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Lies and Statistics Today, AI techniques such as Machine Learning and Deep Learning are being used in more and more critical decision making processes that effect people's lives but there is a growing alarm that these techniques are innately prone to reflect human bias. These concerns are valid. As a statistical process, ML can only learn patterns that already exist in the data sets they are trained on and these are by and learn large vast collections of documents written by and for humans and as such reflect all the attitudes people have about one another.  ML does not understand the meaning of the words in the data set and so cannot apply context. But whether the bias is in the data set or the algorithm designer, the bottom line is that making decisions based solely or largely on statistics is inherently problematic. The famous quote popularized by Mark Twain which he attributed to Benjamin Disraeli comes to mind,  "There are three kinds of lies: lies, damned lies, and statistics." Our technology, Machine Knowledge, does understand what people are saying and applies context naturally and automatically making critical distinctions between subjective experience and emotion, and objective facts. New Sapience Founder Bryant Cruse and author Lynn Woodland have a very interesting conversation about the unique resistance of sapiens to reflect human prejudices and bias.