Staggering predictions were shared at the 2017 Gartner Symposium earlier this month. By 2021 Gartner predicts, artificial intelligence augmentation will generate $2.9 trillion in business value and recover 6.2 billion hours of worker productivity. It is no wonder why companies are moving swiftly to embrace these emerging technologies to assist people and attain a competitive advantage.
Automated machine learning represents a truly transformational opportunity. Next generation business solutions powered by automated machine learning are an agent of change. Automated machine learning helps organizations better serve customers, improve business processes, solve complex problems and optimize outcomes when and where decisions are made. The goal isn’t necessarily to replace humans – it is to help them.
Decrypting the black box
Human resistance to change and decision automation is reasonable and rife. To ease fears and skepticism, start small with a well-known decision process that is not overly complex. Let the machine generate predictions and task humans with comparing actual results. In addition to validating predictions, delve into how the machine makes predictions.
Deciphering the secret sauce of black-box machine learning used to be challenging if it was at all possible. That problem is beginning to abate. Modern machine learning solutions today are becoming more transparent due to increased legislation such as the General Data Protection Regulation (GDPR). Innovations in this space include visibility into predictive model designs, data transformation steps, applied algorithms and triggered prediction data values. Revealing how machines make automated decisions fosters human trust and adoption.
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