an article’s veracity. These findings underscore the need for research on AI fact-checking’s unintended consequences, informing policies to enhance information integrity in the digital age.

Read the full article in PNAS: doi:10.1073/pnas.2322823121

NECSI Winter Session 2025

Explore the world of complexity science with NECSI’s Winter Session 2025. This specially designed course offers an in-depth understanding of complex systems, combining theoretical foundations with real-world applications. Whether you aim to deepen your expertise or begin a new intellectual journey, this program provides a comprehensive and academically rigorous exploration of the field.

Course Dates: 10-21 February 2025

Details at: necsi.edu

Co-evolution of behaviour and beliefs in social dilemmas: estimating material, social, cognitive and cultural determinants

Sergey Gavrilets, Denis Tverskoi, Nianyi Wang, Xiaomin Wang, Juan Ozaita, Boyu Zhang, Angel Sánchez, and Giulia Andrighetto

Evolutionary Human Sciences , Volume 6 , 2024 , e50

Understanding and predicting human cooperative behaviour and belief dynamics remains a major challenge both from the scientific and practical perspectives. Because of the complexity and multiplicity of material, social and cognitive factors involved, both empirical and theoretical work tends to focus only on some snippets of the puzzle. Recently, a mathematical theory has been proposed that integrates material, social and cognitive aspects of behaviour and beliefs dynamics to explain how people make decisions in social dilemmas within heterogeneous groups. Here we apply this theory in two countries, China and Spain, through four long-term behavioural experiments utilising the Common Pool Resources game and the Collective Risk game. Our results show that material considerations carry the smallest weight in decision-making, while personal norms tend to be the most important factor. Empirical and normative expectations have intermediate weight in decision-making. Cognitive dissonance, social projection, logic constraints and cultural background play important roles in both decision-making and beliefs dynamics. At the individual level, we observe differences in the weights that people assign to factors involved in the decision-making and belief updating process. We identify different types of prosociality and rule-following associated with cultural differences, various channels for the effects of messaging, and culturally dependent interactions between sensitivity to messaging and conformity. Our results can put policy and information design on firmer ground, highlighting the need for interventions tailored to the situation at hand and to individual characteristics. Overall, this work demonstrates the theoretical and practical power of the theory in providing a more comprehensive understanding of human behaviour and beliefs.

Read the full article at: www.cambridge.org