Responsible AI

Data Security and Privacy

Data Protection: Implement robust encryption protocols for data at rest and in transit. Regularly update and patch security systems to protect against breaches and unauthorized access.
Privacy by Design: Incorporate privacy considerations into the design and development of AI systems from the outset. Ensure that data anonymization and pseudonymization techniques are employed where appropriate.
Compliance: Adhere to relevant data protection regulations such as GDPR, CCPA, and other local laws. Conduct regular compliance audits and impact assessments.

Learn more about Skan's privacy-first product architecture

Accuracy and Quality: Ensure the data used for AI training and operation is accurate, complete, and up-to-date. Establish data validation processes to detect and correct errors.
Traceability: Maintain detailed records of data sources and changes. Implement data lineage tracking to trace the origin and transformation of data throughout its lifecycle.
Accountability: Assign responsibility for data integrity to designated roles within the organization. Regularly review and update data management policies.

Model Validation: Implement rigorous testing and validation protocols for AI models to ensure they perform accurately and reliably. Regularly retrain models with new data to maintain their effectiveness.
Bias Mitigation: Identify and mitigate biases in AI models. Use diverse datasets and conduct fairness assessments to ensure equitable treatment across different user groups.
Transparency: Provide clear explanations of how AI models make decisions. Develop user-friendly documentation and interfaces that allow stakeholders to understand and trust AI outputs.

Purpose Limitation: Use AI technologies strictly for their intended and stated purposes. Avoid deploying AI in ways that could harm individuals or society.
Human Oversight: Ensure that AI systems have appropriate human oversight and intervention capabilities. Establish protocols for human review of critical AI decisions.
Continuous Improvement: Foster a culture of continuous learning and improvement. Stay updated with the latest advancements in AI ethics and incorporate best practices into Skan’s operations.