In our algorithm-driven world, companies that can demonstrate their trustworthiness will win.
Multi-Stakeholder Feedback is essential to identify potential harms of an artificial intelligence application. MKAI has the largest and most diverse AI de-risking community in the world.
Learn how to gain vital perspectives about the potential risks, harms, exclusions, biases and prejudices from your AI.
Start a conversation with us
Let's talk about reducing your AI risk through accessing diverse perspectives
It is impossible to understand what it is like to experience the world as a person of a different gender, race or age to your own, or as someone with a disability or that thinks differently. The only way to learn is to ask.
Richard Foster-Fletcher
Founder of
Algorithmic bias and injustice are prominent topics in AI ethics and machine learning conversations, and for good reason. From racist chatbots to facial recognition algorithms that fail women, there have been many cases of bias and injustice infiltrating artificial intelligence models. The risk implicit in the technologies we are supposed to trust has been exposed through high-profile failures in artificial intelligence (AI) and autonomous systems.
What does MKAI Multi-Stakeholder Feedback for AI do:
Who is this for?
Anyone deploying AI is open to risk, but there is specific pressure to get it right on those companies involved with:
● HR Automation
● Social Media Algorithms
● Recommendation Engines
● Education Technologies
● Insurance Algorithms
● Health and Medicines
● Security and Surveillance
● Government Related Systems
A word from our Innovation Director...
"Good processes and governance are not enough to address the serious issues that can arise from AI. A broader perspective is needed, and now is the time to mandate that multi-stakeholder feedback is consulted for every high risk AI system. There is simply too much to lose."
Dr. Odilia Coi
Director of Innovation at
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