AI and machine learning: Looking beyond the hype Posted on : Dec 16 - 2017

In every federal agency, critical insights are hidden within the massive data sets collected over the years. But because of a shortage of data scientists in the federal government, extracting value from this data is time consuming, if it happens at all. Yet with advances in data science, artificial intelligence (AI) and machine learning, agencies now have access to advanced tools that will transform information analysis and agency operations.

From predicting terror threats to detecting tax fraud, a new class of enterprise-grade tools, called automated machine learning, have the power to transform the speed and accuracy of federal decision-making through predictive modeling. Technologies like these that enable AI are changing the way the federal government understands and makes decisions.

To use tools like automated machine learning to their full potential to accelerate and optimize data science in the federal government, it’s important to start by understanding the terms used and what they mean.

Data science — the art of analyzing data

Data science is a broad term, referring to the science and art of using data to solve problems. Rooted in statistics, this practice blends math, coding and domain knowledge to answer specific questions from a certain data set. Advances in computing power have transformed this from calculator-based statistical modeling into predictive algorithms that transform historical analysis into forecasts about future behaviors.

Even the very first U.S. census conducted in 1790, using quill and paper, collected about 20 megabytes of data. Today the Census Bureau has a backlog of nearly 400 billion data points, offering a wealth of insights into the demographics and behaviors of a constantly-evolving population. And while the quantity of data has grown over time, data scientists are in short supply, leaving a large gap in the amount of data and insights available, and the people needed to derive those insights from the data.

AI — filling the gaps in data science

AI overlaps with data science by giving machines the ability to interact as though a human engaged in the process. The power for the machine to copy intelligent human behavior by applying mathematical models to extrapolate information from data is at the core of AI. However, AI goes further in the sense that it can make decisions and take action through these machines -- whether on premise in a data center or in the cloud. View More