WEBVTT - Hamlet and the Apprehension of AI

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<v Speaker 1>Welcome to Tech Stuff, a production from iHeartRadio. Hey there,

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<v Speaker 1>and welcome to tech Stuff. I'm your host, Jonathan Strickland.

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<v Speaker 1>I'm an executive producer with iHeartRadio and how the tech

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<v Speaker 1>are you? So? Folks who have followed me for a

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<v Speaker 1>while know that I am a huge Shakespeare fan, which

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<v Speaker 1>means I am insufferable in many ways, but some of

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<v Speaker 1>them very specific to Shakespeare. Namely, I'll find any occasion

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<v Speaker 1>to PLoP in a quote from one of Shakespeare's works,

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<v Speaker 1>and today is no exception. I'd like to start off

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<v Speaker 1>with this gem from Hamlet, act to scene to as

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<v Speaker 1>spoken by the gloomy Dane himself. Quote there is nothing

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<v Speaker 1>either good or bad, but thinking makes it so. End quote. Now,

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<v Speaker 1>that just means that good and bad are subjective concepts.

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<v Speaker 1>It's all, as ob Wan would say, a matter of

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<v Speaker 1>your point of view. What seems good to you could

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<v Speaker 1>seem bad to someone else. But if you were able

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<v Speaker 1>to look at the universe objectively, you would see there's

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<v Speaker 1>no good or bad at all. Another way to frame

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<v Speaker 1>that is to say that good and bad are human concepts.

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<v Speaker 1>And really it gets quite selfish if we think about it,

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<v Speaker 1>because we typically frame if something is good or bad

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<v Speaker 1>in the way it affects us, or, if we're the

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<v Speaker 1>compassionate type, how it affects someone else. Now, the reason

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<v Speaker 1>I wanted to begin with that quote is I thought

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<v Speaker 1>we'd talk about a technology that's not necessarily good or

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<v Speaker 1>bad inherently, but how we use it certainly can have

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<v Speaker 1>good or bad outcomes. Honestly, this could apply to every technology,

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<v Speaker 1>or any technology, but there's some that I feel magnifies

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<v Speaker 1>this quality. Now, I do think some technologies are hard

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<v Speaker 1>to frame as good than others. Right, there's some technologies where,

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<v Speaker 1>if you were to point it at me, I would say,

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<v Speaker 1>I can't in good conscience call this a good technology.

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<v Speaker 1>It's very difficult for me to think of weapons of

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<v Speaker 1>war as being good. For example, Sure, there's the use

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<v Speaker 1>of weapons as a deterrent to convince other people to,

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<v Speaker 1>you know, not trample all over your country, but we've

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<v Speaker 1>seen time and again throughout history that amassing substantial military

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<v Speaker 1>might doesn't guarantee against aggression. See also both world wars.

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<v Speaker 1>So I won't be talking about weapons in this episode.

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<v Speaker 1>But I will, however, talk about a technology that can

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<v Speaker 1>be weaponized, and that is AI. Artificial intelligence. The topic

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<v Speaker 1>of twenty twenty three, and we're gonna start by talking

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<v Speaker 1>about large language models and the chatbots built on top

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<v Speaker 1>of them, because that's top of mind. And this is

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<v Speaker 1>where I remind you that is not the only version

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<v Speaker 1>of AI, right, that's not AI and chatbots slash large

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<v Speaker 1>language models. Those aren't synonyms for each other. You know,

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<v Speaker 1>those chatbots and large language models are a subset of

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<v Speaker 1>artificial intelligence, which is a very broad category. Now, obviously

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<v Speaker 1>these branches of AI have been in the news incessantly

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<v Speaker 1>since OpenAI introduced chat GPT last year, But even before that,

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<v Speaker 1>we had generative AI tools that were making at least

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<v Speaker 1>some headlines. They were the kind that could create images

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<v Speaker 1>based on text inputs. But I would really argue it

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<v Speaker 1>was chat GPT that propelled the conversation into the spotlight.

