Litcius/Paper detail

Cognitive biases in developing biased Artificial Intelligence recruitment system

Melika Soleimani, Ali Intezari, Nazım Taşkın, David J. Pauleen

2021Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences39 citationsDOIOpen Access PDF

Abstract

Artificial Intelligence (AI) in a business context is designed to provide organizations with valuable insight into decision-making and planning. Although AI can help managers make decisions, it may pose unprecedented issues, such as datasets and implicit biases built into algorithms. To assist managers with making unbiased effective decisions, AI needs to be unbiased too. Therefore, it is important to identify biases that may arise in the design and use of AI. One of the areas where AI is increasingly used is the Human Resources recruitment process. This article reports on the preliminary findings of an empirical study answering the question: how do cognitive biases arise in AI? We propose a model to determine people’s role in developing AI recruitment systems. Identifying the sources of cognitive biases can provide insight into how to develop unbiased AI. The academic and practical implications of the study are discussed.

Topics & Concepts

Computer scienceCognitive biasCognitionContext (archaeology)Process (computing)Artificial intelligenceEmpirical researchData scienceApplications of artificial intelligenceHuman intelligenceKnowledge managementPsychologyBiologyEpistemologyNeurosciencePhilosophyOperating systemPaleontologyAI in Service InteractionsAI and HR TechnologiesSmart Systems and Machine Learning