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EdTech Assessment Toolkit

Teacher Recruitment (Houston, US)

Algorithm matching model

The Houston Independent School District (HISD) in Texas, United States, has utilised AI technology in its teacher recruitment efforts. The district partnered with a company named TeacherMatch to implement an AI-powered applicant screening and matching system. The platform uses AI algorithms to assess and rank applicants based on their qualifications, experience, skills, and alignment with the district’s needs. The system analyses CVs, application materials, and responses to a set of questions, aiding in identifying the most promising candidates. The AI algorithms take into account various factors, including specific job requirements, candidate attributes, and the district’s historical data on successful teaching placements. The system provides a match score for each applicant, allowing the district to concentrate on the top-ranked candidates.

While AI is frequently used in hiring practices with the aim of increasing objectivity and fairness, it often overlooks the broader systemic inequalities that influence recruitment. Amazon, for instance, had to scrap its AI recruiting tool in 2018 as it systematically discriminated against women (Dastin, 2018). Research suggests that AI can reinforce bias, potentially exclude appropriate applicants who don’t fit the pre-set criteria, and that there’s an absence of comprehensive regulations governing AI’s role in employment processes. Moreover, companies often exaggerate the capabilities and downplay the limitations of AI-based recruitment tools (Drage & Mackereth, 2022).

Snapshot (July 2023)

System task/function: Teacher Recruitment
Model: Algorithm Matching
Deployment: AI recruitment tool / algorithmic matching of teacher skills & position requirements
Location of application: Houston (US)
Rationale for introduction: Automate the recruitment process and find teacher matches more efficiently
Vendor: TeacherMatc, Powerschool
Pricing: N/A
Data and computation: Candidate data
Inequalities/harms: discrimination of groups historically not considered as ‘ideal’ candidates
Status: Active
Authority/regulation: District level
Unintended consequences: Locks the recruitment of teachers in a permanent present where future capabilities are hard to address due to the use of historical data
Sanction/redress: N/A

References/further reading

Barrett, J., & Convery, S. (2023). Robot recruiters: can bias be banished from AI hiring? Retrieved from

Dastin, J. (2018). Amazon scraps secret AI recruiting tool that showed bias against women. Retrieved from

Drage, E., & Mackereth, K. (2022). Does AI Debias Recruitment? Race, Gender, and AI’s “Eradication of Difference”. Philosophy & Technology, 35(4), 89. doi:10.1007/s13347-022-00543-1

Powerschool. (2022). Candidate Assessment. Retrieved from