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How to Use Behavioral Economics to Turn Soft Data into Actions

Language and the Machine

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Humans instinctively seek patterns, but our approach is oftentimes biased and ineffective. We miss the patterns that are significant and frequent and convince ourselves others exist when they are just random noise.

A goal of machine learning is to find patterns, and extend influence to improve systems with automation and analysis with the aid of artificial intelligence. While we have come a long way in applying these technologies to automate a variety of systems and personalize our online lives, the progress for significant behavior change beyond our purchase history and news feed is lacking.

Behavioral economics can be interpreted as the science of improved decision-making and is at the forefront of examining our wide array of human biases. By combining the power of Artificial intelligence and machine learning with real-time active and passive behavioral data we will give context to our decision making habits and can develop solutions that will modify them for the better.

Only then will we realize our true potential to routinely behave in ways that continually improve our lives on a personal, social, and societal level. At #SMWNYC, a panel of AI experts, psychologists, and data scientists discussed the progression of AI and Machine Learning (ML) in relation to behavioral economics, and how this technology can help address and even solve societal issues.

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