Algorithmically Controlled Automated Decision-Making and Societal Acceptability: Does Algorithm Type Matter?

As technological capabilities expand, an increasing number of decision-making processes (e.g., rankings, selections, exclusions) are being delegated to computerized systems. In this paper, we examine the societal acceptability of a consequential decision-making system (university admission) to those subject to the decision (i.e., applicants). We analyze two key drivers: the nature of the decision-making agent (a human vs an algorithm) and the decision-making logic used by the agents (predetermined vs emerging). Consistent with uniqueness neglect theory, we propose that applicants will be more positive toward the use of human agents compared to computerized systems. Consistent with the theory of procedural justice, we further argue that applicants will find the use of a predetermined logic to be more acceptable than an emerging logic. We present the details and results of a factorial survey designed to test our theoretical model

From User Acceptance to Social Acceptance

Four decades of research on technology acceptance have produced a solid knowledge base on the topic. This literature has predominantly focused on a micro-level perspective (i.e., user acceptance) while sparsely accounting for the social context surrounding technology use. This focus does not serve well the study of contemporary technologies, which involve a larger set of socio-ethical risks and concerns related to their increased deployment in society and increased involvement in socially sensitive processes. To document and start addressing this gap, we have conducted review of the literature on the concept of social acceptance in four fields: two that are closely related (MIS and HCI) and two others, more distant, that have a record of studying social acceptance (energy and healthcare). The paper presents the results of this review work with the hope to trigger a productive discussion on the topic of social acceptance in the context of modern human-computer interaction

The Responsible Adoption of (Highly) Automated Decision-Making Systems

The next-generation technological era will be marked by the prevalence of highly automated decision-making systems (ADMS), which promote technological autonomy at the expense of human agency. In this paper, we examine the role and importance of socio-ethical factors in the responsible adoption of ADMS by organizations. In doing so, we draw on the unique characteristics of ADMS and leverage the literature on social responsibility to conceptualize what a responsible adoption process and a responsible adoption decision involve. The resulting framework makes a much-needed connection between technology adoption and social responsibility and offers a progressive foundation to study ADMS adoption

IT Adoption Research in an Era of Prevalent Algorithmic Intelligence

The theoretical frameworks that are used to study phenomena involving information technology (IT) sometimes need to be revised to better fit the characteristics of evolving or emerging IT innovations. In this paper, we make the claim that the fast diffusion of sophisticated and adaptative algorithmic intelligence, and with it, our increased reliance on highly automated decision-making systems calls for a revision to the IT adoption paradigm. We present the key rationales to such a claim and formulate questions to facilitate a productive debate on the matter

Societal acceptance of mobile contact tracing applications: the moderating effect of construal level

When used by a majority of people, Contact Tracing Applications (CTAs) can be a most effective way to control the spread of a virus within a population. However, the evidence offered from the deployment of several CTAs across the world during the COVID-19 pandemic indicates that adoption rates have remained low. The present study aims to extend the literature on the societal acceptance of these technologies by building on the lens of Construal Level Theory (CLT). We focus on the moderating role of people’s construal level on the relationship between two key factors: people’s privacy uncertainty (emerging from the use of CTAs) and their perceived societal utility of using a CTA - and the societal acceptance of these technologies. The results of this research will extend emerging literature that uses the CLT in the context of studying IT adoption in general. The results will also help provide specific recommendations to public health institutions about which design practices can be used to more effectively promote societal, mass acceptance of CTAs

Explaining Customers’ Utilitarian and Hedonic Perceptions in the Context of Product Search within Social Network-Enabled Shopping Websites

Online social networks and e-Commerce have recently begun to converge into hybrid configurations via which online users search for products in the context of their social relationships. The present study explains how shoppers’ differences in two aspects of their social capital (centrality: their number of online friends, and quality: the relevance of these friends) influence the extent to which their product search experiences are perceived to be useful and enjoyable. For that matter, three value-creation paths (social network activation, effort reduction, and curiosity arousal) are proposed as the main explanatory mechanisms. Providing insights into this process is important as it will help develop a clearer understanding of the mechanisms via which digital networks influence customers’ product search experiences

A Guiding Framework for Developing Theories Investigating the Design Drivers of IT Use and Value

Understanding the benefits individuals derive from information systems (IS) is a long-standing theoretical and practical issue. To address it, a recommended approach is to investigate how individuals use these systems to better achieve their goals. Such an approach can be implemented via focusing on the distinctive object of study of our field, i.e., the information technology (IT) artifact.Hence, this paper is motivated by the lack of existing guidance on how to theorize about IS use when the research intent is to better specify the role of IT artifact design criteria. We provide assistance to scholars in identifying and relating key constructs based on which design-focused system use theories can be developed. To do so, we build on key assumptions and ideas from the Philosophy of Technology about the nature, the use, and the design of technical artifacts. These suggest that a better understanding of the design-related factors involved in the study of IT use and effects can be gained by studying (i) whether designers create IT artifacts that have the potential to support users\u27 goal-oriented actions, and (ii) whether users can exploit these IT artifacts in a way that enables them to reach their goals. Following on these ideas, the paper specifies the key building blocks that could be used by scholars when developing theories explaining the effects derived from using a given class of information systems. It also identifies the key gaps preventing the achievement of users\u27 goals that arise from both (i) the design of IT artifacts for goal-oriented tasks and (ii) the enactment of these artifacts by individuals. Finally, it proposes a series of steps to help researchers theorize about the influence of design-related aspects involved in IT use and IT value

Using information systems effectively: A representational perspective

Although there has been a great deal of research on why individuals adopt and use information systems, there is little research on what it takes for individuals to use information systems effectively. Motivated by the view that much of the impacts of information systems stem from how they are used, we propose a model to explain the nature and drivers of effective system usage. The model is designed to explain effective system usage in the context of an individual user employing any individual information system. In this context, we build on a theory of information systems known as representation theory to propose that effective system usage requires a user to engage in three activities: adaptation activities (adapting the system so that it provides better representations), learning activities (learning how to access the representations offered by the system), and verification activities (verifying the representations in the system as well as the real world domain being represented). The model suggests a set of factors that drive these activities, specifies how these activities drive effective usage, and proposes a link between effective usage and users task performance. After specifying the model, we provide examples of how it could be used to explain the effective use of several types of information systems and we discuss how the model could be expanded to explain other contexts of use (e.g., multiple systems and multiple users) and to incorporate process forms of theorizing as well as variance forms of theorizing

The Utility of Using Social Media Networks for Data Collection in Survey Research

Social media networks (SMNs) such as Facebook, LinkedIn or Twitter seem appealing tools for matters of reaching potential candidates for survey or case study research. Yet scholars remain cautious about leveraging these platforms. This research in progress paper compares and discusses the benefits of six generic strategies for reaching survey candidates on SMNs, and argues that while their use has potential pitfalls, the upside for explanatory type research may outweigh its risks. Furthermore, the paper outlines the empirical setting of a study that has been conducted to assess our propositions, and in which Linkedin was used to identify and solicit survey candidates