Examining Spillover Priming Effects from a Network Perspective
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Artificial Intelligence, Automation, and Work
Artificial Intelligence, Automation, and Work The Economics of Artifi cial Intelligence National Bureau of Economic Research Conference Report The Economics of Artifi cial Intelligence: An Agenda Edited by Ajay Agrawal, Joshua Gans, and Avi Goldfarb The University of Chicago Press Chicago and London The University of Chicago Press, Chicago 60637 The University of Chicago Press, Ltd., London © 2019 by the National Bureau of Economic Research, Inc. All rights reserved. No part of this book may be used or reproduced in any manner whatsoever without written permission, except in the case of brief quotations in critical articles and reviews. For more information, contact the University of Chicago Press, 1427 E. 60th St., Chicago, IL 60637. Published 2019 Printed in the United States of America 28 27 26 25 24 23 22 21 20 19 1 2 3 4 5 ISBN-13: 978-0-226-61333-8 (cloth) ISBN-13: 978-0-226-61347-5 (e-book) DOI: https:// doi .org / 10 .7208 / chicago / 9780226613475 .001 .0001 Library of Congress Cataloging-in-Publication Data Names: Agrawal, Ajay, editor. | Gans, Joshua, 1968– editor. | Goldfarb, Avi, editor. Title: The economics of artifi cial intelligence : an agenda / Ajay Agrawal, Joshua Gans, and Avi Goldfarb, editors. Other titles: National Bureau of Economic Research conference report. Description: Chicago ; London : The University of Chicago Press, 2019. | Series: National Bureau of Economic Research conference report | Includes bibliographical references and index. Identifi ers: LCCN 2018037552 | ISBN 9780226613338 (cloth : alk. paper) | ISBN 9780226613475 (ebook) Subjects: LCSH: Artifi cial intelligence—Economic aspects. Classifi cation: LCC TA347.A78 E365 2019 | DDC 338.4/ 70063—dc23 LC record available at https:// lccn .loc .gov / 2018037552 ♾ This paper meets the requirements of ANSI/ NISO Z39.48-1992 (Permanence of Paper). -
EPA Administrator Lisa P. Jackson Schedule
Release 4 - HQ-FOI-01268-12 All emails sent by "Richard Windsor" were sent by EPA Administrator Lisa Jackson 01268-EPA-5928 Noah Dubin/DC/USEPA/US To 01/26/2012 06:15 PM cc bcc Richard Windsor Subject 01/30/2012 thru 02/12/2012 Schedule for Lisa P. Jackson *** Do not copy or forward this information *** EPA Administrator Lisa P. Jackson Schedule 01/26/2012 06:11:57 PM Monday, 1/30/2012 08:45 AM-09:15 AM Daily Briefing Location: Administrator's Office ------------------------------- 09:30 AM-10:30 AM HOLD: WH POST-SOTU Ct: Ryan Robison - 202-564-2856 Location: Administrator's Office ------------------------------- 10:30 AM-11:00 AM Personnel Discussion Ct:Ryan Robison - 202-564-2856 Staff: Diane Thompson, Jose Lozano (OA) Paul Anastas (ORD) Optional: Bob Perciasepe (OA) Location: Administrator's Office ------------------------------- 11:00 AM-09:00 PM Out of Office See EA or Jose Location: NYC ------------------------------- 01:00 PM-02:00 PM FYI: Senior Staff Location: Bullet Room ------------------------------- Tuesday, 1/31/2012 09:30 AM-10:30 AM HOLD: WH POST-SOTU Ct: Ryan Robison - 202-564-2856 Location: Administrator's Office ------------------------------- 10:30 AM-10:45 AM Depart for White House Location: Ariel Rios ------------------------------- 10:45 AM-12:15 PM Cabinet Meeting Ct: Liz Ashwell 564.1008 Full Cabinet Meeting w/ POTUS and VPOTUS Location: Cabinet Room, White House ------------------------------- 12:15 PM-12:30 PM Depart for Ariel Rios Release 4 - HQ-FOI-01268-12 All emails sent by "Richard Windsor" were sent by EPA Administrator Lisa Jackson Location: White House ------------------------------- 12:45 PM-12:50 PM Drop-By Meeting with Alaska Eskimo Whaling Commission Ct: Earl Comstock - 202-255-0273 **AA DePass will be lead on this meeting, the Administrator will drop by if her schedule permits **This meeting will last from 12:45 to 1:15 -Mr. -
The Work Ahead Machines, Skills, and U.S
