Pearl Education develops and deploys AI-enabled features in its Products with K-12 school districts and state education agencies in mind. The students served by these programs deserve tools that are fair, safe, and transparent. This page describes the principles that guide how Pearl builds, evaluates, and governs AI features. Pearl’s AI features are in-product analytics and insight tools (offered under the name Sparks) for administrators and instructors; students do not interact with AI in the Products.

These principles apply to the AI-enabled features described in Pearl’s AI Use Disclosure and are operationalized through the processes described in Pearl’s AI Risk and Bias Review.

Transparency

Pearl discloses where and how AI is used in its Products. Administrators and the districts and state agencies that contract with Pearl can understand which features are AI-enabled, what data those features process, and how their outputs should be interpreted. Pearl identifies AI-assisted outputs within the platform so that administrators and instructors know when they are working with AI-generated content or recommendations.

This AI documentation — covering use disclosure, data handling, principles, and risk governance — constitutes Pearl’s published AI documentation referenced in its customer agreements (MSA §7.1).

Fairness

Pearl’s AI features are designed to support all students equitably. Before deploying AI features that affect how program data is surfaced to educators and administrators, Pearl evaluates whether the feature could produce disparate outcomes across student populations — including by race and ethnicity, gender, grade level, or program type — and takes corrective action where concerns are identified.

Pearl does not use AI to screen, score, or rank students in ways that limit their access to educational services without Customer review and oversight.

Accountability

Pearl is accountable for the AI features it deploys. Pearl’s product and technical teams maintain governance processes for AI feature development and release. Pearl does not shift accountability for AI-driven outputs onto its customers. District and SEA customers retain control over how AI-generated insights are used within their programs; Pearl provides tools to inform human decision-making, not to replace it (MSA §7.1).

Safety

Pearl does not deploy AI features designed to harm students or produce outputs that are damaging, misleading, or inappropriate for a K-12 educational setting. Before release, AI features are reviewed for safety, accuracy, and appropriateness — including the risk of generating harmful, inaccurate, or biased outputs in context. Pearl’s AI features are advisory and informational; they support human decision-making and are not designed to make consequential decisions about students autonomously.

Data Minimization

Pearl applies data-minimization principles to AI feature design. AI features are built to process the minimum data necessary to deliver a useful result. Pearl does not design AI features to collect Student Data beyond what is needed to provide the Services.

Pearl does not use identifiable Student Data, curriculum content, session recordings, or other Customer Content to train AI models. De-identified and aggregated data may be used consistent with Pearl’s agreements — specifically, the de-identification standard and research use rights in MSA §6 and DPA Article V — but this is distinct from using identifiable Student Data for AI model training. For more, see AI Data Handling.

Human Oversight

Pearl’s AI features are designed with human-in-the-loop principles in mind. AI-generated outputs — such as program alerts, engagement summaries, or natural-language analytics — are surfaced to administrators and instructors for their review and professional judgment. Administrators and instructors remain in control of how they respond to AI-generated information. Pearl staff maintain oversight of AI feature behavior in production and respond to anomalous outputs or customer-reported concerns.

Pearl does not use AI to make autonomous, consequential decisions about students’ educational access or outcomes.

Continuous Improvement

Pearl monitors AI features in production and incorporates feedback from customers and Authorized Users to improve accuracy, fairness, and usefulness. Pearl’s responsible AI practices evolve alongside changes in technology, educational research, and applicable law and regulation.

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Questions or concerns about Pearl’s AI practices can be submitted through the contact form at poweredbypearl.com or sent to responsibleai@poweredbypearl.com, which routes to Pearl’s privacy team (privacy@poweredbypearl.com).