There is a non-zero amount of reporting that would be improved by algorithmic and model driven story generation.
Quite a bit of reporting has become thinly veiled rewrites of press releases, what could be improved by an algorithm that actually had background context and a consistent model for a type of story like a simple preview of a coming game?
The amount of statistics in reporting that lacks any context for the numbers spewed out? Why couldn't a machine do a better job in enforcing context for the numbers?
For example -- "there is a %50 murder increase in the first six months of this year" (common problem with human reporting) vs "there is %50 murder increase from 2 in the first six months of last year to 3 in the first six months of this year, this is down from 20 in the previous year" (an algorithm that automatically enforces context)?
I realize this is a complex topic but wow the average ;) news story is soooo bad that...
"Also distorting our sense of danger is our moral psychology. No one has ever recruited activists to a cause by announcing that things are getting better, and bearers of good news are often advised to keep their mouths shut lest they lull people into complacency. Also, a large swath of our intellectual culture is loath to admit that there could be anything good about civilization, modernity, and Western society."
Steven Pinker in 'The Better Angles of Our Nature - Why Violence Has Declined'.
Pinker makes a convincing argument -with extensive references- that things are getting better. That's no to say that violence isn't still a problem, things have improved though.
What is the collective toll of inducing FUD in our society?
But then... if there's humans tweaking the algorithms machines will just say whatever we want them to.
I'm pretty sure they're "soooo bad" on purpose. News sites can get away with blatant lies because no one holds them responsible, and they get the ad-dollars as people are attracted to controversy...
You're right in pointing out that bad actors in media will continue to manipulate with disinformation and low information articles.
There is a very high amount of simple incompetence/too busy/poor training.
I'll point out that in developing models for these types of story generation that work could, in turn, be done to validate that what you are reading passes some minimum bar of information quality.
Quite a bit of reporting has become thinly veiled rewrites of press releases, what could be improved by an algorithm that actually had background context and a consistent model for a type of story like a simple preview of a coming game?
The amount of statistics in reporting that lacks any context for the numbers spewed out? Why couldn't a machine do a better job in enforcing context for the numbers?
For example -- "there is a %50 murder increase in the first six months of this year" (common problem with human reporting) vs "there is %50 murder increase from 2 in the first six months of last year to 3 in the first six months of this year, this is down from 20 in the previous year" (an algorithm that automatically enforces context)?
I realize this is a complex topic but wow the average ;) news story is soooo bad that...