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"We often shorthand our explanation of AI bias by blaming it on biased training data. The reality is more nuanced: bias can creep in long before the data is collected as well as at many other stages of the deep-learning process."
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Decision Intelligence News
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Decision Intelligence News
AI/BI/CI/DI: Decision intelligence (DI) solves the world's most complex problems by connecting actions to outcomes. It connects collaborating human decision makers to knowledge and also to technologies like machine learning, AI, deep learning, visual decision modeling, complex systems modeling, big data, predictive analytics, UX design, statistical analysis, business intelligence, business process management, causal reasoning, evidence-based analysis, and more. See https://en.wikipedia.org/wiki/Decision_Intelligence. For an overview, see the webinar at http://youtu.be/XRTJt3bVCaE, http://www.lorienpratt.com, and the Decision Intelligence group: http://www.linkedin.com/groups?gid=205078. Also, my company offers DI and machine learning consulting services. See http://bit.ly/1X8O2zF to learn more. Don't miss the latest DI news! Sign up at subscribe.decisionintelligencenews.com. Curated by Lorien Pratt |
Bias in AI efforts seems to be introduced primarily by human constructs and our limited understanding of context and nuance. Whether it's in how we frame the problem we're trying to solve, or how we collect and prepare the data we're using without regard to how it might be implicitly biased, we need to recognize our role in injecting our, or our society's, biases into our efforts.