Advancing the Understanding of the Role of Responsible AI in the Continued Use of IoMT in Healthcare

2023 | Information Systems Frontiers | Citations: 1

Authors: Al-Dhaen, Fatema; Hou, Jiachen; Rana, Nripendra P.; Weerakkody, Vishanth

Abstract: This paper examines the continuous intention by healthcare professionals to use ... Expand

Abstract: This paper examines the continuous intention by healthcare professionals to use the Internet of Medical Things (IoMT) in combination with responsible artificial intelligence (AI). Using the theory of Diffusion of Innovation (DOI), a model was developed to determine the continuous intention to use IoMT taking into account the risks and complexity involved in using AI. Data was gathered from 276 healthcare professionals through a survey questionnaire across hospitals in Bahrain. Empirical outcomes reveal nine significant relationships amongst the constructs. The findings show that despite contradictions associated with AI, continuous intention to use behaviour can be predicted during the diffusion of IoMT. This study advances the understanding of the role of responsible AI in the continued use of IoMT in healthcare and extends DOI to address the diffusion of two innovations concurrently. Collapse

Topics: usage intention artificial intelligence responsible artificial intelligence innovation management online learning system

Methods: SEM tool survey descriptive statistic structural equation modeling survey design

Risk and the future of AI: Algorithmic bias, data colonialism, and marginalization

2023 | Information and Organization | Citations: 0

Authors: Arora, A.; Barrett, M.; Lee, E.; Oborn, E.; Prince, K.

Abstract: ... Expand

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Topics: artificial intelligence algorithmic bias responsible artificial intelligence legal context outsourcing

Methods: computational algorithm design methodology generative adversarial network

Match Made by Humans: A Critical Enquiry into Human-Machine Configurations in Data Labelling

2023 | HICSS | Citations: 0

Authors: Chandhiramowuli, S.; Chaudhuri, B.

Abstract: We present a critical ethnographic study of data labelling conducted in a Banga ... Expand

Abstract: We present a critical ethnographic study of data labelling conducted in a Bangalore-based AI start-up. Labelled datasets are primarily produced by human data workers. We explore how humans and machines are configured together in data labelling and what are the demands placed on human workers, including on their body and cognition, while being assigned in the service of machine intelligence. We also show how these human-machine configurations sustain and reproduce the seamless functioning of apparently "autonomous" AI as a normative vision. Though labelled datasets are an indispensable prerequisite to creating ML/AI-based systems, the human labour that produces these datasets cannot be acknowledged fully if the techno-entrepreneurial vision of "self-learning" machine intelligence is to be celebrated and sustained. In pursuit of a normative position of what AI should be, we are left with a denial of how AI is actually produced now. Collapse

Topics: artificial intelligence price management organization structure outsourcing crowdsourcing

Methods: qualitative interview ethnography participant observation personal interview grounded theory

Theories: sociotechnical systems theory

Prototyping AI-Powered Social Innovation in an Undergraduate MIS course

2023 | International Conference on Information Systems | Citations: 0

Authors: Chen, Yu; Albert, Leslie; Macias, Heather

Abstract: While implementing with caution, Artificial Intelligence (AI) holds potential t ... Expand

Abstract: While implementing with caution, Artificial Intelligence (AI) holds potential to help nations address pressing social issues, such as homelessness, climate change, and healthcare accessibility. With the existing and potential economic and social benefits of AI, it is crucial to integrate AI learning in undergraduate education. This paper presents the preliminary findings of a course project that engages students to learn AI by prototyping solutions to address important social issues in their communities among 120 undergraduate MIS students. Students worked in groups and developed chatbots that addressed a variety of community issues during . A survey study shows students' enhanced understanding and mastery of AI concepts and applications, empowerment of contributing to their communities through AI innovation, and an emerging awareness of diversity, equity, and ethical issues in the community and AI technologies. We conclude with implications of learning AI, innovation, and ethics through the lens of AI for social good. Collapse

Topics: artificial intelligence design thinking societal evaluation criteria innovation management responsible artificial intelligence

Methods: design methodology survey chatbot personal interview design artifact

Pro or Con? Introducing AI Ethics Debates in an Undergraduate MIS Course

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Chen, Yu; Jensen, Scott; Roldan, Malu; Harper, Shannon

