Data equity at Data Con LA 2021
Event highlights by Meghan Wenzel
LA Tech4Good brought a panel on Elevating Data Equity in Practice to Data Con LA 2021 on September 18. Rachel Whaley, our Data Equity Program Manager, moderated the discussion with panelists Dr. Eboni Dotson, Maria Khan, Kathryn Wolterman, and Eva Pereira. All are leading work for data equity in their sectors and have participated in our data equity workshops. We’re happy to share some of the topics covered and insightful perspectives here.
To frame the discussion, Whaley started with a definition of data equity: Data is a thing we make and put to use. We can make and use it differently. She noted that data is not inherently objective – at each phase someone made decisions – who to sample, how to collect it, how to store it, how to analyze it, and how to use it. Additionally, the person(s) analyzing the data has their own inherent biases, which will color their interpretation and conclusions. We need to recognize this subjectivity and center equity in each of these decisions and steps in order to reduce and prevent harm.
What area do you see as the highest priority for the data community to focus on regarding data equity?
Dr. Dotson explained how we need to understand what equitable data practices actually mean. She said they’re complex and multifaceted, but they ultimately refer to the ways in which data is collected, analyzed, and interpreted. She noted that marginalized communities present themselves through data, and we need to hone in on this and change it. She calls out that data isn’t objective – it can create or perpetuate a power dynamic. We need to explore who are we collecting data for? Why are we seeking data? What’s the dynamic between the question asker and the question answerer? Ultimately equity needs to be addressed throughout each stage in the data lifecycle.
“Our goal should be to uphold and protect civil liberties, minimize the risk to individuals, and maximize the public good.”
–Eva Pereira, City of Los Angeles
Pereira elaborates on data ethics, noting they’re the behaviors and norms that guide how we collect, manage, and use data. She argues our goal should be to uphold and protect civil liberties, minimize the risk to individuals, and maximize the public good. She noted we should all be aware of relevant regulations and uphold professional standards when working with data. We should be honest and act with integrity, and she suggests we all establish a clear process for reporting data ethics violations and concerns.
She shared the federal data ethics framework, arguing we all need to be accountable and transparent. Who are the data stakeholders? How will the data be used? Who will be impacted by the data? She recommended having all stakeholders sign data use agreements so everyone is clear on how the data will be used.
Where do you see the biggest opportunity to implement better practices around data equity?
Wolterman drew on her experience at a large global corporation. With roughly 80,000 employees around the world, she argued that promoting education around data ethics and equity can be really impactful. After attending the public LA Tech4Good workshop, she partnered with LA Tech4Good to create a customized 4-week long program for CGI. This program contained a mix of lecture and hands-on activities to help employees learn about data ethics and apply it to their daily work.
“We need to find a delicate balance of equity and trust.”
–Maria Khan, Advancement Project California
Khan asserted that we need to find a delicate balance of equity and trust. She argued we need to present ourselves as not just data holders, but as data sharers. We need to engage with the community, bring them into the data world, and give them equal voice and representation. Whaley agreed, noting that democratizing data can help build transparency. She said we need to make sure that all stakeholders have some level of data literacy and access to the relevant tools and data.
What are the biggest barriers you’ve seen or anticipate as you implement ethical data practices?
Dr. Dotson explained how emerging tech has the potential to reinforce existing inequalities. Artificial intelligence, for example, can reinforce racial and ethnic disparities due to reliance on historical training data. She also noted how lack of trust impedes our ability to get solid data, which is one of the biggest barriers in terms of really having equitable practices within healthcare. She noted that within healthcare there’s a saying “what gets measured gets improved”. But she noted often what we’re measuring is an incomplete picture. While the data gap is really complex, she said we need to advocate for strategies to collect more representative data.
“Emerging tech has the potential to reinforce existing inequalities”
–Dr. Eboni Dotson, Healthcare Strategic Consultants
Wolterman noted that you can’t simply approach data equity as a “bolt on” effort. You have to build it into an organization’s core business strategy and company values in order to make authentic change and lasting progress. At CGI, she started with the educational element. From there, she developed steering committees to get key stakeholders involved and attract executive sponsors. She noted that having leadership on board was fundamental to success.
“You have to build [data equity] into an organization’s core business strategy and company values in order to make authentic change and lasting progress.”
–Kathryn Wolterman, CGI
Community activists often struggle to get access to data, while big companies have massive amounts of data. How do we address this?
Pereira shared that her team helps manage California’s open data portal. She acknowledged that not everyone has the technical skills to review data, so her team developed a new role – the data liaison. They created a whole education program around this, meeting with community members to understand what questions they have. Pereira’s team helps them find the data, plug it into a tool, and analyze it, in order to build the data capacity of neighborhood councils.
Additionally, her team has also developed another program, Know Your Community, to provide insight ready information via an app. They did research to find out people’s most common questions and how to deliver insights in an accessible way. This way, Pereira noted, they’ve come at the problem from both sides, with workshops and education to build knowledge around data as well as providing accessible and insights-ready tools.
What are actionable next steps that we can take?
Khan said to start by asking who your data is about. From there learn about your community. Who’s behind the data set that you’re looking at? Learn about those communities on all different levels.
Dr. Dotson urged individuals to educate themselves on what data equity is and what it means, especially in the space they operate in most often. She suggested checking out The Ethical Algorithm as well as Chicago Beyond’s equity series including Why am I being researched?
Pereira suggested creating a data ethics committee at your org. This can help you start to check yourself - question your assumptions, review your methodology, and discuss if it’s the right approach. This also creates a space to discuss other data ethics issues with colleagues.
Wolterman recommended watching Coded Bias for a great look at algorithmic injustice present in our world today. She notes that the documentary includes interviews with several experts in the field, and you can explore their work as well. Additionally, she recommended LA Tech4Good’s data equity workshop as a great hands-on and supported approach.
In conclusion: Overall it was a great discussion. Data equity is a complex and important topic, and we need to work together to drive it forward. Education is the first step. We need to recognize that data isn’t objective – it’s a reflection of the historical data it was trained on, ripe with inequalities, as well as the inherent biases and perspectives of the people who collected and analyzed it. From there, we need to continue the discussion and implement change. Developing data ethics committees, advocating for data regulations, and implementing standards and processes at our organizations are just the beginning.
About the participants
Dr. Eboni Dotson is Founder and CEO of Healthcare Strategic Consultants, a company transforming the delivery of healthcare services, and The Hue of Health, a curriculum for equitable healthcare
Eva Pereira is Chief Data Officer at the City of Los Angeles
Kathryn Wolterman is Senior Consultant at CGI, a global consulting company focusing on systems integration and IT consulting
Maria T. Khan is Research and Data Analyst at Advancement Project California, a nonprofit focusing on racial justice and equity via data driven research, policy, and advocacy
Moderator Rachel Whaley is LA Tech4Good’s Data Equity Program Manager
Author Meghan Wenzel is Lead User Researcher at Unqork
Our data equity + ethics workshops bring data practitioners together to discuss these topics and develop actionable plans to implement in their organizations.
Data Con LA is a vibrant gathering of data and technology enthusiasts and the largest data conference in Southern California.