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Artificial Intelligence (AI) And The Need Centralizing Worldwide Efforts
No one gets angry at a mathematician or a physicist whom he or she doesn’t understand, or at someone who speaks a foreign language, but rather at someone who tampers with your own language — Jacques Derrida
Almost every Artificial Intelligence (AI) expert agrees that an AI algorithm is only as good as the dataset it works on. Secondly, the larger, more diverse and more global a dataset is, the better the AI algorithm performs. Thirdly, there is a lot of bias that can be introduced in algorithms by using skewed datasets. This bias can wreak havoc in some cases. However, almost everyone disagrees on what the definition of privacy should be, what level of access should be granted to whom and what constitutes good data. Normally, centralization is a sign of crisis. In the past, resources have been pooled to respond to industry regulations. For example, the Basel III accord, the COSO CoBit framework etc. are all good cases of standardization and pooling together of resources to deal with regulations. While AI is not yet subject to stringent regulations and rightfully so-strict laws can stifle innovation, this article makes a case for pooling of…
