From one of the world’s leading data scientists, a landmark tour of the new science of idea flow, offering revolutionary insights into the mysteries of collective intelligence and social influence If the Big Data revolution has a presiding genius, it is MIT’s Alex “Sandy” Pentland. Over years of groundbreaking experiments, he has distilled remarkable discoveries significant enough to become the bedrock of a whole new scientific field: social physics. Humans have more in common with bees than we like to admit: We’re social creatures first and foremost. Our most important habits of action—and most basic notions of common sense—are wired into us through our coordination in social groups. Social physics is about idea flow, the way human social networks spread ideas and transform those ideas into behaviors. Thanks to the millions of digital bread crumbs people leave behind via smartphones, GPS devices, and the Internet, the amount of new information we have about human activity is truly profound. Until now, sociologists have depended on limited data sets and surveys that tell us how people say they think and behave, rather than what they actually do. As a result, we’ve been stuck with the same stale social structures—classes, markets—and a focus on individual actors, data snapshots, and steady states. Pentland shows that, in fact, humans respond much more powerfully to social incentives that involve rewarding others and strengthening the ties that bind than incentives that involve only their own economic self-interest. Pentland and his teams have found that they can study patterns of information exchange in a social network without any knowledge of the actual content of the information and predict with stunning accuracy how productive and effective that network is, whether it’s a business or an entire city. We can maximize a group’s collective intelligence to improve performance and use social incentives to create new organizations and guide them through disruptive change in a way that maximizes the good. At every level of interaction, from small groups to large cities, social networks can be tuned to increase exploration and engagement, thus vastly improving idea flow. Social Physics will change the way we think about how we learn and how our social groups work—and can be made to work better, at every level of society. Pentland leads readers to the edge of the most important revolution in the study of social behavior in a generation, an entirely new way to look at life itself.

Social Physics: How Social Networks Can Make Us Smarter

Politics & Social Sciences

Pentland, Alex

Social Sciences

Penguin Publishing Group

How understanding the signaling within social networks can change the way we make decisions, work with others, and manage organizations.
How can you know when someone is bluffing? Paying attention? Genuinely interested? The answer, writes Alex Pentland in Honest Signals, is that subtle patterns in how we interact with other people reveal our attitudes toward them. These unconscious social signals are not just a back channel or a complement to our conscious language; they form a separate communication network. Biologically based “honest signaling,” evolved from ancient primate signaling mechanisms, offers an unmatched window into our intentions, goals, and values. If we understand this ancient channel of communication, Pentland claims, we can accurately predict the outcomes of situations ranging from job interviews to first dates.
Pentland, an MIT professor, has used a specially designed digital sensor worn like an ID badge―a “sociometer”―to monitor and analyze the back-and-forth patterns of signaling among groups of people. He and his researchers found that this second channel of communication, revolving not around words but around social relations, profoundly influences major decisions in our lives―even though we are largely unaware of it. Pentland presents the scientific background necessary for understanding this form of communication, applies it to examples of group behavior in real organizations, and shows how by “reading” our social networks we can become more successful at pitching an idea, getting a job, or closing a deal. Using this “network intelligence” theory of social signaling, Pentland describes how we can harness the intelligence of our social network to become better managers, workers, and communicators.

Honest Signals: How They Shape Our World (Bradford Books)

