Location
Online
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2022 12:00 AM
End Date
7-1-2022 12:00 AM
Description
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.
Algorithmically Controlled Automated Decision-Making and Societal Acceptability: Does Algorithm Type Matter?
Online
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.
https://aisel.aisnet.org/hicss-55/ks/design/2