Artificial Intelligence (AI) is everywhere. Not just in our phones, and in the websites we visit, and the products we buy, but also in the public conversation. At Festival de Datos this week, AI is the topic the network most want to address. Governments are wrestling with the question of how to regulate this thing which most of us don’t fully understand, while trying to spot the opportunities it presents.

Data is the raw material which powers AI, and AI has turbocharged the power of data. We used to say that data is the new oil – if that’s the case, then AI is the internal combustion engine. 

Data for development, with values at the heart, is the core business of the Global Partnership network, so this is very much our territory. In September, we brought together a stellar group, to discuss with the Global Partnership Board what countries can do now to set the trajectories for future growth from AI that is more equal, and less harmful, than we have seen in past eras. This group included Sir Nigel Shadbolt, Professor of Computing Science at the University of Oxford; Ambassador Amandeep Gill, UN Technology envoy; James Hairston, Head of International Policy at Open AI; and researcher and advocate Nanjira Sambuil.

At its core, sustainable development is about values, and the belief that all people are entitled to the same rights and opportunities. This is the lens through which the data that powers AI must also be viewed. And, just to prove that very few problems are ever new, here’s four cliches that show how this can be done.

1. Garbage in, garbage out

If AI models are built with data that is biased, that’s poor quality, or that’s unrepresentative, the models that are trained on that data will have all kinds of negative consequences. All too often data fails to represent groups such as ethnic minorities, people with disabilities, or specific aspects of people’s lives such as incidence of domestic violence. 

We’ve seen the consequences of this already, with well-documented cases of AI products which lead to harsher sentences for racial minorities, or women being excluded from jobs. Work on inclusive data is all the more important when the consequences of getting it wrong can be so far-reaching and so amplified by the effect of AI. 

A focus on inequality and inclusion in data, through monitoring outcomes, checking datasets for biases, and linking outcomes back to datasets, should be hard wired into the different policy and institutional frameworks springing up globally to manage the production and impact of AI.

If AI models are to benefit people, people have to be fairly represented in the data that powers it.

2. First do no harm

The power differentials between the companies and organizations which collect the data, and which then develop and use AI from that data, and the marginalized communities who might be affected, are stark. LIke any powerful technology, AI can do great harm as well as great good, and data, if it’s misused to invade people’s privacy or to discriminate against certain groups, can be part of this harm. Managing and protecting the data that drives AI in order to protect the most vulnerable groups, is a critical part of ensuring that AI supports sustainable development. 

Calls for change are coming from the industry itself, and many governments are developing policies and frameworks to govern both AI and the data that powers it. It’s vital that as agendas are set, whether at national, regional and global level, they are informed by the participation of those affected.

Data governance at every level should protect the rights of all people, including the most marginalized and those who have the least voice in the political process. 

3. It’s the economy, stupid

AI is powering the profitability of established companies and creating whole new industries. The economic growth and change that comes from the use of data in AI applications offers an opportunity for a more equal pattern of growth. Unlike the natural resources which powered earlier eras of growth, data is produced everywhere, and can be put to work by anyone with the right access, skills and technology. What kind of growth comes from AI is a choice that is being made now, as new investments and new rules are being made.

Current debates over regulation at global, national and regional level offer a unique opportunity to think about creating a new framework for valuing, managing, sharing and distributing the raw material that is currently powering the most dynamic sectors of the economy. The challenge ahead of us is to do that in a way that drives the equitable and sustainable economic growth that all countries signed up to with the UN Sustainable Development Goals, but which has been so conspicuously lacking in the years since.

Global agreements on data and technology need to set parameters for more equitable global growth,  in which all countries can benefit from the new opportunities of AI.

4. If you (can’t) build it, they (won’t) come

There’s equal parts worry and excitement about the AI that is being built. But an equal challenge is the AI that isn’t happening, in places where the skills and infrastructure are absent. Democratizing data skills is essential if the opportunities are to be widely shared. At present, research on AI is overwhelmingly concentrated in just a few countries: seventy percent of the most cited AI research papers in the last three years came from authors in US institutions. Infrastructure too is lacking – with one-third of the world’s population still offline. 

