Originally published in KDNuggets, April, 2020.
Many AI models rely on historical data to make predictions on future behavior. So, what happens when consumer behavior across the planet makes a 180 degree flip? Companies are quickly seeing less value from some AI systems as training data is no longer relevant when user behaviors and preferences change so drastically. Those who are flexible can make it through this crisis in data, and these four techniques will help you stay in front of the competition.
COVID-19 is all over the news. And rightfully so. It’s a tremendously important topic. And it’s having massive effects on the accuracy of AI models.
Before we dive into how AI has changed, let us first say from all of us here at Bennett Data Science that we sincerely hope that you are well and getting through the hardships as best you can.
COVID-19 and AI
Businesses are undergoing tremendous change. It’s hard to find an industry that isn’t drastically affected by COVID-19. In attempts to keep up with either precipitous constriction or massive immediate scaling, companies are seeing their tried and tested methods of interacting with their customers rendered almost meaningless. That means marketing personalization, lifetime value calculations, product recommendations, and churn models, are all inaccurate at best and misleading at worst.
AI uses past actions to predict future events. And nothing in the (recent) past is anything like what we’re experiencing today. So AI is confused. It’s as though we’re all suddenly speaking a new language to Alexa or Siri or Google Assistant. Of course they wouldn’t “understand”. They’d be useless. Global purchase behavior is now speaking a different language. And AI doesn’t understand.
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