Data can be immensely powerful in understanding and addressing complex social issues, but only when you have the right people at the table working together to use it. Applying data science for good requires not only bringing together relevant data sets, but also relevant decision makers, technical and issue area experts, funders and advocates that can inform and help co-design solutions that will have an impact.
After three years of running solely volunteer efforts, we realized that there was huge potential to make social impact if we devoted ourselves full time to building these collectives of decision makers. That’s why we are thrilled to announce the launch of our newest initiative, DataKind Labs, which was designed to convene stakeholders across sectors to determine how data science might be applied to address social issues at a macro level and then work together on long-term projects to make it happen.
Our lead DataKind Labs data scientist, Erin Akred, has been busy scoping and defining our first project in partnership with Microsoft and its Tech & Civic Engagement Group to support the Vision Zero movement in the U.S., reducing traffic-related deaths and severe injuries to zero in Vision Zero Cities nationwide.
We're hiring a data science fellow to help fuel the work ahead - read on to learn more!
Vision Zero is an initiative born in Sweden in the 1990’s that aims to reduce traffic-related deaths and serious injuries to zero. Vision Zero believes that crashes are predictable and preventable, which means there is great potential for data and technology to help uncover patterns of incidents so governments can take action to prevent fatalities before they occur.
While it is known that children, senior citizens and people of lower socioeconomic status are disproportionately affected by traffic incidents, it’s unclear what interventions and policy changes are most effective to protect these vulnerable groups and others from traffic-related fatalities.
A team of data scientists led by our own Erin Akred will be working to help answer this question, leveraging newly-available datasets including open city data, citizen crowd-sourced data as well as data from private companies to identify patterns and predict where traffic and pedestrian fatalities are likely to occur. This will help inform cities’ efforts so they can best allocate their resources – including improvements to infrastructure, enforcement, education efforts and policy changes – to prevent severe traffic collisions and keep all road users safe.