Abstract: Artificial intelligence (AI) is becoming pervasive across industries, making it ... Expand

Abstract: Artificial intelligence (AI) is becoming pervasive across industries, making it important for management information systems (MIS) students to understand the ethical issues involved. We present an active learning approach to teaching the fast-changing topic of AI ethics using a debate format. This approach was piloted in an undergraduate MIS course of 30 students. Over a five-week period, student teams were assigned to argue either the opportunities (pro) or dangers (con) viewpoint for five different AI technologies. A post-project survey indicated this format helps students gain a better understanding of the applications, opportunities, and potential misuse of AI. Students found this to be an engaging and fun way to explore the multiple dimensions of AI ethics that also required them to employ critical thinking, collaboration, research, and communication skills. We share our findings about the benefits of co-creating knowledge in the classroom using a debate format to explore an evolving topic. Collapse

Topics: responsible artificial intelligence artificial intelligence innovation management digital innovation robotic

Methods: survey personal interview image processing design methodology

Exploring the Darkverse: A Multi-Perspective Analysis of the Negative Societal Impacts of the Metaverse

2023 | Information Systems Frontiers | Citations: 0

Authors: Dwivedi, Yogesh K.; Kshetri, Nir; Hughes, Laurie; Rana, Nripendra P.; Baabdullah, Abdullah M.; Kar, Arpan Kumar; Koohang, Alex; Ribeiro-Navarrete, Samuel; Belei, Nina; Balakrishnan, Janarthanan; Basu, Sriparna; Behl, Abhishek; Davies, Gareth H.; Dutot, Vincent; Dwivedi, Rohita; Evans, Leighton; Felix, Reto; Foster-Fletcher, Richard; Giannakis, Mihalis; Gupta, Ashish; Hinsch, Chris; Jain, Animesh; Jane Patel, Nina; Jung, Timothy; Juneja, Satinder; Kamran, Qeis; Mohamed AB, Sanjar; Pandey, Neeraj; Papagiannidis, Savvas; Raman, Ramakrishnan; Rauschnabel, Philipp A.; Tak, Preeti; Taylor, Alexandra; tom Dieck, M. Claudia; Viglia, Giampaolo; Wang, Yichuan; Yan, Meiyi

Abstract: The Metaverse has the potential to form the next pervasive computing archetype t ... Expand

Abstract: The Metaverse has the potential to form the next pervasive computing archetype that can transform many aspects of work and life at a societal level. Despite the many forecasted benefits from the metaverse, its negative outcomes have remained relatively unexplored with the majority of views grounded on logical thoughts derived from prior data points linked with similar technologies, somewhat lacking academic and expert perspective. This study responds to the dark side perspectives through informed and multifaceted narratives provided by invited leading academics and experts from diverse disciplinary backgrounds. The metaverse dark side perspectives covered include: technological and consumer vulnerability, privacy, and diminished reality, human–computer interface, identity theft, invasive advertising, misinformation, propaganda, phishing, financial crimes, terrorist activities, abuse, pornography, social inclusion, mental health, sexual harassment and metaverse-triggered unintended consequences. The paper concludes with a synthesis of common themes, formulating propositions, and presenting implications for practice and policy. Collapse

Topics: virtual reality privacy unintended consequence artificial intelligence IT security

Methods: digital trace data computational algorithm design guideline synthesis ethnography

An Action Design Research Study on Responsible Innovation Teaching and Training for Information Systems Students

2023 | Communications of the Association for Information Systems | Citations: 0

Authors: El Idrissi, Sarah Cherki; Corbett, Jacqueline; Mellouli, Sehl

Abstract: While information systems organizations recognize the importance of incorporati ... Expand

Abstract: While information systems organizations recognize the importance of incorporating responsible innovation into their activities, they often face difficulty implementing this practice because employees lack the required knowledge and skills, particularly the capacity for reflexivity and reflection. This paper aims to accelerate responsible innovation teaching and training for information systems students to expedite the process of positive change for sustainability. Using the action design research methodology and the responsible innovation lens, we developed a workshop enabling information systems students to form measurable reflection skills. The workshop evaluation suggests that learning took place and that students are willing to adopt responsible innovation in their future workplaces. A set of design guidelines is proposed to guide further training programs to enhance students' ability to address complex challenges responsibly. This paper answers the call for more impactful information systems research to address societal and environmental challenges and enriches the literature on sustainable social development and business practices. Collapse

Topics: innovation management task complexity personality responsible artificial intelligence digital innovation

Methods: design guideline qualitative interview action design research design science qualitative coding

Is There a Place for Responsible Artificial Intelligence in Pandemics? A Tale of Two Countries

2023 | Information Systems Frontiers | Citations: 0

Authors: El-Haddadeh, Ramzi; Fadlalla, Adam; Hindi, Nitham M.

