Leading EdTech Vendor: Case Study
Challenge:
A leading EdTech vendor comes under intense public and regulatory scrutiny for potential bias in its core AI product, eroding clients’ trust and initiating costly lawsuits and Senatorial inquiries.
Solution:
BABL AI is engaged to help develop a responsible AI strategy including:
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Conduct a bias assessment of their core face detection algorithm, focusing on mitigating potential sources of societal bias in training data.
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Develop and execute an ethical risk and impact assessment, identifying key ethical risks and governance mechanisms for mitigating those risks.
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Implement a data quality and model monitoring program, with demonstrated success measured through continuous improvement and reduced bias in production algorithms.
Impact:
Through iterative improvement and transparent bias assessment documentation, the vendor can build public trust, address regulatory inquiries in good faith, and retain critical clients.
