Suchergebnisse

'Many of us have stood above a colony of ants and been astounded at their ability to act and organise as a social system. Humans are, of course, smarter, independent free-thinking individuals. Read this book and think again. With eyesight sharpened by math, modeling, and the familiarity with a new landscape he has in part created, Sandy Pentland and his team are mapping out a new world, crawling with information, that offers some real understanding of who we are and who we could be. Welcome to the age of social physics.'

'Many of us have stood above a colony of ants and been astounded at their ability to act and organise as a social system. Humans are, of course, smarter, independent free-thinking individuals. Read this book and think again. With eyesight sharpened by math, modeling, and the familiarity with a new landscape he has in part created, Sandy Pentland and his team are mapping out a new world, crawling with information, that offers some real understanding of who we are and who we could be. Welcome to the age of social physics.'.

Drawing on a unique, multi-year collaboration with the heads of major IT, wireless, hardware, health, and financial firms, as well as the heads of American, EU, and other regulatory organizations, and a variety of NGOs [1,2],I describe the potential for pervasive and mobile sensing and computing over the next decade, and the challenges that will have to be faced in order to realize this potential. ; United States. Army Research Laboratory (Cooperative Agreement Number W911NF-09-2-0053) ; United States. Air Force Office of Scientific Research (Award Number FA9550-10-1-0122)

Fintech foundations : convergence, blockchain, big data, and AI / David Shrier and Alex Pentland -- Edge effects : bridging from old to new / Boris Khentov -- Opening up open banking / Markos Zachariadis and Pinar Ozcan -- Digital financial services / David Shrier -- Policy & fintech : frameworks / Oliver R. Goodenough, Mark Flood, Matthew Reed, David Shrier, Thomas Hardjono, and Alex Pentland -- Policy & fintech : case studies / Oliver R. Goodenough, Mark Flood, Matthew Reed, David Shrier, Thomas Hardjono, and Alex Pentland -- Digital banking manifesto 2020 : the end of banks / Alex Lipton, David Shrier, and Alex Pentland -- Regulatory sandboxes / Oliver R. Goodenough and David Shrier -- Leapfrog for the growth of Africa / Michelle Chivunga -- The rise of RegTech and the divergence of compliance and risk / Amias Moore Gerety and Lev Menand -- On governance and (technical) complexity / John D'Agostino (with contributions from Sharmila Kassam) -- Responsible technology--advancing trust and securing the ecosystem / Ajay Bhall.

Abstract
Evidence-based and human-centric design of digital media platforms could reduce many of the problems of misinformation, polarization, and misaligned incentives that plague both society and individual organizations. With these sorts of design changes, it may become possible to build deliberative digital media that are useful both for discussions of contentious issues and for achieving successful collective action. In this Perspective paper, we discuss several issues in which current-day social science indicates the origin of these problems and suggests methods for improvement. Finally, we analyze a popular deliberative democracy platform to illustrate how social science might enable design of next-generation digital media suitable for democratic deliberation, and in which generative artificial intelligence might be useful.

© Springer International Publishing AG 2016. Understanding political phenomena requires measuring the political preferences of society. We introduce a model based on mixtures of spatial voting models that infers the underlying distribution of political preferences of voters with only voting records of the population and political positions of candidates in an election. Beyond offering a costeffective alternative to surveys, this method projects the political preferences of voters and candidates into a shared latent preference space. This projection allows us to directly compare the preferences of the two groups, which is desirable for political science but difficult with traditional survey methods. After validating the aggregated-level inferences of this model against results of related work and on simple prediction tasks, we apply the model to better understand the phenomenon of political polarization in the Texas, New York, and Ohio electorates. Taken at face value, inferences drawn from our model indicate that the electorates in these states may be less bimodal than the distribution of candidates, but that the electorates are comparatively more extreme in their variance. We conclude with a discussion of limitations of our method and potential future directions for research.