The data deluge
As technology penetrates further into everyday life, we’re creating lots of data. (We could quote all the Gartner and Forrester made-up numbers, but we’ll spare you.)
Businesses are scrambling to find data scientists – a hybrid of computer scientist, statistician, and domain expert – to make sense of all this data and turn it into better decisions.
Businesses aren’t alone. Data science – we use the current buzzword, but earlier ones such as analytics, machine learning, and data mining also apply – could transform how governments and nonprofits tackle society’s problems.
By analyzing data from police reports to website clicks to sensor signals, governments are starting to spot problems in real-time and design programs to maximize impact. More nonprofits are measuring whether or not they’re helping people, and experimenting to find interventions that work.
We’re just realizing the potential of using data for social impact and face several hurdles to it’s widespread adoption:
- Most governments and nonprofits simply don’t know what’s possible yet. They have data – but often not enough and maybe not the right kind.
There are too few data scientists out there – and too many spending their days optimizing ads instead of bettering lives.
To make an impact, we need to show social good organizations the power of data and analytics. We need to work on analytics projects that have high social impact. And we need to expose data scientists to the problems that really matter.
That’s exactly why we’re doing the Eric and Wendy Schmidt Data Science for Social Good summer fellowship at the University of Chicago.
We want to bring three dozen aspiring data scientists to Chicago, and have them work on data science projects with social impact.
Working closely with governments and nonprofits, fellows will take on real-world problems in education, health, energy, transportation, and more.
Over the next three months, they’ll apply their coding, machine learning, and quantitative skills, collaborate in a fast-paced atmosphere, and learn from mentors in industry, academia, and the Obama campaign.
The program is led by a strong interdisciplinary team from the Computation institute and the Harris School of Public Policy at the University of Chicago.
Google Chairman Eric Schmidt and Rayid Ghani hatched the idea in March, and we put out a call for applications immediately.
The response was overwelming: 550 aspiring data scientists applied from all over the world.
We read every application and interviewed nearly a hundred people. In the end, we picked 36 amazing fellows. (That’s 6.545% of the applicant pool, for you bean counters.)
They’ll be flying to Chicago from all across the country at the beginning of June and will spend the next three months with us.
The fellows are a mix of grad students and undergrads.
They strike a good balance of the computer science, machine learning, statistics, and domain expertise skills that make up data science.
This is deliberate: we don’t believe in the all-knowing, do-everything data scientist rock star. We’re going to focus on building data science teams this summer.
Our deepest thanks to everyone who applied, and everyone who’s helped the fellowship in ways big and small.
This is our first time running this program, and we’re still figuring things out. There have been a few kinks along the way. We’re busy fixing them – thanks for your patience!
- To follow our work and learn about our projects, keep watching this space.
We can’t wait to show you how data science can better the world – and why Chicago is the place the do it.