Product Pay offs in Machine Learning

Ash Fontana, Managing Partner, Zetta Venture PartnersUber's cars are crashing, Microsoft's bots abusing people on twitter and U.S. judges sentencing people using biased algorithms. Machine learning models rely on probabilistic assumptions because they're trying to model things that are uncertain. Probabilistic assumptions don't always hold, so the models don't always work. We should keep this in mind when building machine learning products so that we meet the expectations of our customers, at best, and avoid the unchecked use of machine learning in high-stakes situations, at worst. As a venture capital firm focused on intelligent software for the enterprise, we at Zetta Venture Partners have developed a framework for understanding the impact of products built on machine learning.