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Full-Text Articles in Social and Behavioral Sciences
“Faking” Is Neither Good Nor Bad, It Is A Misleading Concept: A Reply To Tett And Simonet (2021), Bernd Marcus
“Faking” Is Neither Good Nor Bad, It Is A Misleading Concept: A Reply To Tett And Simonet (2021), Bernd Marcus
Personnel Assessment and Decisions
This paper comments on Tett and Simonet’s (2021) outline of two contradictory positions on job applicants’ self-presentation on personality tests labelled “faking is bad” (FIB) versus “faking is good” (FIG). Based on self-presentation theory (Marcus, 2009) Tett and Simonet assigned to their FIG camp, I develop the ideas of (a) understanding self-presentation from the applicant’s rather than the employer’s perspective, (b) avoiding premature moral judgment on this behavior, and (c) examining consequences for the validity of applicant responses with a focus on the intended use for, and the competitive context of, selection. Conclusions include (a) that self-presentation is motivationally and …
Scientific, Legal, And Ethical Concerns About Ai-Based Personnel Selection Tools: A Call To Action, Nancy T. Tippins, Frederick L. Oswald, S. Morton Mcphail
Scientific, Legal, And Ethical Concerns About Ai-Based Personnel Selection Tools: A Call To Action, Nancy T. Tippins, Frederick L. Oswald, S. Morton Mcphail
Personnel Assessment and Decisions
Organizations are increasingly turning toward personnel selection tools that rely on artificial intelligence (AI) technologies and machine learning algorithms that, together, intend to predict the future success of employees better than traditional tools. These new forms of assessment include online games, video-based interviews, and big data pulled from many sources, including test responses, test-taking behavior, applications, resumes, and social media. Speedy processing, lower costs, convenient access, and applicant engagement are often and rightfully cited as the practical advantages for using these selection tools. At the same time, however, these tools raise serious concerns about their effectiveness in terms of their …
Applicant Faking On Personality Tests: Good Or Bad And Why Should We Care?, Robert P. Tett, Daniel V. Simonet
Applicant Faking On Personality Tests: Good Or Bad And Why Should We Care?, Robert P. Tett, Daniel V. Simonet
Personnel Assessment and Decisions
The unitarian understanding of construct validity holds that deliberate response distortion in completing self-report personality tests (i.e., faking) threatens trait-based inferences drawn from test scores. This “faking-is-bad” (FIB) perspective is being challenged by an emerging “faking-is-good” (FIG) position that condones or favors faking and its underlying attributes (e.g., social skill, ATIC) to the degree they contribute to predictor–criterion correlations and are job relevant. Based on the unitarian model of validity and relevant empirical evidence, we argue the FIG perspective is psychometrically flawed and counterproductive to personality-based selection targeting trait-based fit. Carrying forward both positions leads to variously dark futures for …
Faking And The Validity Of Personality Tests: An Experimental Investigation Using Modern Forced Choice Measures, Christopher R. Huber, Nathan R. Kuncel, Katie B. Huber, Anthony S. Boyce
Faking And The Validity Of Personality Tests: An Experimental Investigation Using Modern Forced Choice Measures, Christopher R. Huber, Nathan R. Kuncel, Katie B. Huber, Anthony S. Boyce
Personnel Assessment and Decisions
Despite the established validity of personality measures for personnel selection, their susceptibility to faking has been a persistent concern. However, the lack of studies that combine generalizability with experimental control makes it difficult to determine the effects of applicant faking. This study addressed this deficit in two ways. First, we compared a subtle incentive to fake with the explicit “fake-good” instructions used in most faking experiments. Second, we compared standard Likert scales to multidimensional forced choice (MFC) scales designed to resist deception, including more and less fakable versions of the same MFC inventory. MFC scales substantially reduced motivated score elevation …
Threat Of Technological Unemployment, Use Intentions, And The Promotion Of Structured Interviews In Personnel Selection, Kevin P. Nolan, Dev K. Dalal, Nathan Carter
Threat Of Technological Unemployment, Use Intentions, And The Promotion Of Structured Interviews In Personnel Selection, Kevin P. Nolan, Dev K. Dalal, Nathan Carter
Personnel Assessment and Decisions
Meehl (1986) proposed that an important factor underlying professional decision makers’ resistance to standardized decision aids is threat of technological unemployment – fear that using the practices would reduce the perceived value of their employment. Nolan, Carter, and Dalal (2016) provided initial support for threat of technological unemployment being a factor that contributes to practitioners’ reluctance to adopt scientifically meritorious standardized hiring practices. This study serves to further develop the theory of threat of technological unemployment in personnel selection by (a) replicating the findings of our earlier research using a within-subjects methodology that is more generalizable to the cognitive processes …
Decoy Effects Improve Diversity Hiring, Nathan R. Kuncel, Jeffrey A. Dahlke
Decoy Effects Improve Diversity Hiring, Nathan R. Kuncel, Jeffrey A. Dahlke
Personnel Assessment and Decisions
A growing literature demonstrates that when making choices among multiple options, decision makers are strongly influenced by the mere presence of additional options, even when those options are largely undesirable and are never actually selected. The effects of irrelevant options on decisions, often called decoy effects, have been observed in hiring and admissions decisions where the nature of a third candidate can radically shift preferences. In this study, we examine the influence of decoy effects on diversity hiring and extend research by examining choices with more than two organizational goals. Results indicate that the presence of a second candidate who …
