Data experts, academics, practitioners, and social sector leaders led sessions on topics ranging from aligning practice with policy to creating a culture of data, and how Silicon Valley is facilitating data practices in civil society.
Causal Inference Meets Big DataPresentation from this session
In this session, Hal Varian will discuss the conceptual framework required to establish causal inference and computational methods that can allow causality to be inferred. His presentation will explore the possibility of testing causality in large data settings, and will raise certain basic questions: Will access to massive data be a key to understanding the fundamental questions of basic and applied science? Or does the vast increase in data confound analysis, produce computational bottlenecks, and decrease the ability to draw valid causal inferences? Hal Varian’s presentation will be followed by a Q&A with Andrew Means.
Creating a Culture of Data
It’s not as easy as it looks to use big data for social change. A discussion with four organizations about the lessons they have learned on their data journey. Julia Angwin, senior reporter at Pro Publica, moderates a conversation with HyeSook Chung, deputy mayor of Washington DC, Perla Ni, CEO of Citizen Insights, and Stephanie Zidek, senior analytics manager at Feeding America.
Organizational Data Literacy and ChangePresentation from this session
Data is permeating every facet of your organization. In this session, Harshil Parikh, the Co-founder and CEO of Tuva will share the importance of building a strong foundation in data and statistical literacy across all levels of your organization.
Software for Good: Empowering the Social Sector Data RevolutionPresentation from this session
Leading for-profit companies thrive by embracing data insights to drive increased efficiency, effectiveness, and scale. They view information and analytics as core strategic assets in running a modern business. The social sector must follow this lead by embracing the Software for Good movement characterized by data-driven decisions that maximize social impact. This session will be led by Jim Fruchterman, founder and CEO of Silicon Valley’s original tech nonprofit, Benetech, and author of the recent SSIR article, “Using Data for Action and for Impact.” He will lead an interactive discussion on how Software for Good empowers social enterprises to harness data to better serve their communities. Through small group work, real world examples, and best practices, attendees will learn about and collaborate on applying data for action and impact.
Unlocking Data and Unleashing Its PotentialPresentation from this session
Data has the potential to help fuel social change across the world, yet many relevant datasets remain locked away and siloed across government agencies, nonprofits and corporations. What kind of collaboration does it take to make this data available and actionable for different actors working to create change? In a series of TED-style talks, hear from experts from the nonprofit sector, public sector and academia that not only know how to develop the right tools and dashboards, but also the right relationships to make it happen. DataKind Founder and Executive Director Jake Porway will then lead an audience discussion on how together, we can collectively harness data for the greater good. He will be joined by Greg Bloom of Civic Hall Labs and Open Referral, ST Mayer of Code for America, John Wilbanks of Sage Bionetworks, and Melinda Rolfs from the Mastercard Center for Inclusive Growth.
Listening for Good: Experiences From the Field Implementing Feedback LoopsPresentation from this session
Have you heard about beneficiary feedback and thought, “That sounds great in theory, but how do I support feedback loops?” Do you see the critical role that beneficiary feedback plays in promoting community engagement and inclusion within your work? Do you want to hear the relatively simple steps that some nonprofits have taken to systematically collect and use feedback from those they seek to help? If your answer to any of these questions is “Yes!” then we hope you’ll join this session coordinated by the Fund for Shared Insight, a collaborative of eight core funders that supports the practice of systematically listening to and incorporating feedback from the beneficiaries of social organizations. Shared Insight has provided more than 60 grants to organizations around the country to advance their listening practices. In this session, we’ll hear from two grantees, Brad Dunning of the Center for Employment Opportunities and Krystle Onibukon of the Boys and Girls Club of the Peninsula, about their feedback journeys—why they pursued this work, how they do it, and what they have learned. Session moderator Valerie Threlfall will also discuss Listen for Good, Shared Insight’s largest grant program, which provides grants and technical assistance to dozens of different nonprofits to build the practice of high quality feedback loops with those they serve.
Cyber-Technologies in Our Social Systems: Opportunities and Challenges
ADigital technologies have been produced and introduced into markets with little consideration of their short- or long-term social ramifications. In some cases, there is an optimistic premise that market forces or government action will correct for unforeseen problems. The prospect of path dependencies from market-driven adoption of technologies, however, raise large and complex questions as to their largely unintended impact on social welfare. In this session Rob Reich, Political Science Professor, Stanford University, George Triantis, Charles J. Meyers Professor of Law and Business, Stanford University Law School, and Eli Sugarman, Program Officer, Cyber Initiative at William and Flora Hewlett Foundation discuss the Stanford Cyber Initiative and the growing realization that given the wide range of human activities and social systems undergoing fundamental transformation through waves of new digital technologies, the need for better understanding of cyber-social systems is urgent and requires a new analytical approach.
