You have some system that tried to balance bias, variance, and utility. Sometimes that best way to do that is to have some bias. The classic example of this is you may jump when you see something that looks like a predator, but then turns out not to be. The cost of being wrong (see nothing when predator, see predator when nothing) means it's optimal to sometimes see danger that isn't there.
It's hard to answer your question, since both ethics and rationality are fuzzy, slippery concepts that need to be nailed down firmly to reason meaningfully about.
Or, put less pretentiously, I don't know.
Humans are notoriously great at pattern matching, and seeing things that aren't there simply based on a prior mental model. Stereotypes of all kinds are a result of this.
And if my group was more aggressive, there are some probability that yours didn't even survived and mine did. Or if I was more "racist", perhaps my genes would spread better. So, some genetic that makes me don't like "different" people might have a role.
If our genes didn't evolve (in that aspect) in some few thousand years, simply because there wasn't enough ambiental/social/whatever pressure in that direction... here we are.
This is the purpose of technology. To enhance our skills. From fire to machine learning, tools are built to make our lives easier and help us make decisions better.
In the end we're better off with more empirical computing in our decision loops. Eventually hopefully we totally replace ourselves with better, more consisitently optimized decision making systems.
We also see a decrease in the ability to focus with people using a lot devices with screens.
I'm quite concerned of what AI is doing to our brain skills: pattern recognition, memory, data processing and summary... Al that stuff, left untrained, could lead to regression.
We already see a lot of people going to the gym, doing artificial exercice to keep their body in shape. And now we got those popular games to "train your mind" on phones and consoles.
It's a issue IMO, but not an easily solved one. Who don't want to use innovations bringing confort, productivity and increased lifespan ?
I don't see a material distinction in here. A machine is simply a more effective tool - effective enough to do the work mostly by itself. The "replace human labour" part is a consequence of the economic systems we have.
Technology arises out of a sense of purpose from it's user. This is pretty common understanding in philosophy of science.
If you look at the long term, in the world that the article describes (slow, gradual with rare cataclysmic changes), most wrong decision makers will still die at a higher chance than correct decision makers. It's just in those rare situations that they survive.
The bigger assumption in this article is in what natural selection selects for with humans. For sole individuals in any species, you typically need only to live long enough to reproduce viable offspring. With humans, we've evolved intelligence that has lead to a tribal culture.
That means that natural selection doesn't apply to the individual, but the majority of the species. The best individual of the entire human species is enough to hold natural selection back for everyone else (i.e. vaccines, engineering feats, etc.). That doesn't mean we've evolved to making bad decisions, it just means that the collective knowledge of our species is now being subjected to natural selection instead.
Two ant colonies A and B. Sugar is abundant in the area and all ants in colony B prefer sugar. 95% of the ants in colony A prefer sugar while 5% prefer peanut butter. The ants that like peanut butter have a higher risk of getting killed because peanut butter is scarce and they must travel further. They also use more energy in getting food. One day a truck drops sugar near the colonies that is poisoned. Colony B is wiped out. Colony A survives on because of the 5% of ants that prefer peanut butter. The queen may die but the surviving ants reproduce.
We all know someone who hates a particular food that most people love. We all know someone who loves a food we think is disgusting. Why don't we all like the same healthiest foods?
I'm not an expert on genes but it's possible that in one species, taste or some other variable is determined by 1 or 2 genes. In another species it may be determined by 8 or 9 genes. This complexity in taste determination may cause more variation in how it manifests. Maybe that complexity causes odd variations to occur over generations. Even as other factors select for sugar in one species, individuals keep popping up that like peanut butter.
So the more complicated explanation as to why humans vary is that humans have a specific set of adaptations for learning and filling their place in the social environment. This is the entire point of childhood - trying things, seeing what works well, doing more of it, and winding up a person who does the sorts of things that work well for them. This means that if you happen to be gifted with bad eyesight and good verbal processing, you'll get early successes at storytelling that lead you to that sort of role as an adult.
That, in a nutshell, is why humans have such variance. It's the result of childhood, which is a specific algorithm that genes use to find and exploit the things the hosts happen to be better at.
And this built-in ability to vary oneself is helpful both for the strong and the weak, the pretty and the ugly, the clever and the dull, and so forth. It means instead of over-fitting for behaviors that work for the strong, the trait enacts a strategy that does strong-person behavior in strong people and weak-person behavior in weak people.
Crucially, this shows the difference between Traditionalism and just having a lot of cultural context. Culture itself is just weight - more of it is harder to change, but it's the same difficulty no matter how fast you go. Traditionalists, on the other hand, will fight you harder the more quickly you're changing cultural facts.
their general-purpose nature means that our minds take on the additional complexity of context switching as we use our tools for multiple simultaneous tasks, and indeed this generality means that they can be quickly adapted to new contexts. contrast this to specialist tools which, once learned, provide significant increases in efficiency in the specific context to which they have been adapted (including the benefits of increased concentration owing to lack of distraction!) but cannot always be re-engineered easily to suit new contexts.
Reading this made me think of the numerous financial firms in history that become very efficient at making money in a particular type of market environment, which inevitably changes suddenly in unexpected ways, causing those financial firms to blow up and maybe even start a financial crisis:
* https://en.wikipedia.org/wiki/List_of_stock_market_crashes_a...
* https://en.wikipedia.org/wiki/List_of_banking_crises
Society might be better off with financial firms that are "dumber!"
The takeaways: - The path to success is through NOT trying to succeed - To achieve our highest goals we must be willing to abandon them - It is in you interest that others DO NOT follow the path you think is right
Put another way, animals have upper bounds on the positive value they receive from risks. In human terms the first billion is worth vastly more than the second.
[0]: https://people.hss.caltech.edu/~camerer/Ec101/JudgementUncer... [1]: http://www.math.mcgill.ca/vetta/CS764.dir/bounded.pdf
It's worth considering, especially in light of the authors' suggestion that we use computer/human decision-making systems to improve performance, as the world is still unpredictable, and can still break our paradigms. The biggest danger of setting up a good system to improve knowledge is that you'll think you've got a perfect one--we could improve our rationality and decision-making with computers for a long time, before an unexpected case cracks the system, and we're left floundering.
Although there's so many factors and chance that influence the results of every decision and you can only have so much information and perspective, so you can only do the best you can.
The map is not the territory. We work with models of how the world works when deciding things, not the actual world, so it's bound to not be 100% accurate.
Computers do the same, although they can crunch a lot more data than we can, they still work with models of the world, not the world itself.
For survival reasons the brain needed to evolve to make both quick decisions and well thought decisions.
If a predator appears in front of you you might not be able to give a lot of thinking to the decision of what you need to do.
If you are a nomad during the ice age and you need to collect food and prepare a shelter, or track a prey for long distances, you probably need to give it some thought.
