For many cognitive processes, I don't see a clear survival value to conscious awareness of that process, so I don't expect that awareness to be a reliable feature. The survival relevant result of that cognition can still come through.
I also think that an internal voice that doesn't get conscious awareness is likely to become a process that doesn't present as voice. So it's not like someone can just pay more attention and hear something, because it stopped talking a long time ago.
I look at this like Multimedia and the web in 1995. Yes some of this is a shadow of Microsoft Bob. We don't know what we're doing with VR yet but the technology has crossed over the line from being a toy or experiment. Skeuomorphism is a temporary workaround until we (users and designers both) learn what conventions are most powerful and port more applications to VR.
They're paying for credibility, but assigning the credibility to an organization instead of an open and understood process of vetting. This confuses me.
I think this is a reference class problem. One could also say software replaced work done in offices with work still being done in offices. (until recently) Most of the work was still done on literal desktops. but significant changes have been happening within the subset of the office and within the use of the desk.
General construction kit for real world applications. In theory you could take a machine apart and use the beams for some other machine. A smaller kit could build any of the machine designs as needed.
If someone is subsequently charged with fleeing, having a reasonable belief that someone was impersonating officers could be an easier defense than merely fearing danger, however founded those fears may be.
Friendly suggestion to all that Bayes Theorem is the right way to deal with this kind of weak evidence. We should not adhere to arbitrary legal standards in our own thinking about the truth.
I just signed up to prolific. Their onboarding tutorial/example survey references prescreening and eligibility. I'm guessing it was on researchers to filter the demographics to what was relevant to their study.
I think this is actually the right approach. Some 'balancing' algorithm would have to make assumptions about what's normal, then then the excluded participants wouldn't even show up in the research data.
If 2x programmers are paid ~2x then the company is using some performance metric to influence pay, but then for pay to remain secret the performance metric also has to be secret.
You have to weight the validity of the reasoning across all turtle observers through history. If you reject probabilistic reasoning because it sometimes tell you things that are wrong, then you have no way to reason about uncertainty.
There is virtually no real diversity in experimentation on social decision making processes. (Governments, Economies, Science) So debates devolve into some form of e.g. capitalism vs. socialism, but both system are governed by similar variations of a sovereign nation state, which are adapted from monarchies. Compare this to the space of all possible government descriptions and we're only looking at a weird narrow slice.
Because evolutionary pressures on governments produce stability and power instead of 'goodness of people', I suspect any random system that sounds remotely sensible would probably be superior to anything we have now. If we actually designed something that took into account new knowledge and technology, we could do much better.
Expectation of future profits is equivalent to belief that markets are inefficient. (Which of course they often are.) Open source economic planning could yield massive economic gains and doesn't require centralized power or use of force. (Pacifist governance is one of those unexplored spaces) An open public ledger would allow for resource allocation and incentivizing work without needing a monetization strategy.
If we track and account for externalities doing a good thing funds itself. You don't need a way to take money from the people you're helping. This also disincentivizes negative externalities.
As an example of how bad things are: We still debate on natural language forums instead of using structured arguments that link to common datasets and simulations. These comments get 'points' instead of bayesian probabilities, and there's no way to filter or rescore anything based on it's epistemological support or new data.
I agree with incentivizing health in general. Doing so without providing healthcare seems wrong.
Doing so through income tax rates is muddling the issues. The rich would hire dieticians and trainers just to save money. If public health is actually a priority, those kinds of services would be subsidized.
It is unpopular among university and research institutions that get federal grants. Also development companies that win contracts to create government websites/backends.
I agree with it, but it would disrupt a whole industry.
* Low friction, nothing to install, near instant feedback.
* Fun starting at simple shapes, gradients, distortions, all the way to absurdly good looking rendering.
I did have that experience of growing up with fun programming, for me shader programming brings that back.