mlsanityData to 14 Oct 2026

"This is not a data problem": Algorithms and Power in Public Higher Education in Canada

arXiv 2403.13969 ↗First posted 20 Mar 2024cs.HC cs.AI cs.CYcited by 6

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Abstract (arXiv)

Algorithmic decision-making is increasingly being adopted across public higher education. The expansion of data-driven practices by post-secondary institutions has occurred in parallel with the adoption of New Public Management approaches by neoliberal administrations. In this study, we conduct a qualitative analysis of an in-depth ethnographic case study of data and algorithms in use at a public college in Ontario, Canada. We identify the data, algorithms, and outcomes in use at the college. We assess how the college's processes and relationships support those outcomes and the different stakeholders' perceptions of the college's data-driven systems. In addition, we find that the growing reliance on algorithmic decisions leads to increased student surveillance, exacerbation of existing inequities, and the automation of the faculty-student relationship. Finally, we identify a cycle of increased institutional power perpetuated by algorithmic decision-making, and driven by a push towards financial sustainability.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 16 of its 71 references that are in the map. First posted on arXiv 20 Mar 2024.

Builds on

16 of 71 references.

References · 16

  1. 2019A Survey on Bias and Fairness in Machine Learningcited by 1,917
  2. 2019A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cyclecited by 193
  3. 2020The Problem with Metrics is a Fundamental Problem for AIcited by 37
  4. 2022A Validity Perspective on Evaluating the Justified Use of Data-driven Decision-making Algorithmscited by 30
  5. 2023Understanding Frontline Workers' and Unhoused Individuals' Perspectives on AI Used in Homeless Servicescited by 29
  6. 2022The Principles of Data-Centric AI (DCAI)cited by 26
  7. 2020A Human-Centered Review of the Algorithms used within the U.S. Child Welfare Systemcited by 23
  8. 2021A Framework of High-Stakes Algorithmic Decision-Making for the Public Sector Developed through a Case Study of Child-Welfarecited by 23
  9. 2021Algorithms and Decision-Making in the Public Sectorcited by 20
  10. 2023Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberationcited by 17
  11. 2023Algorithmic Harms in Child Welfare: Uncertainties in Practice, Organization, and Street-level Decision-Makingcited by 12
  12. 2022An Uncommon Task: Participatory Design in Legal AIcited by 10
4 more
  1. 2023Rethinking "Risk" in Algorithmic Systems Through A Computational Narrative Analysis of Casenotes in Child-Welfarecited by 10
  2. 2023Counterfactual Prediction Under Outcome Measurement Errorcited by 10
  3. 2022Unpacking Invisible Work Practices, Constraints, and Latent Power Relationships in Child Welfare through Casenote Analysiscited by 8
  4. 2023A Human-Centered Review of Algorithms in Decision-Making in Higher Educationcited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 3.

6 papers.

  1. 2025Talking About the Assumption in the Roomcited by 2
  2. 2025How do datasets, developers, and models affect biases in a low-resourced language?: The Case of the Bengali Languagecited by 0
  3. 2025Advancing Data Equity: Practitioner Responsibility and Accountability in NLP Data Practicescited by 0
  4. 2026Bureaucratic Silences: What the Canadian AI Register Reveals, Omits, and Obscurescited by 0
  5. 2026Fairness Audits of Institutional Risk Models in Deployed ML Pipelinescited by 0
  6. 2026Fairness Theatre: Evaluating Post-Hoc Fairness Interventions in Vendor-Controlled Early Warning Systemscited by 0