scholarly journals Artificial intelligence(A.I.)in Social Sciences: A Primer

2021 ◽  
Vol 07 (04) ◽  
pp. 48-53
Author(s):  
Matthew N. O. Sadiku ◽  
OmobayodeI Fagbohungbe ◽  
Sarhan M. Musa
Keyword(s):  
Social Sciences ◽  
Artificial Intelligence

Applications of Artificial Intelligence Methodologies to Behavioral and Social Sciences

2019 ◽  
Vol 29 (10) ◽  
pp. 2954-2966 ◽  
Author(s):  
Mihaela Robila ◽  
Stefan A. Robila
Keyword(s):  
Social Sciences ◽  
Artificial Intelligence

scholarly journals Artificial Intelligence and Artificial Sociality: New Phenomena and Challenges for the Social Sciences

2021 ◽  
Author(s):  
Андрей Владимирович Резаев ◽  
Наталья Дамировна Трегубова
Keyword(s):  
Social Sciences ◽  
Artificial Intelligence ◽  
Research Project ◽  
The Social ◽  
Rfbr Grant ◽  
New Phenomena

Acknowledgements. The study was conducted in the framework of the research project supported by RFBR grant No. 20-04-60033.

scholarly journals Comparing the Emergence of Technical and Social Sciences Research in Artificial Intelligence

2021 ◽  
Vol 3 ◽  
Author(s):  
Alexandre K. Ligo ◽  
Krista Rand ◽  
Jason Bassett ◽  
S. E. Galaitsi ◽  
Benjamin D. Trump ◽  
...  
Keyword(s):  
Social Sciences ◽  
Artificial Intelligence ◽  
Social Science ◽  
Scientific Development ◽  
Societal Implications ◽  
Security Engineering ◽  
Research Areas ◽  
The Social ◽  
Collaborative Engagement ◽  
Scientists And Engineers

Applications of Artificial Intelligence (AI) can be examined from perspectives of different disciplines and research areas ranging from computer science and security, engineering, policymaking, and sociology. The technical scholarship of emerging technologies usually precedes the discussion of their societal implications but can benefit from social science insight in scientific development. Therefore, there is an urgent need for scientists and engineers developing AI algorithms and applications to actively engage with scholars in the social sciences. Without collaborative engagement, developers may encounter resistance to the approval and adoption of their technological advancements. This paper reviews a dataset, collected by Elsevier from the Scopus database, of papers on AI application published between 1997 and 2018, and examines how the co-development of technical and social science communities has grown throughout AI's earliest to latest stages of development. Thus far, more AI research exists that combines social science and technical explorations than AI scholarship of social sciences alone, and both categories are dwarfed by technical research. Moreover, we identify a relative absence of AI research related to its societal implications such as governance, ethics, or moral implications of the technology. The future of AI scholarship will benefit from both technical and social science examinations of the discipline's risk assessment, governance, and public engagement needs, to foster advances in AI that are sustainable, risk-informed, and societally beneficial.

The Future of ICT/LKT in the Teaching and Learning of Social Sciences, Geography, and History

2020 ◽  
pp. 268-291
Keyword(s):  
Social Sciences ◽  
Artificial Intelligence ◽  
Adaptive Learning ◽  
Teaching And Learning ◽  
Industrial Revolution ◽  
Learning Goals ◽  
Fourth Industrial Revolution ◽  
Online Tools ◽  
The Social ◽  
New Challenges

Most experts consider that society has entered in a Fourth Industrial Revolution that implies ubiquitous changes characterized by a fusion of technologies that is blurring the lines that differentiate physical, digital, and biological spheres. This implies to open a door to important changes in the teaching and learning of the social sciences, geography, and history. Regarding this, it is necessary that both citizens and organizations develop new skills. Artificial intelligence as education technology is possible due to digital and online tools. Adaptive learning, meanwhile, is related to artificial intelligence, personalizing the learning and offering contents adapted to students. New challenges in the teaching of social sciences extends beyond the learning of facts and events. As a result of changes in society of Fourth Industrial Revolution, thinking-based learning (TBL) with the support of learning and knowledge technologies (LKT), creativity, critical thinking, and cooperation are some of the essential learning goals to participate in society.

scholarly journals The influences of religion on the Japanese conception of robots

2020 ◽  
Author(s):  
Tung Manh Ho
Keyword(s):  
Social Sciences ◽  
Artificial Intelligence ◽  
Close Attention ◽  
Social Sciences And Humanities ◽  
Digital World ◽  
And Behaviors ◽  
Technological World ◽  
The Way

The studies on the Japanese conception of robots and artificial intelligence (AI) represent an example of the unexpected way cultural specificities influence people’s emotions, thoughts,and behaviors. In a digital world where rapid social and institutions innovation must occur to adapt to the speed of the cyberspace, it is imperative for social sciences and humanities researchers to pay close attention to how the undercurrents of cultures and religions might influence the way people interact with the technological world.

scholarly journals Ethics as attention to context: recommendations for the ethics of artificial intelligence

2021 ◽  
Vol 1 ◽  
pp. 27
Author(s):  
Anais Resseguier ◽  
Rowena Rodrigues
Keyword(s):  
Social Sciences ◽  
Artificial Intelligence ◽  
Social Inequalities ◽  
Environmental Damage ◽  
Ethical Theories ◽  
Political Issues ◽  
Social Sciences And Humanities ◽  
Ai Ethics ◽  
Guidance Documents ◽  
Practical Recommendations

