Data Science for Social Good Adds UK Locations, Opens 2019 Applications Now seeking students, staff and project partners for program’s seventh year The 2019 edition of the Data Science for Social Good (DSSG) Summer Fellowship will feature two new international sites in the UK, through collaborations with The Alan Turing Institute, the University of Warwick, [...]
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Improving Workplace Safety in Chile through Proactive InspectionsEvery year, thousands of Chileans are killed or injured in work-related accidents. This was recently brought to light during the 2010 Copiapó mining accident. Chile’s labor ministry, Dirección del Trabajo (DT), is tasked with increasing workplace safety through inspections and enforcement. But DT’s inspections are largely reactive: complaints come [...]
João Caldeira, Alex Fout, Aniket Kesari, Raesetje Sefala UPDATE: We are pleased to announce that this project team won a Highlighted Paper Award at the AI For Social Good NIPS2018 Workshop! Congratulations to the Jakarta Fellows! Improving Traffic Safety in Jakarta Through Video Analysis The World Health Organization (WHO) estimates that over 1.25 million people [...]
Jerica Copeny, Samantha Fu, Rebecca Johnson, and Teng Ye Tackling Tenant Harassment in New York City: A Data-Driven Approach This summer, our team of Data Science for Social Good fellows at the University of Chicago has partnered with the New York City Mayor’s Public Engagement Unit (PEU) with the goal of helping them better target [...]
2018 Data Science for Social Good Goes Global, Tackling Diabetes, Tenant Harassment, Unemployment, and More Fellows in Chicago and Portugal adapt data science and AI approaches for projects with non-profits and international governments In Chicago and Portugal this summer, the science behind self-driving cars, virtual assistants, and targeted advertising will be repurposed for nobler pursuits: [...]
Human Lessons Learned Implementing Early Intervention Systems in Charlotte and Nashville This is the third in our three-part series “Lessons Learned Deploying Early Intervention Systems.” The first part (you can read it here) discussed the importance of data science deployments, while the second blog post in the series discussed the technical challenges related to the [...]
Tech Lessons Learned Implementing Early Intervention Systems in Charlotte and Nashville This is the second in our three-part series “Lessons Learned Deploying Early Intervention Systems.” The first part (you can find it here) discussed the importance of data science deployments. For the past two years, we have worked with multiple police departments to build and [...]
Lessons Learned Implementing Early Intervention Systems in Charlotte and Nashville, Part 1 From the company’s creation, Netflix has relied on the scalability and accuracy of machine learning to deliver content and turn profits. One way Netflix uses machine learning is to recommend movies to its users. A model that provides accurate and tailored recommendations at [...]
Representativeness Analysis: How Our Data Reflects the Real Labor Market Dynamics This month, we will discuss the representativeness of Data@Work Research Hub data. The Data@Work Research Hub is a collection of public datasets produced by the Open Skills Project from a growing pool of public and private administrative data sources, such as job postings, resumes, [...]
Introducing the Training Provider Outcomes Toolkit Trying to find a good job training program can be daunting. How do you know if the skills they teach are valuable in the job market? And how can you be sure they’re doing a good job of teaching those skills? Especially, when the costs can be high. It [...]