A blog about Product Management, Data Management and Self-Driven Learning
Reflecting on the decline of my personal blog during the pandemic, driven by changes in search rankings and competition made me realise that there is more to the system than meets the eye. Inspired by a podcast featuring Cory Doctorow's concept of "enshittification," I now am determined to empower others to regain control over their online experiences and focus. Future posts will explore strategies for online protection.
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.
The post discusses the importance of quality data in AI product management, outlining the DASUD model: Design, Acquire, Store, Use, and Delete. It emphasises defining success, collecting accurate data, securely storing it, ethical use, and timely deletion. Trust in data is crucial for effective AI implementation, ensuring good governance.
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 