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<v Speaker 1>It's certainly what forced Google's hand to unveil Google Bard

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<v Speaker 1>well before they were prepared to do so. Now much

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<v Speaker 1>has been said of the potential and real dangers of

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<v Speaker 1>chatbots like chat GPT or Google Bard. Even on this show,

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<v Speaker 1>I've talked about it quite a bit, but you know,

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<v Speaker 1>we have dedicated episodes to talk about the tendency for

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<v Speaker 1>chatbots to invent information, for example, to hallucinate to use

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<v Speaker 1>the terminology of the biz. This happens when a chatbot

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<v Speaker 1>doesn't necessarily have information to draw upon in response to

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<v Speaker 1>a prompt, so instead the chatbot relies on statistical models

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<v Speaker 1>to generate sentences that, strictly speaking, are coherent. They're correct,

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<v Speaker 1>but they don't hold correct information right. They're grammatically correct,

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<v Speaker 1>but they aren't correct from a sense of content. The

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<v Speaker 1>information within them are false. So in other words, you

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<v Speaker 1>get grammatically and structurally sound passages, but the content itself

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<v Speaker 1>is untrustworthy. That's just one way stuff can go wrong, however,

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<v Speaker 1>and we have numerous examples of that where the technology

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<v Speaker 1>is working as intended, it's just generating responses that are untrustworthy. Now,

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<v Speaker 1>the folks that open AI, as well as Google and

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<v Speaker 1>several other AI businesses, have understood that there are real

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<v Speaker 1>potential problems with the use of AI, and to that end,

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<v Speaker 1>these companies frequently will build in guardrails to attempt to

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<v Speaker 1>wrangle AI chatbots so that they don't go rogue and

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<v Speaker 1>produce hateful or malicious content. Now, these guardrails include rules

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<v Speaker 1>that are meant to keep AI from doing things like

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<v Speaker 1>generating hate speech or trying to intimidate someone, or make threats,

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<v Speaker 1>or use deceit to trick people, or even create malicious code.

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<v Speaker 1>These guardrails aren't actually fool proof. There are countless articles

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<v Speaker 1>that detail how people and research organizations with enough patients

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<v Speaker 1>and gumption have convinced AI bots to do stuff that,

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<v Speaker 1>in theory, at least, they should not be able to do.

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<v Speaker 1>And if you don't believe me, just do a search

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<v Speaker 1>on that. Do a search for chat GPT or a

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<v Speaker 1>Google bard and about how they are capable of creating

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<v Speaker 1>hateful or malicious content even though there are rules that

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<v Speaker 1>are supposed to prevent that. Now here's the thing. These

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<v Speaker 1>AI constructs are meant to be benign, right. They are

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<v Speaker 1>built to be tools that a corporation can sell to

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<v Speaker 1>other corporations. So to make the tool marketable, they need

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<v Speaker 1>to be safe to use. But then that's something that's

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<v Speaker 1>been artificially put onto these tools to prevent them from

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<v Speaker 1>going you know, super bad. What if someone made a

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<v Speaker 1>chat pot built on top of a large language model,

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<v Speaker 1>but all of those pieces lacked those guardrails. Well, that's

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<v Speaker 1>not a hypothetical situation. It has already happened. PCMag dot

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<v Speaker 1>Com recently published an article titled worm GPT is a

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<v Speaker 1>chat GPT alternative with quote no ethical boundaries or limitations

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<v Speaker 1>end quote. In that article, writer Michael Kahn explains that

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<v Speaker 1>someone developed worm GPT specifically as a way to help

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<v Speaker 1>people who have bad intentions act upon them. The developer

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<v Speaker 1>is hawking this tool on hacker groups online and explains

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<v Speaker 1>that their version of an AI chat bought worm GPT

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<v Speaker 1>will lean on the power of a large language model

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<v Speaker 1>gptj I believe to help design malware or to create

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<v Speaker 1>better phishing attacks. Now, I'm sure all of y'all know

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<v Speaker 1>that a lot of phishing attacks are ultimately pretty sloppy.

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<v Speaker 1>If you pay any attention, you're going to see red

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<v Speaker 1>flags indicating that this is not an email you should trust.

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<v Speaker 1>I bet you've received an email or three or three

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<v Speaker 1>thousand that contained spelling errors and grammatical mistakes and format

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<v Speaker 1>errors and other red flags, and that you figured out

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<v Speaker 1>right away that the email you received isn't legit, that

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<v Speaker 1>it's a poorly disguised attempt to bait you into clicking

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<v Speaker 1>on a link or sharing sensitive information or otherwise taking

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<v Speaker 1>an action that would ultimately result in negative consequences. For you.

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<v Speaker 1>My company, we receive fake emails from our security team.

