@ariadne When did CCS become obsolete?

@aud To me, and after further thoughts, this seems a lot like Wikipedia, so I would start by describing how you would differ from Wikipedia.

@ireneista @aud I was thinking of long-established reputations, such as those of well-known scientists and organizations. That would be able to filter out the vast majority of e.g. COVID-19 or climate change misinformation.

@ireneista @aud Maybe the solution is to instead change the incentive structure. If people aren’t incentivized to game the system, then they won’t.

One option might be to tie results to something that has value and cannot be replaced easily, such as the author’s real-world verified identity. Legitimate scientists and other scholars will not have a problem with this, but it will hopefully make life much harder for spammers.

@aud @ireneista I think it is best to avoid generating results directly, instead merely linking to results found elsewhere. Generating results means generative AI and that is a nightmare.

@aud @ireneista I think it would be best to start with text only, as opposed to images, video, or audio. The reason is that the requirements for moderating media are much stricter than for text IIUC. (IANAL, of course.)

@aud @ireneista Are anonymous contributions a requirement? My understanding is that one can have anonymous contributions or prevent ban evasion but not both. One can use a trusted third party but that just leads to an infinite descent problem.

@ariadne is this a joke or do you want a serious response?

@ireneista @multioculate @emma Can you explain fruther? I haven’t dealt with textbooks since college, so my memory of that isn’t too great.

@ireneista @multioculate @emma Codebase I agree with, but how can someone jump into code without first understanding the problem the code is trying to solve?

My first programming internship involved writing simulations, and my main problem was not the programming (even though I was a very new programmer), but rather insufficient knowledge of numerical algorithms and the underlying problem domain.

@ireneista @multioculate @emma Do you mean training on the specific codebase, or training on software development and/or the underlying problem domain?

@ireneista @multioculate @emma I would argue that the problems these systems are solving are complicated, and so any system that solves them must also be complicated. To give just one example, one cannot understand software that flies an airplane without first understanding how airplanes fly!

I suspect hiring difficulties are due to one of a few factors:

1. Not being willing to train software developers in the problem domain and/or being unwilling to train domain experts in software development. It is not realistic to expect someone to already have training in both software development and aerospace engineering. Employers need to be willing to train people in one or both of these.
2. Problem domains that are not attractive to potential employees. Lots of people simply are not interested in working in the finance or aerospace sectors, either because they do not find them interesting or because of personal ethics. (Remember that aerospace and the military have a lot of overlap.)
3. Employers are not willing to pay competitive salaries.