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Mere algorithms can be demotivating

Nature Reviews Psychology volume 1, page 682 (2022)Cite this article

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In the final paragraph of their article, Gagné and colleagues write, “it is not algorithms that shape workers’ motivation, but how organizations design and use them” (Gagné, M. et al. Understanding and shaping the future of work with self-determination theory. Nat. Rev. Psychol. 1, 378–392 (2022))1. However, this assertion is too general and warrants nuance because algorithms by their very nature might thwart workers’ autonomy and subsequently their intrinsic motivation under certain circumstances.

Algorithmic decision-making systems comprise model architecture, parameters and training data. Models are designed to learn from training data and remain constricted by them. Introducing algorithmic decision-making systems into organizational functions such as recruitment requires the use of large volumes of personal data to train the algorithm. Training data might miss or misrepresent certain categories of workers. For example, candidates hired for construction jobs might have historically been men of a specific ethnicity. Recruitment algorithmic decision-making systems trained using these data might incorrectly idealize this candidate profile, eliminating otherwise ideal candidates on the basis solely of algorithmic expectations of ethnicity or gender. Such decisions inadvertently (or intentionally) repeat and propagate organizational biases, creating negative feedback loops that are difficult to correct. Outputs of algorithmic decision-making systems are therefore not objective; however, implicit assumptions of algorithmic objectivity, correctness and fairness2 make it difficult for users to question their decisions. Technological innovation might render human input redundant or even expendable. Thus, people will be unable to examine the steps that lead to a decision, to correct erroneous or illogical decisions resulting from algorithmic failure, or to provide feedback to improve the process3. Workers might therefore become passive recipients of critical professional decisions based on possibly misrepresented historical data. This is autonomy-thwarting and subsequently demotivating for workers.

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References

  1. Gagné, M. et al. Understanding and shaping the future of work with self-determination theory. Nat. Rev. Psychol. 1, 378–392 (2022).

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Authors and Affiliations

  1. Indian Institute of Management, Kozhikode, India

    Anjana Karumathil

  2. Indian Institute of Management, Bangalore, India

    Ritu Tripathi

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  1. Anjana Karumathil
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  2. Ritu Tripathi
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Correspondence to Anjana Karumathil.

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Karumathil, A., Tripathi, R. Mere algorithms can be demotivating. Nat Rev Psychol 1, 682 (2022). https://doi.org/10.1038/s44159-022-00112-5

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