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Navigating AI in Personnel Selection: A Scenario-based Study on Applicants' Perceptions

2023 | International Conference on Information Systems | Citations: 0
Authors: Czernietzki, Charlotte; Märtins, Julian; Westmattelmann, Daniel; Grotenhermen, Jan-Gerrit; Oldeweme, Andreas; Baumeister, Viktoria; Schewe, Gerhard

Abstract: AI-based systems are increasingly deployed on organizational tasks, such as per ... Expand

Abstract: AI-based systems are increasingly deployed on organizational tasks, such as personnel selection decisions. As existing research indicates that applicants generally react negatively to the use of AI in personnel selection, this study examines how organizations can mitigate adverse reactions to fully exploit the benefits of AI. To obtain robust results, we recruited an online sample of German participants (N = 1,852) and presented them with various selection scenarios. Using a between-subject design, the process stage (preselection vs. interview) and the degree of process automation (augmented vs. automated) were manipulated. By employing a multidimensional conceptualization of transparency, we show that disclosure and accuracy positively impact procedural justice perceptions, a strong predictor of process quality assessment. This relationship is robust across selection contexts. Results indicate that applicants prefer AI for pre-selection and as human decision support, thus offering overall insights into design choices for AI in selection, optimizing applicant reactions. Collapse

Semantic filters: organizational justice theory

Topics: artificial intelligence business process automation data quality electronic mail virtual reality

Methods: qualitative interview partial least squares path modeling survey parametric test ANOVA

Theories: procedural justice theory organizational justice theory
A Longitudinal Examination of AI Fairness on Online Labor Markets

2023 | Americas Conference on Information Systems | Citations: 0
Authors: Green, Brittany; Ahuja, Manju; Sundrup, Rui

Abstract: ... Expand

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Semantic filters: organizational justice theory

Topics: artificial intelligence IT career online labor market software developer electronic market

Methods: agent based simulation simulation longitudinal research experiment regression analysis method

Theories: organizational justice theory contingency theory
A Longitudinal Examination of AI Fairness on Online Labor Markets

2023 | International Conference on Business Informatics | Citations: 0
Authors: Green, Brittany; Ahuja, Manju; Sundrup, Rui; Quinn, Ryan

Abstract: While online labor markets (OLMs) provide many benefits including flexibility a ... Expand

Abstract: While online labor markets (OLMs) provide many benefits including flexibility and data driven AI matching systems, gender and other social biases have been shown in OLMs, and research demonstrates AI can also perpetuate bias. However, previous OLM research assumes bias is static over time and independent of the AI algorithm. To help design OLMs that minimize the detrimental impact of biases on marginalized social groups, we investigate the interaction among individual characteristics and AI sources of biases over the long-term and evaluate auditing strategies using an agent-based simulation model. We also empirically investigate hiring bias using a cross section of data from a popular online labor market, and we use this data to inform our simulation. We then plan to develop and empirically test a framework to evaluate AI fairness and the interaction of different biases on OLMs and test an audit strategy to mitigate biases. We plan to extend the literature on OLMs by integrating fairness and intersectionality research to evaluate the impact of biases. Collapse

Semantic filters: organizational justice theory

Topics: artificial intelligence online labor market IT career task characteristic individual characteristic

Methods: simulation longitudinal research agent based simulation Student's t-test experiment

Theories: contingency theory organizational justice theory
How to Compensate After a Data Breach? Investigating Compensation Types and Role of Fairness in Customer Repatronage Intentions
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2023 | ACM SIGMIS Database | Citations: 0
Authors: Mohammed, Zareef A.; Tejay, Gurvirender P.

