scholarly journals Human Perceptions of Fairness in Algorithmic Decision Making

2018 ◽  
Author(s):  
Nina Grgic-Hlaca ◽  
Elissa M. Redmiles ◽  
Krishna P. Gummadi ◽  
Adrian Weller
Keyword(s):  
Decision Making ◽  
Perceptions Of Fairness ◽  
Human Perceptions

The Individual and Administrative Justice

2021 ◽  
Author(s):  
Naomi Creutzfeldt
Keyword(s):  
Decision Making ◽  
Justice System ◽  
Service Users ◽  
Perceptions Of Fairness ◽  
Decision Making Processes ◽  
The Subject ◽  
Individual Justice ◽  
The Individual ◽  
Individual Service ◽  
Administrative Justice

This chapter discusses what individual justice means in the realm of administrative justice. The standards of justice and fairness that apply in administrative decision-making need consideration from the perspective of the service user. Should the administrative justice system serve the citizen or the state? What role do individual service users have in the design, use, and evaluation of more bureaucratic systems of redress? Different notions of justice, as they relate to primary decision-making processes, have been described through various models. This chapter provides a set of tools with which to study the subject and argues for the importance of user voice and perceptions of fairness in the provision of a more citizen-focussed justice.

scholarly journals Is Family Decision-making Power?

2018 ◽  
Author(s):  
Joanna Pepin
Keyword(s):  
Decision Making ◽  
Gender Inequality ◽  
Original Data ◽  
Survey Experiment ◽  
Perceptions Of Fairness ◽  
Proxy Indicators ◽  
Family Decision Making ◽  
Family Choices ◽  
Relative Resources ◽  
Gender System

Do ‘final say’ survey questions measure power within families? Researchers rely on these items as proxy indicators of gender inequality within households, although there are reasons to doubt decision-making is equated with power. I review relative resources and exchange theory predictions about decision-making and two potential moderators: the gender system and methods of allocating income. Using original data (n = 3,975) from a vignette-survey experiment to disentangle the mechanisms leading to decision making authority, I find higher relative earners within families are not regarded as entitled to the final word in decisions. Whether respondents considered earnings individually or community owned did not explain the lack of association between financial resources and decision-making clout. Findings show a significant association between the decider’s gender and perceptions of fairness: specifically, when women were presented as the decider over monetary family choices, unilateral decision-making was viewed more favorably. Results from the qualitative analysis of the reasoning behind these evaluations were consistent with beliefs in egalitarian essentialism, that women and men are equal but characteristically different. Findings suggest ‘final say’ measures should be interpreted cautiously as markers of power and offers insights in to why gender equality within families remains stalled.

scholarly journals Artificial Fairness? Trust in Algorithmic Police Decision-Making

2021 ◽  
Author(s):  
Zoe Hobson ◽  
Julia Yesberg ◽  
Ben Bradford ◽  
Jonathan Jackson
Keyword(s):  
Decision Making ◽  
Mere Exposure ◽  
Online Experiment ◽  
Specific Instance ◽  
Police Decision Making ◽  
Perceptions Of Fairness ◽  
General Acceptability

Objectives: Test whether: (1) people view a policing decision made by an algorithm as more or less trustworthy than when an officer makes the same decision; (2) people who are presented with a specific instance of algorithmic policing have greater or lesser support for the general use of algorithmic policing in general; and (3) people use trust as a heuristic through which to make sense of an unfamiliar technology like algorithmic policing.Methods: An online experiment tested whether different decision-making methods, outcomes and scenario types affect judgements about the appropriateness and fairness of decision-making, and the general acceptability of police use of this particular technology. Results: People see a decision as less fair and less appropriate when an algorithm decides, compared to when an officer decides. Yet perceptions of fairness and appropriateness were strong predictors of support for police use of algorithms, and being exposed to a successful use of an algorithm was linked via trust in the decision made to greater support for police use of algorithms.Conclusions: Making decisions solely based on algorithms might damage trust, and the more police rely solely on algorithmic decision-making, the less trusting people may be in decisions. However, mere exposure to the successful use of algorithms seems to enhance the general acceptability of this technology.

