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.

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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

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

Taking the Person Seriously: Ethically Aware IS Research in the Era of Reinforcement Learning-Based Personalization

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

Authors: Greene, Travis; Shmueli, Galit; Ray, Soumya

Abstract: Advances in reinforcement learning and implicit data collection on large-scale ... Expand

Abstract: Advances in reinforcement learning and implicit data collection on large-scale commercial platforms mark the beginning of a new era of personalization aimed at the adaptive control of human user environments. We present five emergent features of this new paradigm of personalization that endanger persons and societies at scale and analyze their potential to reduce personal autonomy, destabilize social and political systems, and facilitate mass surveillance and social control, among other concerns. We argue that current data protection laws, most notably the European Union's General Data Protection Regulation, are limited in their ability to adequately address many of these issues. Nevertheless, we believe that IS researchers are well-situated to engage with and investigate this new era of personalization. We propose three distinct directions for ethically aware reinforcement learning-based personalization research uniquely suited to the strengths of IS researchers across the sociotechnical spectrum. Collapse

Topics: usability personalization legal context General Data Protection Regulation information privacy law

Methods: reinforcement learning computational algorithm simulation language model experiment

Theories: social sciences theory

Ethical management of human-AI interaction: Theory development review

2023 | Journal of Strategic Information Systems | Citations: 0

Authors: Heyder, Teresa; Passlack, Nina; Posegga, Oliver

Abstract: AI-based technologies have changed the nature of the symbiosis between humans an ... Expand

Abstract: AI-based technologies have changed the nature of the symbiosis between humans and AI, and so strategic management of human-AI interaction in organizations requires deeper ethical consid­ erations. Aligning AI with human values requires a systematic understanding of the ethical management of human-AI interaction. We conduct a theoretical review, from a sociotechnical perspective, and analyze ethical management of human-AI interaction through the lens of soci­ omateriality. Our systematic approach helps explain and clarify the interdependencies between two ethical perspectives – duty and virtue ethics – in sociotechnical systems. We also provide a theoretical framework that leads to seven avenues for future research. Collapse

Topics: human AI collaboration artificial intelligence database system strategic management responsible artificial intelligence

Methods: literature sample theory development literature study synthesis chatGPT

Theories: sociomaterialism theory socio technical theory sociotechnical systems theory

Can you trust me? Using AI to review more than three decades of AI trust literature

2023 | European Conference On Information Systems | Citations: 0

Authors: Knickrehm, Charlotte; Voss, Marleen; Barton, Marie-Christin

Abstract: The ability of artificial intelligence (AI) to take on complex tasks can facili ... Expand

Abstract: The ability of artificial intelligence (AI) to take on complex tasks can facilitate humans' life, but also raise concerns about AI replacing the human workforce. Acceptance and prior trust are prerequisites for successfully using AI. Yet, there is no overview of the research streams that covers the topic of AI trust. We, therefore, analyzed all AI trust literature to this date. We first organized a large number of publications using a topic modeling approach, clustered the results into research streams within AI trust, and built a conceptual framework of human trust in AI. Our analysis yielded 56 topics which we assigned to 11 clusters. Further in-depth analysis of the cluster "human trust" revealed different organizational, AI, and human factors influencing AI trust. Our results contribute to the AI trust literature by reviewing the field, offering a model of human trust in AI using a novel mixed methods approach and uncovering areas for further research. Collapse

Topics: artificial intelligence privacy explainable artificial intelligence usability ergonomics

Methods: topic model cluster analysis literature sample literature study mixed method

From the “rush to ethics” to the “race for governance” in Artificial Intelligence

2023 | Information Systems Frontiers | Citations: 0

Authors: Koniakou, Vasiliki

Abstract: This paper engages with the emerging field of Artificial Intelligence (AI) gover ... Expand

Abstract: This paper engages with the emerging field of Artificial Intelligence (AI) governance wishing to contribute to the relevant literature from three angles grounded in international human rights law, Law and Technology, Science and Technology Studies (STS) and theories of technology. Focusing on the shift from ethics to governance, it offers a bird-eye overview of the developments in AI governance, focusing on the comparison between ethical principles and binding rules for the governance of AI, and critically reviewing the latest regulatory developments. Secondly, focusing on the role of human rights, it takes the argument that human rights offer a more robust and effective framework a step further, arguing for the necessity to extend human rights obligations to also directly apply to private actors in the context of AI governance. Finally, it offers insights for AI governance borrowing from the Internet Governance history and the broader technology governance field. Collapse

Topics: artificial intelligence IT governance disruptive innovation decision making responsible artificial intelligence

Methods: computational algorithm

Co-Shaping an Ecosystem for Responsible AI: Five Types of Expectation Work in Response to a Technological Frame

2023 | Information Systems Frontiers | Citations: 0

Authors: Minkkinen, Matti; Zimmer, Markus Philipp; Mäntymäki, Matti

Abstract: Governing artificial intelligence (AI) requires cooperation, although the collab ... Expand

Abstract: Governing artificial intelligence (AI) requires cooperation, although the collaboration’s form remains unclear. Technological frames provide a theoretical perspective for understanding how actors interpret a technology and act upon its development, use, and governance. However, we know little about how actors shape technological frames. In this paper, we study the shaping of the technological frame of the European ecosystem for responsible AI (RAI). Through an analysis of EU documents, we identified four expectations that constitute the EU’s technological frame for the RAI ecosystem. Moreover, through interviews with RAI actors, we revealed five types of expectation work responding to this frame: reproducing, translating, and extending (congruent expectation work), and scrutinizing and rooting (incongruent expectation work). Furthermore, we conceptualize expectation work as actors’ purposive actions in creating and negotiating expectations. Our study contributes to the literature on technological frames, technology-centered ecosystems, and RAI while also elucidating the dimensions and co-shaping of technological frames. Collapse

Topics: artificial intelligence responsible artificial intelligence Twitter value creation electronic mail

Methods: qualitative interview qualitative content analysis personal interview qualitative coding theory development

Theories: technological frames of reference socio technical theory sociotechnical systems theory