There has been a lot of focus and concern around bias in technology. Recent research has tried to create less biased algorithms, less falsely represented machine learning accuracy and demonstrate how artificial intelligence (AI) can become corrupted with bad data. This interesting and important information came to us from TDWI in their article, “Data Digest: AI Bias, Machine Learning Lies, and Poisoning AI.”
It is no longer conjecture, there is bias in AI and other smart technologies. Scientists are working on ways to reduce and eliminate it. They have developed a framework to make computer algorithms safer to use without creating bias based on race, gender or other factors. The challenge is to make it possible for users to tell the algorithm what kinds of pitfalls to avoid — without having to know a lot about statistics or AI.
Biases originate in the real world. An algorithm uses historical data. When that data is a result of human bias the pattern is hard to break.
Melody K. Smith
Sponsored by Access Innovations, the world leader in thesaurus, ontology, and taxonomy creation and metadata application.