Abstract: Data breach recovery is often likened to service failure recovery. Like service ... Expand

Abstract: Data breach recovery is often likened to service failure recovery. Like service failure recovery, compensation is a major factor toward data breach recovery. However, compensation involves different types, which may have varying effects on data breach recovery. This study investigates the effect of compensation types on customer's repatronage intentions to organizations that have suffered a data breach. Three compensation types were identified in this study: monetary, service, and psychological compensation. The findings of this study indicate that only service and psychological compensation have a significant effect on customers' perceptions of being treated fairly by the organization following a data breach. Furthermore, service compensation impacts the trust a customer regains in the company. Monetary compensation did not play a statistically significant role in the data breach recovery process. In turn, both perceived fairness and regained trust influences customer repatronage intentions. This study contributes to the information privacy field by identifying the types of compensation that are impactful to re-engage individuals who suffered PII related data breach. Collapse

Semantic filters: organizational justice theory

Topics: data breach privacy service quality electronic commerce word of mouth

Methods: survey statistical power analysis partial least squares path modeling factor analysis data transformation

Theories: social exchange theory organizational justice theory justice theory
How Does Technological Entitlement Affect Cyberdeviance? The Role of Organizational Justice.

2023 | Americas Conference on Information Systems | Citations: 0
Authors: Owusu, Gabriel; Xiao, Nan

Abstract: The widespread use of technology in the workplace has led to an increase in cyb ... Expand

Abstract: The widespread use of technology in the workplace has led to an increase in cyberdeviance, where employees deliberately violate organizational norms when using IT resources. Drawing on literature on technological entitlement and organizational justice, this study explores the relationship between cyberdeviance, technological entitlement, and organizational justice. We propose that technological entitlement is a personality trait of employees who are more likely to engage in cyberdeviance and use organizational justice as a justification for their behavior. This paper contributes to recent studies on technological entitlement and has implications for organizations seeking to mitigate cyberdeviance. Collapse

Semantic filters: organizational justice theory

Topics: security policy personality

Methods: theory development

Theories: procedural justice theory distributive justice theory organizational justice theory
Exploring the Role of AI Explanations in Delivering Rejection Messages: A Comparative Analysis of Organizational Justice Perceptions between HR and AI

2023 | International Conference on Information Systems | Citations: 0
Authors: Tian, Yuyang; Claudy, Marius; Xu, David (Jingjun); LIAO, Stephen Shaoyi

Abstract: The increasing use of AI decision systems in recruitment processes has created ... Expand

Abstract: The increasing use of AI decision systems in recruitment processes has created challenges, including potential resistance from job applicants. To address this issue, drawing on organizational justice theory, we identify dimensions of AI explanations in the employment context and examine their impact on job applicants' perceptions of organizational justice. We conducted an experiment to understand applicants' reactions to AI versus HR managers without explanations and examined the impact of AI explanations on organizational justice perceptions and acceptance intention. Our findings show that without explanation, AI is perceived as lower organizational just and acceptance intention compared to HR managers. Organizational justice mediates the effects between outcome/process explanations of AI on acceptance intention. However, outcome explanations have a stronger impact compared to process explanations. Our study contributes to understanding explanation structures for AI-based recruitment and offers practical implications for developing explanations that improve the perceived justice of AI recruitment systems. Collapse

Semantic filters: organizational justice theory

Topics: artificial intelligence explainable artificial intelligence human resource management Google+ website

Methods: parametric test computational algorithm one sample t-test ANOVA experiment

Theories: distributive justice theory procedural justice theory equity theory organizational justice theory
What is fair enough? Reconciling complementors’ needs for fairness management on digital platforms

2023 | International Conference on Information Systems | Citations: 0
Authors: Zhou, Yawen Vivian; LEONG, Carmen; Guo, Zixiu

Abstract: ... Expand

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Semantic filters: organizational justice theory

Topics: social media value creation

Methods: qualitative interview qualitative coding case study archival research longitudinal research

Theories: organizational justice theory
Algorithmic bias: review, synthesis, and future research directions
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2022 | European Journal of Information Systems | Citations: 26
Authors: Kordzadeh, Nima; Ghasemaghaei, Maryam

Abstract: As firms are moving towards data-driven decision making, they are facing an emer ... Expand

