CxBooks

For many years, the development of large-scale quantitative social science was hindered by a lack of data. Traditional methods of data collection like surveys were very useful, but were limited. The situation has of course changed with the development of computing and information communication technology, and we now live in a world of data deluge, where the question has become how to extract important information from the plethora of data that can be accessed. Big Data has made it possible to study societal questions which were once impossible to deal with, but new tools and new multidisciplinary approaches are required. Physicists, together with economists, sociologists, computer scientists, etc. have played an important role in their development.

This book presents the 9 lectures delivered at the CCIII Summer Course Computational Social Science and Complex Systems, held as part of the International School of Physics Enrico Fermi in Varenna, Italy, from 16-21 July 2018. The course had the aim of presenting some of the recent developments in the interdisciplinary fields of computational social science and econophysics to PhD students and young researchers, with lectures focused on recent problems investigated in computational social science.

Addressing some of the basic questions and many of the subtleties of the emerging field of computational social science, the book will be of interest to students, researchers and advanced research professionals alike.

The International Conference on Complex Networks and their Applications aims at bringing together researchers from different scientific communities working on areas related to complex networks.

Ever since its origin in post-war research, AI has been subject to profound hyperbole, rapturous prognostications, and projected nightmares. In 2019, things have once again reached fever pitch in what Science Board co-chair and External Professor Melanie Mitchell wryly notes is a hype cycle that routinely ripples through her fellow computer scientists and those who fund them. Her illuminating new book, Artificial Intelligence: A Guide for Thinking Humans, lays bare the inner workings of these potent tools, exposing their realistic limits and patiently detailing our deployment errors. It is a solid history of how we got from pocket calculators to facial recognition and self-driving cars, a lucid tour of how these systems operate, and a tempered read on just how far we have to go before we’re obsolete.

Human Current, the complexity podcast, emerged from the belief that the world will be a better place if more people learn about complexity—as a scientific theory and way of understanding the world. Our Human Current is a story of listening and learning, and of the power of mentorship, inspired by our own mentor, Douglas Drane.

We conducted more than 125 thoughtful interviews with scientists, influencers, and practitioners in the fields of complexity science and systems thinking. Let us take you on a 365-day journey through the stories, research, anecdotes, and advice from Doug and our conversations with guests including: Stephen Wolfram, a founding father of complexity science; Yaneer Bar-Yam, president of the New England Complex Systems Institute; Jean Boulton, co-author of Embracing Complexity; Melanie Mitchell, professor at the Santa Fe Institute; Margaret Wheatley, best-selling author; Dean Radin, chief scientist at the Institute of Noetic Sciences; Albert-László Barabási, author; and so many more!

Our Human Current: Stories about Complexity, Systems, and Mentorship
By Angela Cross & Haley Campbell-Gross

A World Beyond Physics: The Emergence and Evolution of Life Stuart A. Kauffman Oxford University Press (2019)

(...)

His key insight is motivated by what he calls “the nonergodic world” — that of objects more complex than atoms. Most atoms are simple, so all their possible states can exist over a reasonable period of time. Once they start interacting to form molecules, the number of possible states becomes mind-bogglingly massive. Only a tiny number of proteins that are modestly complex — say, 200 amino acids long — have emerged over the entire history of the Universe. Generating all 20020 of the possibilities would take aeons. Given such limitations, how does what does exist ever come into being?

Nature 569, 36-38 (2019)

As I elaborate extensively in my new book, The Idea of the World, none of this implies solipsism. The mental universe exists in mind but not in your personal mind alone. Instead, it is a transpersonal field of mentation that presents itself to us as physicality—with its concreteness, solidity and definiteness—once our personal mental processes interact with it through observation. This mental universe is what physics is leading us to, not the hand-waving word games of information realism.

[...] as The Gendered Brain reveals, conclusive findings about sex-linked brain differences have failed to materialize. Beyond the “missing five ounces” of female brain — gloated about since the nineteenth century — modern neuroscientists have identified no decisive, category-defining differences between the brains of men and women. In women’s brains, language-processing is not spread any more evenly across the hemispheres than it is in men’s, as a small 1995 Nature study proclaimed but a large 2008 meta-analysis disproved (B. A. Shaywitz et al. Nature 373, 607–609 (1995) and I. E. Sommer et al. Brain Res. 1206, 76–88; 2008). Brain size increases with body size, and certain features, such as the ratio of grey to white matter or the cross-sectional area of a nerve tract called the corpus callosum, scale slightly non-linearly with brain size. But these are differences in degree, not kind. As Rippon notes, they are also seen when we compare small-headed men to large-headed women, and have no relationship to differences in hobbies or take-home pay.