Abstract: This research examines the considerations of responsible Artificial Intelligence ... Expand

Abstract: This research examines the considerations of responsible Artificial Intelligence in the deployment of AI-based COVID-19 digital proximity tracking and tracing applications in two countries; the State of Qatar and the United Kingdom. Based on the alignment level analysis with the Good AI Society’s framework and sentiment analysis of official tweets, the diagnostic analysis resulted in contrastive findings for the two applications. While the application EHTERAZ (Arabic for precaution) in Qatar has fallen short in adhering to the responsible AI requirements, it has contributed significantly to controlling the pandemic. On the other hand, the UK’s NHS COVID-19 application has exhibited limited success in fighting the virus despite relatively abiding by these requirements. This underlines the need for obtaining a practical and contextual view for a comprehensive discourse on responsible AI in healthcare. Thereby offering necessary guidance for striking a balance between responsible AI requirements and managing pressures towards fighting the pandemic. Collapse

Topics: Twitter responsible artificial intelligence mobile application artificial intelligence pandemic

Methods: sentiment analysis qualitative content analysis synthesis

Responsible Artificial Intelligence as a Secret Ingredient for Digital Health: Bibliometric Analysis, Insights, and Research Directions

2023 | Information Systems Frontiers | Citations: 0

Authors: Fosso Wamba, Samuel; Queiroz, Maciel M.

Abstract: With the unparallel advance of leading-edge technologies like artificial intelli ... Expand

Abstract: With the unparallel advance of leading-edge technologies like artificial intelligence (AI), the healthcare systems are transforming and shifting for more digital health. In recent years, scientific productions have reached unprecedented levels. However, a holistic view of how AI is being used for digital health remains scarce. Besides, there is a considerable lack of studies on responsible AI and ethical issues that identify and suggest practitioners’ essential insights towards the digital health domain. Therefore, we aim to rely on a bibliometric approach to explore the dynamics of the interplay between AI and digital health approaches, considering the responsible AI and ethical aspects of scientific production over the years. We found four distinct periods in the publication dynamics and the most popular approaches of AI in the healthcare field. Also, we highlighted the main trends and insightful directions for scholars and practitioners. In terms of contributions, this work provides a framework integrating AI technologies approaches and applications while discussing several barriers and benefits of AI-based health. In addition, five insightful propositions emerged as a result of the main findings. Thus, this study’s originality is regarding the new framework and the propositions considering responsible AI and ethical issues on digital health. Collapse

Topics: health information system artificial intelligence responsible artificial intelligence robotic big data

Methods: bibliometric analysis deep learning machine learning literature sample literature study

Design, Development, and Implementation of Artificial Intelligence Technology: A Scoping Review

2023 | European Conference On Information Systems | Citations: 0

Authors: Grashoff, Imke; Recker, Jan

Abstract: Research on artificial intelligence technology has not only increased rapidly o ... Expand

Abstract: Research on artificial intelligence technology has not only increased rapidly over recent years, it is also no longer limited to the technical disciplines from which it originates. AI technologies are also at the center of social and sociotechnical studies including those conducted in information systems. Through a scoping review we explore how the research on different kinds of AI technologies has progressed over the past decade. Particularly, we explore whether the research on AI technologies has been informed by and informs our sociotechnical understanding of phenomena related to their design, development and implementation. For this purpose, we develop an analytical framework that differentiates sociotechnical perspectives, categorizes AI technologies into different kinds, and distinguishes research on AI technology design, development, and implementation. The findings from our review point to several directions for future research. Collapse

Topics: artificial intelligence systems design systems development decision making competitive advantage

Methods: structured literature research literature sample literature study machine learning cross sectional research

Theories: sociotechnical systems theory