This interview, our discussion, and our views are now a part of the global data set.
According to Laura, data is impartial. It doesn't have human-like qualities. The unclean data, the unstructured data is the best mirror to ourselves. Ultimately, we are responsible for the data-sets that are pulled into other organizations. i.e. we buy, we post, we upload, we like, we repost.
We can clean data to redefine a better 'prettier' answer, but if we want to fix the data, we may want to shift that focus to ourselves. "... you play an active role whether you have known it or not. You have been in it all along", Laura. "We focus on all the things that can go wrong (when discussing AI technologies), but there are benefits that can be used for good with the right gaurd rails. We have to sift through the not good in order to acheive the good", Laura.
Additional Topics Discussed: - Definition of ethics - Applying ethic concepts to AI technologies - What does it mean to be a human in today's world - Moral decisions and consequences - Bias exists comes from us, the human interaction - Broken mirror theory, Laura's theory based on years or observation and reflection - AI algorithms are not entirely responsible for all the bias themes - Ethics look at the harm when the result provide the wrong answer that is harmful - Ethics-washing - we always want the pretty version without the work - Books: How to Lie with Statistics & Merchants of Doubt - Transparency Fact Sheet - Are we missing anything? - Regulations are written after innovation, i.e. Copyright Act, written in 1976 - Policies.The future requires dedicated resources to revise policies on demand or every quarter. - Right, good, fair, and just - Laura' answers the question, 'what can someone do to start thinking differently about ethics, that impacts us personally' - Protecting your images, what your have contributed yourself you may not have thought much about until now
https://www.linkedin.com/in/lmiller-ethicist/
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