As for the topic of “gender detecting”, a “receptionist” for an office is usually female, for a hotel is usually male; a “nurse” is usually female, a “taxi driver” is usually male, etc. So if the bot is wrong in making that assumption, it’s actually very human-like!
I would love to see you say that in a room full of women. Please wait until I’ve got the camera.
Good one Jan.
rule of thumb #1. humans, in general wear pajamas more so than elephants.
rule of thumb #2. females, in general are nurses more than males.
So these probabilities change over time.
Rule #2 held for decades, up to say the 70’s perhaps. Now rule #2 is not so much. The bot should not perhaps assume this rule now-a-days.
However, I think Rule#1 is at a quite different level of assurance
It is pretty easy to know which rules can be assumed and which not.
For example, whether it is going to rain 3 weeks from today is a bit uncertain, but I think I can assume tomorrow the sun will still rise in the east and set in the west (Rule #3).
Common sense pretty much tells us which rules our bots can assume, and which not.
There are some, like Rule 3, which perhaps won’t be able to be assumed fifty million years from now, and others like Rule 1, which can be assumed for the next thousand, until elephants perhaps evolve and start thinking like humans.
But then other categories, like Rule 2, which like Jan pointed out, is pretty much not a rule anymore.
I hardly think though, that we need to ‘calculate’ the relative weight of these rules. I think pretty much anyone could put these rules into categories of how long they are likely to be in effect… and simply enter them into a chat bot, along with there relative “time to live” approximation (whether it be days, years, decades, millennium or millions of years… ‘ball park’ estimate is good enough)
Again, these rules are just that.. rules of thumb, and if the bot makes an error, doesn’t matter, people also do make the same errors.
You simply want to minimize the number of errors made… and these rules of thumb would help in that way.
Some of these rules would also be affected by context. For example, in Iran, women aren’t allowed to do many things that men are allowed… so the rules would be adjusted if the context of the conversation was Iran. You get the idea.
Perhaps this Time-To-Live factor, associated with each category, could be such that we would have categories of : a) physics b) human employment trends, c) animal versus human behaviors ,etc.