Understanding society in terms of reinforcement learning

Creating models which understand causal inference and can reason

Data is being used to train the algorithms which are controlling our society. we have the ability to include the nuance of our society to create more just systems and create a real American Dream.

This talk focuses on how we can examine the world that we live in and the injustice at play within it. Given the nuance of this society, we need algorithms which pull data from multiple sources and can infer how to interpret that data in a just way.

We have yet to see this in action because there are so many facets of the society which operate in a silo, but once we start pulling that data together to understand the causal inference from said metadata we can begin to see the reason behind the dysfunction.

This talk will explore applications in terms of the criminal justice system and the health care system. Some of the examples will explore applications in metabolite analysis and human diagnostics in terms of public health and youth criminality in terms of poverty and educational outcomes.