Grandfather Paradox in AI – Bias Mitigation & Ethical AI1

This submission offers a valuable exploration of the intersection between philosophical theory and real-world AI challenges. However, the explanation of the Grandfather paradox could be expanded to better clarify its relevance to the proposed mitigation strategies. Additionally, the connection between the paradox and each strategy could be more thoroughly explained to strengthen the overall argument.

There are also some gaps in the discussion on how ethical and fairness metrics will be applied in technology solutions. Specifically, the proposed techniques could benefit from a more detailed explanation of how they will address potential feedback bias. While the importance of mitigating bias is acknowledged, there isn’t enough clarity on how the approach will handle data that is already influenced by societal biases. A more robust strategy for addressing these concerns would strengthen the submission. Overall, the submission demonstrates a strong understanding of the complexities at the intersection of AI and ethics, and with a bit more detail in the areas mentioned, it could be even more impactful.

Clear and articulate problem with a plausible solution

The concepts of data validation, data provenance/ transparent, verifiable data handling all give a very good reason to use blockchain rather than being an ad-hoc addition for novelty value

Coluld benefit with detail on how smaller organizations or under-resourced sectors could adopt these measures without excessive cost. Including examples of pilot implementations would also be useful