Ideas

Fighting Archetypal Overfitting of Data

Overfitting is common-place in machine learning. But, in confining ourselves to graphical data explorations, we are creating a risk for another form of overfitting, notably archetypal overfitting. In this post, I outline why this is a problem, and how to reduce overfitting through better data analysis.

Read

We Need a New Maps App

We need a new maps app. Our maps define our cities, and well, Google and Apple just don't make the city shine. They get you from point A to point B fine, but there is so much more to urban life than that.

Read

Personalizing Campaigns Though Machine Learning

Machine learning, the field upon which the vast majority of artificial intelligence systems depend on, has tremendous potential to do good if harnessed correctly. When used properly, algorithms can allow for better timed phone calls, and conversations directly related to a voter's interests, and hopefully, less robocalls in the middle of dinner.

Read
Ideas

Time for Digital Citizenship

The United States needs a new digital infrastructure. Looking to Estonia, and its recent approach to identification and virtual residency provides a model for America to follow. Perhaps among the greatest selling points of this program, is that the federal government need not be the administrator of it, rather this could be tested and tweaked state-by-state.

Read