Does Feedback Increase Decision Aid Use Among Hiring Professionals?, Aneeqa Thiele, Alexander T. Jackson, Stacey M. Stremic, Satoris S. Howes
Does Feedback Increase Decision Aid Use Among Hiring Professionals?, Aneeqa Thiele, Alexander T. Jackson, Stacey M. Stremic, Satoris S. Howes
Personnel Assessment and Decisions
We examined the influence of formative and outcome feedback on people’s reliance on decision aids. Decision aids are tools that managers can use to increase the accuracy of their hiring decisions. In our study, participants were asked to make 20 different hiring decisions and make predictions of a candidate’s performance on the job, with the option of using a decision aid formula. We manipulated whether participants received feedback on the accuracy of their predictions, the accuracy of the decision aid’s predictions, or both. The results demonstrated that feedback failed to have a significant impact on decision aid use for both …
Pushing The Limits For Judgmental Consistency: Comparing Random Weighting Schemes With Expert Judgments, Martin C. Yu, Nathan R. Kuncel
Pushing The Limits For Judgmental Consistency: Comparing Random Weighting Schemes With Expert Judgments, Martin C. Yu, Nathan R. Kuncel
Personnel Assessment and Decisions
Consistent use of information has been identified as a critical issue that can undermine expert predictions. Using three personnel assessment datasets, we conduct Monte Carlo simulations to compare the accuracy of expert judgements for predicting the job performance of managers against four different weighting schemes: consistent random weights, completely random weights, unit weights, and optimal weights. Expert accuracy fell within the completely random weight distribution in two samples and at the low end of the consistent random weight distribution in one sample. In other words, consistent random weights reliably outperformed expert judgment for hiring decisions across three datasets with a …
“Where’S The I-O?” Artificial Intelligence And Machine Learning In Talent Management Systems, Manuel F. Gonzalez, John F. Capman, Frederick L. Oswald, Evan R. Theys, David L. Tomczak
“Where’S The I-O?” Artificial Intelligence And Machine Learning In Talent Management Systems, Manuel F. Gonzalez, John F. Capman, Frederick L. Oswald, Evan R. Theys, David L. Tomczak
Personnel Assessment and Decisions
Artificial intelligence (AI) and machine learning (ML) have seen widespread adoption by organizations seeking to identify and hire high-quality job applicants. Yet the volume, variety, and velocity of professional involvement among I-O psychologists remains relatively limited when it comes to developing and evaluating AI/ML applications for talent assessment and selection. Furthermore, there is a paucity of empirical research that investigates the reliability, validity, and fairness of AI/ML tools in organizational contexts. To stimulate future involvement and research, we share our review and perspective on the current state of AI/ML in talent assessment as well as its benefits and potential pitfalls; …
A New Scoring Procedure In Assessment Centers: Insights From Interaction Analysis, Janneke K. Oostrom, Nale Lehmann-Willenbrock, Ute-Christine Klehe
A New Scoring Procedure In Assessment Centers: Insights From Interaction Analysis, Janneke K. Oostrom, Nale Lehmann-Willenbrock, Ute-Christine Klehe
Personnel Assessment and Decisions
This paper proposes interaction analysis as an alternative scoring procedure in assessment centers (ACs). Interaction analysis allows for a more fine-grained scoring approach by which candidate behaviors are captured as they actually happen, thus avoiding judgment errors typically associated with traditional scoring procedures. We describe interaction analysis and explain how this procedure can improve the validity of ACs. In a short research example, we showcase how interaction analysis can be implemented in AC settings. Finally, we integrate our arguments in terms of three key propositions which we hope will inspire future research on more dynamic scoring procedures.
Selection Tool Use: A Focus On Personality Testing In Canada, The United States, And Germany, Stephen D. Risavy, Peter A. Fisher, Chet Robie, Cornelius J. König
Selection Tool Use: A Focus On Personality Testing In Canada, The United States, And Germany, Stephen D. Risavy, Peter A. Fisher, Chet Robie, Cornelius J. König
Personnel Assessment and Decisions
The purpose of this paper is to provide new data regarding the current staffing practices being used by organizations in Canada and the United States (US) as well as a comparison with existing data from Germany (Diekmann & König, 2015). Data regarding the beliefs of human resource (HR) practitioners in terms of using personality tests in personnel selection is also provided. A geographically representative sample of 453 HR practitioners across Canada and the US were surveyed. Although general mental ability testing has previously been found to be highly valid and cost effective, this selection tool was among the least commonly …
Examining Factors Influencing Use Of A Decision Aid In Personnel Selection, Alexander T. Jackson, Michael E. Young, Satoris S. Howes, Patrick A. Knight, Sydney L. Reichin
Examining Factors Influencing Use Of A Decision Aid In Personnel Selection, Alexander T. Jackson, Michael E. Young, Satoris S. Howes, Patrick A. Knight, Sydney L. Reichin
Personnel Assessment and Decisions
In this research, two studies were conducted to examine factors influencing reliance on a decision aid in personnel selection. Specifically, this study examined the effect of feedback, validity of selection predictors, and presence of a decision aid on the use of the aid in personnel selection. The results demonstrate that when people are provided with the decision aid, their predictions were significantly more similar to the predictions made by the aid than people who were not provided with the aid. This suggests that when people are provided with an aid, they will use it to some degree. This research also …