Search results

Role-taking is a basic social process underpinning much of the structural social psychology paradigm – a paradigm built on empirical studies of human interaction. Yet today, our social worlds are occupied by bots, voice assistants, decision aids, and other machinic entities collectively referred to as artificial intelligence (AI). The integration of AI into daily life presents both challenges and opportunities for social psychologists. Through a vignette study, the authors investigate role-taking and gender in human-AI relations.

Participants read a first-person narrative attributed to either a human or AI, with varied gender presentation based on a feminine or masculine first name. Participants then infer the narrator's thoughts and feelings and report on their own emotions, producing indicators of cognitive and affective role-taking. The authors supplement results with qualitative analysis from two open-ended survey questions.

Participants score higher on role-taking measures when the narrator is human versus AI. However, gender dynamics differ between human and AI conditions. When the text is attributed to a human, masculinized narrators elicit stronger role-taking responses than their feminized counterparts, and women participants score higher on role-taking measures than men. This aligns with prior research on gender, status, and role-taking variation. When the text is attributed to an AI, results deviate from established findings and in some cases, reverse.

This first study of human-AI role-taking tests the scope of key theoretical tenets and sets a foundation for addressing group processes in a newly emergent form.

From labor conditions to public health and environmental justice, globalization has created an increasingly complex web of issues surrounding human rights. Research in social studies education points to adolescents’ intrinsic curiosity when engaged in these multiple issues, as well as their idealistic thirst for involving themselves in social progress campaigns. Many students desire involvement and believe in the importance of human rights education within the formal educational setting, especially within social studies curriculum. We report the findings from a qualitative study conducted during a two-week intensive summer institute on human rights and genocide studies in western New York in the summer of 2011. In our study, we found while student participants felt empowered by the institute and their desire to take action was heightened during the experience, they questioned the disconnect between the genocide and human rights education in the Institute and the human rights education they experienced in their social studies classrooms. In comparing the two, they wished there were more authentic learning experiences and a higher level of academic rigor in their social studies classes. Although the New York State curricula, at the time of the study, included human rights education related topics, the interviewed student participants did not recognize its presence and felt human rights education is not a prevalent part of the enacted public school curriculum.

This study aims to explore the implementation of artificial intelligence (AI) into recruitment by considering its potential to maximise the effectiveness of the human resources (HR) processes, challenges associated with the implementation and ethical concerns.

A qualitative research approach was used to reach the stated objectives within the context of the small open economy – the Czech Republic. Interviews were conducted with four participants, Czech-based recruiters, each with five or more years of experience in their field. The interviews were conducted in Autumn 2023 within the online platform. The answers were transcribed and thematically analysed.

The participants who were interviewed heavily emphasised the importance of the role of the human factor in recruitment, yet several observations and insights were obtained. In particular, some interviewees indicated a possible usage of a chatbot for the first round of the candidates' selection, but they see it as problematic in the final decision on the position fulfilment, where the human factor is not replaceable so far. The key ethical challenges of the broader implementation of AI in the recruitment practices of the respondents remain the risks regarding privacy and data protection, especially the General Data Protection Regulation (GDPR) legislation.

This article delivers pertinent insights for recruiters on using AI in recruitment, bringing forth a more subtle understanding of the faceted subject of AI-based recruitment.

Human lab experiments have become an established method in information systems research for investigating user behavior, perception and even neurophysiology. The purpose of this paper is to facilitate experimental research by providing a practical guide on how to implement and conduct lab experiments in the freely available experimental platform Brownie.

Laying the groundwork of the tutorial, the paper first provides a brief overview of common design considerations for lab experiments and a generic session framework. Building on the use case of the widely used trust game, the paper then covers the different stages involved in running an experimental session and maps the conceptual elements of the study design to the implementation of the experimental software.

The paper generates findings on how computerized lab experiments can be designed and implemented. Furthermore, it maps out the design considerations an experimenter may take into account when implementing an experiment and organizing it along a session structure (e.g. participant instructions, individual and group interaction, state and trait questionnaires).

The paper reduces barriers for researchers to engage in experiment implementation and replication by providing a step-by-step tutorial for the design and implementation of human lab experiments.

The purpose of this paper is to make a case for the political use of methods to shape posthumanist futures that are for animals. It makes this case by drawing on findings from qualitative research on the lived experience of navigating human–pet relationships.

The argument in this paper draws on qualitative data from interviews and observations with human participants and “their” companion animals to demonstrate that centring animals in research highlights new data and encourages participants to challenge anthropocentric narratives of pet relationships.

The findings of this project indicate that using animal-inclusive research methods is effective in centring non-human animals in discussions and providing new insights into human–animal relations that can inform and move towards critical posthumanist futures.

If the central argument that methods play an important role in shaping social worlds is accepted then human–animal studies scholars may need to think more carefully about how they design, conduct and frame research with non-human animals.

If the argument for centring companion animals in research is taken seriously, then those working with humans and companion animals in the community might significantly alter their methods to more meaningfully engage with non-human animals' experiences.

Current research has concerned itself with the challenge of how to understand animals' experiences through research. There has been little consideration of how multi-species research reflects and shapes social worlds and how methods might be considered a fruitful site of transforming relations and pursuing posthumanist futures.

