Building Trust in AI: Holistically and Intentionally

Thank you for your questions and responses, I have scheduled a Linkedin Live event to talk about some of the global AI workgroups and what is good, bad or missing in some of these efforts. Please indicate if you would like to attend as I want to keep the group small so as to ease participation. https://www.dhirubhai.net/video/event/urn:li:ugcPost:6909711102389989376/

Pamela Gupta I would like to hear more about the AI TIPS model. Do you have a white paper on it, I agree with Dr. Joseph Nwoye and even more.. Ethics needs to be TOP of mind. Whose Values are being programmed into AI. We seem to be driven into the road to transhumanism where Technology becomes our Master. Too many decision makers are believers in the our brains are a machine concept and we are just a high level intelligent machine. This is why we see headlines like AI becomes first AI/Digital Citizen, ZAFTIG Dreams fattened on Technophilia will lead to ZERO Futures. I would like to hear more about AI in the service of Humanity that remains anchored in the mindset of humans as part of nature - Living Conscious Sentient beings and thus move towards co-creating ZOETIC Futures... My book SMART FUTURES FOR A FLOURISHING WORLD touches on how we might do this individually by using design lens as we well as a value system where the principles spell out the acronym SMART. I hope we have a chance to exchange ideas. #smartfutures

Excellent. I have been following the work of Pearl on Causal Inference which I think has a great potential to address most of the aspects highlighted here.

After reading a couple of your influential works, I have become regular, and the more I read, the more questions I have. This time is no different, especially as you underscored in your work “the crucial need for AI professionals to be trusted to get the best out of AL.” My question, though, is how one can learn to trust a system that has repeatedly demonstrated the reason not to be trusted due to proven evidence of subjugation, oppression, and mistreatment of victims based on their skin pigmentations (people of color). I can give you a litany of why I believe it is challenging to get some folks to trust. Imagine being a person of color and witnessing consistent pain and anguish people go through because of who they are. Imagine being a parent to a person of color who has to endure in their elementary and having pure acts of racism as evidenced in this research link: https://tinyurl.com/4cz3bszc; these are in our elementary schools. It goes on to middle schools, college, university, jobs, including professors discriminated against and sometimes dislodged from their positions by bigots in such institutions, as evidenced in some of the investigations I have personally been a part as we searched for the truth on what highly skilled professional still go through because of who they are. It does not stop there; you can see similar experiences in our criminal justice system. Note, not long ago, the Department of Justice investigated the racist police system and what they do to people of color in Ferguson, Missouri; Baltimore, Maryland; and Chicago, Illinois. The DOJ clearly showed consistent mistreatment of people of color compared to their white counterparts in each of the three reports. I am sure that if they investigated other places, the results would not be different.? I am not even going to banks discriminating based on Zipcode, health care discriminatory practices, etc. So how can you convince people who are now seeing how the bigots in the system misuse artificial intelligence at the airport, like the Hispanic lady I interviewed on her experience with police as she came out from a restaurant and got harassed? I certainly would like a robust articulation of how new you can ensure first that those who are trusted to employ AI can demonstrate what they can do to gain the trust of those whose past experiences do not give them reasons to trust AL?

Brilliant framing Pamela, we need to define our goals for AI in such broad terms if we want at least to properly frame our goals. Rufo