Presented By O'Reilly and Cloudera
Make Data Work
Sept 29–Oct 1, 2015 • New York, NY

Data Science for Social Good conference sessions

Be sure to check out Bloomberg's Poster Sessions and Reception: Bloomberg will be featuring over 30 poster projects in Booth #857, that share success stories, challenges, and visions for the future of applications of data science to problems around social good.

1:15pm–1:55pm Wednesday, 09/30/2015
Alex Kelly (General Motors), Kim Le (General Motors)
This session will demonstrate how data enables people to overcome their disabilities and live to their fullest. We will also point out critical underlying flaws of data interpretation (due to human bias), and offer action items for us to make the data world more inclusive, efficient, and connected.
4:30pm–4:50pm Tuesday, 09/29/2015
Gary Short (Microsoft)
The future of humankind depends on farming greater yields using fewer resources. This talk looks at a European Space Agency-funded project to explore the intersection of farming, big data, and data science.
4:35pm–5:15pm Wednesday, 09/30/2015
Jay Margalus (MapR), Mike Emerick (MapR)
Slides:   external link
Who will watch the watchmen? This session will cover data integrity problems in open government introduced by the human element. We’ll then explore possible methodologies that will allow us to derive value from open government data, while still keeping a skeptical eye on the validity of the data itself.
1:30pm–2:00pm Tuesday, 09/29/2015
Tanzeem Choudhury (Cornell and HealthRhythms)
How ubiquitous computing is transforming the treatment of mental health disorders
2:55pm–3:35pm Wednesday, 09/30/2015
Mike Lee Williams (Cloudera Fast Forward Labs)
Because of the way sentiment analysis algorithms are trained, they systematically amplify the voices of those who express themselves unsubtly and aggressively. I will extrapolate from this observation to show the ways in which supervised machine learning has the potential to amplify social and economic privilege.
4:35pm–5:15pm Thursday, 10/01/2015
Susanna Pirttikangas (University of Oulu)
Oulu Smart City has a lively living lab tradition; we continuously collect data and expand our ecosystem of companies, research institutes, city officials, and citizens, and develop data-intensive services on top of the ecosystem. We present real use cases implementing big data platforms and development of higher level distributed reasoning and machine learning to exploit our data lake.
1:15pm–1:55pm Wednesday, 09/30/2015
Jake Porway (DataKind), Cathy O'Neil (Weapons of Math Destruction), Vladimir Dubovskiy (DonorsChoose.org), Kamalesh Rao (DataKind)
No matter how good the intentions, ethical questions are inherent in the work of using data for social good. How are organizations navigating ethical pitfalls in order to make an impact? The key is protecting the humanity behind the numbers. In this series of talks, we'll learn how organizations are dealing with ethical considerations inherent in projects that aim to use data for good.
2:05pm–2:45pm Wednesday, 09/30/2015
Jake Porway (DataKind), Bob Filbin (Crisis Text Line), danah boyd (Microsoft Research | Data & Society)
Slides:   1-PDF 
No matter how good the intentions, ethical questions are inherent in the work of using data for social good. How are organizations navigating ethical pitfalls in order to make an impact? The key is protecting the humanity behind the numbers. In this series of talks, we'll hear from four speakers on how they are dealing with ethical considerations inherent in projects that aim to use data for good.
1:35pm–1:55pm Wednesday, 09/30/2015
Lauralea Banks Edwards (Washington State University)
Slides:   1-PPTX 
This presentation identifies some of the areas in data creation and analytics where we perpetuate the simplistic representation of the world. It uses queer theory to demonstrate alternative ways of creating and analyzing data to take non-normative cases into consideration.
9:50am–10:00am Thursday, 10/01/2015
Jake Porway (DataKind)
Jake Porway, founder and executive director of DataKind, unveils five keys for successful data science for good projects, based on the organization's three years of work rallying thousands of volunteers worldwide to give back.