Artificial Intelligence and Risk in Design

Abstract

As artificial intelligence (AI) technologies are more and more integrated into everyday lives, both scholarly and popular discourses on AI's often revolve around charting the various risks that may be associated with them. The manner and magnitude of risk that various researchers identify and foresee varies; however, what is common between them is, undoubtedly, the concept of risk itself. This concept, we argue, has been largely taken for granted by the fields involved in the research on AI's; in other words, "risk" has been employed with an everyday sensibility without due critical examination. In this paper, we address risk as a concept directly, by examining interdisciplinary theories and literatures on risk to discuss examples of AI technologies. Through this work, we aim to begin a critical discussion of the importance of theorising risk within design research and practice, and within the development of emerging technologies.

Urban AI: understanding the emerging role of artificial intelligence in smart cities

“…Urban technologies in general turn these localities into hybrid places (de Souza e Silva 2006), where urban experiences and governance are digitally augmented and mediated (Aurigi and DeCindio 2008). Furthermore, we can understand these hybrid cities also as landscapes for producing and harvesting big data (Luusua and Ylipulli 2020a;Ylipulli and Luusua 2019;Zuboff 2020), serving as a part of business-driven smart city planning agendas .…”

Research agenda for algorithmic fairness studies: Access to justice lessons for interdisciplinary research

“…To put it concretely, discrimination of certain types of individuals seeking justice is an age-old structural problem that is renewed and reinterpreted in algorithmisation. The potential of algorithmic systems to amplify existing societal biases should also be seen as a structural problem (e.g., Luusua and Ylipulli, 2020 ). Here we see a blatant similarity between studies of access to justice and algorithmic fairness.…”

“…An avenue of legal research to algorithmisation deals with the role and value reserved for the human decision maker. This is a strand distinct from human replaceability (Pasquale, 2020 ) and from uncertainty and the risk inherent in both (AI) design as well as human decision-making and experience (Luusua and Ylipulli, 2020 ). The dilemma is two-pronged.…”

Nordic Cities Meet Artificial Intelligence

“…This worried E1; however, he also reflected on whether it was unethical to not use the health data if human suffering can be alleviated. While on the surface this seems like a reasonable and ethical proposition, it can also be contested; in our previous work, we have also reflected on the question of how far societies should be willing to go in order to remove risk, and consequently, suffering, from human lives with technology [38]. While such a topic is outside the scope of this paper, overall, we interpret from our discussions that the introduction of AI had taken the officials into a place of forced ethical problem-solving that was very convoluted, difficult and, to some extent, perhaps outside of their job descriptions.…”

“…Thus, we can hypothesize that both the hype and the real potential of these technologies as applied to urban settings is increasing. There is much to be done here, and a singular case study can only touch the surface of this novel research theme, which we can refer to as 'urban AI' [37,38]. However, we deem it important to begin to study this phenomenon empirically, and from multidisciplinary perspectives.…”