scholarly journals A THEORETICAL AND PRACTICAL COMPREHENSIVE FRAMEWORK FOR ARTIFICIAL INTELLIGENCE ANDSOCIO-PSYCHOLOGICAL CHALLENGES

2020 ◽  
Vol 13(62) (1) ◽  
pp. 33-40
Author(s):  
L. POGAN ◽  
R.I. POPA
Keyword(s):  
Social Sciences ◽  
Artificial Intelligence ◽  
Theoretical Perspective ◽  
Research Trends ◽  
Psychological Perspective ◽  
Human Machine Interaction ◽  
Personality Variables ◽  
The Social ◽  
Comprehensive Framework ◽  
Machine Interaction

The present paper aims to highlight the major up to date findings and research trends on the topic of artificial intelligence (AI) from a theoretical perspective, analysed in association with the human-machine interaction challenges. The existing research and scholarly literature display quite heterogenous approaches on these topics, and only a few of them tackle the social sciences view on the matter. In conclusion, there is a need for a more specific approach from the socio-psychological perspective, especially in topics concerning human centricity, human training at work, personality variables and other indicators when using AI devices.

scholarly journals Radiology Community Attitude in Saudi Arabia about the Applications of Artificial Intelligence in Radiology

Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 834
Author(s):  
Magbool Alelyani ◽  
Sultan Alamri ◽  
Mohammed S. Alqahtani ◽  
Alamin Musa ◽  
Hajar Almater ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Saudi Arabia ◽  
Vital Role ◽  
Human Machine Interaction ◽  
The Future ◽  
Level Of Knowledge ◽  
Electronic Questionnaires ◽  
Machine Interaction ◽  
Applications Of Ai

Artificial intelligence (AI) is a broad, umbrella term that encompasses the theory and development of computer systems able to perform tasks normally requiring human intelligence. The aim of this study is to assess the radiology community’s attitude in Saudi Arabia toward the applications of AI. Methods: Data for this study were collected using electronic questionnaires in 2019 and 2020. The study included a total of 714 participants. Data analysis was performed using SPSS Statistics (version 25). Results: The majority of the participants (61.2%) had read or heard about the role of AI in radiology. We also found that radiologists had statistically different responses and tended to read more about AI compared to all other specialists. In addition, 82% of the participants thought that AI must be included in the curriculum of medical and allied health colleges, and 86% of the participants agreed that AI would be essential in the future. Even though human–machine interaction was considered to be one of the most important skills in the future, 89% of the participants thought that it would never replace radiologists. Conclusion: Because AI plays a vital role in radiology, it is important to ensure that radiologists and radiographers have at least a minimum understanding of the technology. Our finding shows an acceptable level of knowledge regarding AI technology and that AI applications should be included in the curriculum of the medical and health sciences colleges.

Microcomputer Simulations of Presidential Elections

1983 ◽  
Vol 38 ◽  
pp. 20-20
Author(s):  
Robert S. Ross
Keyword(s):  
Social Sciences ◽  
Large Scale ◽  
Role Playing ◽  
Science Students ◽  
Instructional Programs ◽  
Santa Barbara ◽  
Large Scale Systems ◽  
The Social ◽  
User Friendly ◽  
Machine Interaction

Simulations have been an important adjunct to instructional programs for some time. These have ranged from games, or role playing exercises, such as SIMSOC or Internation Simulation, to student-machine interaction, such as the inter-school simulation run out of University of California, Santa Barbara in the early 70's, to the all machine activities found in some of the early SETUPS. Having social science students use the mainframe computer, however, always posed problems: it definitely was not user-friendly and most instructors had little if any training or interest in the use of large scale systems.The wide-spread use of the micro computer is not only revolutionizing areas traditionally relying upon the computer, but is going to have an impact on the social sciences as well.

scholarly journals Transparency in Autonomous Teammates

2019 ◽  
Vol 14 (2) ◽  
pp. 174-190 ◽  
Author(s):  
April Rose Panganiban ◽  
Gerald Matthews ◽  
Michael D. Long
Keyword(s):  
Social Cues ◽  
Social Benefits ◽  
Human Machine Interaction ◽  
Team Collaboration ◽  
Task Setting ◽  
The Social ◽  
Team Environment ◽  
Near Term ◽  
Occupational Settings ◽  
Machine Interaction

Human–Machine teaming is a very near term standard for many occupational settings and still requires considerations for the design of autonomous teammates (ATs). Transparency of system processes is important for human–machine interaction and reliance but standards for its implementation are still being explored. Embedding social cues is a potential design approach, which may capture the social benefits of a team environment, yet vary with task setting. The current study examined the manipulation of transparency of benevolent intent from an AT within a piloting task requiring suppression of enemy defenses. Specifically, the benevolent AT maintained task communication as in a neutral condition, but included messages of support and awareness of errors. Benevolent communication reduced reported workload and increased reported team collaboration, indicating that this team intent was beneficial. In addition, trust and acceptance of the AT were rated higher by individuals tasked with depending on the system to protect them from missile threats. The need for information from ATs is beneficial, however may vary depending on team type.

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.