Independent Task Force Report No. 76 The Work Ahead Machines, Skills, and U.S. Leadership in the Twenty-First Century John Engler and Penny Pritzker, Chairs Edward Alden, Project Director Laura Taylor-Kale, Deputy Project Director ENDNOTES 1. Bureau of Labor Statistics, “Labor Force Statistics From Current Population Survey: Databases, Tables and Calculators by Subject,” February 16, 2018, http://data.bls.gov /timeseries/LNS11300000. See also Arne L. Kalleberg and Till M. von Wachter, “The U.S. Labor Market During and After the Great Recession: Continuities and Transformations,” RSF: The Russell Sage Foundation Journal of the Social Sciences 3, no. 3 (April 2017): 1–19, http://rsfjournal.org/doi/full/10.7758/RSF.2017.3.3.01; Sandra E. Black, Diane Whitmore Schanzenbach, and Audrey Breitwieser, “The Recent Decline in Women’s Labor Force Participation,” Hamilton Project, October 2017, http:// hamiltonproject.org/assets/files/decline_womens_labor_force_participation_ BlackSchanzenbach.pdf. While labor force participation did fall more steeply during the recession, there has been a reasonably steady decline since 2000 driven by rising retirements and declining work among prime-age men. See Alan B. Krueger, “Where Have All the Workers Gone? An Inquiry Into the Decline in the U.S. Labor Force Participation Rate,” Brookings Papers on Economic Activity, September 2017, http:// brookings.edu/bpea-articles/where-have-all-the-workers-gone-an-inquiry-into-the -decline-of-the-u-s-labor-force-participation-rate. 2. Annie Lowrey, “The Great Recession Is Still With Us,” Atlantic, December 1, 2017, http://theatlantic.com/business/archive/2017/12/great-recession-still-with-us/547268. 3. -
Structural Balance and Partitioning Signed Graphs
Structural Balance and Partitioning Signed Graphs Patrick Doreian Andrej Mrvar Department of Sociology Faculty of Social Sciences University of Pittsburgh University of Ljubljana Abstract Signed graphs have been used frequently to model affect ties for social actors. In this context, structural balance theory has been used as a theory for the organization and form of these relations. Based on a graph theoretical formalization of this theory, for signed graphs, there are theorems stating that balanced structures have clear parti- tioned forms. We discuss the use of local optimization procedures as a method of obtaining these partitioned structures – or partitioned structures that are as close to a balanced partition as possible for structures that are not balanced. In addition, this method provides a measure of the extent to which a signed graph is imbalanced. For a time series of signed graphs, this permits a test of the balance hypoth- esis that human groups tend towards balance over time. Examples are provided of interpersonal ties in networks and institutionalized rela- tions among collective units. Since the pioneering work of Heider (1946) there has been an enduring concern with theories of structural balance. See, for example, Taylor (1970) and Forsythe (1990). Central to this formulation is the idea of triads made up of two actors, p and q, and some object, x. There is a direct social relation between the two actors and there are unit formation links between the actors and the object. The set of such triads is displayed in Figure 1. The relation between the actors can be positive (for example, liking) or negative (disliking) and the unit formation relations can be positive (for example, approve) or negative (disapprove). -
Administration of Barack Obama, 2014 Remarks on the Nomination Of
Administration of Barack Obama, 2014 Remarks on the Nomination of Maria Contreras-Sweet To Be Administrator of the Small Business Administration January 15, 2014 Please have a seat. Thank you so much. Well, welcome to the White House. And I am pleased to be joined by many of the people on the frontlines when it comes to creating jobs and new opportunities: America's small-business owners. And I want to thank all of them for the hard work and the sacrifice of these entrepreneurs, as well as the workers and the families across the country that have helped us pull ourselves out of one of the worst recessions in our history. Now what we're seeing is businesses having created more than 8 million new jobs since we hit bottom. Manufacturing is growing, led by a booming auto industry. Our investments have helped bring about new technologies, more affordable energy, and are slowing health care costs, all of which are making America even more attractive for investors. And we're starting to see a lot of the jobs that had left our shores in manufacturing, for example, starting to come back, because we put ourselves in a much more competitive position. And so all the pieces are there to bring back even more new jobs to America this year, but it's not going to happen by itself. This has to be a year of action. We've got to keep our economy growing. We've got to make sure that our working families are sharing in growth and increasing success. -
