If you’re wondering why every week seems to bring some new disruption to your world, why once-solid institutions seem shaky, author Darrell West has some explanations. At the heart of them is the idea of megachange – itself rooted mostly in economics. Such periods of rapid disruption are cyclical, argues West, director of governance studies and the Center for Technology Innovation at the Brookings Institution. He explored these ideas in his new book, entitled Megachange: Economic Disruption, Political Upheaval, and Social Strife in the 21st Century.

Source: knowledge.wharton.upenn.edu

Scariest of all is a scenario in which a computer figures out both the advantages of collusion and how to make it happen. Here, the situation might resemble what happened with AlphaGo, the computer program developed to play the board game Go. The program’s success was mostly due to machine learning. The computer played countless games against itself and figured out what worked best. The end result is a black box: We don’t really know how the computer is making decisions, only that it works. Because successful collusion leads to higher profits, it would make sense that computers—left to their own devices—would figure this out. Antitrust authorities would have no way to punish this type of collusion under existing laws.

 

Priceless
Barry Nalebuff
Virtual Competition The Promise and Perils of the Algorithm-Driven Economy Ariel Ezrachi and Maurice E. Stucke Harvard University Press, 2016. 364 pp.
Science  04 Nov 2016:
Vol. 354, Issue 6312, pp. 560
DOI: 10.1126/science.aaj2011

Source: science.sciencemag.org

Trees are networkers. Far from the solitary splendour of the ancient old stager, it turns out that trees communicate with one another through their roots. Underground fungi — mycorrhizae associated with the root network — form a sort of subterranean internet that connects trees, passing messages and even nourishment between neighbours. Nor do trees passively tolerate the onslaught of insects on their tasty young leaves. Chemical signals carried on the breeze from infested trees cause forest fellows to crank up their own chemical armouries. It’s not a case of every tree for itself: the forest can behave as a single entity when it yields a great crop of acorns or beechnuts, or lies fallow for a year. Trees share a common response to weather and nourishment.

 

Dendrology: The community of trees
Richard Fortey
Nature 537, 306 (15 September 2016) doi:10.1038/537306a

Source: www.nature.com

The ALife conferences are the major meeting of the artificial life research community since 1987. For its 15th edition in 2016, it was held in Latin America for the first time, in the Mayan Riviera, Mexico, from July 4 -8. The special them of the conference: How can the synthetic study of living systems contribute to societies: scientifically, technically, and culturally? The goal of the conference theme is to better understand societies with the purpose of using this understanding for a more efficient management and development of social systems.

 

Proceedings of the Artificial Life Conference 2016

Edited by Carlos Gershenson, Tom Froese, Jesus M. Siqueiros, Wendy Aguilar, Eduardo J. Izquierdo and Hiroki Sayama

Source: mitpress.mit.edu

This book presents a new approach that can be applied to complex, integrated individual and social human processes. It provides an alternative means of addressing complexity, better suited for its purpose than and effectively complementing traditional strategies involving isolation and separation assumptions.
Network-oriented modeling allows high-level cognitive, affective and social models in the form of (cyclic) graphs to be constructed, which can be automatically transformed into executable simulation models. The modeling format used makes it easy to take into account theories and findings about complex cognitive and social processes, which often involve dynamics based on interrelating cycles. Accordingly, it makes it possible to address complex phenomena such as the integration of emotions within cognitive processes of all kinds, of internal simulations of the mental processes of others, and of social phenomena such as shared understandings and collective actions. A variety of sample models – including those for ownership of actions, fear and dreaming, the integration of emotions in joint decision-making based on empathic understanding, and evolving social networks – illustrate the potential of the approach. Dedicated software is available to support building models in a conceptual or graphical manner, transforming them into an executable format and performing simulation experiments. The majority of the material presented has been used and positively evaluated by undergraduate and graduate students and researchers in the cognitive, social and AI domains.
Given its detailed coverage, the book is ideally suited as an introduction for graduate and undergraduate students in many different multidisciplinary fields involving cognitive, affective, social, biological, and neuroscience domains.

 

Network-Oriented Modeling
Addressing Complexity of Cognitive, Affective and Social Interactions
Jan Treur

Source: link.springer.com