Norrsken

Challenge 01

Building a sustainable and healthy city for the future

In collaboration with Transport Committee, City of Stockholm.

Stockholm is expanding: new districts are being built, infrastructure is growing, and the population is rising. Now the question is how we design a city that improves life for both people and the planet.

Picture a Stockholm with clean air, thriving biodiversity, and more accessible green spaces. A city where movement is easy, energy is renewable, and every neighborhood feels safe and connected. A place where urban planning, data, and technology come together to support well-being, not just efficiency.

Climate adaptation, housing, transportation, and energy use are all deeply intertwined, and the choices we make today will shape how people live for generations to come. How can AI and data-driven design help us create a more livable, sustainable, and inclusive city for the future?

Assignment

Build an AI solution within one of the following areas:

A) Movement & Mobility

How can we reduce emissions and congestion while making it easier to move through the city in sustainable ways? How can data on movement patterns, noise, emissions, and infrastructure be used to create smarter, more accessible, and climate-friendly mobility solutions?

B) Green Space & Health

How can trees, parks, water, and nature contribute to well-being, cooling, and biodiversity – while protecting vulnerable groups such as children and the elderly from heat stress? How can we combine climate and green-space data with information on where people spend time to identify areas with the greatest need for shade and cooling?

C) Air and Energy

How can we measure, understand, and reduce urban emissions using open data and new tools? By combining real-time and model-based data on air quality, emissions, and energy supply, we can create visualizations, predictive models, and solutions for smarter energy optimization.

D) Participation & Equality

How can more people take part in shaping a sustainable lifestyle, regardless of background or circumstances? Data related to social, economic, and health dimensions can reveal inequalities and inspire solutions that strengthen inclusion, equity, and participation.

E) Climate & Resilience

How can we make the city more resilient to heatwaves, flooding, and climate change – especially for those most affected? By mapping risk zones and analyzing how extreme weather impacts people and infrastructure, data can support local adaptation measures and help build a more resilient city.

Output

A prototype (dashboard, AI-assistant, or interactive simulator) that demonstrates the impact of different transport policies on emissions, air quality, and health by 2030.

A pitch explaining how the solution could help cities design smarter and more sustainable mobility strategies.

Data sources and tools

For this challenge, some data sources may require pre-approved access. Make sure to review the data source document well in advance. We recommend preparing your data setup ahead of the Fixathon – some sources are open, while others require an account or API key. You can find more details in the document under Data sources and tools below.

Data sources

Approaches

Challenge 02

Building an inclusive future of work

In collaboration with Arbetsförmedlingen.

A strong and inclusive labour market is the foundation of a resilient society. Yet today, too many people are left standing on the sidelines — recent graduates struggling to enter their first job, professionals needing retraining, or newcomers finding it hard to match their skills to the opportunities available.

At the same time, the demand for new competencies is shifting faster than ever. Traditional systems for matching people with jobs, or for updating skills, can’t always keep up.

What if we could use AI not just to automate work — but to open doors? To identify hidden potential, connect people to meaningful learning paths, and make transitions smoother for those at risk of being left behind?

The challenge: How can AI help build a more inclusive, adaptive, and equitable labour market — one where everyone has the chance to contribute, learn, and thrive?

Assignment

Develop an AI-driven prototype within one of the following areas:

Support reskilling and learning: Design tools that recommend new skills, courses, or micro-credentials based on each person’s background and ambitions.

Rethink how we recognize human potential: Explore new ways to identify skills, creativity, and problem-solving abilities that don’t appear in traditional CVs or formal education data.
Prepare people for the jobs of tomorrow: Create tools that help young people and career-changers understand emerging roles and build the capabilities needed in an AI-driven economy.
Bridge opportunity gaps: Design inclusive systems that connect individuals currently outside the labour market to real opportunities for learning, work, and participation.

Build fairness into the future of work: Ensure that AI-driven tools promote equity, accessibility, and diversity, helping everyone to participate in and benefit from economic transformation.

Output

A prototype (app, dashboard, AI assistant, or data model) that demonstrates your idea in action and addresses the challenge.

A short video (1–3 minutes) that explains your solution — what problem it addresses, how it works, and the potential impact it could have.

Data sources and tools

Here, you’re encouraged to explore and identify your own data sources, research, and insights that can help you shape your idea.

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Data sources

Society

Building a sustainable and healthy city for the future

Assignment

Output

Data sources and tools

Approaches

Building an inclusive future of work

Assignment

Output

Data sources and tools

Approaches

Jury

Prizes