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<v Speaker 1>They are always testing to make sure that employees practice

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<v Speaker 1>good security hygiene on company devices and company accounts, and

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<v Speaker 1>one of the tips frequently shared by this team is

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<v Speaker 1>to be on the lookout for mistakes like that. Because

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<v Speaker 1>attackers often lack attention to detail, they create messages that

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<v Speaker 1>lack professionalism while they try to target our more base instincts.

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<v Speaker 1>So most phishing emails try to engage us on kind

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<v Speaker 1>of a primal level, and the goal is to prompt

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<v Speaker 1>a response that will be akin to fear or greed

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<v Speaker 1>or something like that. And sometimes that's enough if you

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<v Speaker 1>hit someone at just the right time with a message

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<v Speaker 1>that explains have got, say a huge amount of money

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<v Speaker 1>sitting in a bank account that's been dormant for years,

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<v Speaker 1>or maybe they need to take action right now, or

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<v Speaker 1>their insurance is going to expire. Well, those can be

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<v Speaker 1>effective attacks, even if you forgot to use proper punctuation

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<v Speaker 1>or spelling. But those mistakes can be an indicator that

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<v Speaker 1>you're up to no good and it can tip off

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<v Speaker 1>your target. So let's bring this back around to AI.

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<v Speaker 1>One thing these AI chatbots are really good at is

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<v Speaker 1>formatting sentences with correct grammar and spelling. They're also pretty

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<v Speaker 1>good at building paragraphs, where each sentence builds upon the

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<v Speaker 1>point that was made previously, and new paragraphs introduce a

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<v Speaker 1>new idea. If you were to read a passage written

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<v Speaker 1>by AI, you might not think that it's the most

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<v Speaker 1>brilliant prose committed to text, but you'd at least think

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<v Speaker 1>it had been written correctly. And that means a malicious

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<v Speaker 1>hacker could use AI to craft messages that are less

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<v Speaker 1>likely to set off those red flags and pass as legitimate. So,

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<v Speaker 1>out of curiosity, I decided to put this to the test.

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<v Speaker 1>I went to Google Bard and I wrote the prompt

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<v Speaker 1>draft a letter informing someone they have a dormant account

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<v Speaker 1>with seventeen three hundred and forty eight dollars in it.

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<v Speaker 1>That was the prompt. I picked that amount because it's

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<v Speaker 1>a lot of money. It's more money than a lot

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<v Speaker 1>of people ever managed to have in a bank account.

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<v Speaker 1>It's also not a round number, which makes it seem

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<v Speaker 1>less likely to be fake. And I just thought, well,

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<v Speaker 1>you don't want to go super crazy, like the higher

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<v Speaker 1>it is, the less likely someone's going to believe it

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<v Speaker 1>to be true. But you want it to be enough

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<v Speaker 1>to convince someone to take action, because who couldn't use

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<v Speaker 1>another seventeen grand And google Bard drafted a letter without hesitation.

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<v Speaker 1>When we come back, I'm gonna quote part of the

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<v Speaker 1>letter that google Bard wrote to kind of illustrate my

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<v Speaker 1>point here. But first, let's take a moment to thank

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<v Speaker 1>our sponsors. Okay, we're back. So the letter the google

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<v Speaker 1>Bard wrote read, in part quote, I am writing to

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<v Speaker 1>inform you that you have a dormant account with our bank.

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<v Speaker 1>The account number is then there's brackets and it says

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<v Speaker 1>account number not an actual number, just as account number,

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<v Speaker 1>and then in brackets and the balance is seventeen three

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<v Speaker 1>and forty eight dollars. A dormant account is an account

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<v Speaker 1>that has not been used in a certain period of time.

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<v Speaker 1>In our case, a dormant account is an account that

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<v Speaker 1>has not been used in over twelve months. We are

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<v Speaker 1>required by law to inform you of the balance in

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<v Speaker 1>your dormant account. If you do not contact us within

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<v Speaker 1>six months, the fund in your account will be forfeited

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<v Speaker 1>to the state. To avoid this, please contact us at

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<v Speaker 1>your earliest convenience to discuss your options. End quote. So

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<v Speaker 1>that draft is already a big step up from the

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<v Speaker 1>sort of sloppy fishing attacks you typically see. Right, you've

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<v Speaker 1>got the amount listed there, you've got the explanation of

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<v Speaker 1>what a dormant account is, which seems to be helpful.

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<v Speaker 1>The explanation that if action is not taken within half

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<v Speaker 1>a year, then this money is going to be forfeited

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<v Speaker 1>to the state. And of course you could always go

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<v Speaker 1>in and edit that statement so that you make it

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<v Speaker 1>a tighter deadline to create a greater sense of urgency.