Balance and Fragmentation in Societies with Homophily and Social Balance Tuan M
www.nature.com/scientificreports OPEN Balance and fragmentation in societies with homophily and social balance Tuan M. Pham1,2, Andrew C. Alexander3, Jan Korbel1,2, Rudolf Hanel1,2 & Stefan Thurner1,2,4* Recent attempts to understand the origin of social fragmentation on the basis of spin models include terms accounting for two social phenomena: homophily—the tendency for people with similar opinions to establish positive relations—and social balance—the tendency for people to establish balanced triadic relations. Spins represent attribute vectors that encode G diferent opinions of individuals whose social interactions can be positive or negative. Here we present a co-evolutionary Hamiltonian model of societies where people minimise their individual social stresses. We show that societies always reach stationary, balanced, and fragmented states, if—in addition to homophily— individuals take into account a signifcant fraction, q, of their triadic relations. Above a critical value, qc , balanced and fragmented states exist for any number of opinions. Te concept of so-called flter bubbles captures the fragmentation of society into isolated groups of people who trust each other, but clearly distinguish themselves from “other”. Opinions tend to align within groups and diverge between them. Interest in this process of social disintegration, started by Durkheim 1, has experienced a recent boost, fuelled by the availability of modern communication technologies. Te extent to which societies fragment depends largely on the interplay of two basic mechanisms that drive social interactions: homophily and structural balance. Homophily is the “principle” that “similarity breeds connection”2. In particular, for those individuals who can be characterised by some social traits, such as opinions on a range of issues, homophily appears as the tendency of like-minded individuals to become friends 3. -
Annual Report M Ission
2012 ANNUAL REPORT M ISSION The New England Council is an alliance of businesses, academic and health institutions, and public and private organizations throughout New England formed to promote economic growth and a high quality of life in the New England region. The New England Council is a leading voice on the issues that shape the region’s economy and quality of life. The Council focuses on key industries that drive the region’s economic growth including education, energy, transportation, technology and innovation, healthcare and financial services. THE NEW ENGLAND COUNCIL TABLE OF CONTENTS 2012 4 President’s Letter 5 Chairman’s Letter ADVOCACY & INITIATIVES 6 Overview 6 Defense 8 Energy & Environment 10 Financial Services 12 Healthcare 13 Higher Education 15 New England Economic Partnership 16 Smart Infrastructure Report 17 Technology 19 Transportation EVENTS 20 Annual Dinner 22 Annual Spring Event 24 Congressional Roundtable Series 26 Featured Events 27 Governors’ Forums 28 Politics & Eggs Series ABOUT THE COUNCIL 29 DC Dialogue 30 Board of Directors 34 New Members 3 THE NEW ENGLAND COUNCIL 2012 PRESIDENT’S LETTER DEAR NEW ENGLAND COUNCIL MEMBER: As I look back at 2012, I am once again truly astounded at how much The New England Council has accomplished during the past year. Over the course of my 16 years at the helm of The New England Council, it has been remarkable to watch the organization evolve and grow as each year passes. When people ask me how we continue to thrive—particularly during the challenging economic situation in recent years—I tell them that it is because of our members. -
Chapter 5 Positive and Negative Relationships
