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- 저자 : Talhelm, Thomas (검색결과 2 건)
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Thomson, Robert,Yuki, Masaki,Talhelm, Thomas,Schug, Joanna,Kito, Mie,Ayanian, Arin H.,Becker, Julia C.,Becker, Maja,Chiu, Chi-yue,Choi, Hoon-Seok,Ferreira, Carolina M.,Fü,lö,p, Marta,Gul, Peli National Academy of Sciences 2018 PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF Vol.115 No.29
<▼1><P><B>Significance</B></P><P>Biologists and social scientists have long tried to understand why some societies have more fluid and open interpersonal relationships—differences in relational mobility—and how those differences influence individual behaviors. We measure relational mobility in 39 societies and find that relationships are more stable and hard to form in east Asia, North Africa, and the Middle East, while they are more fluid in the West and Latin America. Results show that relationally mobile cultures tend to have higher interpersonal trust and intimacy. Exploring potential causes, we find greater environmental threats (like disease and warfare) and sedentary farming are associated with lower relational mobility. Our society-level index of relational mobility for 39 societies is a resource for future studies.</P></▼1><▼2><P>Biologists and social scientists have long tried to understand why some societies have more fluid and open interpersonal relationships and how those differences influence culture. This study measures relational mobility, a socioecological variable quantifying voluntary (high relational mobility) vs. fixed (low relational mobility) interpersonal relationships. We measure relational mobility in 39 societies and test whether it predicts social behavior. People in societies with higher relational mobility report more proactive interpersonal behaviors (e.g., self-disclosure and social support) and psychological tendencies that help them build and retain relationships (e.g., general trust, intimacy, self-esteem). Finally, we explore ecological factors that could explain relational mobility differences across societies. Relational mobility was lower in societies that practiced settled, interdependent subsistence styles, such as rice farming, and in societies that had stronger ecological and historical threats.</P></▼2>
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CAN ARTIFICIAL INTELLIGENCE IMPROVE REAL LIFE? : THE INFORMATION AGE COMES TO COMMUNITY DEVELOPMENT
Hong, Seong-Gwan,Talhelm,Daniel R. HANUL ACADEMY 1999 Global Transformation Toward A Sustainable Civil S Vol.- No.1
Can artificial intelligence improve real life? We expect new decision-support systems to exponentially improve human decision-making capabilities regarding social issues in the next few decades. Specifically, we show how artificial intelligence models utilizing human knowledge can help communities determine which choices are more likely to improve their quality of life over time. Our case in point is the Community Options Model: a simple form of artificial intelligence developed to mimic the understandings and decision rules contributed by a panel of experts. The Community Options Model is a desktop computer model of community social and economic systems. Community leaders can evaluate options by posing scenarios of local actions(of their own or by others), and comparing estimated future local outcomes for each scenario. The current version forecasts about 400 indicators of socio-economic conditions in any specific community and its districts for 15 to 20 years. Indicators include population by age class, local tax rates, public service Ievels(e. g., education attainment, public safety), employment and income by sector, traffic levels/congestion, property values, and many others. Three relatively recent developments have collectively made it feasible to create and utilize such models. First, two new approaches to model estimation make it possible to estimate detailed models involving hundreds of interrelated equations: Expert knowledge, used to design an overall model framework/ and fitting of equation sets to time series data from diverse case study communities. Experts from a variety of disciplines and practices can provide both an advanced, comprehensive systems analysis and a narrow focus on the most relevant aspects. Further, they can contribute rules-of-thumb and even common understandings such as details of community social and economic life. The equation fitting process contributes a relatively objective assessment of individual relationships. Second, the availability of low cost, high-speed personal computers, and commercial simulation modeling software greatly facilitates model development and statistical fitting. Third, people are becoming more capable of understanding and utilizing graphical data and other kinds of indicator variables. The widespread use of personal computers and the worldwide web, and media use of such data and indicators have familiarized many people with these kinds of information, Models such as this can facilitate more-nearly-holistic, long-term thinking, strategic planning and decision making at the community level. Future models will be even more comprehensive, and will be linked to other new tools such as GIS and virtual reality. The stage now seems set for wide utilization of effective, realtime decision support systems and information systems throughout private, public and personal sectors. Perhaps the greater challenge will be utilizing the information wisely, to better humanity and our part of the universe.
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