What is new with Artificial Intelligence? Human-agent interactions through the lens of social agency

The introduction of automated systems, and more broadly of Artificial Intelligence (AI), into many domains has profoundly changed the nature of human activity, as well as the subjective experience that agents have of their own actions and their consequences – an experience that is commonly referred to as "sense of agency" (SoA). In this review, we propose to examine the empirical evidence supporting this impact of automation on individuals’ sense of agency, and hence on measures as diverse as operator performance, system explicability and acceptability. Because of some of its key characteristics, AI occupies a special status in the artificial systems landscape. We suggest that this status prompts us to reconsider human-AI interactions in the light of human-human relations. We therefore approach the study of joint actions in human social interactions to deduce what are the key features necessary to develop a reliable SoA in a social context. We suggest that the study of social interactions and the development of SoA in joint actions can help determine the content of relevant explanations to be implemented in AI to make it "explainable". Finally, we propose possible directions to improve human-AI interactions and, in particular, to restore the SoA of human operators, improve their confidence in the decisions made by artificial agents, and increase the acceptability of such agents.

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Supporting Social Interactions In Human-Ai Teams: Profiling Human Teammates From Sparse Data

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/1071181321651354b ◽

2021 ◽

Vol 65 (1) ◽

pp. 665-669

Author(s):

Rhyse Bendell ◽

Jessica Williams ◽

Stephen M. Fiore ◽

Florian Jentsch

Keyword(s):

Artificial Intelligence ◽

Social Cognition ◽

Social Interactions ◽

Team Performance ◽

Intelligent Agents ◽

Social Intelligence ◽

Social Cognitive ◽

Social Cues ◽

Cognitive Mechanisms ◽

Human Agent

Artificial intelligence has been developed to perform all manner of tasks but has not gained capabilities to support social cognition. We suggest that teams comprised of both humans and artificially intelligent agents cannot achieve optimal team performance unless all teammates have the capacity to employ social-cognitive mechanisms. These form the foundation for generating inferences about their counterparts and enable execution of informed, appropriate behaviors. Social intelligence and its utilization are known to be vital components of human-human teaming processes due to their importance in guiding the recognition, interpretation, and use of the signals that humans naturally use to shape their exchanges. Although modern sensors and algorithms could allow AI to observe most social cues, signals, and other indicators, the approximation of human-to-human social interaction -based upon aggregation and modeling of such cues is currently beyond the capacity of potential AI teammates. Partially, this is because humans are notoriously variable. We describe an approach for measuring social-cognitive features to produce the raw information needed to create human agent profiles that can be operated upon by artificial intelligences.

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Towards alignment strategies in human-agent interactions based on measures of lexical repetitions

Language Resources and Evaluation ◽

10.1007/s10579-021-09532-w ◽

2021 ◽

Author(s):

Guillaume Dubuisson Duplessis ◽

Caroline Langlet ◽

Chloé Clavel ◽

Frédéric Landragin

Keyword(s):

Agent Interactions ◽

Human Agent

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Towards Learning ‘Self’ and Emotional Knowledge in Social and Cultural Human-Agent Interactions

Developments in Intelligent Agent Technologies and Multi-Agent Systems ◽

10.4018/978-1-60960-171-3.ch019 ◽

2011 ◽

pp. 305-324

Author(s):

Wan Ching Ho ◽

Kerstin Dautenhahn ◽

Meiyii Lim ◽

Sibylle Enz ◽

Carsten Zoll ◽

...

Keyword(s):

Autonomous Agents ◽

Virtual Learning Environment ◽

Virtual Agents ◽

Cultural Backgrounds ◽

Social Agents ◽

Agent Interactions ◽

Human Agent ◽

The World ◽

Intelligent Virtual Agents ◽

Emotional Knowledge

This article presents research towards the development of a virtual learning environment (VLE) inhabited by intelligent virtual agents (IVAs) and modelling a scenario of inter-cultural interactions. The ultimate aim of this VLE is to allow users to reflect upon and learn about intercultural communication and collaboration. Rather than predefining the interactions among the virtual agents and scripting the possible interactions afforded by this environment, we pursue a bottom-up approach whereby inter-cultural communication emerges from interactions with and among autonomous agents and the user(s). The intelligent virtual agents that are inhabiting this environment are expected to be able to broaden their knowledge about the world and other agents, which may be of different cultural backgrounds, through interactions. This work is part of a collaborative effort within a European research project called eCIRCUS. Specifically, this article focuses on our continuing research concerned with emotional knowledge learning in autobiographic social agents.