From the book Networks, Crowds, and Markets: Reasoning about a Highly Connected World. By David Easley and Jon Kleinberg. Cambridge University Press, 2010. Complete preprint on-line at http://www.cs.cornell.edu/home/kleinber/networks-book/ Chapter 5 Positive and Negative Relationships In our discussion of networks thus far, we have generally viewed the relationships con- tained in these networks as having positive connotations — links have typically indicated such things as friendship, collaboration, sharing of information, or membership in a group. The terminology of on-line social networks reflects a largely similar view, through its em- phasis on the connections one forms with friends, fans, followers, and so forth. But in most network settings, there are also negative effects at work. Some relations are friendly, but others are antagonistic or hostile; interactions between people or groups are regularly beset by controversy, disagreement, and sometimes outright conflict. How should we reason about the mix of positive and negative relationships that take place within a network? Here we describe a rich part of social network theory that involves taking a network and annotating its links (i.e., its edges) with positive and negative signs. Positive links represent friendship while negative links represent antagonism, and an important problem in the study of social networks is to understand the tension between these two forces. The notion of structural balance that we discuss in this chapter is one of the basic frameworks for doing this. In addition to introducing some of the basics of structural balance, our discussion here serves a second, methodological purpose: it illustrates a nice connection between local and global network properties. -
Chapter 5 Positive and Negative Relationships
Chapter 5 Positive and Negative Relationships Often, knowing just the nodes and edges of a network is not enough to understand the full picture — in many settings, we need to annotate these nodes and edges with additional information to capture what’s going on. This is a theme that has come up several times in our discussions already: for example, Granovetter’s work on the strength of weak ties is based on designating links in a social network as strong or weak, and empirical analyses of social networks that evolve over time is based on annotating edges with the periods during which they were “alive.” Here we describe a rich part of social network theory that involves annotating edges with positive and negative signs — to convey the idea that certain edges represent friendship, while other edges represent antagonism. Indeed, an important problem in social networks is to understand the tension between these two forces, and the notion of structural balance that we discuss is one of the basic frameworks for doing this. In addition to introducing some of the basics of structural balance, our discussion here serves a second, methodological purpose: it illustrates a nice connection between local and global network properties. A recurring issue in the analysis of networked systems is the way in which local effects — phenomena involving only a few nodes at a time — can have global consequences that are observable at the level of the network as a whole. Structural balance offers a way to capture one such relationship in a very clean way, and by purely mathematical analysis: we will consider a simple definition abstractly, and find that it inevitably leads to certain macroscopic properties of the network. -
Structural Balance in Signed Networks: Separating the Probability to Interact from the Tendency to Fight∗
Structural Balance in Signed Networks: Separating the Probability to Interact from the Tendency to Fight∗ J¨urgenLernery Abstract Structural balance theory implies hypothetical network effects such as \the enemy of an enemy is a friend" or \the friend of an enemy is an enemy." To statistically test such hypotheses researchers often estimate whether, for instance, actors have an increased probability to collaborate with the enemies of their enemies and/or a decreased probability to fight the enemies of their enemies. Empirically it turns out that the support for balance theory from these tests is mixed at best. We argue that such results are not necessarily a contradiction to balance theory but that they could also be explained by other network effects that influence the probability to interact at all. We propose new and better interpretable models to assess structural balance in signed networks and illustrate their usefulness with networks of international alliances and conflicts. With the new operationalization the support for balance theory in international relations networks is much stronger than suggested by previous work. Keywords: signed networks, structural balance theory, international re- lations, conditional sign of interaction 1 Introduction Generalizing Heider's theory of cognitive balance (Heider 1946), Cartwright and Harary (1956) called a signed network structurally balanced if every cycle has an even number of negative ties. They proved that a network is balanced if and only if its actors can be divided into two groups with only positive ties within the groups and only negative ties between groups. The fundamental claim of structural balance theory is that actors have a preference for balanced states and if a network is unbalanced then actors have a tendency to increase balance by adapting their ties. -
