Last September, at the UN General Assembly, Sheryl Sandberg announced a five-year pledge from Facebook to use its data and resources to help partners advance progress on the Sustainable Development Goals (SDGs).
Over the last 6 months, Facebook commissioned a study by consulting firm Ladysmith to learn how it can use its access to gender data to help inform social policy.
On March 10th, Facebook released these findings, with an introduction from Marne Levine, VP of Global Partnerships, Business and Corporate Development:
Helping to Close the Gender Data Gap
If we want to make progress on the 17 Sustainable Development Goals (SDGs) adopted at the United Nations in 2015, the next decade really matters. Goal #17 is to use partnerships to strengthen sustainable development work around the world. Today, Facebook is announcing Project17, a new initiative that takes a partnership approach to help drive progress on the SDGs. Our first area of focus is gender equality.
One of the biggest barriers to achieving the SDGs, according to the UN, is a lack of access to real-time and representative data. So we’re working with gender equality organizations and experts to help provide this data and close the gender data gap. Our goal is to increase the availability and use of gender data, which is critical to guiding the development of inclusive policies, programs and services, and for tracking progress on achieving gender equality.
Much of the data available today is gender blind: it doesn’t account for differences in men and women’s lives. Missing or unavailable data around women’s experiences creates gender data gaps, an incomplete picture of people’s experiences around the world, and an inability to accurately measure progress. In STEM fields, for example, we don’t have accurate global breakdowns of women versus men working in artificial intelligence or data science — basic information that could help us achieve SDG #9, inclusive growth and innovation.
Gender Data Research and Findings
Over the last six months, we’ve met with partners and experts, including Data2x, Girl Effect and the Global Partnership for Sustainable Development Data, to better understand gender data needs and constraints. We partnered with Ladysmith, an independent research firm, to conduct expert interviews, review academic research and produce a report identifying areas where tech companies can help strengthen the gender data ecosystem.
Today, on the heels of International Women’s Day, and inspired by the sixty-fourth session of the Commission on the Status of Women, we share Ladysmith’s report. It identifies gender data gaps across many different areas, including the data used by policymakers to inform decisions and the data used to understand global challenges such as climate change induced migration.
The report also found a lack of communication between tech companies and gender equality organizations, recommending they work closer together to close gender data gaps. It suggests tech companies leverage their resources, including data scientists, to uncover new insights from existing data, share some of their own privacy-protected, de-identified datasets, and develop new tools to help researchers answer critical questions.
This research is a catalyst, focusing our time and effort. We will work with development organizations, experts and other trusted partners to leverage Facebook’s dataset to bridge gender data gaps, answer research questions, and help drive progress on gender equality. Here’s how.
First, we will provide gender-based breakdowns of some of our existing Data for Good work. We asked our partners which insights would be most valuable if broken down by gender, and they highlighted Facebook’s Displacement Maps, which are part of our Disaster Maps product. Displacement Maps already share real-time data on population movement with humanitarian response agencies, helping to determine community-specific needs in times of crisis. Our partner, the Internal Displacement Monitoring Center (IDMC) explained how sharing this data could help humanitarian aid agencies meet the needs of affected communities more efficiently. Early results show that partners with access to these maps understand what proportion of those displaced are men and women, where women are relocating, and when they are able to return. All of these calculations use aggregated and de-identified data from people using Facebook on their devices who have opted in to location history.
Next, in partnership with the World Bank Group and EqualMeasures2030, we’ll leverage the wide reach of our apps to run a global survey focused on gender equality. This will build on the success of the Future of Business survey, which we’ve been partnering with the World Bank and OECD on to survey small businesses around the world on Facebook. We’re also working with The Institute for Technology and Social Change, TechChange, to develop educational tools that share information about the ways unconventional datasets could be used in gender and development projects. Throughout 2020, we’ll continue to explore what datasets we should build to provide helpful insights based on the priorities identified in the report. Again, all data shared will be anonymized, aggregated and de-identified.
The Path Forward
It will take more than data to achieve gender equality and reach the SDGs. We need deeper collaboration between tech companies and development organizations to pave a path forward. The tech community has resources, unique data and data science capacity. Academics and practitioners within the gender and development community have thematic expertise and proximity to affected communities.
We hope Project17 helps our partners make progress on the SDGs and that our focus on gender data does its part to help improve gender equality around the world.
You can read the full report here.
In reading through this paper, I have picked out a few guideposts to understanding it as a whole. Essentially, the paper attempted to gather data around two questions:
- What are common gender data needs–and concerns–within the
international community working to achieve the SDGs?; and
- How might the tech community contribute its data, processing power, or human resources to meeting these needs?
The paper then covers a range of issues that impact women’s lack of power in society including access to sanitation, electricity, health care, violence and harassment, lack of access to jobs of any kind, and lack of access to STEM jobs in particular. Finally, around page 28, the paper gets really interesting. It starts to talk about “Hidden Economies”:
‘Hidden’ economies are one of the areas where social media platforms have a huge impact on people’s lives. It is possible that through privacy-preserved data sharing, the tech community could help feminist economists better understand of the dynamics of how, where, and when women engage in informal employment, using this data to address gaps in access to social protection including health insurance and maternity leave. We also know that funding for social programming for women is stymied by tax avoidance and evasion; measuring the impact of tax evasion on gender inequality could be a big support to ensuring stronger regulation.
As Elizabeth Warren and others pointed out on the campaign trail, a better tax system is key to a better economy for women. But there’s more. The report goes on to feature this ending section (bold emphasis mine):
Tax justice and funding for gender equality
Around the world, a widely embraced strategy for reducing women’s unpaid labour and addressing other inequalities is for states to progressively tax their citizens and use the revenue to fund social programs. A study in Guatemala, Honduras, and the Dominican Republic found that their gender-blind tax policies effectively deepen inequalities between men and women. In many countries direct taxation, and corporate and wealth taxes, as well as systems that prevent elite tax avoidance and evasion, help fund services like childcare and social protection programs that redistribute the burden of women’s unpaid care work. Our informants urged the tech community to develop methods for measuring the impact of tax avoidance on gender inequality. In doing so, they could help make visible the social protection needs of those women working in ‘invisible’ economies as well as spur better tax regulation.
This is one of the most important points in the paper, from my perspective, since it starts to bring into focus the source of the problem: that our governing bodies are making inequality worse, and without structural changes to the way that money is taxed, we are putting gender equality movements at a disadvantage.
Another important point relating to the uncharted territory of the online world:
Among experts in our study, one of the most frequently emphasized data gaps had to do with our poor understanding of harmful gendered behavior online and how people engage with online content.
We’ve discussed this point here at Philanthropy Women before, and it is important for Facebook to acknowledge and begin to take responsibility for the harmful gendered behavior that happens on its own platform. More understanding of how this is happening is needed.
The paper makes no mention of Facebook’s internal issues with gender data. Facebook still employs nearly two men for every woman, and those numbers get even worse in technical and senior leadership roles at the company. The paper also does not discuss how Facebook gave Cambridge Analytica data that was used to influence U.S. elections. The paper does repeatedly allude to using only de-identified data, but in terms of tracking issues like hidden economies and tax evasion, it seems like a sticky wicket to say this information is going to be de-identified while at the same time it is going to help us create a fairer tax system. The data collection methods for this work need to be thoroughly vetted to protect privacy, or else this data harvesting could be used for ill instead of for good.