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<v Speaker 1>But you already see the steps here that could make

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<v Speaker 1>this a pretty effective phishing attack. There are some details

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<v Speaker 1>that the hacker would need to fill in, but that

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<v Speaker 1>wouldn't be too tricky. You'd have to create a random

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<v Speaker 1>account number, you have to throw in a URL that

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<v Speaker 1>will push people to a fake login page to share

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<v Speaker 1>usernames and passwords, and then you could start stealing data

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<v Speaker 1>and money from them. Now, in that case, I didn't

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<v Speaker 1>ask google bard to create a phishing attack. If I

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<v Speaker 1>had done that, if I had gone to google Bard

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<v Speaker 1>and asked to create a phishing email, I would have

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<v Speaker 1>gotten a denial for that request. That's against the rules.

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<v Speaker 1>But it took me no effort at all to get

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<v Speaker 1>the same result just by typing up some parameters and

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<v Speaker 1>asking Bard to draft a letter. I didn't, you know,

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<v Speaker 1>I didn't even mention phishing. I didn't do that at all.

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<v Speaker 1>I didn't try that first. I just tried this approach

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<v Speaker 1>and it worked a treat. Now, I suppose you could

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<v Speaker 1>say this is the difference between being a willing accomplice

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<v Speaker 1>in the part of Google Bard to being an unknowing

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<v Speaker 1>accomplice that Bard could not possibly know that I'm planning

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<v Speaker 1>on using this text for my nefarious phishing schemes, but

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<v Speaker 1>the result ends up being the same for the victims.

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<v Speaker 1>It doesn't matter if Google Bard knew it was part

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<v Speaker 1>of the crime or not. Even so, you can hardly

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<v Speaker 1>blame Bard for creating a letter after I asked it to.

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<v Speaker 1>That's its job, right, I mean, that's the kind of

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<v Speaker 1>thing these chatbots were made for. Malicious code is another matter.

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<v Speaker 1>Entirely by its nature, it's meant to do something harmful

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<v Speaker 1>to a target device. That could include creating a backdoor

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<v Speaker 1>so that a hacker can remotely gain access to that

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<v Speaker 1>infected machine and then do all sorts of stuff to it.

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<v Speaker 1>It might involve logging keystrokes, so that the hacker can

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<v Speaker 1>read everything someone's typed into a device, usually stuff like

0:14:21.920 --> 0:14:26.000
<v Speaker 1>bank details and credit card numbers and that kind of stuff.

0:14:26.880 --> 0:14:32.280
<v Speaker 1>Maybe it's ransomware. Ransomware typically will encrypt a target machines

0:14:32.400 --> 0:14:35.320
<v Speaker 1>drives and then include a message that says unless the

0:14:35.400 --> 0:14:38.760
<v Speaker 1>victim pays a ransom, typically in some form of cryptocurrency,

0:14:39.240 --> 0:14:43.000
<v Speaker 1>their data will remain inaccessible, perhaps even with a deadline

0:14:43.000 --> 0:14:45.320
<v Speaker 1>that if they don't pay the ransom by a certain date,

0:14:46.120 --> 0:14:49.680
<v Speaker 1>they will delete the decryption key, which means it will

0:14:49.680 --> 0:14:52.760
<v Speaker 1>be really hard to get the data back. Not impossible,

0:14:53.160 --> 0:14:57.920
<v Speaker 1>but practically impossible if the encryption method is sophisticated enough,

0:14:58.920 --> 0:15:00.960
<v Speaker 1>like not impossible, but it take so much time that

0:15:01.000 --> 0:15:04.360
<v Speaker 1>you might as well say it's impossible. Chat, GPT and

0:15:04.440 --> 0:15:07.440
<v Speaker 1>BARD are meant to guard against this kind of stuff.