This is primarily an investment agenda. If the world wants, as it says it does, an AI that solves the greatest challenges of the world, and that does good in the places where the need is greatest, then it has to come from those places. This needs money – investment in both the hardware and the human skills needed to successfully develop, manage and use the technologies of the future.

A fair AI future needs to offer opportunities for all - people should not be held back by lack of skills or lack of infrastructure simply because of where in the world they live.

AI is the future. To bend this future towards the outcomes we want, getting the data right is a critical part of policy agendas, for all our sakes.

Watch the replay of the insightful and hopeful town hall debate on AI, opportunities and threats at Festival de Datos:

Photo: The AI, opportunities and threats town hall at Festival de Datos. Credit: Nicolás Donatte 

Around the world, youth face pressing challenges. Conflicts, the climate crisis, education and employment gaps, structural inequities, and the lingering effects of COVID-19 all have an effect on the health and wellbeing of the world’s 1.2 billion adolescents. Already existing, siloed datasets from governments, international organizations, and companies might be reused to mitigate the consequences of these challenges.

Yet, young people often do not have a clear way to make their voice heard in decisions that directly affect them, now and in the years to come. This is particularly true when it comes to questions about data use where information for and about children may be used or shared by a variety of organizations without their knowledge or consent.

Young people often have little say in what data is shared about them, when it is shared, under what conditions, and with whom. Even when it is done by organizations who have their interests in mind, young people are excluded from conversations, which can lead to a lifelong loss of trust, a failure to consider their innate rights, and reduce their agency.

In March 2023, The Lancet Commission on Adolescent Health and Well-Being, UNICEF, and The GovLab at NYU joined together to understand what youth would like to see regarding data (re)use. Through six virtual studio workshops or “Youth Solutions Labs”, we hosted over 123 youth between the ages of 16 and 20 from around the world to hear about what solutions they thought could address issues affecting them and the role of data in addressing those issues. 

We learned not only valuable lessons about what might constitute a global agenda for youth health and well-being but also ways to responsibly use data for and about youth in ways aligned with global frameworks such as the Responsible Data for Children principles.

Responsible Data for Children

Responsible Data for Children is a framework and initiative for assessing risks and opportunities for advancing children’s rights through data and across the data lifecycle, grounded in a set of principles for responsible data handling. It recognizes that children face unique vulnerabilities that can be best addressed by spotting the particular risks and opportunities in the contexts that children reside in.

Core to the effort is a recognition that data moves through distinct stages from collection to use to impact and that a flexible framework that centers youth and children is essential. As such, it identifies several principles to emphasize throughout a data-driven effort—being participatory, professionally accountable, people-centric, preventative of harms across the data lifecycle, proportional, protective of children’s rights, and purpose-driven.

Responsible data practices

These principles proved relevant throughout the Labs as participants discussed the ways that they thought data should be used to address the challenges they identified.

They spoke on what young people were comfortable with organizations reusing, how they thought that data should be used, who should gain access to it, and when. The resulting discussions revealed an immense amount of information about the ways youth see data about young people and the importance of principle-led frameworks.

When it came to the kinds of data used (or reused for purposes other than initially collected), youth suggested that experts rely on many different kinds of data—from search and social media trends to hospital records to location data. They expressed the importance of including surveys, interviews, and other direct methods to learn from a diverse range of lived realities.

Most participants were only comfortable so long as the data re-use for or about youth aimed to solve public problems and was de-identified. Consistent with the Responsible Data for Children principle of being proportional and purpose-led, they wanted data collection and retention aligned with an intended purpose with outcomes that could improve their lives.

Note: The Youth Solutions Labs included participants from North America and Western Europe (26), Latin America and The Caribbean (20), Asia-Pacific (22), Middle East and North Africa (19), Sub-Saharan Africa (16), and Eastern Europe and Central Asia (20).

