Thread: Riderless Bikes
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Old 10-31-16, 11:40 AM
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ThermionicScott 
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Bikes: 1991 Bianchi Eros, 1964 Armstrong, 1988 Diamondback Ascent, 1988 Bianchi Premio, 1987 Bianchi Sport SX, 1980s Raleigh mixte (hers), All-City Space Horse (hers)

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Originally Posted by dabigboy
ThermionicScott, I wouldn't say I have a huge amount of faith in the ability of humans to make good decisions on the road, I just have faith in the tendency of them to make reasonably predictable decisions (vs completely wild and counter-intuitive decisions). Plus, while humans may not always make the best decisions, by taking on the responsibility for the drive into your own hands, your level of risk is more closely tied to your own personal decisions. And I think that is always a good thing. I like known risk: my own skills, condition, and decision-making ability. I don't like unknown risk: the minds of the programmers who designed the car's AI to foresee or somehow allow for every possible circumstance that could ever arise, which of course is impossible.

I'm not really disagreeing with you or trying to invalidate your point of view, I'm just trying to clarify my approach to the whole idea. We differ in where we want to allocate risk.

Imnotchinese, you're hitting on a very interesting paradox of computers vs the human mind. There are certain procedural, logical operations that computers are far superior at. For instance, if an AI-controlled car has information on all nearby vehicles, a sufficiently powerful computer can, in a matter of milliseconds, simulate a number of potential outcomes depending on different courses of action, and choose the one that would seem to have the lowest risk based on pre-programmed conditions and the laws of physics. Furthermore, if the computer is able to accurately measure things like distance, relative speed, direction, etc, it can do very accurate calculations for things like required stopping distance and likely path of travel. But the human mind can do other things in near-instant time, things that continue to baffle our understanding (such as highly abstract associations, inference, etc). Simple example: two people who know each other very well are talking. One says something rather vague and poorly worded, like "it's going to be worth it", when such a statement has no bearing on the current conversation. But the other person will, in their mind, instantly go to something they know the first person is working at, or a goal the two friends were recently trying to accomplish, and make a pretty accurate guess that that's the thing the first person was talking about. Or it may be as simple as a comment that goes back to a conversation the two had some minutes ago. Oftentimes, the mind is somehow able to pick up that comment and associate it almost instantly with one of perhaps many recent conversations.

These truly disparate strengths of humans vs computers are why, while I'm very skeptical of an AI-controlled car, I think a computer-aided car (as we are already seeing) has huge potential. Imagine having graphical vectors of other traffic's movement projected onto your windshield, or markers showing where you'll likely stop if you apply maximum braking!

Ah, this is interesting stuff. I've been interested in AI and software failure modes for some time. My career is in computers, and I've been programming for fun since 2002 or so. Being "passionately curious" is a good thing, I think it's the most important component of learning.

Matt
To the bolded point, indeed. And it's always good to look at the potential failure modes of any system.

If you were severely nearsighted and wanted to do away with your glasses or contacts, would you rather have LASIK or radial keratotomy?
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