Implication of Leiden Declaration on Artificial Intelligence and Mathematics on Design

On June 2, 2026, the International Mathematical Union (IMU) published a call to action on the challenges posed by artificial intelligence on mathematical research and expectation from researchers and educators in the field. Perhaps this is the right time for the global design community to do the same.

Link to declaration: https://leidendeclaration.ai

The declaration is structures as follows and it seems like a great starting point for design field:

• About our values
• Potential threats
• Recommendations for individual mathematicians designers
• Recommendations for mathematical design organizations and not-for-profit research funders
• Recommendations for policymakers in government and elsewhere
• Recommendations for commercial artificial intelligence

Design (my focus is on information technology sector) is undergoing a period of deep uncertainty and it would seem is on the cusp of being replaced by artificial intelligence. An industy wide, consultative approach for design industry is the call of the hour and I implore the design leaders and organizations at the forefront of design need to act quickly and define the road ahead.

In absence of such a guiding north start, our design industry might be in for a lot of pain and skill gap. Till this happens, we at Maya Studios are defining our own AI declaration with goes as follows:

One of the reason we got into the field of design was to be part of a community that works directly in endeavours that makes the world better, just and equitable. As individuals, groups and communities, designers at heart like to create artifacts that improve lives. We absorb the world around us, search for unique experiences, and create meaningful solutions that, we believe, cater to these unique human conditions. With automation, more of our work is becoming commoditized and for a while it seemed alright. But as technology and economic liberation spreads around the world, people are no longer looking for commodity experiences. We have a duty to uphold the core characteristic of our work so we pledge:

• Discourage the use of AI in our work and daily practices
• Disclose work created by use of automation
• Focus on connecting with and knowing our uses as unique individuals and as part of a community
• Respecting the humanity of people who will be effected by our directly or indirectly
• Accommodate human uniqueness and their unique needs in our work
• Help the next generation of designer to acquire skills that bring them closer to human condition and experiences
• Reject work, no matter how lucrative, that requires human surveillance of any kind (data collection in particular)
• Reject work that force individuals, groups and communities to hand over their data by force or otherwise

These are the values we at Maya Studios practice, and should not be taken as a prescription for anyone else.

• Focus of core skills, without skills you will work for automation and not the other way
• Humble yourself (easier said than done), find out the least empowered user that might be effected by your work
• People are real, not numbers, segments, audiences and personae, have genuine connect with them
• Tools define what you produce, choose your tools wisely. Go for least powerful tool you can find
• Technology is your friend only when you have the respect for humanity, unleash it with care
• You are only disempowered if you love less and want more
• Designers are not special, just one among equals

• Put humanity and environment first, no amount of AI will feed people
• Put the rights of humans, groups and communities first
• Ground, any and all, policies around the least empowered and represented and then expand for the rest
• Make artificial intelligence a public good and not an investment avenue
• Reject the myth of surveillance is necessary for security
• Redistribute AI wealth for public welfare

• Please stop, as per your own admission, AI is too dangerous for humanity to be in the hands of individuals and corporations
• Be honest and disclose your date sources, algorithms, weights, water and energy usage
• Make it legally mandatory for all your employees, associates, etc., for them to disclose harm done, or possibility of harm by your models to the public
• Share dataset life-cycle for public scrutiny
• Take consent for derivative data uses for new applications from users