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Human agency beliefs influence behaviour during virtual social interactions

10.7287/peerj.preprints.3018v1 ◽

2017 ◽

Cited By ~ 1

Author(s):

Nathan Caruana ◽

Dean Spirou ◽

Jon Brock

Keyword(s):

Social Interactions ◽

Subjective Experience ◽

Eye Contact ◽

Human Agency ◽

Mental States ◽

Human Condition ◽

Human Interaction ◽

Intentional Stance ◽

Agency Beliefs ◽

The Impact

In recent years, with the emergence of relatively inexpensive and accessible virtual reality technologies, it is now possible to deliver compelling and realistic simulations of human-to-human interaction. Neuroimaging studies have shown that, when participants believe they are interacting via a virtual interface with another human agent, they show different patterns of brain activity compared to when they know that their virtual partner is computer-controlled. The suggestion is that users adopt an “intentional stance” by attributing mental states to their virtual partner. However, it remains unclear how beliefs in the agency of a virtual partner influence participants’ behaviour and subjective experience of the interaction. We investigated this issue in the context of a cooperative “joint attention” game in which participants interacted via an eye tracker with a virtual onscreen partner, directing each other’s eye gaze to different screen locations. Half of the participants were correctly informed that their partner was controlled by a computer algorithm (“Computer” condition). The other half were misled into believing that the virtual character was controlled by a second participant in another room (“Human” condition). Those in the “Human” condition were slower to make eye contact with their partner and more likely to try and guide their partner before they had established mutual eye contact than participants in the “Computer” condition. They also responded more rapidly when their partner was guiding them, although the same effect was also found for a control condition in which they responded to an arrow cue. Results confirm the influence of human agency beliefs on behaviour in this virtual social interaction context. They further suggest that researchers and developers attempting to simulate social interactions should consider the impact of agency beliefs on user experience in other social contexts, and their effect on the achievement of the application’s goals.

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Video Meeting Signals: A randomised controlled trial of a technique to improve the experience of video conferencing

10.31234/osf.io/q3sa6 ◽

2021 ◽

Author(s):

Daniel C. Richardson ◽

Miles R. A. Tufft ◽

Mackenzie Clavin ◽

Paul Hills

Keyword(s):

Randomised Controlled Trial ◽

Social Interactions ◽

Personal Experience ◽

Subjective Experience ◽

Video Conferencing ◽

Controlled Trial ◽

Training Session ◽

Socially Isolated ◽

Randomised Controlled ◽

Video Meeting

We found evidence from a randomised controlled trial that a simple set of techniques can improve the experience of online meetings. Video conferencing technology has practical benefits, but psychological costs. It has allowed industry, education and social interactions to continue in some form during the covid-19 lockdowns. But it has left many users feeling fatigued and socially isolated, perhaps becausethe limitations of video conferencing disrupt users’ability to coordinate interactions and foster social affiliation. Video Meeting Signals (VMS™) is a simple technique that uses gestures to overcome some of these limitations. We carried out a randomisedcontrolled trial with over 100 students, in which half underwent a short training session in VMS. All participants rated their subjective experience of two weekly seminars, and transcripts were objectively coded for the valence of language used. Compared to controls, seminar groups with VMS training rated their personal experience, their feelings toward their group, and their perceived learning outcomes as significantly higher. Also, they were more likely to use positive language and less likely to use negative language. While future, pre-registered experiments will explore which aspects of the technique are responsible for these benefits, the current results establish that VMS has great potential to overcome the psychological problems of group video meetings.