Self-Help

Relationships

The MIT Press

Product Description 
How to empower people and communities with user-centric data ownership, transparent and accountable algorithms, and secure digital transaction systems. \nData is now central to the economy, government, and health systems—so why are data and the AI systems that interpret the data in the hands of so few people? 
Building the New Economy calls for us to reinvent the ways that data and artificial intelligence are used in civic and government systems. Arguing that we need to think about data as a new type of capital, the authors show that the use of data trusts and distributed ledgers can empower people and communities with user-centric data ownership, transparent and accountable algorithms, machine learning fairness principles and methodologies, and secure digital transaction systems. \nIt’s well known that social media generate disinformation and that mobile phone tracking apps threaten privacy. But these same technologies may also enable the creation of more agile systems in which power and decision-making are distributed among stakeholders rather than concentrated in a few hands. Offering both big ideas and detailed blueprints, the authors describe such key building blocks as data cooperatives, tokenized funding mechanisms, and tradecoin architecture. They also discuss technical issues, including how to build an ecosystem of trusted data, the implementation of digital currencies, and interoperability, and consider the evolution of computational law systems.\nReview 
“Beating the pandemic is a tough challenge, but also an opportunity to retool for the bigger disruptions of digitization and AI. 
Building the New Economy brings together the best thinking on exactly how to do that, with perfect combination of rigor and relevance.” 
— 
Erik Brynjolfsson, Stanford University\n“These essays together offer depth and a path forward. Required reading for a sane future.” 
— 
Lawrence Lessig, Harvard University\n“Each chapter of 
Building the New Economy tackles an urgent and important societal question, from how to build effective health surveillance without a national healthcare system to how to protect people’s right to control their own data while exploiting its economic value, to how to enjoy the economic benefits of asset-backed securitization while reducing fraud. This boundary-pushing preview of the future we could have is a must-read for policymakers, thought leaders, and all of us wishing to reimagine and build a better society on the other side of the pandemic.” 
— 
Beth Noveck, former Deputy CTO, United States\n“An assembly of some of the brightest minds in engineering and data science, 
Building the New Economy bravely tackles not only what the economy needs of technology in our crisis-riddled age, but also what technology demands of financial ecosystems in order for it to make our lives more efficient, fairer, and safer. An ingenious collection of essays, the book provides a fresh new perspective on some of the most cutting-edge technologies of our time.” 
— 
Chris Brummer, Georgetown University 
 About the Author 
Alex “Sandy” Pentland directs the MIT-wide initiative MITConnection Science. Called one of the “seven most powerful data scientists in the world” by 
Forbes, he has cofounded more than a dozen companies and is the author of 
Honest Signals (MIT Press) and 
Social Physics. Alexander Lipton is Professor and Dean’s Fellow at the Jerusalem Business School at the Hebrew University of Jerusalem, Cofounder and Chief Information Officer at Sila, and Connection Fellow at MIT. Thomas Hardjono is Technology Director of the MIT Connection Science and the MIT Trust::Data Consortium.

Building the New Economy: Data as Capital

Lipton, Alexander

Hardjono, Thomas

Reference

MIT Connection Science & Engineering

This is the Spanish translation of "Honest signals", by Alex Pentland. Los grupos de animales toman decisiones conjuntas, comunicándose entre ellos mucha información por medio de actitudes, sonidos, gestos... cuando los humanos evolucionamos hasta emplear el lenguaje para compartir información, este otro sistema de comunicación social no desapareció. Las investigaciones del profesor Pentland demuestran no solo su existencia, sino también que este tipo de información tiene tanto valor para nosotros que incluso prevalece sobre la información lingüística, aunque no seamos conscientes de ella. Este libro cuenta cómo el MIT ha desarrollado herramientas y métodos para medir estas señales y convertirlas en información manejable. Con ella pueden establecerse patrones de comportamiento y predecirse conductas individuales y de grupos. Señales honestas es el resultado de una disciplina nueva y emergente, llamada ciencia de las redes, que intenta entender a las personas en el contexto de sus redes sociales en lugar de considerarlas como individuos aislados. «Tal vez la consciencia no sea tan importante como tendemos a creer. Quizá necesitemos reexaminar nuestras suposiciones sobre el rol que juegan tanto las fuerzas conscientes como las inconscientes en la configuración de nuestras conductas cotidianas. La información de nuestros sociómetros apoya la idea de que gran parte de la conducta humana es automática o está determinada por procesos inconscientes».

Señales honestas: El lenguaje que gobierna el mundo (Spanish Edition)

CreateSpace Independent Publishing Platform

Social Physics: How Good Ideas Spread-The Lessons from a New Science

Penguin Press

This book offers a comprehensive analysis of the theory and tools needed for the development of an efficient and robust infrastructure for the design of collaborative patrolling unmanned aerial vehicle (UAV) swarms, focusing on its applications for tactical intelligence drones. It discusses frameworks for robustly and near-optimally analyzing flocks of semi-autonomous vehicles designed to efficiently perform the ongoing dynamic patrolling and scanning of pre-defined “search regions”. It discusses the theoretical limitations of such systems, as well as the trade-offs between the systems’ various economic and operational parameters.Current UAV systems rely mainly on human operators for the design and adaptation of drones’ flying routes. However, recent technological advances have introduced new systems, comprised of a small number of self-organizing vehicles, manually guided at the swarm level by a human operator.With the growing complexity of such man-supervised architectures, it is becoming increasingly harder to guarantee a pre-defined level of performance. The use of large scale swarms of UAVs as a combat and reconnaissance platform therefore necessitates the development of an efficient optimization mechanism of their utilization, specifically in the design and maintenance of their patrolling routes.The book is intended for researchers and engineers in the fields of swarms systems and autonomous drones. 

Swarms and Network Intelligence in Search (Studies in Computational Intelligence, 729)

Computers & Technology

Altshuler, Yaniv

Bruckstein, Alfred M.

Computer Science

Springer

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