The Horn of Africa is experiencing a catastrophic drought. Five rainy seasons in a row have failed — and experts predict a sixth. Millions of desperate people in Ethiopia, Kenya and Somalia have abandoned their homes in search of water and pasture. 

This crisis is a huge challenge for already taxed government organizations. Where should limited resources be deployed? Real-time climate data can help predict areas where conditions will be most severe and the most likely migration routes. 

These gaps are everywhere. Data disparities underpin not only climate-related challenges but also the crises we face in public health and social justice. The twin revolutions in cloud technology and artificial intelligence are producing more data and analysis than ever before. As we grow ever more reliant on data, we must ensure that data represents everyone. People can benefit from data-driven innovation only if the data sets that address their most pressing issues are accessible and include them. 

What is a data disparity? Think of systematic undertesting of women in clinical trials, unequal access to primary school education and faulty climate models. These are real problems with real impacts that stem from how we manage information. 

Solving data disparities is one of the great opportunities of our time. 

The United Kingdom experiences 32,000 excess deaths each winter. Of those deaths, 9,700 are attributable to living in a cold home — about the same as the number of people who die from breast or prostate cancer each year — and 3,200 are directly linked to people who cannot afford fuel to make a warm home. Energy insecurity should not mean life or death. 

In an ideal world, governments and nongovernmental organizations could couple their weather data with usage metrics from energy suppliers to anticipate which homes will be most vulnerable in winter and offer aid. Accessing and deploying that data has long been near-impossible, but that’s changing. EDF, which supplies gas and electricity to homes across Britain, now uses machine learning to identify financially vulnerable customers and step in to provide assistance in times of need. 

Inequitable data access exacerbates global inequalities. We now rely on data to inform the most pressing socioeconomic conversations and influence policy, but we must make a concerted effort — across private and public entities — to make that data whole. That means dismantling data silos, bridging gaps in data collection and safely and securely sharing knowledge. 

Despite commendable efforts, we’re falling short. Globally, we are on track to achieve only 15% of the United Nations Sustainable Development Goals (SDGs), which aim to secure “peace and prosperity for people and the planet.” These are the most important representations of what we must do to ensure a good life for all. More needs to be done. 

SDG 17 focuses on building partnerships between organizations for more sustainable development. This goal recognizes that no one company or organization can solve our global problems; instead, we need a global movement. 

Many of those players will be private companies. There have been notable efforts through “data for good” efforts from Meta, Google and others to provide massive data sets for use in research and studies. A new End Data Disparity campaign, which brings together data leaders like Snowflake with on-the-ground groups like the UN’s International Organization for Migration, builds on these efforts by encouraging companies to share their growing technology capabilities with those who traditionally have done with less. 

Even a leading nonprofit likely has only a couple of people on its data science team. Compare that to hundreds of data scientists at an equivalent multinational company. Nonprofits and NGOs don’t always have the expertise or capacity to fill in gaps in data sets and make complex multi-factor calculations. But that can change. 

We can draw on recent breakthroughs in AI and classic machine learning to inform how we address the world’s biggest issues. Imagine it were possible to adjust the deployment of doctors and relief workers in real time based on anonymized phone data. This could improve access to services and ultimately save lives. By sharing knowledge — listening closely to people on the ground — and using technology, organizations can work toward meeting the UN’s Global Goals.

As world leaders convene for crucial discussions at the United Nations General Assembly, COP29 and the World Economic Summit Davos, let’s make sure to keep data on the agenda. 

It’s time we end data disparity together.