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Towards Learning ‘Self' and Emotional Knowledge in Social and Cultural Human-Agent Interactions

Social Computing ◽

10.4018/978-1-60566-984-7.ch039 ◽

2010 ◽

pp. 602-621

Author(s):

Wan Ching Ho ◽

Kerstin Dautenhahn ◽

Meiyii Lim ◽

Sibylle Enz ◽

Carsten Zoll ◽

...

Keyword(s):

Autonomous Agents ◽

Virtual Learning Environment ◽

Virtual Agents ◽

Cultural Backgrounds ◽

Social Agents ◽

Agent Interactions ◽

Human Agent ◽

The World ◽

Intelligent Virtual Agents ◽

Emotional Knowledge

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Artificial intelligence and copyright

Theory and Practice of Intellectual Property ◽

10.33731/22021.236526 ◽

2021 ◽

pp. 15-22

Author(s):

Daryna Prylypko

Keyword(s):

Artificial Intelligence ◽

Computer Program ◽

Key Words ◽

Automatic Generation ◽

The Other ◽

International Level ◽

Human Agent ◽

Foreign Countries ◽

The One ◽

Justice Practice

Key words: copyright, work, artificial intelligence, computer program In the article, the problemsof legislation of Ukraine regarding the issues of copyright on works created due to artificialintelligence were analyzed. Particularly, who is the owner of copyright ofworks created due to artificial intelligence. On the one hand, it could be a developer ofa computer program, from the other hand, it could be a client or an employer. Because,it could happen that there is a situation when robots created something newand original, e.g., how it happened with the project “New Rembrandt”. In this case,computers created a unique portrait of Rembrandt. And here is a question, where isin this portrait original and intellectual works of developers of these computers andprograms. In the contrast, this portrait could be created without people who developedspecial machines, programs, and computers. The article’s author proposes to addinto Ukrainian legislation with following norm: the owner of the copyright createddue to artificial intelligence should be a natural person who uses artificial intelligencefor these purposes within the official relationship or on the basis of a contract. In caseof automatic generation of such work by artificial intelligence, the owner of copyrightshould be the developer.Also, another question arises, particularly, who will be responsible for the damagecaused by the artificial intelligence. As an example, of the solution for this issue Resolution2015/2103 (INL) was given, where is mentioned that human agent could be responsiblefor the caused damage. Because, it is not always a developer is responsiblefor the damage.Also, the legislation and justice practice of foreign countries was explored. Theways of overcoming mentioned problems in legislation of Ukraine were proposed.Such as changing our legislation and giving the exact explanation in who is the ownerof copyright on works created due to artificial intelligence and in which cases this personcould become an owner of the copyright. However, probably, these issues shouldbe resolved at international level regarding globalization.

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Automating intellectual freedom: Artificial intelligence, bias, and the information landscape

IFLA Journal ◽

10.1177/03400352211057145 ◽

2021 ◽

pp. 034003522110571

Author(s):

Catherine Smith

Keyword(s):

Artificial Intelligence ◽

Intellectual Freedom ◽

Digital Information ◽

Personal Freedom ◽

Library Users ◽

Human Operators ◽

Information Landscape ◽

Resource Description

Anxieties over automation and personal freedom are challenging libraries’ role as havens of intellectual freedom. The introduction of artificial intelligence into the resource description process creates an opportunity to reshape the digital information landscape—and loss of trust by library users. Resource description necessarily manipulates a library’s presentation of information, which influences the ways users perceive and interact with that information. Human catalogers inevitably introduce personal and cultural biases into their work, but artificial intelligence may perpetrate biases on a previously unseen scale. The automation of this process may be perceived as a greater threat than the manipulation produced by human operators. Librarians must understand the risks of artificial intelligence and consider what oversight and countermeasures are necessary to mitigate the harm to libraries and their users before ceding resource description to artificial intelligence in place of the “professional considerations” the IFLA Statement on Libraries and Intellectual Freedom calls for in providing access to library materials.

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