Worries are that juicing or doping of AI Machine Learning is gaining traction, an AI Ethical woe and dangerous, including for the case of AI self-driving cars.
As you might directly guess, trying to pin down the specifics underlying these principles can be extremely hard to do. Even more so, the effort to turn those broad principles into something entirely tangible and detailed enough to be used when crafting AI systems is also a tough nut to crack.
I think you can guess where this is heading. If humans that have been making the patterned upon decisions have been incorporating untoward biases, the odds are that the data reflects this in subtle but significant ways. Machine Learning or Deep Learning computational pattern matching will simply try to mathematically mimic the data accordingly. There is no semblance of common sense or other sentient aspects of AI-crafted modeling per se.
In the AI arena, there is a semblance of competition to see who can arrive at the “best” ML/DL models. Various benchmarks can be used to run an ML/DL and gauge how well the ML/DL seems to score on the benchmark. Leaderboards and informal sharing of benchmark results are often used to tout who has achieved the latest topmost position with their ML/DL configurations.
I won’t go further into that ethical abyss here. You can easily go round and round on such a topic. Let’s just say that the spirit of the ML/DL benchmarks is that those utilizing the benchmarks are hoped or presumed to do so in a sportsmanship manner. This might seem naïve to some, while it might seem aboveboard and proper to others.
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