Tracing the Legitimacy of Artificial Intelligence – A Media Analysis, 1980-2020

Artificial Intelligence (AI) has received ambivalent evaluations, ranging from AI as a great opportunity and solution to crucial problems of our time to AI as a threat to humanity. For AI technologies to diffuse, they need to gain legitimacy. We trace the legitimacy of AI in society from 1980 to 2020. For our analysis, we rely on 2,543 newspaper articles from The New York Times as a reflection of societal discourse over the legitimacy of AI. Using computer-assisted content analysis, we find a sharp increase in media coverage around the mid-2010s. We find the language used in the articles to be predominantly positive and to show little changes over time. Our analysis also uncovers six highly discussed industries in the context of AI

Privacy Risk Perceptions in the Connected Car Context

Connected car services are rapidly diffusing as they promise to significantly enhance the overall driving experience. Because they rely on the collection and exploitation of car data, however, such services are associated with significant privacy risks. Following guidelines on contextualized theorizing, this paper examines how individuals perceive these risks and how their privacy risk perceptions in turn influence their decision-making, i.e., their willingness to share car data with the car manufacturer or other service providers. We conducted a multi-method study, including interviews and a survey in Germany. We found that individuals’ level of perceived privacy risk is determined by their evaluation of the general likelihood of IS-specific threats and the belief of personal exposure to such threats. Two cognitive factors, need for cognition and institutional trust, are found to moderate the effect that perceived privacy risk has on individuals’ willingness to share car data in exchange for connected car services

Stage-gate and agile development in the digital age: Promises, perils, and boundary conditions

Some artists begin with careful plans, sketches, preliminary drawings and even paintings before settling on one particular direction. Claude Monet, for example, carefully planned and prepared his work to coincide with specific natural light, timing his activity according to when and how daylight touched his canvas (House, 2004). His work was revolutionary: masterpieces such as his famous Impressions, Sunrise and subsequent Water Lilies series were intended to capture the feelings initiated by observation and interpretation; they exceeded the mere recording of scenery details. Other artists seemed to obtain their inspiration internally, beginning with little formal preparation. They approached the canvas experientially. Jackson Pollock adopted this style with his famous drip paintings - action pieces that were acclaimed to show motion, depicting accidents and energy

The Evolution of Privacy Norms: Mapping 35 Years of Technology-Related Privacy Discourse, 1980-2014

Today, information disclosure decisions are characterized by their growing ubiquity and complexity. Endowed with limited cognitive resources, individuals therefore rely ever more on heuristic rather than deliberate decision-making. This paper argues that collective privacy norms serve as such a heuristic that guides individuals in their disclosure decisions and gradually replaces the individual privacy calculus. It is hence crucial to shed light on the evolution, efficiency, and behavioral implications of privacy norms as they unfold over time. To gain insights into the interplay of privacy norms and technological innovation, we explore 35 years of technology-related privacy discourse in The New York Times. When unpacking the dynamics of privacy norms and their salience for disclosure decision-making in such a way, privacy norms emerge as fragile social constructions that are increasingly vulnerable to collective myopia and purposive manipulation

Privacy Concerns and Data Sharing in the Internet of Things: Mixed Methods Evidence from Connected Cars

The Internet of Things (IoT) is increasingly transforming the way we work, live, and travel. IoT devices collect, store, analyze, and act upon a continuous stream of data as a by-product of everyday use. However, IoT devices need unrestricted data access to fully function. As such, they invade users’ virtual and physical space and raise far-reaching privacy challenges that are unlike those examined in other contexts

Creating Value from Personal Data – On the Legitimacy of Business Practices in the Field of Internet-Enabled Services

Practices to create value from personal data in internet-enabled services (IES) remain socially contested. Indeed, the commercial exploitation of personal data violates social expectations and conflicts with individuals’ privacy needs. To explore this tension, we draw on media coverage on IES between 1990-2015. In doing so we examine what, why and to what extent particular business practices have struggled to gain legitimacy. Our findings provide evidence for 1) the power of social control mechanisms in enforcing business practices to match with social expectations, and, paradoxically 2) a fundamental change in these very social expectations in the form of a shift in the dominant institutional logics surrounding IES. By elaborating on the underlying processes of collective assessments of legitimacy in the field of IES, we draw attention to the role of a collective privacy calculus, which might be more salient in shaping flows of personal data than previously expected