How AI chatbots have reshaped the frontline interface in China: examining the role of sales–service ambidexterity and the personalization–privacy paradox

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hua Fan ◽  
Bing Han ◽  
Wei Gao ◽  
Wenqian Li
Keyword(s):  
Artificial Intelligence ◽  
Mixed Methods Research ◽  
Online Survey ◽  
Polynomial Regression ◽  
Customer Experience ◽  
Human Machine Interaction ◽  
Content Type ◽  
Positive Effects ◽  
Privacy Paradox ◽  
Machine Interaction

PurposeThis study serves two purposes: (1) to evaluate the effects of organizational ambidexterity by examining how the balanced and the combined sales–service configurations of chatbots differ in their abilities to enhance customer experience and patronage and (2) to apply information boundary theory to assess the contingent role that chatbot sales–service ambidexterity can play in adapting to customers' personalization–privacy paradox.Design/methodology/approachAn online survey of artificial intelligence chatbots users was conducted, and a mixed-methods research design involving response surface analysis and polynomial regression was adopted to address the research aim.FindingsThe results of polynomial regressions on survey data from 507 online customers indicated that as the benefits of personalization decreased and the risk to privacy increased, the inherently negative (positive) effects of imbalanced (combined) chatbots' sales–service ambidexterity had an increasing (decreasing) influence on customer experience. Furthermore, customer experience fully mediated the association of chatbots' sales–service ambidexterity with customer patronage.Originality/valueFirst, this study enriches the literature on frontline ambidexterity and extends it to the setting of human–machine interaction. Second, the study contributes to the literature on the personalization–privacy paradox by demonstrating the importance of frontline ambidexterity for adapting to customer concerns. Third, the study examines the conduit between artificial intelligence (AI) chatbots' ambidexterity and sales performance, thereby helping to reconcile the previously inconsistent evidence regarding this relationship.

Synchronous Physiological Electrical Fields

2016 ◽  
pp. 107-127
Author(s):  
J.F. Pagel
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Processing ◽  
Current Knowledge ◽  
Human Machine Interaction ◽  
Similar Frequency ◽  
Electrical Fields ◽  
Electrical Potentials ◽  
Interface Potential ◽  
External Stimuli ◽  
Machine Interaction

Humans utilize sensory and motor systems developed genetically, physically and socially for interfacing with our external environment. We use these same systems to interface in our interactions with artificial intelligence. There are other functioning central nervous system (CNS) systems, however, involved in cognitive processing for which the function and environmental interface is less clear. The synchronous physiologic electrical field system utilizes broadcast extracellular electrical fields for a wide variety of CNS functions. The operations of this system are usually non-conscious and most apparent during sleep (especially the conscious states of sleep that include dreaming), and un-focused waking. The electrical fields of this system are altered and affected by both internal and external stimuli. These fields can be monitored and analyzed by artificial intelligence (AI) systems, and independently of human input, AI systems can utilize similar frequency based electrical potentials to convey data, communicate, supply power, and to store memory. From both human and AI perspectives, these systems have the potential to function more fully in human/machine interaction. This chapter reviews our current knowledge as to function, current interactive approaches, and interface potential for these physiological electrical fields.

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.

Ambient Intelligence Environments

2011 ◽  
pp. 92-98 ◽  
Author(s):  
Carlos Ramos
Keyword(s):  
Artificial Intelligence ◽  
Embedded Systems ◽  
Ambient Intelligence ◽  
New World ◽  
Physical World ◽  
Human Being ◽  
Human Machine Interaction ◽  
Artificial Intelligence Research ◽  
Essential Knowledge ◽  
Machine Interaction

The trend in the direction of hardware cost reduction and miniaturization allows including computing devices in several objects and environments (embedded systems). Ambient Intelligence (AmI) deals with a new world where computing devices are spread everywhere (ubiquity), allowing the human being to interact in physical world environments in an intelligent and unobtrusive way. These environments should be aware of the needs of people, customizing requirements and forecasting behaviours. AmI environments may be so diverse, such as homes, offices, meeting rooms, schools, hospitals, control centers, transports, touristic attractions, stores, sport installations, and music devices. Ambient Intelligence involves many different disciplines, like automation (sensors, control, and actuators), human-machine interaction and computer graphics, communication, ubiquitous computing, embedded systems, and, obviously, Artificial Intelligence. In the aims of Artificial Intelligence, research envisages to include more intelligence in the AmI environments, allowing a better support to the human being and the access to the essential knowledge to make better decisions when interacting with these environments

An intelligent interface for online interaction

1984 ◽  
Vol 9 (1) ◽  
pp. 7-18 ◽  
Author(s):  
A. Vickery
Keyword(s):  
Artificial Intelligence ◽  
Online Interaction ◽  
Search System ◽  
Human Machine Interaction ◽  
Retrieval Systems ◽  
Intelligent Interface ◽  
Machine Interaction

In this paper, the author discusses the ways of improving the performance of online retrieval systems by introducing an automated interface between the enquirer and the system. In the first part of the paper, the main features of such human/machine interaction and the characteristics that the user would like to see incorporated in an interface, are de scribed. Then, studies in artificial intelligence that are particu larly relevant to the problems of implementing an intelligent interface, are discussed. The author concludes with a summary of automated mechanisms that will be needed to improve the quality of interaction between the user and the search system.

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