Process vs. Outcome? How to Evaluate the Effects of Participatory Processes on Legitimacy Perceptions

2020 ◽  
pp. 1-8
Author(s):  
Hannah Werner ◽  
Sofie Marien
Keyword(s):  
Decision Making ◽  
Status Quo ◽  
Participatory Process ◽  
Total N ◽  
Fairness Perceptions ◽  
Perceptions Of Fairness ◽  
Participatory Processes ◽  
The Status ◽  
Process Effects ◽  
Representative Process

Abstract The potential for participatory processes to address deficits in perceptions of legitimacy is strongly debated. This letter discusses how to evaluate the effects of participatory procedures. It argues that participatory processes should not be compared to normative ideals about how citizens should behave, but rather to the status quo of representative decision making. The authors use the example of winner–loser gaps in perceptions of fairness to illustrate the importance of evaluation frameworks, drawing on twelve experiments from the Netherlands and Sweden (total N = 5,352). The study shows that the choice of benchmarks matters substantially for the interpretation of process effects. When comparing participatory processes to the status quo of representative decision making, it finds higher fairness perceptions for a participatory process than for a representative process across all twelve experiments, even when the outcomes are unfavourable.

scholarly journals The Apparent Locus of Managerial Decision Making and Perceptions of Fairness in Public Personnel Management

2018 ◽  
Vol 48 (3) ◽  
pp. 392-412
Author(s):  
Justin M. Stritch ◽  
Mogens Jin Pedersen
Keyword(s):  
Decision Making ◽  
Public Management ◽  
Case Vignette ◽  
Management Research ◽  
Managerial Decision ◽  
Personnel Decisions ◽  
Heterogeneous Effects ◽  
Perceptions Of Fairness ◽  
Case Vignettes ◽  
Locus Of Decision

A topic that remains underexplored in public management research is how the appearance of a formal rule or policy as guiding personnel decisions may affect employee perceptions of organizational decision outcomes. In this article, we consider how the locus of decision making (e.g., the apparent source of a decision) affects perceptions of a decision’s fairness. We examine this question with three survey experiments using case vignettes, each describing a distinct personnel decision-making scenario. In each case vignette, we manipulate the locus of decision making (a single supervisor, a team of supervisors, or an organizational policy). We find heterogeneous effects across the three case vignettes. We conclude with a discussion of the implications and future directions for public management research.

scholarly journals Artificial fairness? Trust in algorithmic police decision-making

2021 ◽  
Author(s):  
Zoë Hobson ◽  
Julia A. Yesberg ◽  
Ben Bradford ◽  
Jonathan Jackson
Keyword(s):  
Decision Making ◽  
Mere Exposure ◽  
Online Experiment ◽  
Specific Instance ◽  
Police Decision Making ◽  
Perceptions Of Fairness ◽  
General Acceptability

Abstract Objectives Test whether (1) people view a policing decision made by an algorithm as more or less trustworthy than when an officer makes the same decision; (2) people who are presented with a specific instance of algorithmic policing have greater or lesser support for the general use of algorithmic policing in general; and (3) people use trust as a heuristic through which to make sense of an unfamiliar technology like algorithmic policing. Methods An online experiment tested whether different decision-making methods, outcomes and scenario types affect judgements about the appropriateness and fairness of decision-making and the general acceptability of police use of this particular technology. Results People see a decision as less fair and less appropriate when an algorithm decides, compared to when an officer decides. Yet, perceptions of fairness and appropriateness were strong predictors of support for police use of algorithms, and being exposed to a successful use of an algorithm was linked, via trust in the decision made, to greater support for police use of algorithms. Conclusions Making decisions solely based on algorithms might damage trust, and the more police rely solely on algorithmic decision-making, the less trusting people may be in decisions. However, mere exposure to the successful use of algorithms seems to enhance the general acceptability of this technology.

Discarding optimality: Throwing out the baby with the bathwater?

2018 ◽  
Vol 41 ◽  
Author(s):  
Patrick Simen ◽  
Fuat Balcı
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Reward Rate ◽  
Perceptual Decision ◽  
Standard Observer ◽  
Rate Maximization ◽  
Reward Rate Maximization ◽  
Descriptive Standard ◽  
Observer Model

AbstractRahnev & Denison (R&D) argue against normative theories and in favor of a more descriptive “standard observer model” of perceptual decision making. We agree with the authors in many respects, but we argue that optimality (specifically, reward-rate maximization) has proved demonstrably useful as a hypothesis, contrary to the authors’ claims.

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