0:15:07.440 --> 0:15:09.640
<v Speaker 1>You're not supposed to be able to use those tools

0:15:09.920 --> 0:15:14.960
<v Speaker 1>to make malicious code. However, researchers at Checkpoints Software found

0:15:14.960 --> 0:15:18.640
<v Speaker 1>that both chat, GPT and BARD could be cajoled into

0:15:18.680 --> 0:15:23.280
<v Speaker 1>creating malicious code. It might require a more circuitous approach

0:15:23.600 --> 0:15:26.040
<v Speaker 1>to get it to work, like you can't just come

0:15:26.120 --> 0:15:29.320
<v Speaker 1>straight at it and do it, but with a little

0:15:29.320 --> 0:15:33.680
<v Speaker 1>persistence and a little ingenuity on your part, it was

0:15:33.720 --> 0:15:38.080
<v Speaker 1>possible they could get chat GPT and to a greater extent,

0:15:38.160 --> 0:15:42.800
<v Speaker 1>Google bard to create stuff that could be used maliciously. Now,

0:15:42.840 --> 0:15:48.040
<v Speaker 1>worm GPT, the tool made by the developer who's marketing

0:15:48.040 --> 0:15:51.440
<v Speaker 1>this to hackers, it doesn't even require the circuitous approach.

0:15:51.480 --> 0:15:55.160
<v Speaker 1>You can be straightforward and direct with it. You ask

0:15:55.240 --> 0:15:58.880
<v Speaker 1>it to help you create some code that's malicious in intent,

0:15:59.240 --> 0:16:02.520
<v Speaker 1>and it will to the challenge. So if you wanted

0:16:02.520 --> 0:16:04.920
<v Speaker 1>to craft a phishing attack message, you could provide the

0:16:04.960 --> 0:16:07.920
<v Speaker 1>parameters to worm gpt and it would craft a message

0:16:07.920 --> 0:16:11.440
<v Speaker 1>for you. That message might pass as legitimate, much more

0:16:11.480 --> 0:16:14.960
<v Speaker 1>readily than a cobbled together email with poor syntax and

0:16:15.080 --> 0:16:18.560
<v Speaker 1>grammar would. But beyond that, worm GPT will also help

0:16:18.600 --> 0:16:23.600
<v Speaker 1>hackers create actual malicious code to infect target machines. Now,

0:16:23.640 --> 0:16:27.320
<v Speaker 1>that code may or might may not work, because just

0:16:27.360 --> 0:16:29.480
<v Speaker 1>because an AI built it doesn't mean it will be

0:16:29.560 --> 0:16:33.320
<v Speaker 1>perfect or even working. Like we've seen examples recently of

0:16:33.440 --> 0:16:38.360
<v Speaker 1>chat gpt getting very sloppy with code that it was doing,

0:16:38.400 --> 0:16:41.600
<v Speaker 1>things like failing to close brackets, like you would have

0:16:41.600 --> 0:16:45.360
<v Speaker 1>an open bracket section, but the AI would quote unquote

0:16:45.440 --> 0:16:48.480
<v Speaker 1>forget to put a closed bracket in there, and thus

0:16:48.520 --> 0:16:51.160
<v Speaker 1>you would end up getting errors in your code. That's

0:16:51.200 --> 0:16:55.040
<v Speaker 1>still a possibility, Like it's it's not like AI is

0:16:55.320 --> 0:16:57.520
<v Speaker 1>going to make perfect stuff rut of the gate, but

0:16:57.600 --> 0:17:02.240
<v Speaker 1>it certainly can work faster than humans can. And even

0:17:02.280 --> 0:17:05.240
<v Speaker 1>if the code only kind of works, it may be

0:17:05.600 --> 0:17:08.960
<v Speaker 1>a great leg up if you've got hackers who can

0:17:09.119 --> 0:17:12.960
<v Speaker 1>go through the malicious code and make edits and tweaks

0:17:13.160 --> 0:17:16.600
<v Speaker 1>and corrections. And there's a real danger to AI building

0:17:16.640 --> 0:17:20.040
<v Speaker 1>out code meant to exploit vulnerabilities, or even to pour

0:17:20.200 --> 0:17:24.320
<v Speaker 1>over available code and find new exploits that as of

0:17:24.400 --> 0:17:27.680
<v Speaker 1>yet are unknown. Like it's possible that AI could be

0:17:27.800 --> 0:17:32.160
<v Speaker 1>used to identify zero day exploits that the hacker community

0:17:32.200 --> 0:17:35.760
<v Speaker 1>can then take advantage of before anyone in security has

0:17:35.840 --> 0:17:40.600
<v Speaker 1>any awareness of it. Now, there's also the issue of

0:17:40.920 --> 0:17:45.160
<v Speaker 1>new malicious code can confound anti virus production as well, right,

0:17:45.680 --> 0:17:49.040
<v Speaker 1>because the way antivirus software typically works is you've got

0:17:49.160 --> 0:17:54.919
<v Speaker 1>some code, some program that is searching for examples of

0:17:55.040 --> 0:17:58.720
<v Speaker 1>malicious programs that exist within a huge library of malware.

