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Anchoring effects in state-of-the-art personnel selection processes: How artificial intelligence influences people’s decision-making

Ruwe, Theresa LU (2019) PSYP01 20191
Department of Psychology
Abstract
The robustness of anchoring effects underlines the importance of investigating its repercussions in various situations, including personnel selection. Additionally, technological developments and the planned implementation of artificially intelligent (AI) systems in personnel selection create a new decision-making process offering another possibility for anchoring effects to occur. This study investigated the influence of AI vs human ratings on the hiring-decision of participants considering their attitudes and hiring-experience as moderating factors. Data from 321 participants were collected online. The 2 (AI vs hiring manager) ✕ 2 (above vs below average) within-subject design prompted participants to rate five video interview excerpts... (More)
The robustness of anchoring effects underlines the importance of investigating its repercussions in various situations, including personnel selection. Additionally, technological developments and the planned implementation of artificially intelligent (AI) systems in personnel selection create a new decision-making process offering another possibility for anchoring effects to occur. This study investigated the influence of AI vs human ratings on the hiring-decision of participants considering their attitudes and hiring-experience as moderating factors. Data from 321 participants were collected online. The 2 (AI vs hiring manager) ✕ 2 (above vs below average) within-subject design prompted participants to rate five video interview excerpts on five scales. As predicted and in line with previous research, participants adjusted their initial judgement towards the respective anchor. There was no difference between the influence of humans vs AI systems as a source of information. Furthermore, neither did participants’ attitudes interact with the anchoring effect, nor did age predict the valence of the attitude scores. Finally, hiring experience was found to interact with the anchor information, suggesting that participants with less experience rely heavier on low anchor information. The study provides implications for implementing AI in personnel selection processes as well as general information about the influential nature of AI and anchoring effects in general. (Less)
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author
Ruwe, Theresa LU
supervisor
organization
course
PSYP01 20191
year
type
H2 - Master's Degree (Two Years)
subject
keywords
artificial intelligence, linear mixed effects model, decision-making, personnel selection, anchoring effects
language
English
id
8993932
date added to LUP
2019-09-06 08:40:10
date last changed
2019-09-06 08:40:10
@misc{8993932,
  abstract     = {The robustness of anchoring effects underlines the importance of investigating its repercussions in various situations, including personnel selection. Additionally, technological developments and the planned implementation of artificially intelligent (AI) systems in personnel selection create a new decision-making process offering another possibility for anchoring effects to occur. This study investigated the influence of AI vs human ratings on the hiring-decision of participants considering their attitudes and hiring-experience as moderating factors. Data from 321 participants were collected online. The 2 (AI vs hiring manager) ✕ 2 (above vs below average) within-subject design prompted participants to rate five video interview excerpts on five scales. As predicted and in line with previous research, participants adjusted their initial judgement towards the respective anchor. There was no difference between the influence of humans vs AI systems as a source of information. Furthermore, neither did participants’ attitudes interact with the anchoring effect, nor did age predict the valence of the attitude scores. Finally, hiring experience was found to interact with the anchor information, suggesting that participants with less experience rely heavier on low anchor information. The study provides implications for implementing AI in personnel selection processes as well as general information about the influential nature of AI and anchoring effects in general.},
  author       = {Ruwe, Theresa},
  keyword      = {artificial intelligence,linear mixed effects model,decision-making,personnel selection,anchoring effects},
  language     = {eng},
  note         = {Student Paper},
  title        = {Anchoring effects in state-of-the-art personnel selection processes: How artificial intelligence influences people’s decision-making},
  year         = {2019},
}