Responsible living labs: what can go wrong?Habibipour, Abdolrasoul
2024 Journal of Information Communication and Ethics in Society
doi: 10.1108/jices-11-2023-0137
This study aims to investigate how living lab (LL) activities align with responsible research and innovation (RRI) principles, particularly in artificial intelligence (AI)-driven digital transformation (DT) processes. The study seeks to define a framework termed “responsible living lab” (RLL), emphasizing transparency, stakeholder engagement, ethics and sustainability. This emerging issue paper also proposes several directions for future researchers in the field.Design/methodology/approachThe research methodology involved a literature review complemented by insights from a workshop on defining RLLs. The literature review followed a concept-centric approach, searching key journals and conferences, yielding 32 relevant articles. Backward and forward citation analysis added 19 more articles. The workshop, conducted in the context of UrbanTestbeds.JR and SynAir-G projects, used a reverse brainstorming approach to explore potential ethical and responsible issues in LL activities. In total, 13 experts engaged in collaborative discussions, highlighting insights into AI’s role in promoting RRI within LL activities. The workshop facilitated knowledge sharing and a deeper understanding of RLL, particularly in the context of DT and AI.FindingsThis emerging issue paper highlights ethical considerations in LL activities, emphasizing user voluntariness, user interests and unintended participation. AI in DT introduces challenges like bias, transparency and digital divide, necessitating responsible practices. Workshop insights underscore challenges: AI bias, data privacy and transparency; opportunities: inclusive decision-making and efficient innovation. The synthesis defines RLLs as frameworks ensuring transparency, stakeholder engagement, ethical considerations and sustainability in AI-driven DT within LLs. RLLs aim to align DT with ethical values, fostering inclusivity, responsible resource use and human rights protection.Originality/valueThe proposed definition of RLL introduces a framework prioritizing transparency, stakeholder engagement, ethics and sustainability in LL activities, particularly those involving AI for DT. This definition aligns LL practices with RRI, addressing ethical implications of AI. The value of RLL lies in promoting inclusive and sustainable innovation, prioritizing stakeholder needs, fostering collaboration and ensuring environmental and social responsibility throughout LL activities. This concept serves as a foundational step toward a more responsible and sustainable LL approach in the era of AI-driven technologies.
The ChatGPT dilemma: unravelling teachers’ perspectives on inhibiting and motivating factors for adoption of ChatGPTBhaskar, Preeti; Rana, Shikha
2024 Journal of Information Communication and Ethics in Society
doi: 10.1108/jices-11-2023-0139
This study aims to address the existing knowledge gap by investigating teachers’ adoption of ChatGPT for educational purposes. The study specifically focuses on identifying the factors that motivate and inhibit teachers in adoption of ChatGPT in higher education institutions (HEIs).Design/methodology/approachThis research has used interpretative phenomenological analysis – a qualitative approach. Through in-depth interviews among the teachers, data was collected to identify the motivating and inhibiting factors that impacted teachers’ willingness to adopt ChatGPT. The data was collected from 48 teachers working across HEIs of Uttarakhand region in India.FindingsThe analysis revealed seven themes under motivating factors that encourage teachers to adopt ChatGPT for their educational purposes. These include time factor, tool for competitive edge, learning enhancement tool for students, research facilitator, benefits in educational settings, troubleshooter and easy to use. On the other hand, inhibiting factors comprise five themes, which include technical difficulties, limited features for educational and research purposes, tool for handicapping innovation and creativity, lack of personal touch and ethical considerations.Practical implicationsThe findings will be valuable for HEIs in establishing policies that promote the appropriate and effective use of ChatGPT. Moreover, the study provides recommendations to ChatGPT solution providers for improving ChatGPT services for effective adoption of ChatGPT among teachers and implementation at HEIs. Further, it contributes to the body of literature by filling a knowledge gap about teacher adoption of ChatGPT in the HEIs. Through qualitative research, the study has pinpointed specific motivating and inhibiting factors that affect teacher adoption of ChatGPT.Originality/valueUnlike previous studies that primarily explored the potential advantages and drawbacks of ChatGPT in education, this research study delves deeper into the topic. It makes a substantial contribution to our understanding of ChatGPT adoption among teachers by identifying distinct factors that either motivate or inhibit teachers from adopting ChatGPT for job related purposes. The study provides novel insights that were previously mislaid, thereby introducing a fresh perspective to the existing literature
Rumours. Who believes them?Zhu, Runping; Liu, Qilin; Krever, Richard
2024 Journal of Information Communication and Ethics in Society
doi: 10.1108/jices-08-2023-0116
