On the other side, the prospect of having an oracle that answers all trivia, fixes spelling and grammar, and allows humans to focus on higher level information processing is interesting.
Reviews that look just like real reviews but are actually a weighted average of comments on a different product are negative. Customer service bots that go beyond FAQ to do a very convincing impression of a human service rep promising an investigation into an incident but can't actually start an investigation into the incident are negative. An information retrieval tool which has no information on a subject but can spin a very plausible explanation based on data on a different subject is negative.
Of course, it's entirely possible for humans to bullshit, but unlike text generation algorithms it isn't our default response to everything.
It indeed does. The problem is that societies and cultures are heavily influenced and changed by communication, media, and art.
By replacing big portions of these components with artificial content, generated from previously created content, you run the risk of creating feedback cycles (e.g. train future systems from output of their predecessors) and forming standards (beauty, aesthetics, morality, etc.) controlled by the entities that build, train, and filter the output of the AIs.
You'll basically run the risk of killing individuality and diversity in culture and expression; consequences on society as a whole and individual behaviour are difficult to predict, but seeing how much power social media (an unprecedented phenomenon in human culture) have, there's reason to at the very least be cautious about this.
Sure, I might not be able to tell the difference the majority of the time, but when I can tell the difference it's gonna bother me a lot.
There are creative applications for bullshit, but something that cites its sources (so you can check) and doesn’t hallucinate things would be much more useful. Like a search engine.
So in theory, the rise of deep fakes could lead to more people getting suckered into conspiracy theories and other such extreme opinions. We've already seen a small trend this way with low resolution images of different people with vaguely similar physical features because used as "evidence" of actors in hospitals / shootings / terrorist scenes / etc.
That all said, I don't see this as a reason not to pursue GPT-3. From that regard the proverbial genie is already out of the bottle. What we need to work on is a better framework for distributing knowledge.
At the moment a lot of people seem to have trouble engaging with reality, and that seems to be caused by relatively small disinformation campaigns and viral rumours. How much worse could it get when there's a vast number of realistic-sounding news articles appearing, accompanied by realistic AI-generated photos and videos?
And that might not even be the biggest problem. If these things can be generated automatically and easily, it's going to be very easy to dismiss real information as fake. The labelling of real news as "fake news" phenomenon is going to get bigger.
It's going to be more work to distinguish what is real from what is fake. If it's possible to find articles supporting any position and a suspicion that any contrary new is then a lot of people are going to find it easier to just believe what they prefer to believe... even more than they do now.
[1] made-up number, but doesn't feel far off.
Even fact checkers are not immune to this and brand other news as true or false not based on facts but based on the political spin they favour.
Fake news is a vastly overstated problem. Thanks to internet, we now have a wider breadth of political news and opinions and it's easy to label everything-but-your-side as fake news.
There are a few patently false lies on the internet which are taken as examples of fake news - but they have very few supporters.
Could you give an example?
> There are a few patently false lies on the internet which are taken as examples of fake news - but they have very few supporters.
How many do you consider "few"?
I can go to my local news site and read a story about the novel coronavirus and the majority of comments below the article are stating objectively false facts.
"It's just a flu" "Hospitals are empty" "The survival rate is 99.9%" "Vaccines alter your DNA"
...and so on.
There is the conspiracy theory or cult called QAnon, which "includes in its belief system that President Trump is waging a secret war against elite Satan-worshipping paedophiles in government, business and the media."
One QAnon Gab group has more than 165,000 users. I don't think these are small numbers.
Pew Research says 18% report getting news primarily from social media (fielded 10/19-6/20)[0]. November 2019 research said 41% among 18-29 year olds, which was the peak age group. Older folks largely watch news on TV[1].
[0] https://www.journalism.org/2020/07/30/americans-who-mainly-g... [1] https://www.pewresearch.org/pathways-2020/NEWS_MOST/age/us_a...
Or am I missing your point?
Related xkcd: https://xkcd.com/810/
Given how much bunk “science” (and I'm talking things completely transparent to someone remotely competent in the field) gets published, especially in psychology, it's difficult to do even that.
I mean, Pfizer could dump their clinical trial reports at me, and I would probably be unable to compute their vaccine's efficiency, let alone find any flaws.
Our trust fabric is already quite fragile post-truth. GPT-3 might make it even more fragile.
Why? Cause there is always someone on campus who knows something about a subject to guide you to the right stuff.
Have a look at Russias interference in the previous US election. This is what they did, but manually. To be able to scale and automate it is huge.
The exact balance must be orchestrated by a human.
I think neural nets could help finding fake news and factual mistakes. Then it wouldn't matter who wrote it if it is helpful and true.
Regarding photo news there has been quite a lot of scandals to the point that I’d guess the touchups is more or less accepted.
To hammer the point home I let them retouch a picture by themselves to see what is possible even for a completely untrained manipulator.
It was eye-opening - one of the things that should absolutely be taught in school but isn't.
Namely, critical thinking?
As an extreme example: would you ever checked 20 years ago a newspaper text to know if it was generated by an AI or by a human? Obviously no, because you didn't know of any AI that could do that.
I am lamenting that teenagers were, in this day and age, surprised at what can be done with Photoshop. And that let loose on the appropriate software were surprised at what can be altered and how easily.
My point is suggesting this may be so because people have not been taught how to think for themselves and accept things (in this case female images) 'as is', without a hint of curiosity. It is also a problem but at the other end of the stick, with many young people I work with considering Wikipedia to be 100% full of misinformation and fake news.
There is a secondary aspect of becoming aware that society has agreed on beauty standards (different for different societies) and PS being used as a means to adhere to these standards.
The conversation needs to move on whether making it open and democratic is a good idea, but the tech itself is here to stay.
There are worthwhile conversations to have about democratizing technology, but this stuff is already out there regardless of what you or I do.
This problem should be solved with cryptography, not by banning large neural nets.
Massively plagiarize articles and the search engine probably have no way to identify which is the original content. It's like to rewrite everything on the internet using your own words, this may lead to the internet filled with this kind of garbage.
Reddit and platforms alike filled with bots say bullshits all the time but hard to identify by the human in the first place (current model is pretty good at generating metaphysical bullshits, but rarely insightful content). People may be surrounded by bot bullshitters and trolls, and very few of them are real.
Scams at larger scales. The skillset is essentially like customer service plus bad intentions. With new models, scammers can do their things at scale and find qualified victims more efficiently.
Wait, are we talking about bots posting crap, or the average political discussion?
I hope it's not only due to a decline in the quality of human support. If we could have really useful automated support agents, I for one would applaud that.
As for support, I don't really see why it matters if I'm talking to a clever script or an unmotivated human.