Month: December 2021

Introduction to the special issue: quantifying collectivity

Bryan C. Daniels, Manfred D. Laubichler & Jessica C. Flack 

Theory in Biosciences volume 140, pages 321–323 (2021)

Biological systems are diverse, ranging from tightly packed, highly integrated, many-body systems like eukaryotic cells to decentralized microbial biofilms, to relatively small primate groups with on the order of 100 behaviorally flexible individuals all the way to large, complex societies (both insects and human) and ecosystems. This range suggests there is variation in both how collective a system is as well as how it is collective.

Read the full article at: link.springer.com

Field Experiments on Social Media

Mohsen Mosleh, Gordon Pennycook, David G. Rand

Current Directions in Psychological Science

Online behavioral data, such as digital traces from social media, have the potential to allow researchers an unprecedented new window into human behavior in ecologically valid everyday contexts. However, research using such data is often purely observational, which limits its usefulness for identifying causal relationships. Here we review recent innovations in experimental approaches to studying online behavior, with a particular focus on research related to misinformation and political psychology. In hybrid lab-field studies, exposure to social-media content can be randomized, and the impact on attitudes and beliefs can be measured using surveys, or exposure to treatments can be randomized within survey experiments, and their impact on subsequent online behavior can be observed. In field experiments conducted on social media, randomized treatments can be administered directly to users in the online environment (e.g., via social-tie invitations, private messages, or public posts) without revealing that they are part of an experiment, and the effects on subsequent online behavior can then be observed. The strengths and weaknesses of each approach are discussed, along with practical advice and central ethical constraints on such studies.

Read the full article at: journals.sagepub.com

Simon DeDeo on Good Explanations & Diseases of Epistemology

What makes a satisfying explanation? Understanding and prediction are two different goals at odds with one another — think fundamental physics versus artificial neural networks — and even what defines a “simple” explanation varies from one person to another. Held in a kind of ecosystemic balance, these diverse approaches to seeking knowledge keep each other honest…but the use of one kind of knowledge to the exclusion of all others leads to disastrous results. And in the 21st Century, the difference between good and bad explanations determines how society adapts as rapid change transforms the world most people took for granted — and sends humankind into the epistemic wilds  to find new stories that will help us navigate this brave new world.

This week we dive deep with SFI External Professor Simon DeDeo at Carnegie Mellon University to explore his research into intelligence and the search for understanding, bringing computational techniques to bear on the history of science, information processing at the scale of society, and how digital technologies and the coronavirus pandemic challenge humankind to think more carefully about the meaning that we seek, here on the edge of chaos…

Read the full article at: complexity.simplecast.com

Cooperation evolves by the payoff-difference-based probabilistic reward

Tetsushi Ohdaira 
The European Physical Journal B volume 94, Article number: 232 (2021)

In the previous studies, the author proposes the payoff-difference-based probabilistic peer-punishment that the probability of punishing a defector increases as the difference of payoff between a player and a defector increases and shows that the proposed peer-punishment effectively increases the number of cooperators and the average payoff of all players. On the other hand, reward as well as punishment is considered to be a mechanism promoting cooperation, and many studies have discussed the effect of reward in the public goods game, a multiplayer version of the prisoner’s dilemma game. Based on the discussion of those existing studies, this study introduces the payoff-difference-based probabilistic reward that the probability of rewarding a cooperator increases as the difference of payoff between a player and a cooperator increases. The author utilizes the framework of the spatial prisoner’s dilemma game of the previous study and shows that the reward of this study realizes the evolution of cooperation except some cases.

Read the full article at: link.springer.com