Data Ethics evaluates how a company collects, generates, analyses, shares and monetises data in a manner that respects human rights, fosters trust and minimises harm. It covers:

• purpose limitation & proportionality - gathering and processing only the data needed for a legitimate, clearly stated objective, with regular reviews to prevent mission creep or function-creep;
• fairness & bias mitigation - assessing datasets and analytics (including AI/ML models) for discriminatory patterns, ensuring inclusive representation and equitable outcomes;
• transparency & agency - providing stakeholders with plain-language explanations of data practices, meaningful consent choices, access / correction rights and clear opt-out pathways;
• privacy & security by design - embedding encryption, anonymisation, data-minimisation and robust access controls throughout the information-lifecycle, aligned with GDPR, CCPA/CPRA, ISO 27701 and NIST Privacy Framework principles;
• responsible data sharing & monetisation - evaluating third-party requests, partnerships and business models against ethical guidelines, contractual safeguards and societal impact assessments;
• governance & accountability - board-level oversight, cross-functional data-ethics councils, impact-assessment checklists, incident-response protocols and transparent reporting of key metrics (e.g., ethical reviews conducted, bias issues resolved, stakeholder grievances addressed).