While psychology, sociology and communications studies hypothesise a range of independent variables that might impact on individuals’ acceptance or rejection of rumours, almost all studies of the phenomenon have taken place in environments featuring notable, and sometimes very deep, partisan divisions, making it almost impossible to isolate the impact of partisan influences on views on different rumour subjects. This study aims to remove the possibility of partisan influences on readers of internet rumours by testing the impact of independent demographic variables in China, a one-party state with no overt partisan divisions. The study provides an opportunity to strip away the influence of ideology and see whether this factor may have coloured previous studies on susceptibility to believe rumours.Design/methodology/approachAn empirical study was used to examine belief in false and true online rumours in a non-partisan environment. A large sample group was presented with rumours across four subject areas and respondents’ conclusions and demographic information was then subject to logistic regression analysis to identify relationships between factors and ability to identify the veracity of online rumours.FindingsUnexpectedly, the regression analysis revealed no statistically significant nexus between many independent demographic variables and patterns of believing or disbelieving rumours. In other cases, a statistically significant relationship was revealed, but only to a limited degree. The results suggest that once the role of partisanship in explaining the proliferation of and belief in false rumours and the ability to identify true ones is removed from consideration, no other independent variables enjoy convincing links with rumour belief.Originality/valueThe study tests in China, a jurisdiction featuring a non-partisan environment, the impact of independent variables on media users’ belief in a wide range of rumours.
Understanding public sentiments and misbeliefs about Sustainable Development Goals: a sentiment and topic modeling analysisVerma, Abhinav; Nayak, Jogendra Kumar
2024 Journal of Information Communication and Ethics in Society
doi: 10.1108/jices-05-2023-0073
Misinformation surrounding the Sustainable Development Goals (SDGs) has contributed to the formation of misbeliefs among the public. The purpose of this paper is to investigate public sentiment and misbeliefs about the SDGs on the YouTube platform.Design/methodology/approachThe authors extracted 8,016 comments from YouTube videos associated with SDGs. The authors used a pre-trained Python library NRC lexicon for sentiment and emotion analysis, and to extract latent topics, the authors used BERTopic for topic modeling.FindingsThe authors found eight emotions, with negativity outweighing positivity, in the comment section. In addition, the authors identified the top 20 topics discussing various SDGs and SDG-related misbeliefs.Practical implicationsThe authors reported topics related to public misbeliefs about SDGs and associated keywords. These keywords can be used to formulate social media content moderation strategies to screen out content that creates these misbeliefs. The result of hierarchical clustering can be used to devise and optimize response strategies by governments and policymakers to counter public misbeliefs.Originality/valueThis study represents an initial endeavor to gain a deeper understanding of the public’s misbeliefs regarding SDGs. The authors identified novel misbeliefs about SDGs that previous literature has not studied. Furthermore, the authors introduce an algorithm BERTopic for topic modeling that leverages transformer architecture for context-aware topic modeling.
Unmasking user vulnerability: investigating the barriers to overcoming dark patterns in e-commerce using TISM and MICMAC analysisSingh, Vibhav; Vishvakarma, Niraj Kumar; Kumar, Vinod
2024 Journal of Information Communication and Ethics in Society
doi: 10.1108/jices-10-2023-0127
E-commerce companies use dark patterns to manipulate customer decisions to survive in the crowded online market and make profit. Although some online customers are aware of the dark patterns, they cannot overcome such manipulations. Therefore, the purpose of this study is to identify and model the barriers to overcoming dark patterns using total interpretive structural modeling (TISM).Design/methodology/approachBarriers to overcoming dark patterns were identified from the extant literature and were validated by a panel of 18 domain experts. In the modeling phase, TISM technique was used to identify the relationships between the barriers and assign priority to the barriers. Finally, the barriers were plotted and classified into three categories.FindingsUser unawareness, trust in brands and normalization of aggressive marketing were found to be the highest priority barriers. Whereas, designer bias, user fatigue, short-term user benefits and design complexity were identified as the most challenging barriers because they have least dependence over the other barriers.Research limitations/implicationsBecause TISM results are based on the opinion of domain experts, other statistical techniques could be applied for validation.Practical implicationsThis study would educate online customers, while assisting online user communities and regulatory bodies to devise strategies to overcome dark patterns. Additionally, business managers could use the study’s findings to encourage designers to embrace ethical design methods as a competitive advantage.Originality/valueThis study contributes to the research as it is first of its kind to examine the link between dark pattern barriers.