In part 1 of this blog post, we discussed the need to be mindful of data bias and the resulting consequences when certain parameters are skewed. Surely there are ways to comb through the data to minimise the risks from spiralling out of control. We need to get to the root of the problem. In 2019, the Gradient institute published a white paper outlining the practical challenges for Ethical AI.
For Cloudera ensuring data security is critical because we have large customers in highly regulated industries like financial services and healthcare, where security is paramount. Also, for other industries like retail, telecom or public sector that deal with large amounts of customer data and operate multi-tenant environments, sometimes with end users who are outside of their company, securing all the data may be a very time intensive process.
