As the clock ticks towards 2030, the world finds itself at a critical crossroads. The United Nations’ Sustainable Development Goals (SDGs) — a global blueprint to eradicate poverty, protect the planet, and ensure prosperity — remain far from reach. At the heart of this challenge lies a stark problem: incomplete and outdated data, especially on environmental indicators. Without better information, meaningful progress is difficult to achieve.
A study from the International Institute for Applied Systems Analysis [48.01°N, 16.35°E] spotlights the significant value of artificial intelligence (AI) and citizen science. When combined, these can offer a revolutionary path forward, that involves everyone in creating a sustainable future.
The Missing Pieces of the Sustainability Puzzle
Data is the currency of sustainable development. It tells us where we are falling behind, where progress is being made, and who is being left behind. Yet, a staggering 50% of environmental SDG indicators remain unmeasured globally. Traditional methods — like large-scale surveys — are costly, slow, and often miss critical local nuances.
AI offers an elegant solution. Through its ability to sift through vast datasets, identify patterns, and automate tasks, AI has already shown promise in monitoring climate change, tracking poverty, and even detecting marine plastic pollution. But AI has its limitations. The technology requires reliable, diverse, and localised data — something that is often unavailable. Worse, without inclusive input, AI systems can unintentionally amplify biases and exclude the very people who need solutions the most.
Here’s where citizen science comes in. Citizen science harnesses the collective power of everyday people—volunteers armed with mobile apps, cameras, or just their senses—to contribute observations and data from their own communities. From recording bird sightings on eBird to mapping marine litter on local coastlines, citizens are already helping scientists address sustainability issues.
A Collaborative Solution: AI Meets Citizen Science
While AI and citizen science have each made strides, it’s their integration that offers the most exciting opportunities. AI tools can enhance citizen science projects through features like image recognition, which help volunteers identify plant species or classify galaxies. Meanwhile, data collected by citizen scientists can help improve AI’s accuracy, ensuring models reflect local realities, not global generalisations.
Take, for instance, the marine litter problem in Ghana. European-developed AI tools struggled to identify common litter items like water sachets—a locally specific form of plastic waste—because they were trained on European datasets. By integrating data collected by Ghanaian citizen scientists, the AI became better equipped to identify local litter, making it far more effective for tackling environmental challenges on the ground.
Tackling AI’s Biases and Disconnection
AI systems are often criticised for perpetuating societal biases—reinforcing stereotypes related to race, gender, or wealth. For example, some AI tools have incorrectly linked darker skin tones with poverty or depicted women exclusively as domestic workers. These biases are often the result of skewed datasets and unrepresentative input.
Citizen science can help counter these flaws. By involving diverse communities—including marginalised and underrepresented groups—citizen science initiatives generate data that is richer, more inclusive, and truly representative of the world’s diversity. Moreover, engaging the public can also demystify AI and increase digital literacy, helping people critically evaluate and shape how AI technologies are used in their lives.
Public participation is not just about data collection; it’s about building trust. By involving citizens in monitoring and decision-making, we can ensure AI works for people, not against them. Projects like Public Editor, where volunteers identify biased news content, show how citizens can actively hold technology developers accountable for fairness and accuracy.
Building a Path Forward: A Roadmap for Integration
The collaboration between AI and citizen science is still in its early days, but its potential is vast. A clear roadmap has emerged:
- Identify Priorities: Pinpoint SDG goals and indicators where AI and citizen science can work hand-in-hand.
- Forge Partnerships: Bring together governments, scientists, AI developers, and communities to foster collaboration.
- Test and Innovate: Pilot projects that integrate AI into citizen science while leveraging citizen science principles in AI development.
- Measure Success: Develop tools to track the impact of these efforts on sustainability goals and community engagement.
- Scale with Care: Expand successful initiatives, tailoring them to local contexts to ensure they meet community needs.
Throughout this process, ethical considerations—like data privacy, transparency, and inclusivity—must remain front and centre. Only then can this powerful partnership realise its potential without compromising human rights or values.
A Role for Everyone
For individuals, the opportunity to contribute is clear. By participating in citizen science projects—whether through a smartphone app or a local community initiative—you can directly support sustainable development in your area. Your observations, when combined with AI’s analytical power, can drive meaningful change, from identifying pollution hotspots to tracking biodiversity loss.
For policymakers, scientists, and tech developers, the message is equally compelling: collaboration is key. The integration of AI and citizen science offers a practical, scalable, and inclusive way to overcome the world’s sustainability data gaps, empower communities, and tackle systemic biases in technology.
A More Inclusive Future
The marriage of AI and citizen science is about more than data—it’s about shifting power and responsibility. It’s about ensuring that the solutions to our global challenges are informed not only by advanced algorithms but also by the lived experiences of people on the ground. This collaborative approach has the potential to revolutionise how we monitor, measure, and achieve sustainability.
As individuals, communities, and a global society, the question we must ask ourselves is simple: How can we harness this synergy to create the sustainable, equitable future we all deserve?
The tools are in our hands. It’s time to act.
Source
Leveraging the collaborative power of AI and citizen science for sustainable development, Nature Sustainability, 2024-12-16
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