A blog about Product Management, Data Management and Self-Driven Learning
Generative AI complicates data deletion compared to traditional governance, as it involves multiple artefacts like logs and user memories. Organisations must define clear deletion policies for each artefact, including user-triggered options and emergency controls. Balancing auditability and privacy is crucial, necessitating regular reviews of retention policies for compliance and risk management.
Deploying Generative AI fundamentally alters creation and decision-making processes. Proper governance in its "Use" stage is essential to prevent risks such as hallucinated facts and harmful content. By categorising use cases into risk levels and implementing structured review processes, organisations can ensure safe and effective usage of GenAI technologies.
After launching the DASUD Framework, I am now focused on AI governance, emphasising the importance of understanding fundamental problems to govern efficiently. I highlight the risks of multi-agent systems compromising data security and stress collaborative governance solutions. The piece invites readers to seek guidance on Data Governance and related topics.
Free apps often seem costless, but they exploit personal data as their main revenue source. Users unknowingly grant access to sensitive information, which can be sold or used for targeted advertising. To safeguard privacy, it's crucial to review app permissions, read privacy policies, and choose privacy-focused alternatives.
Public Wi-Fi is convenient but poses significant security risks, including Man-in-the-Middle attacks, fake hotspots, and unencrypted networks. To enhance safety, users should employ VPNs, avoid sensitive activities, verify network legitimacy, and enable two-factor authentication. Staying informed and adopting security measures can help protect personal data while using public Wi-Fi.
Nigel D'Souza 