Inclusive AI: empirical data from the civil society

I am thrilled about this most recent collaboration: together with Swissnex San Francisco, the think thank foraus and AI commons I have worked on a report that presents empirical data on what the ethical principle of inclusiveness means when it comes to artificial intelligence. Its title is: “Towards an Inclusive Future in AI – A Global Participatory Process“and it can be accessed for free on the foraus website.

Based on the policy kitchen method (explained in more details in the report) people from four continent have gathered in “11 workshops in 8 countries, involving 10 partner organizations and about 120 participants from a wide range of perspectives, collaboratively generated 43 ideas for an insclusive future in AI.”

The key take-aways of how inclusivity is understood, and can be achieved, are the following:

  1. Aim at inclusive inclusion
  2. Prevent, detect and eliminate bias in AI systems
  3. Establish open standards & access to data
  4. Alleviate power differentials between corporations and individuals
  5. Guarantee shared benefits and prosperity
  6. Provide access to education
  7. Commit to participatory governance

What is most remarkable about this report is the fact that it draws on empirical data from civil society. It therefore applies its own value of inclusivity to the very process by which the conclusions are achieved: by including and listening to stakeholders when it comes to defining what is at stake.

The report is in English — for a short German summary click here.

By the way, our report has been publishes simultaneously with another great paper on “Making Sense of Artificial Intelligence – Why Switzerland Should Support a Scientific UN Panel to Assess the Rise of AI” which I encourage you to read here.

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