This article shows that current ethics guidance documents and initiatives for artificial intelligence (AI) tend to be dominated by a principled approach to ethics. Although this brings value to the field, it also entails some risks, especially in relation to the abstraction of this form of ethics that makes it poorly equipped to engage with and address deep socio-political issues and the material impacts of AI. This is particularly problematic considering the risk for AI to further entrench already existing social inequalities and injustices and contribute to environmental damage. To respond to this challenge posed by AI ethics today, this article proposes to complement the existing principled approach with an approach to ethics as attention to context and relations. It does so by drawing from alternative ethical theories to the dominant principled one, especially the ethics of care or other feminist approaches to ethics. Related to this, it encourages the inclusion of social sciences and humanities in the development, deployment and use of AI, as well as in AI ethics discussions and initiatives. This article presents this proposal for an ethics as attention to context and formulates a series of practical recommendations to implement this proposal concretely.

Martin Heidegger

2019 ◽  
pp. 24-34
Author(s):  
Anthony Vincent Fernandez
Keyword(s):  
Social Sciences ◽  
Artificial Intelligence ◽  
Twentieth Century ◽  
Martin Heidegger ◽  
Early Life ◽  
Being And Time ◽  
The Third ◽  
Human And Social Sciences ◽  
The World ◽  
Work Up

Martin Heidegger (1889–1976) is one of the most influential philosophers of the twentieth century. His influence, however, extends beyond philosophy. His account of Dasein, or human existence, permeates the human and social sciences, including nursing, psychiatry, psychology, sociology, anthropology, and artificial intelligence. This chapter outlines Heidegger’s influence on psychiatry and psychology, focusing especially on his relationships with the Swiss psychiatrists Ludwig Binswanger and Medard Boss. The first section outlines Heidegger’s early life and work, up to and including the publication of Being and Time, in which he develops his famous concept of being-in-the-world. The second section focuses on Heidegger’s initial influence on psychiatry via Binswanger’s founding of Daseinsanalysis, a Heideggerian approach to psychopathology and psychotherapy. The third section turns to Heidegger’s relationship with Boss, including Heidegger’s rejection of Binswanger’s Daseinsanalysis and his lectures at Boss’s home in Zollikon, Switzerland.

Ubiquitous tools, connected things and intelligent agents: Disentangling the terminology and revealing underlying theoretical dimensions

First Monday ◽  
2019 ◽  
Author(s):  
Katrin Etzrodt ◽  
Sven Engesser
Keyword(s):  
Social Sciences ◽  
Artificial Intelligence ◽  
Intelligent Agents ◽  
Rapid Evolution ◽  
Social Implications ◽  
Theoretical Frameworks ◽  
The Social ◽  
Technological Developments ◽  
Similarities And Differences ◽  
Key Questions

Research on the social implications of technological developments is highly relevant. However, a broader comprehension of current innovations and their underlying theoretical frameworks is limited by their rapid evolution, as well as a plethora of different terms and definitions. The terminology used to describe current innovations varies significantly among disciplines, such as social sciences and computer sciences. This article contributes to systematic and cross-disciplinary research on current technological applications in everyday life by identifying the most relevant concepts (i.e., Ubiquitous Computing, Internet of Things, Smart Objects and Environments, Ambient Environments and Artificial Intelligence) and relating them to each other. Key questions, core aspects, similarities and differences are identified. Theoretically disentangling terminology results in four distinct analytical dimensions (connectivity, invisibility, awareness, and agency) that facilitate and address social implications. This article provides a basis for a deeper understanding, precise operationalisations, and an increased anticipation of impending developments.

scholarly journals Building University-Industry Co-Innovation Networks in Transnational Innovation Ecosystems: Towards a Transdisciplinary Approach of Integrating Social Sciences and Artificial Intelligence

2019 ◽  
Vol 11 (17) ◽  
pp. 4633 ◽  
Author(s):  
Yuzhuo Cai ◽  
Borja Ramis Ferrer ◽  
Jose Luis Martinez Lastra
Keyword(s):  
Social Sciences ◽  
Artificial Intelligence ◽  
Initial Step ◽  
Future Research ◽  
Innovation Networks ◽  
Transdisciplinary Approach ◽  
Industrial Firms ◽  
Innovation Ecosystems ◽  
University Cooperation ◽  
University Industry

This paper presents a potential solution to fill a gap in both research and practice that there are few interactions between transnational industry cooperation (TIC) and transnational university cooperation (TUC) in transnational innovation ecosystems. To strengthen the synergies between TIC and TUC for innovation, the first step is to match suitable industrial firms from two countries for collaboration through their common connections to transnational university/academic partnerships. Our proposed matching solution is based on the integration of social science theories and specific artificial intelligence (AI) techniques. While the insights of social sciences, e.g., innovation studies and social network theory, have potential to answer the question of why TIC and TUC should be looked at as synergetic entities with elaborated conceptualization, the method of machine learning, as one specific technic off AI, can help answer the question of how to realize that synergy. On the way towards a transdisciplinary approach to TIC and TUC synergy building, or creating transnational university-industry co-innovation networks, the paper takes an initial step by examining what the supports and gaps of existing studies on the topic are, and using the context of EU–China science, technology and innovation cooperation as a testbed. This is followed by the introduction of our proposed approach and our suggestions for future research.

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