Soleimani MIntezari ATaskin NPauleen DBui TX2025-05-282025-05-282021-01-01Soleimani M, Intezari A, Taskin N, Pauleen D. 2021-01-05 to 2021-01-08. Cognitive biases in developing biased artificial intelligence recruitment system. 54th Hawaii International Conference on System Sciences (HICSS 2021). Maui, Hawaii, United States of America.978-0-9981331-4-01530-1605https://mro.massey.ac.nz/handle/10179/72967Artificial 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.(c) The author/shttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.enconference2572-6862CC BY-NC-NDconference5091-5099