Through theoretical analysis, we show how a superorganism may react to stimulus variations according to psychophysical laws observed in humans and other animals. We investigate an empirically-motivated honeybee house-hunting model, which describes a value-sensitive decision process over potential nest-sites, at the level of the colony. In this study, we show how colony decision time increases with the number of available nests, in agreement with the Hick-Hyman law of psychophysics, and decreases with mean nest quality, in agreement with Piéron’s law. We also show that colony error rate depends on mean nest quality, and difference in quality, in agreement with Weber’s law. Psychophysical laws, particularly Weber’s law, have been found in diverse species, including unicellular organisms. Our theoretical results predict that superorganisms may also exhibit such behaviour, suggesting that these laws arise from fundamental mechanisms of information processing and decision-making. Finally, we propose a combined psychophysical law which unifies Hick-Hyman’s law and Piéron’s law, traditionally studied independently; this unified law makes predictions that can be empirically tested.
A. Reina, T. Bose, V. Trianni, J.A.R. Marshall (2018). Psychophysical Laws and the Superorganism. Scientific Reports 8:4387. doi:10.1038/s41598-018-22616-y
Indirect reciprocity is the most elaborate and cognitively demanding1 of all known cooperation mechanisms2, and is the most specifically human1,3 because it involves reputation and status. By helping someone, individuals may increase their reputation, which may change the predisposition of others to help them in future. The revision of an individual’s reputation depends on the social norms that establish what characterizes a good or bad action and thus provide a basis for morality3. Norms based on indirect reciprocity are often sufficiently complex that an individual’s ability to follow subjective rules becomes important4,5,6, even in models that disregard the past reputations of individuals, and reduce reputations to either ‘good’ or ‘bad’ and actions to binary decisions7,8. Here we include past reputations in such a model and identify the key pattern in the associated norms that promotes cooperation. Of the norms that comply with this pattern, the one that leads to maximal cooperation (greater than 90 per cent) with minimum complexity does not discriminate on the basis of past reputation; the relative performance of this norm is particularly evident when we consider a ‘complexity cost’ in the decision process. This combination of high cooperation and low complexity suggests that simple moral principles can elicit cooperation even in complex environments.
Social norm complexity and past reputations in the evolution of cooperation
Fernando P. Santos, Francisco C. Santos & Jorge M. Pacheco
Nature volume 555, pages 242–245 (08 March 2018)
The rise of fake news highlights the erosion of long-standing institutional bulwarks against misinformation in the internet age. Concern over the problem is global. However, much remains unknown regarding the vulnerabilities of individuals, institutions, and society to manipulations by malicious actors. A new system of safeguards is needed. Below, we discuss extant social and computer science research regarding belief in fake news and the mechanisms by which it spreads. Fake news has a long history, but we focus on unanswered scientific questions raised by the proliferation of its most recent, politically oriented incarnation. Beyond selected references in the text, suggested further reading can be found in the supplementary materials.
The science of fake news
David M. J. Lazer, Matthew A. Baum, Yochai Benkler, Adam J. Berinsky, Kelly M. Greenhill, Filippo Menczer, Miriam J. Metzger, Brendan Nyhan, Gordon Pennycook, David Rothschild, Michael Schudson, Steven A. Sloman, Cass R. Sunstein, Emily A. Thorson, Duncan J. Watts, Jonathan L. Zittrain
Science 09 Mar 2018:
Vol. 359, Issue 6380, pp. 1094-1096
We investigated the differential diffusion of all of the verified true and false news stories distributed on Twitter from 2006 to 2017. The data comprise ~126,000 stories tweeted by ~3 million people more than 4.5 million times. We classified news as true or false using information from six independent fact-checking organizations that exhibited 95 to 98% agreement on the classifications. Falsehood diffused significantly farther, faster, deeper, and more broadly than the truth in all categories of information, and the effects were more pronounced for false political news than for false news about terrorism, natural disasters, science, urban legends, or financial information. We found that false news was more novel than true news, which suggests that people were more likely to share novel information. Whereas false stories inspired fear, disgust, and surprise in replies, true stories inspired anticipation, sadness, joy, and trust. Contrary to conventional wisdom, robots accelerated the spread of true and false news at the same rate, implying that false news spreads more than the truth because humans, not robots, are more likely to spread it.
The spread of true and false news online
Soroush Vosoughi, Deb Roy, Sinan Aral
Science 09 Mar 2018:
Vol. 359, Issue 6380, pp. 1146-1151
The idea that genes encode all the heritable features of living things has been a fundamental tenet of genetics and evolutionary biology for many years, but this assumption has always coexisted uncomfortably with the messy findings of empirical research. The complications have multiplied exponentially in recent years under the weight of new discoveries.