It’s easier when what happens is left to chance and the only one accountable is the driver, isn’t it? > Moral Machine is learning how we want self-driving cars to kill https://t.co/NrQ4jj5Npv

Shame the time didn’t allow to go deeper into each slide. Plenty to say that was not said. https://t.co/yxFET60HEw

@fintanr I think there’s a misunderstanding. See, you think that “noops” means “(there’s)noops”, but in reality they mean “(I do)no(t want to deal with)ops”. Which is the ultimate proof that cross-silos collaboration is more of a bunch of good intentions than an attainable strategy.

This is a high potential #AI application. I bet military orgs would love it (if they are not working on it already) > Machine vision has learned to use radio waves to see through walls and in darkness https://t.co/wc5Kh192RU

Paradox: the organizations connecting most humans in the world (government, news, social media, etc.) are the ones that fail the trust of their user base the most.

What is the name of the paradox where the organisations connecting most humans in the world (government, news, social media, etc.) are the ones that fail the trust of their user base the most? https://t.co/OVYlpqk0dj

I see forgetting over and over that “a vendor” is an organization made of people. People that read what other people write. People that are distracted/influenced/manipulated by what other people say. People that feed on the opinion of other people.

New non-sensical definition: “data-driven monitoring”.

“either do a job where your best judgment is required, or do a job where management will work hard to replace you with someone cheaper” > Use your best judgment https://t.co/XATEhNylzn

Just in case. The problem, tho, is that once the video has spread and is relayed by multiple sources, it creates a bias that is very hard to eliminate > California has banned political deepfakes during election season https://t.co/K7Oq56i1eX