Driverless cars worse at detecting children and darker-skinned pedestrians say scientists::Researchers call for tighter regulations following major age and race-based discrepancies in AI autonomous systems.

  • angelsomething@lemmy.one
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    11 months ago

    Easy solution is to enforce a buddy system. For every black person walking alone at night must accompanied by a white person. /s

  • Dave@lemmy.nz
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    11 months ago

    Weird question, but why does a car need to know if it’s a person or not? Like regardless of if it’s a person or a car or a pole, maybe don’t drive into it?

    Is it about predicting whether it’s going to move into your path? Well can’t you just just LIDAR to detect an object moving and predict the path, why does it matter if it’s a person?

    Is it about trolley probleming situations so it picks a pole instead of a person if it can’t avoid a crash?

    • fresh@sh.itjust.works
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      11 months ago

      Conant and Ashby’s good regulator theorem in cybernetics says, “Every good regulator of a system must be a model of that system.”

      The AI needs an accurate model of a human to predict how humans move. Predicting the path of a human is different than predicting the path of other objects. Humans can stand totally motionless, pivot, run across the street at a red light, suddenly stop, fall over from a heart attack, be curled up or splayed out drunk, slip backwards on some ice, etc. And it would be computationally costly, inaccurate, and pointless to model non-humans in these ways.

      I also think trolley problem considerations come into play, but more like normativity in general. The consequences of driving quickly amongst humans is higher than amongst human height trees. I don’t mind if a car drives at a normal speed on a tree lined street, but it should slow down on a street lined with playing children who could jump out at anytime.

      • theluddite@lemmy.ml
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        11 months ago

        Anyone who quotes Ashby et al gets an upvote from me! I’m always so excited to see cybernetic thinking in the wild.