Thank you, I think that's a very good point -- all the talk around whether we should lie to people because they're too stupid to understand science, plays right into the power games of the powerful, who want to just manipulate things for corrupt reasons.

Here's $100 million, now go write some papers that support some policy which ultimately gives our corporation more power and profit. And if any other scientists question it, just tell them that they're not in the field. And if that doesn't work, we can think of other methods to discredit their criticism.

One of the other comments mentioned how Margaret Thatcher was a scientist. It's a hilarious one to mention because there are people out there who point out that Thatcher deliberately chose global warming as a scientific reason to break up the coal industry and basically defeat the miners unions and strikes. The story goes that she chose global warming because it was science and therefore no politician would be able to question the reasoning for the policy. Which I think is an example which shows that there are layers of manipulation and if you really want to, you can take any piece of science and manipulate it to support your own interests, and then claim that the policy you want to institute is "because of science" when actually, there could be all sorts of other options, but if anyone questions and asks for options, you call them anti-science.

Did science explain that subtle difference between relative risk and absolute risk?

Because if they didn't, then they still weren't telling the public the honest picture.

There's a pernicious habit that, because the majority of people are stupid, we have to convince them using dumbed down arguments.

This new law/policy is justified because of scientific facts...

and then anyone who questions not just the quality of the science but even whether the policy is a reasonable response, gets called a flat earther.

It's entirely dumb, because it really doesn't help anyone. Anyone with half a brain senses they are being lied to.

So yes, if you think the scientific issue is nuanced and based on a best effort of what data can be measured, and all the limitations, and the existence of counter evidence, then the only answer is to help the public to think harder.

Trust is processed at emotional levels and it is a form of thinking, albeit nonverbal. Even "stupid" people notice when others are being economical with explaining the situation. All anyone has to do is avoid answering a question. Everyone sees it. Oh but we're scientists and you're not... trust blown.

So seems like a good and sensible point from some scientists.

Because they watched Mr Robot and hence knew it was normal for extra Raspberry Pi's to be laying around.

Yep, why not buy the book, remove the binding, scan the pages, and even throw away the paper. This whole license thing is going too far.

Everyone I know who makes my equivalent AGI, except for my household, has 1+ dogs, work crazy hours, and have been told that their dogs are lonely and depressed.

Not one or two people.

EVERYONE. Dozens upon dozens of my clients, colleagues, peers, friends from grade school, etc, have a dog or two, and then they have to have someone come spend time with said dog when they're putting 10+ hours away from them.

Wag/Rover/etc is part of their crazy consumer spending. I always am shocked to hear they're spending $1000 a month on their pets.

Americans are insane about their pets. Instead of buying a dog, I invest in corporate veterinary hospitals, because it's crazy profitable.

Opinions identifying people are under GDPR, albeit with balances.

If it identifies you and states something about you then GDPR says you have rights about that information, as I understand it.

I mean that a quality control process would slap a big label on these AIs and tell everyone what they are capable of and what they aren't. Like a use-by date on food.

Exactly, and well said!

At least with traditional programs based on running logic rules, the lack of an "I" (which can check with other felt experiences, like, did I just hammer my own thumb) isn't a problem as much, if the rules are well defined enough, and we're not getting tripped up by logic flaws, like unanticipated coercion of values etc.

Crucially, it is the programmer who is the "I" performing the hard work of representing the real world using symbols and rules, of creating a working logical model representation.

But with AI, the "I" programmer is gone and instead we're relying on it training itself on a vast dataset — and assuming that the resulting working model isn't just a machine but somehow "understands" what it is doing — this was never the case with traditional programs, and so far isn't the case with LLMs either? But because the method is training, rather than a human doing the work of figuring out the logical representation model, we actually end up with less reliable models?

Hence the need for humans to find ways to retrain and bias the resulting correlations, basically beat it with a stick when it gets things wrong, and we rely on people finding all of those problems, and hope the model remains stable enough to not have that forcing mess up some other correlations.

If I understand correctly.

Well yes, if the people developing these models aren't interested in quality control then it's going to get real interesting.

The hyperbole, around general intelligence models replacing humans, is a massive, massive distraction from their real value.

Their real value is to apply these deep learning models in a very domain specific way, get them to solve very specific problems; analyzing voice, images, picking out patterns in data, etc.

We seem to have gone down a very weird deluded story which is boosted by the delusion that, because these models can sound and talk like a human, that they can suddenly replace a thinking human in all sorts of jobs and areas -- even though a human being is a product of three million years of evolution, and even each job requires years of experience and skill to understand. Many jobs are networks of relationships between people and contexts -- things the people have to learn as they enter the organisation and find their feet. (And why outsourcing or even reverse outsourcing is so often problematic.)

It's a fantastically ironic situation, that people are betting huge sums of money on intelligence, out of their own ignorance about what intelligence is.

What these general LLMs seem to be doing very well, is to do what people often do, which is to hear and repeat the kinds of things which are often said and which are therefore taken to be kinds of truisms and general guides to what the assume and believe about problems and issues.

If you're surrounded by a culture that believes for example that Russia is our eternal enemy, then that's pretty much what you're going to pick up from people around you, from the news, from the media, and it's what will hence also get fed back to you by the LLM. None of that is original thinking.

For a small company with some on-site stuff, there's tons of options.

First make sure the backup server can access live servers and desktops and not the other way round. That stops an infected server being able to encrypt its own existing backups.

Next, use a file system that does checksums like ZFS. Have a separate isolated machine scrub each drive periodically to ensure that they still work. This just means having someone do it and having a clipboard with a checklist like how cafés have rotas for cleaning the toilet.

Then, put drives in a on-site fireproof safe which gives you 40 minutes in the event of a fire.

A small company may have a couple of other locations which they can just carry disks to as well. If that is too much of a hassle, then use an entirely separate cloud storage area to upload snapshots.

There's going to want to be a temptation to automate everything and then forget about it, but an advantage of having to have all these manual steps is that it means someone has to take care of doing it which means it's being done consciously.

The benefits of a Game of Thrones education.

Accidentally replied to a sub post!