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.
Founder of MKAI.org
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:
Access Diverse Thinking: We provide access to our 1,000+ AI ethics stakeholders that will engage with you to discover the 'blind spots' in your AI plans.
Gain Greater Perspective: Many unique individuals will work together to review your AI processes. We help you to spot the mistakes before they materialise into embarrassing or expensive errors.
Be challenged: MKAI stakeholders will ask the difficult questions that might not get raised otherwise. They will challenge you to think wider and deeper about the impact of your AI.
Unlock unique lived experiences: We enable you to speak to people that don't think you like you do, and help you and 'your AI systems' to see the world through their eyes.
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."