1. Transparency and Explainability
• Facilitating auditability by keeping a comprehensive record of data provenance, procurement, preprocessing, lineage, storage, and security.
1. Transparency and Explainability
Deployers should, however, note that auditability does not necessarily entail making certain confidential information about business models or intellectual property related to the AI system publicly available.
3. Security and Safety
security and Safety
3. Security and Safety
AI systems should be safe and sufficiently secure against malicious attacks.
3. Security and Safety
security refers to ensuring the cybersecurity of AI systems, which includes mechanisms against malicious attacks specific to AI such as data poisoning, model inversion, the tampering of datasets, byzantine attacks in federated learning5, as well as other attacks designed to reverse engineer personal data used to train the AI.
3. Security and Safety
Security refers to ensuring the cybersecurity of AI systems, which includes mechanisms against malicious attacks specific to AI such as data poisoning, model inversion, the tampering of datasets, byzantine attacks in federated learning5, as well as other attacks designed to reverse engineer personal data used to train the AI.
3. Security and Safety
Deployers of AI systems should work with developers to put in place technical security measures like robust authentication mechanisms and encryption.
3. Security and Safety
Just like any other software, deployers should also implement safeguards to protect AI systems against cyberattacks, data security attacks, and other digital security risks.
3. Security and Safety
Just like any other software, deployers should also implement safeguards to protect AI systems against cyberattacks, data security attacks, and other digital security risks.
3. Security and Safety
Just like any other software, deployers should also implement safeguards to protect AI systems against cyberattacks, data security attacks, and other digital security risks.
3. Security and Safety
It is also important for deployers to make a minimum list of security testing (e.g.
3. Security and Safety
vulnerability assessment and penetration testing) and other applicable security testing tools.
5. Privacy and Data Governance
Privacy enhancing technologies include, but are not limited to, differential privacy, where small changes are made to raw data to securely de identify inputs without having a significant impact on the results of the AI system, and zero knowledge proofs (ZKP), where ZKP hide the underlying data and answer simple questions about whether something is true or false without revealing additional information