TalentVector AI Principles

Last updated: April 12, 2026

At TalentVector, we use AI to support innovation, learning, assessment, and talent development in a manner that respects human rights, democratic values, and applicable law. These AI Principles apply across our platforms, including www.talentvector.com, and set standards for our design, development, deployment, and use of AI systems in a practical and adaptable manner aligned with international standards.

These Principles apply to AI systems used internally by TalentVector and to AI-enabled services made available to customers, learners, candidates, employees, and other users. They apply across the AI lifecycle, including design, procurement, testing, deployment, monitoring, and improvement.

TalentVector is the market-facing brand and trade name of EdMyst Inc. References to “TalentVector,” “we,” “us,” or “our” in these Terms mean EdMyst Inc. d/b/a TalentVector.

1. Drive inclusive growth, sustainable development, and well-being

Engage in responsible stewardship of trustworthy AI in pursuit of beneficial outcomes for people and the planet, such as augmenting human capabilities and enhancing creativity, advancing inclusion of underrepresented populations, reducing economic, social, gender and other inequalities, and protecting natural environments, thus invigorating inclusive growth, sustainable development, and well-being. We aim to use AI in ways that are appropriate to the educational, assessment, and talent-development context, and to avoid outcomes that unlawfully disadvantage individuals or groups.

2. Human-centered values and fairness

Respect the rule of law, human rights, and democratic values, throughout the AI system lifecycle. These include freedom, dignity and autonomy, privacy and data protection, non-discrimination and equality, diversity, fairness, social justice, and internationally recognized labor rights.

Implement mechanisms and safeguards, such as capacity for human determination, that are appropriate to the context and consistent with the state of the art. We implement human oversight measures appropriate to the context, especially where AI outputs may influence educational, assessment, or talent-related decisions. We do not intentionally use AI for unlawful discrimination, prohibited manipulation, social scoring, or other uses that conflict with applicable law or fundamental rights protections. Where applicable, we consider risk-based regulatory frameworks, including the EU AI Act, which prohibits certain AI practices and imposes stronger controls for higher-risk systems.

3. Transparency and explainability

Commit to transparency and responsible disclosure regarding our AI systems; provide meaningful information, appropriate to the context, and consistent with the state of the art:

• (a)to foster a general understanding of AI systems
• (b)to make stakeholders aware of their interactions with AI systems
• (c)to enable those affected by an AI system to understand the outcome
• (d)to enable those adversely affected by an AI system to challenge its outcome based on plain and easy-to-understand information on the factors, and the logic that served as the basis for the prediction, recommendation or decision

Where appropriate, we make users aware when they are interacting with AI or when content, recommendations, or outputs are AI-assisted. We seek to provide clear information about the role of AI in our services, the nature of outputs, and appropriate channels for questions, feedback, or challenge. The EU AI Act specifically includes transparency obligations for certain AI systems, including situations where people should know they are interacting with AI.

4. Robustness, security and safety

AI systems should be robust, secure and safe throughout their entire lifecycle so that, in conditions of normal use, foreseeable use or misuse, or other adverse conditions, they function appropriately and do not pose unreasonable safety risk.

Ensure traceability, including in relation to datasets, processes and decisions made during the AI system lifecycle, to enable analysis of the AI system’s outcomes and responses to inquiry, appropriate to the context and consistent with the state of the art.

Apply a systematic risk management approach to each phase of the AI system lifecycle on a continuous basis to address risks related to AI systems, including privacy, digital security, safety and bias.

We apply testing, monitoring, and periodic review to help identify and mitigate risks relating to safety, privacy, cybersecurity, bias, reliability, and misuse. Where appropriate, we maintain records, traceability, and escalation processes to support investigation, remediation, and continuous improvement.

5. Privacy, Data Governance, and Security

We design and use AI systems in a manner consistent with applicable privacy and data protection requirements. We seek to apply data minimization, purpose limitation, access controls, and appropriate technical and organizational safeguards to personal and sensitive data used in connection with AI systems. Where required, we conduct privacy and risk assessments before deploying new or materially changed AI use cases.

6. Accountability

We are accountable for the proper functioning and governance of AI systems used in our business, and for adherence to these Principles, based on our role, the context, and the state of the art. We assign internal responsibility for AI oversight, risk review, and compliance, and we periodically review our AI uses, controls, and documentation. Accountability remains a core OECD principle for trustworthy AI.

7. Risk Classification and Review

We assess AI use cases based on their context, purpose, data use, and potential impact on individuals and organizations. Higher-risk use cases are subject to greater review, oversight, documentation, and control prior to deployment and during operation. This reflects current risk-based regulatory expectations for trustworthy AI governance. The EU AI Act is structured around a risk-based framework, and the OECD Principles continue to emphasize lifecycle risk management.

8. AI Literacy and Responsible Use

TalentVector seeks to ensure that relevant employees and stakeholders have an appropriate understanding of the AI systems they build, procure, deploy, or use. Training and awareness should be proportionate to the role, technical knowledge, and risk profile of the relevant AI system. Where applicable, regulatory guidance may require or encourage AI literacy measures for personnel involved in AI deployment or use.

9. Review and Updates

These AI Principles will be reviewed periodically and updated as needed to reflect changes in law, regulation, technology, and TalentVector’s services and platforms.