I'm going to let you in on a secret-- not everything you read on the Internet is true.
I know it's shocking, but it's the case.
In fact, it turns out there's a lot of good information and then there's some other that's not.
In trying to figure out which sources are reliable and which ones aren't is actually not always that easy.
But where do we go if we're looking for answers?
Well, it tends to be any more these days, we go to a search engine on the Internet.
And Google happens to be one of the best of these, so that's the one that we go to, probably most often.
So let's take a look.
What would happen if we did a search on Google and we asked it to tell us "Who invented the airplane?"
Okay, you're going to see results that look like this and it's going to get-- you see a number of names there.
And apologies to my friends in Brazil, but since I'm in North Carolina,
I'm going to go with the Wright brothers as the inventors, not Dumont.
But these are the different sources-- so there's some debate.
And if you look through the list of Google results, you're going to see things that are links that could be reliable.
You're going to see some links that may be fake news, and you're going to see a bunch of ads.
And trying to figure out which one is which, again, not always obvious.
Also, you're going to see a discussion about this controversy as to who was actually the inventor.
So if you're just looking for a quick answer, we really didn't get it there, but we did get a lot of information.
Now, it turns out that we have newer technology, AI-based technology-- chatbots
--that are giving us information in a much different sort of way.
One of the new ones that's really taking the Internet by storm these days is called chatGPT.
Let's ask it the same question.
Okay, "Who invented the airplane?"
And we see a very simple, succinct, authoritative sounding answer.
We don't see a controversy.
We don't see lots of links.
We don't see ads.
We don't see fake news.
We don't see--there's nothing to really sort through.
It's just the answer that we're looking for.
Well, that's really attractive.
If I can just ask a question and get "the" answer and not have to sort through it? Well, look, who isn't going to go for that?
We're going to, as these chatbots get better and better, rely on them more and more.
Now, this may not be a complete replacement for search engines
because sometimes I really do want to look at all the different sources and sort through it.
But the point is, we're going to start relying-- probably more and more --on these kinds of sources.
But what makes something reliable?
Well, it tends to be that we look for observability, we look for the citation of sources
and things like that, because some sources we trust more than we do others.
But when we're looking at something like a chatbot's answer, we don't get that.
So there's a tradeoff here.
Bottom line, though, if you look at these two results, one's really long and I have to sort through
and pore through all the details and do my own thinking and the other and just tells me is the answer.
What do you think most people are going to go for?
The simple answer.
Now, that sounds great.
What could possibly go wrong?
Let me tell you what could possibly go wrong.
Well, so how does this stuff work?
Well, it turns out that we have an AI system and the AI that is behind the chatbot has to get its information from somewhere.
So we use a knowledge base, sometimes many different sources, and this knowledge base, we call a corpus.
And that corpus is what we use to train the AI, so that then we can have a user come along here,
ask a question of the AI, and get an answer back.
So this is the model, and that's all fine and good until somebody decides to mess it up.
Somebody like this guy comes along and says,
"Wouldn't it be fun if I corrupted some of the information in this corpus?"
"What if I introduced a little bit of wrong information and had it mixed in with the good?"
Because if it came in, which is really, really blatantly wrong information, this guy is going to detect that.
But if we come in with a little bit and just corrupt a little bit of the results,
then we corrupt a little bit of the answers and this guy ends up with the wrong information.
And as we become more and more relying on these kinds of sources, something like this can be insidious.
It slips in, and before we know it, we've now made decisions based upon bad information.
Now, one of the popular ones of these that I said before is called chatGPT.
It's a great resource.
And you saw what kind of answer it gave.
I'm not saying that this has ever happened with chatGPT.
I'm saying let's take a look at this as an example and see what could happen.
What if this happened in this case?
Well, in the example I gave before, we might get the wrong answer about who invented the airplane.
Not the end of the world.
Nobody is harmed by this.
But what could happen if the corpus poisoning case led to something more important, something more insidious?
Let's say I go to chatGPT and say "I want to come up with a household cleaner just using stuff around the house."
Well, we could do that kind of search.
And if I do that, I'm going to get back a very simple answer that says,
you know what, you could use baking soda and vinegar and water and mix them in exactly this way.
It's a nice formula.
Again, I didn't have to search a thousand links and figure out which ones to use and which ones don't.
I got a simple authoritative answer right there.
So let's say I mix it up and I clean my house.
Great!
However, let's look at the case where a bad guy snuck in a little bit of bad information into the corpus.
Again, not saying this happened with chatGPT, but I'm saying it's possible with any AI to potentially poison the corpus.
And if that were to happen, what if the formula that came out then came out and said,
instead of using those ingredients, let's mix ammonia and bleach.
Okay, those are two things you have around the house.
Well, it turns out that's quite toxic.
That's a bad result for you.
And it could result in health problems for the individual that ends up mixing these two things together.
So this is just an example.
I'm not saying that the world is going to come to an end because somebody mixed up bleach and ammonia.
But imagine that example where this person is making decisions-- important decisions
--based upon information in their AI, and they become so reliant because this chatbot
has been so trustworthy for so long that we end up with a problem.
Well, this is not without precedent.
In fact, we've had chatbots go rogue before.
There was a case where a chatbot went on the internet, started learning the language of the internet and the way people interacted,
and within a day it was spouting all kinds of offensive things to people and had to be shut down.
So, again, not everything that we see on the internet is in fact true, and not everything that's true is worth talking about.
So there's a filter that has to go on.
So what should we expect of our AI?
Well, we want some sort of observability in order to create this level of trustworthiness.
We want to be able to verify.
In an ideal world, I'd like for the chatbot to cite its sources so that I can then go to those sources and verify.
I'd like to even it, almost in a math way, say "show me your work." Don't just give me the answer.
Sometimes we just want the answer, but in some cases we really need it to show its work.
And a lot of times, these systems don't do that.
But we're going to need to rely on that.
Another example where this could come along is with code samples.
You can go into chatGPT for instance, and it's very good, tell it to write you a particular routine--
and tell it the language --and it will give you source code. You can copy and paste it into yours.
Again, great stuff.
But what if the corpus was poisoned and in fact it inserts malware or a backdoor into your code.
If you start relying on that as your source and all you do is say, "write me a code snippet," copy and paste,
and you don't verify what's happening, you could end up with a program that's a disaster and not even know about it.
So this is what we have to do: It's the old lesson that we've always had when it comes to sources--trust, but verify.
And don't stop doing it just because it's a computer or just because it's AI, also insist on verification.
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