Similarly, many participant groups suggested providing the public sector and trusted intermediaries access to de-identified data about or for youth. Many young people viewed research centers and policymakers as uniquely accountable. Many youth saw avenues to express concerns and hold people responsible when they served in public-facing bodies.

Youth participants also had other views on what ethical and responsible data reuse entails. Some spoke on the need for informed consent while others emphasized the need to account for inequities. Still others spoke about the need to reflect the local context and culture. Groups were divided on whether data re-use should be done only in a crisis or every day to prevent today’s problems from turning into crises.

Reflecting on these perspectives and ensuring the needs and expectations of youth are met can be critical when it comes to being people-centric.

Important lessons

Overall, the Youth Solutions Labs reveal several key lessons.

First, they demonstrate a need for new processes and engagements to increase youth participation in discussions around defining ethical and responsible data re-use. 

Second, there is an opportunity to explore new data types and sources that could be re-used to accelerate youth health and wellbeing—beyond data about youth themselves.

Finally, there is a need to increase institutional trust to address concerns about the re-use of data by different actors. Principle-led frameworks like Responsible Data for Children can be a valuable resource here in ensuring that practices keep in mind the people at the center of data—children and youth themselves.

We’ll reflect on these and other takeaways in the 2024 Lancet Commission Report on Adolescent Health and Wellbeing, which we’ll publish in the coming weeks. In the meantime, if this work interests you, we encourage you to email [email protected] for more information on the Youth Solutions Labs and opportunities to participate in future initiatives. Reach out to [email protected] for information on the Responsible Data for Children initiative.

Francisco Benavides, UNICEF Uruguay Country Representative, and Stefaan G. Verhulst, Co-Founder and Chief Research and Development Officer of The GovLab, discussed the Youth Solutions Labs at the Youth takeover plenary at Festival de Datos. Watch the replay; the session begins at 31 minutes, 54 seconds: 

Earlier this year, the Global Partnership and World Bank ran a data visualization storytelling contest focused on data and the power it holds to accelerate sustainable development.

The challenge was to tell a data visualization story that showed the interconnectedness of sustainable development goals and revealed how the mobilization of different resources could be linked to impact.

A global response

With submissions from 34 countries across six continents and ideas spanning the impact of climate change, gender inequality, governance, debt management, energy supply, and food security, we are excited to announce the top three entries, as chosen by a panel of expert judges.

The winner of the contest will be revealed at the closing ceremony of Festival de Datos on Thursday November 9, 2023.

Introducing the three standout ideas

Read about our three finalists and find links to explore their full data visualizations below:

El territorio es la vida

By María Camila Posada and Michael Bally from Colombia

El territorio es la vida (The territory is life) highlights the challenges posed by rising temperatures, increased precipitation, and armed conflict, all of which affect food security and livelihoods in Nariño, Colombia.

Using various data sources and visualization approaches, the project examines the impact of these challenges on local communities, and outlines various initiatives aimed at tackling these issues, including early warning systems, ecosystem restoration, and climate risk insurance.

Explore the full data viz here.

From drought to floods: The Impact on Labor in the Coastal Zones of Uruguay, from East to West

By Miguel Ángel Dobrich and Gabriel Farías from Uruguay

How is climate change reshaping workers' lives in Uruguay? This project examines the impact of drought, flooding, and other climatic effects on labor in coastal zones across the country.

Focusing on three regions: Valizas, Montevideo, and Ciudad del Plata, it uses geospatial data and open databases to illustrate these impacts on the population and ecosystems.

Explore the full data viz here.

Climate action needs more women on board

By Surbhi Bhatia from India

"Within the climate crisis, there exists a gender crisis," says Surbhi Bhatia. 

Surbhi's data visualization focuses on the relationship between gender inequality and climate action, using data to illustrate the impact of climate change on the health and livelihoods of women and girls, compared to men.

It also highlights how women's unequal access to resources and underrepresentation in climate decision-making forums can hinder progress on Sustainable Development Goal 13, which is about urgent actions to combat climate change.

Explore the full data viz here.

Tune in on Thursday November 9 to hear the winner announcement during the closing ceremony of Festival de Datos.