Perfectionism vs. Practicality: Can Imperfect Data Still Point Us in the Right Direction?Presentation from this session
The data we all work with is inherently messy. Whether it’s missing fields, nonstandard questioning procedures, or simply the biased nature of the dataset you are working with, the data you have is imperfect. But that doesn’t mean it doesn’t have value. In this session you’ll hear from leading practitioners on how they make the most of messy data. We will discuss issues of bias and how they might be overcome as well as discussing options for inputting unknown values. If you are looking to the make the most of the data you have, this session is for you.
Human-Centered Data Science for Good: Creating Ethical AlgorithmsPresentation from this session
From online news feeds to college admissions to credit scoring, algorithms are deeply embedded in and can sway the trajectory of our lives, yet go largely unquestioned. Algorithms are widely perceived to be impartial ways of using data and computing to make “scientific” conclusions, but the truth is that they are the result of many human decisions along the way. What data was used? What tradeoffs were made? Without oversight and sensitivity, these algorithms can simply become an echo chamber that reinforces historic inequities of racism and sexism, enabling them to persist. Join DataKind’s Jake Porway and The Engine Room’s Zara Rahman for an interactive workshop to look “under the hood” of an algorithm to understand the thought process behind its creation and uncover common pitfalls algorithm-based solutions must overcome to have a positive impact on the world.
Silicon Valley for Social Good
Many of the leading companies in Silicon Valley are helping social sector organizations use data more effectively. Moderated by Marc Jones of Aeris Communications, this session looks in depth at four real-life examples.
Crowd Collectives to Tackle Problems at ScalePresentation from this session
The nature of collaboration is being reshaped by computational systems, which increasingly draw on the web to motivate and direct peoples’ behavior at scale. Today, these crowdsourcing systems have successfully synthesized many amateurs’ efforts to recreate an expert’s abilities. However, across domains from design to engineering to art, few goals are truly the effort of just one person — even one expert. How might computation coordinate many peoples’ diverse abilities toward far more complex and interdependent goals? In his talk, Michael Bernstein will present systems for gathering and guiding crowds of experts, including professional programmers, designers, singers and artists. The resulting collectives tackle problems modularly and at scale, dynamically grow and shrink depending on task demands, and combine into larger organizations. Bernstein will demonstrate how crowd collectives can pursue goals such as designing new user experiences overnight, producing animated shorts in two days, and even pursuing novel research.
Prediction vs. Bias: A DebatePresentation from this session
This plenary panel features a spirited conversation among conference co-hosts Lucy Bernholz and Andrew Means; Candace Thille, associate professor at the Stanford Graduate School of Education; and Kristian Lum, lead statistician at the Human Rights Data Analysis Group. Among the topics to be covered will be risk, machine bias, and criminal justice.
Data Therapy: Telling Your Story WellPresentation from this session
Want to create a visual of your data? You have a flabbergasting array of possibilities available. How can you make an appropriate and effective choice? We’ll review evocative, real-world examples to flesh out a tool-belt of techniques for telling data-driven stories, and discuss best practice for when to deploy each. This fun, hands-on session will leave you better equipped to pick a presentation technique based on your audience and goals.
Ethical Data Practice as a Driver of Organizational ChangePresentation from this session
It’s difficult to coordinate ethical data practices across departments, to integrate those practices with organizational values, and to put organizational leaders in a position to manage data the way they manage other programmatic assets. But it’s worth the effort, because ethics matter, and also because an organization with a healthy culture of data governance can be more efficient, responsive and effective in pursuing its mission. Eric Vieland, chief corporate counsel and data governance counsel of the American Civil Liberties Union, will discuss the pains and joys of several organizations’ struggles with data governance, and lead exercises on identifying problems and opportunities in your own organizations.
When Data Science Meets Evaluation PracticePresentation from this session
This session will share lessons from Monitor Institute’s Re-imagining Measurement initiative, a year-long innovation and design project that has been exploring how we can build a better future for monitoring, evaluation, and learning. This includes promoting data for decision making; empowering constituents and promoting diversity, equity, and inclusion; and learning at scale. Participants will hear about bright spots in using data science for monitoring, evaluation, and learning, and take away ideas for using these insights in their work.
Closing Plenary: Commitment to the FuturePresentation from this session
Lucy Bernholz and Andrew Means will reflect on the what was learned during the conference, and discuss the future of Data on Purpose | Do Good Data as we move through 2017 and beyond.