In the USA, 22–40% of youth who have been accepted to college do not enroll. Researchers call this phenomenon summer melt, which disproportionately affects students from disadvantaged backgrounds. A major challenge is providing enough mentorship with the limited number of available college counselors. The purpose of this study is to present a case study of a design and user study of a chatbot (Lilo), designed to provide college advising interactions.

This study adopted four primary data sources to capture aspects of user experience: daily diary entries; in-depth, semi-structured interviews; user logs of interactions with the chatbot; and daily user surveys. User study was conducted with nine participants who represent a range of college experiences.

Participants illuminated the types of interactions designs that would be particularly impactful for chatbots for college advising including setting reminders, brokering social connections and prompting deeper introspection that build efficacy and identity toward college-going.

As a growing body of human-computer interaction research delves into the design of chatbots for different social interactions, this study illuminates key design needs for continued work in this domain. The study explores the implications for a specific domain to improve college enrollment: providing college advising to youth.

Digitally driven virtual streamers are increasingly utilized in live-streaming commerce, possessing distinct advantages compared to human streamers. However, the applicable scenarios of virtual streamers are still unclear. Focusing on product attribute variances, this paper compares the livestreaming effects of virtual and human streamers to clarify the applicable scenarios for each and assist companies in strategically choosing suitable streamers.

We conducted four experiments utilizing both images and video as stimulus materials, and each experiment employed different products. To test the proposed model, a total of 1,068 valid participants were recruited, encompassing a diverse group of individuals, including undergraduates and employed workers.

The results indicate no significant difference between virtual and human streamers in increasing consumers’ purchase intention for utilitarian products. In contrast, human streamers are more effective in enhancing consumer purchase intention for hedonic products, with a mediating role of mental imagery quality. Consumers’ implicit personality variances also influence their willingness to accept virtual streamers.

This paper is the first to compare the effects of virtual and human streamers in promoting different products to enhance our comprehension of virtual streamers. Given the potential risks associated with human streamers, a comprehensive understanding of the role of virtual streamers is imperative for brands when deploying live-streaming commerce activities.

This study investigates the level of artificial intelligence (AI) awareness among library leaders, practitioners and scientists of Indonesian academic libraries to elucidate the benefits of AI implementation and its necessary infrastructure and challenges.

The study adopted a purposive sampling technique to select the 38 participants and thematic analysis to analyze the data, identifying eight themes: understanding of AI, AI adoption, benefits of AI, competencies needed to support AI, facilities to support AI, factors supporting AI adoption, AI-inhibiting factors and expectations of AI.

Different viewpoints provided full awareness among library stakeholders and sufficient information to begin AI initiatives in Indonesian libraries as leaders, practitioners and scientists had a favorable, open and encouraging outlook on AI.

The study does not investigate variations in perspectives between the participants, but it examines their understanding of AI and elaborates the results into the concept of an intelligent library. Moreover, this study only uses samples from academic libraries.

Libraries can take these results into consideration before implementing AI, especially in technology and facilities, librarian competency with regard to AI and leadership roles in AI projects.

Library boards and library associations can use this research as a source to create guidelines about AI implementation in academic libraries.

The study addresses the gap in the research on university libraries' readiness and awareness to implement AI, especially in developing countries.

The purpose of this study is to explore the process of initial sensemaking that organizational members activate when they reflect on AI adoption in their work settings, and how the perceived features of AI technologies trigger sensemaking processes which in turn have the potential to influence workplace learning modes and trajectories.

We adopted an explorative qualitative and interactive approach to capture free fantasies and imaginative ideas of AI among people within the industry. We adopt a conceptual perspective that combines theories on initial sensemaking and workplace learning as a theoretical lens to analyze data collected during 23 focus groups held at four large Swedish manufacturing companies. The data were analyzed using the Gioia method.

Two aggregated dimensions were defined and led to the development of an integrated conceptualization of the initial sensemaking of AI technology adoption. Specifically, sensemaking triggered by abstract features of AI technology mainly pointed to an exploitative learning path. Sensemaking triggered by concrete features of the technology mainly pointed to explorative paths, where socio-technical processes appear to be crucial in the process of AI adoption.

This is one of the first studies that attempts to explore and conceptualize how organizations make sense of prospective workplace learning in the context of AI adoption.

This paper tracks the network of actors participating in the initial implementation of a “Lean management” system, in order to identify associations between human and non-human participants conducive to successful adoption of the system.

The perspective of actor–network theory (ANT) helps reveal the complex dynamics at play in a “Lean” intervention at a manufacturing firm. It allows to identify key actors (human and non-human), as well as the possible associations between them, and helps produce network diagrams to track the changes in actors' roles and in network coherence over time.

Through a network analysis, the study charts the complexity of the process of Lean intervention, by accounting for the distinct possibility that actors' roles may shift over time, as they engage and disengage with the proposed intervention, until they fully cohere into a new system. Based on this, it derives a conceptual model to describe relevant factors for successful implementation of Lean improvement projects.

The ANT perspective affords new insights into Lean Management systems implementation, by highlighting associations between human and non–human actors. This novel focus suggests corresponding management guidelines and reflective practices for successful intervention.