Structural Balance in Signed Digraphs: Considering Transitivity to Measure Balance in Graphs Constructed by Using Different Link Signing Methods
Structural balance in signed digraphs: considering transitivity to measure balance in graphs constructed by using different link signing methods Ly Dinh*, Rezvaneh Rezapour*, Lan Jiang, Jana Diesner University of Illinois at Urbana{Champaign * These authors contributed equally to this work Abstract Structural balance theory assumes triads in networks to gravitate towards stable configurations. The theory has been verified for undirected graphs. Since real-world networks are often directed, we introduce a novel method for considering both transitivity and sign consistency for calculating balance in signed digraphs. We test our approach on graphs that we constructed by using different methods for identifying edge signs: natural language process- ing to infer signs from underlying text data, and self-reported survey data. Our results show that for various social contexts and edge sign detection methods, balance is moderately high, ranging from 67.5% to 92.4%. Keywords: Structural balance, Transitivity, Signed digraphs, Natural language processing, Communication networks, Organizational networks 1. Introduction Real-world social and communication networks are composed of complex arXiv:2006.02565v1 [cs.SI] 3 Jun 2020 and continually evolving interactions among social agents. Network scholars have examined core principles that explains patterns of social interactions at various levels of analysis, i.e., at the node level [4], dyadic level [3], triadic level [5, 30], subgroup level [44], and the graph level [31]. Each level of analysis enables different types of hypotheses to be tested, e.g., with respect Email address: {dinh4,rezapou2,lanj3,jdiesner}@illinois.edu (Ly Dinh*, Rezvaneh Rezapour*, Lan Jiang, Jana Diesner) to structural properties, such as reciprocity at the dyad level, transitivity at the triad level, clusterability at the subgroup level, and centralization at the network level [54, 35]. -
A Simple Approach for Quantifying Node Centrality in Signed and Directed Social Networks Wei-Chung Liu1 , Liang-Cheng Huang1, Chester Wai-Jen Liu2 and Ferenc Jordán3*
Liu et al. Applied Network Science (2020) 5:46 Applied Network Science https://doi.org/10.1007/s41109-020-00288-w RESEARCH Open Access A simple approach for quantifying node centrality in signed and directed social networks Wei-Chung Liu1 , Liang-Cheng Huang1, Chester Wai-Jen Liu2 and Ferenc Jordán3* * Correspondence: jordan.ferenc@ gmail.com Abstract 3Balaton Limnological Institute, MTA Centre for Ecological Research, The position of a node in a social network, or node centrality, can be quantified in Klebelsberg Kuno, Tihany 3, 8237, several ways. Traditionally, it can be defined by considering the local connectivity of Hungary a node (degree) and some non-local characteristics (distance). Here, we present an Full list of author information is available at the end of the article approach that can quantify the interaction structure of signed digraphs and we define a node centrality measure for these networks. The basic principle behind our approach is to determine the sign and strength of direct and indirect effects of one node on another along pathways. Such an approach allows us to elucidate how a node is structurally connected to other nodes in the social network, and partition its interaction structure into positive and negative components. Centrality here is quantified in two ways providing complementary information: total effect is the overall effect a node has on all nodes in the same social network; while net effect describes, whether predominately positive or negative, the manner in which a node can exert on the social network. We use Sampson’s like-dislike relation network to demonstrate our approach and compare our result to those derived from existing centrality indices.