Abstract: As firms are moving towards data-driven decision making, they are facing an emerging problem, namely, algorithmic bias. Accordingly, algorithmic systems can yield socially-biased outcomes, thereby compounding inequalities in the workplace and in society. This paper reviews, summarises, and synthesises the current literature related to algorithmic bias and makes recommendations for future information systems research. Our literature analysis shows that most studies have conceptually discussed the ethical, legal, and design implications of algorithmic bias, whereas only a limited number have empirically examined them. Moreover, the mechanisms through which technology-driven biases translate into decisions and behaviours have been largely overlooked. Based on the reviewed papers and drawing on theories such as the stimulus-organism-response theory and organisational justice theory, we identify and explicate eight important theoretical concepts and develop a research model depicting the relations between those concepts. The model proposes that algorithmic bias can affect fairness perceptions and technology-related behaviours such as machine-generated recommendation acceptance, algorithm appreciation, and system adoption. The model also proposes that contextual dimensions (i.e., individual, task, technology, organisational, and environmental) can influence the perceptual and behavioural manifestations of algorithmic bias. These propositions highlight the significant gap in the literature and provide a roadmap for future studies. Collapse

Semantic filters: organizational justice theory

Topics: algorithmic bias artificial intelligence technology adoption database system individual characteristic

Methods: computational algorithm literature study theory development literature sample machine learning

Theories: organizational justice theory organizational theory justice theory
Antecedents and Consequences of Perceived Fairness in Pay for Crowdwork

2020 | International Conference on Information Systems | Citations: 0
Authors: Alpar, Paul; Osterbrink, Lars

Abstract: Businesses and researchers use crowdwork to conveniently and cost-efficiently ou ... Expand

Abstract: Businesses and researchers use crowdwork to conveniently and cost-efficiently outsource work. Some research suggests that even low payments can achieve high quality work. However, recent research and ethical considerations suggest that low payments and especially a low perceived fairness in pay may come at a price. Crowdworkers may refuse to work for an employer, put less effort in a task, or even leave the microtask crowdsourcing platform entirely. We develop a model to understand how perceived fairness in pay is formed before task execution based on justice theory. We test the model and find that promised pay and expected enjoyment have a significant positive impact on perceived fairness in pay, while work experience has a significant negative impact. Education and expected complexity have no significant impact. Perceived fairness in pay significantly increases the odds of task execution, while expected complexity decreases it. Collapse

Semantic filters: organizational justice theory

Topics: crowdsourcing task complexity

Methods: partial least squares path modeling experiment logistic regression partial least squares regression survey

Theories: justice theory organizational justice theory procedural justice theory distributive justice theory
Post Data Breach Use of Protective Technologies: An Examination of Users’ Dilemma

2020 | HICSS | Citations: 0
Authors: Ayaburi, Emmanuel W; Andoh-Baidoo, Francis K; Ung, Jae

Abstract: This preliminary research addresses the technology use uncertainties that arise ... Expand

Abstract: This preliminary research addresses the technology use uncertainties that arise when users are presented with protective technologies following a data breach or privacy violation announcement. Prior studies have provided understanding of determinants of technology use through several perspectives. The study complements prior research by arguing that, beyond individual dispositions or technology features, data breach announcements bring users’ focus on the actions of the breaching organization. Fair process and information practices provide avenue for organizations to alleviate users’ concerns and increase service usage. We draw on organizational justice theory to develop a model that explicates the effect of organizational fairness process and use of technologies. We test this model using data from 200 Facebook users recruited from Amazon MTurk. We found that procedural and informational justice have differential effect on users’ desire to use protective technologies. Our findings have both theoretical and practical implications. Collapse

Semantic filters: organizational justice theory

Topics: data breach information system use privacy Facebook information privacy concern

Methods: partial least squares regression psychometrics data transformation exploratory factor analysis robustness check

Theories: procedural justice theory organizational justice theory

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Found 21 articles

Navigating AI in Personnel Selection: A Scenario-based Study on Applicants' Perceptions

A Longitudinal Examination of AI Fairness on Online Labor Markets

A Longitudinal Examination of AI Fairness on Online Labor Markets

How to Compensate After a Data Breach? Investigating Compensation Types and Role of Fairness in Customer Repatronage Intentions

How Does Technological Entitlement Affect Cyberdeviance? The Role of Organizational Justice.

Exploring the Role of AI Explanations in Delivering Rejection Messages: A Comparative Analysis of Organizational Justice Perceptions between HR and AI

What is fair enough? Reconciling complementors’ needs for fairness management on digital platforms

Algorithmic bias: review, synthesis, and future research directions

Antecedents and Consequences of Perceived Fairness in Pay for Crowdwork

Post Data Breach Use of Protective Technologies: An Examination of Users’ Dilemma