The Gendered Brain: The New Neuroscience That Shatters The Myth Of The Female Brain. Gina Rippon The Bodley Head (2019)

Through a blend of compelling exercises, illustrations, and stories, the bestselling author of Thinking in Bets will train you to combat your own biases, address your weaknesses, and help you become a better and more confident decision-maker.

What do you do when you're faced with a big decision? If you're like most people, you probably make a pro and con list, spend a lot of time obsessing about decisions that didn't work out, get caught in analysis paralysis, endlessly seek other people's opinions to find just that little bit of extra information that might make you sure, and finally go with your gut.

What if there was a better way to make quality decisions so you can think clearly, feel more confident, second-guess yourself less, and ultimately be more decisive and be more productive?

Making good decisions doesn't have to be a series of endless guesswork. Rather, it's a teachable skill that anyone can sharpen. In How to Decide, bestselling author Annie Duke and former professional poker player lays out a series of tools anyone can use to make better decisions. You'll learn:

• To identify and dismantle hidden biases.
• To extract the highest quality feedback from those whose advice you seek.
• To more accurately identify the influence of luck in the outcome of your decisions.
• When to decide fast, when to decide slow, and when to decide in advance.
• To make decisions that more effectively help you to realize your goals and live your values.

Through practical exercises and engaging thought experiments, this book helps you analyze key decisions you've made in the past and troubleshoot those you're making in the future. Whether you're picking investments, evaluating a job offer, or trying to figure out your romantic life, this book is the key to happier outcomes and fewer regrets.

This book focuses on the theoretical side of temporal network research and gives an overview of the state of the art in the field. Curated by two pioneers in the field who have helped to shape it, the book contains contributions from many leading researchers. Temporal networks fill the border area between network science and time-series analysis and are relevant for the modeling of epidemics, optimization of transportation and logistics, as well as understanding biological phenomena.

Network theory has proven, over the past 20 years to be one of the most powerful tools for the study and analysis of complex systems. Temporal network theory is perhaps the most recent significant development in the field in recent years, with direct applications to many of the "big data" sets. This monograph will appeal to students, researchers and professionals alike interested in theory and temporal networks, a field that has grown tremendously over the last decade.

Temporal Network Theory
Editors: Holme, Petter, Saramäki, Jari 

The 2007–2008 financial crisis exposed the shortcomings of mainstream economic theory with economists unprepared to deal with it. In the face of this, a major rethinking of economics seems necessary and in presenting alternative approaches to economic theory, this book contributes to the rebuilding of the discipline.

This volume brings together contributions from different perspectives and theoretical approaches that address the challenge of updating the economic theory corpus and seek to recover prestige for this discipline after the failure of neoclassical economics. It addresses a range of topics, including the complexity approach to economics, category theory, the Post-Keynesian approach to micro and macroeconomics, financialisation, multidimensional analysis and ecological economics.

The book is aimed at economics scholars, researchers, academics and practitioners, as well as upper undergraduates and graduates in this area of knowledge. It may also be of interest for people interested in methodological issues in economics and the relationship between economic theory and the real world.

Alternative Approaches to Economic Theory:
Complexity, Post Keynesian and Ecological Economics
Edited By Victor A. Beker

This book offers insights on the study of natural language as a complex adaptive system. It discusses a new way to tackle the problem of language modeling, and provides clues on how the close relation between natural language and some biological structures can be very fruitful for science. The book examines the theoretical framework and then applies its main principles to various areas of linguistics. It discusses applications in language contact, language change, diachronic linguistics, and the potential enhancement of classical approaches to historical linguistics by means of new methodologies used in physics, biology, and agent systems theory. It shows how studying language evolution and change using computational simulations enables to integrate social structures in the evolution of language, and how this can give rise to a new way to approach sociolinguistics. Finally, it explores applications for discourse analysis, semantics and cognition.

Complexity Applications in Language and Communication Sciences

Editors: Massip Bonet, Àngels, Bel-Enguix, Gemma, Bastardas-Boada, Albert