Big data has become ubiquitous in recent years. Whether it is data-driven marketing, sports analytics, political campaigns, or national security threats, data has become central to any type of informed analysis and plan of action. Consequently, the arrival of Big data has also spawned a data industry and the emergence of data professions – data analysts, data architects, data scientists, and chief data officers. Against this backdrop, governmental and social service organizations are following suit and initiating efforts to apply sound data practices to a range of societal challenges. These can range from matching scarce resources to acute needs, detecting disparities in social justice administration, or the establishment of policies for ethical data usage. Here are some of the initiatives that are being undertaken to advance data for social good as we look ahead for 2018:
Bloomberg’s Data for Good Exchange
The Bloomberg Data for Good Exchange was launched in 2015 to encourage and promote the use of data science and human capital to solve problems at the core of society. Each year, the program focuses on themes pertaining to how data science can play a role in helping drive change in the delivery of public services, city operations, public health, climate resilience and the environment, criminal justice and other areas of public concern. Over 1,000 data scientists, thought leaders, and public policymakers gather at Bloomberg's Global Headquarters in New York City for a day of discussion. The program committee for the 2017 program considered over 170 proposals for papers, panels, and presentations.
Big Data in Public Health
Bloomberg Philanthropies has been an active partner in organizing and supporting the Data for Good Exchange, in addition to sponsoring a range of initiatives including Bloomberg Philanthropies' Public Health programs. In 2015, Dr. Kelly Henning, who leads the public health program, delivered a keynote on the topic of Data for Health, an initiative that is enabling countries to improve public health data collection with the goal of addressing public health problems. Working with partners, Data for Health aims to help more than one billion people in 20 countries across Africa, Asia, and Latin America. With this information and training in data analysis, participating countries are able to turn insights from data into public policy, and direct resources to issues affecting public health. To date, 20 countries have partnered with the Data for Health, reaching more than 1 billion people.
Big Data in Criminal Justice
Big data is making a difference in addressing disparities in criminal justice sentencing and in tackling challenges of poverty and crime. According to the data-driven justice initiative, more than 11 million people move through America’s 3,100 local jails each year. Many are low-level, non-violent offenders, costing local governments approximately $22 billion a year. Data shows that 64 percent of those incarcerated in local jails suffer from mental illness, 68 percent have a substance abuse disorder, and 44 percent suffer from chronic health problems.
I hosted a panel at the 2017 Data for Good Exchange, bringing together experts in this field. Mary McKernan McKay, dean of the Brown School of Social Work at Washington University in St. Louis, and former professor of poverty studies and director of poverty policy at New York University, joined co-panelists Kelly Jin, director of the data-driven justice initiative for the The Laura and John Arnold Foundation, and former policy advisor for the Obama White House data-driven justice initiative, and Rebecca Ackerman, a data scientist with New York Defender Services, to bring their perspectives on links between poverty, mental health, and racial discrimination. With an annual prison bill of $70B in the United States and an incarceration rate that is 5x the average rate in other developed nations, universities and community organizations are undertaking bi-partisan initiatives to address root causes that can lead to systemic change.
Algorithmic Equality
Cathy O’Neil is an outspoken advocate for greater transparency in the social uses of Big data, and is on a mission to ensure data and algorithmic “equality”. Her 2016 book, Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, was intended as a “wake up call”. O’Neil, who also serves as an advisor to the Data for Good Exchange, believes that many people are intimidated by math, and as a result, algorithms may be employed to support biases without critical and objective consideration. She calls this “hiding behind mathematics”, and laments a lack of diverse perspectives that are missing from many of the algorithms that she discusses in her book. O’Neil warns of the dangers of algorithms which have become “accepted truths”, and cautions about the damage that can result when algorithms become “widespread, mysterious, and destructive”. She notes that “algorithms are often opinions embedded in code, which reflect subjective biases and decisions”, and believes that algorithms are having an “outsized impact of algorithms” in areas ranging from teacher evaluations to academic admissions. She calls this the “weaponization of math”, and advocates that data and algorithms do no harm.
Ethical Data Sharing
Bloomberg has recently been spearheading the development of a code of ethics for data scientists. The “Community Principles on Ethical Data Sharing (CPEDS)” initiative, which was announced at the Data for Good Exchange in September 2017, will provide a set of guidelines about responsible data sharing and collaboration. Characterized as a 'Hippocratic Oath' for the industry, Bloomberg believes that data scientists should be thoughtful, responsible, and ethical agents for change. This partnership will collect input from the global data science community through social media, conversations and working groups to define the values and priorities for ethical behavior by data scientists.
Across the public and private sector, organizations are confronting the responsible use of data, and exploring ways in which data can be applied to a wide range of social issues, needs, and challenges. Data ethics and data for good initiatives promise to be an increasing area of focus in 2018 in the ongoing advance and application of Big data to a broad range of business as well as societal challenges.
Randy Bean is an industry thought-leader and author, and CEO of NewVantage Partners, a strategic advisory and management consulting firm which he founded in 2001. He is a contributor to Forbes, Harvard Business Review, MIT Sloan Management Review, and The Wall Street Journal, and is Founder and Executive Director of the Big Data for Social Justice Foundation. You can follow him at @RandyBeanNVP.
