Responsible AI

Our principles

AI at HealthTasks is built for competency-based education programs that need scale without surrendering academic integrity.

• Augment educators, never replace them

  AI handles first-pass work at scale. Faculty retain judgment, overrides, and final accountability for student outcomes.

• Human oversight by design

  Critical workflows keep educators in the loop. Faculty can review, edit, appeal, and disable AI features when your program needs full manual control.

• Protect educational and clinical data

  AI processing follows the same FERPA- and HIPAA-aligned controls as the rest of the platform, with clear limits on how model providers may use your data.

• Prefer evidence over claims

  We publish validation studies, ROI case studies, and methodology so partners can evaluate how AI performs in real programs. Demos alone are not enough.

Human oversight

Educators remain accountable for assessment quality. AI can draft, score, summarize, or surface patterns. Faculty decide what stands. In skills checkoffs, educators can intervene on appeals or structural divergence rather than re-grading every submission by hand. They still retain full override authority.

Programs can also turn AI features off when institutional policy or accreditation context requires a fully manual path.

Data, privacy, and model providers

Our AI features are powered by Google Gemini API under contractual data-processing terms. Google does not use your prompts or responses to improve their products. Prompt and response logging is limited to abuse detection and required legal disclosures, as described in our Privacy Policy.

Platform infrastructure is designed for FERPA- and HIPAA-aligned use, including encryption and Business Associate Agreements with relevant cloud providers. AI-processed data follows the same retention limits as other personal data on the Service.

More details are in our Privacy Policy and Terms.

Safeguards

Practical controls we build into AI-assisted workflows:

• Educator override and appeal paths on AI-assisted grading
• Optional disablement of AI features for institutions that need it
• Media-quality checks that fail closed when recordings are unsuitable for evaluation
• Institution-controlled environments and role-based access
• Google does not use your prompts or responses to improve their products
• Encryption in transit and at rest, with BAAs covering HIPAA-relevant infrastructure

What we will not do

• Replace faculty judgment as the final authority on student competency
• Train public foundation models on your institutional content without contractual controls
• Present AI output as professional medical, legal, or accreditation advice
• Hide where AI is used in a workflow or how educators can intervene

Evidence

For validation studies, case studies, and related publications, see our Research.

Questions

Contact [email protected] or visit our contact page.