0:17:58.840 --> 0:18:03.000
<v Speaker 1>So when you run an antivirus scan, what your antivirus

0:18:03.000 --> 0:18:09.000
<v Speaker 1>software really is doing is looking for symptoms of malware

0:18:09.359 --> 0:18:13.320
<v Speaker 1>that are part of the antivirus software's record if it

0:18:13.359 --> 0:18:16.040
<v Speaker 1>finds when it's like, ah, I found evidence that such

0:18:16.040 --> 0:18:19.879
<v Speaker 1>and such malware has been executed on this machine, and

0:18:19.920 --> 0:18:23.080
<v Speaker 1>then you get a little alert. But if it's a

0:18:23.119 --> 0:18:26.000
<v Speaker 1>new type of attack, well, it's not going to be

0:18:26.080 --> 0:18:29.760
<v Speaker 1>in that database, right, So you might have a malicious

0:18:29.800 --> 0:18:33.000
<v Speaker 1>piece of code on your machine that's doing some really

0:18:33.080 --> 0:18:36.280
<v Speaker 1>dangerous stuff and your antivirus software has no way of

0:18:36.280 --> 0:18:38.720
<v Speaker 1>knowing it because it's brand new, it's not something it's

0:18:38.720 --> 0:18:42.360
<v Speaker 1>seen before, so it doesn't register it as a virus

0:18:42.440 --> 0:18:46.960
<v Speaker 1>or other type of malware. And there's huge value in

0:18:47.000 --> 0:18:50.200
<v Speaker 1>that kind of code within the hacker community because obviously

0:18:50.640 --> 0:18:54.040
<v Speaker 1>you're going to have a much more effective attack if

0:18:54.080 --> 0:18:58.400
<v Speaker 1>your target machines aren't capable of detecting it. Now, there's

0:18:58.440 --> 0:19:03.159
<v Speaker 1>no shortage of warning us that generative AI is dangerous.

0:19:03.720 --> 0:19:06.120
<v Speaker 1>I mean, I'm arguably one of them. There are lots

0:19:06.160 --> 0:19:07.840
<v Speaker 1>of people who have been saying for a long time

0:19:07.880 --> 0:19:13.920
<v Speaker 1>that generative AI is dangerous. And again we've seen how

0:19:14.080 --> 0:19:17.320
<v Speaker 1>tools that even have guardrails can still be used maliciously.

0:19:17.720 --> 0:19:19.879
<v Speaker 1>So it should come as no surprise that someone was

0:19:19.920 --> 0:19:22.440
<v Speaker 1>willing to go to the effort of building out an

0:19:22.480 --> 0:19:27.399
<v Speaker 1>outright dangerous version of this technology. Right, Yes, we expect

0:19:27.440 --> 0:19:30.720
<v Speaker 1>the big companies that are marketing this to corporations to

0:19:30.800 --> 0:19:33.200
<v Speaker 1>go to the trouble of building out those guardrails because

0:19:33.200 --> 0:19:34.679
<v Speaker 1>that's the only way they're going to be able to

0:19:34.680 --> 0:19:37.600
<v Speaker 1>do business. Otherwise you're going to have way too much

0:19:37.680 --> 0:19:42.160
<v Speaker 1>regulatory pressure put on you. But for criminals, I mean,

0:19:42.200 --> 0:19:45.800
<v Speaker 1>breaking the law comes with the territory, right, and there's

0:19:45.840 --> 0:19:50.040
<v Speaker 1>clearly a demand for malicious AI, or at least AI

0:19:50.080 --> 0:19:53.520
<v Speaker 1>that can behave in malicious ways. So in the case

0:19:53.520 --> 0:19:56.680
<v Speaker 1>of WORMGPT, at the time of this recording, the developer

0:19:56.720 --> 0:19:59.320
<v Speaker 1>who created it is asking for a subscription of sixty

0:19:59.320 --> 0:20:03.160
<v Speaker 1>euros per month or five hundred and fifty euros per year,

0:20:03.440 --> 0:20:05.919
<v Speaker 1>and a euro for those of you in the US

0:20:05.960 --> 0:20:10.160
<v Speaker 1>like myself, that's about a dollar and twelve cents per euro.

0:20:10.359 --> 0:20:13.000
<v Speaker 1>So it's really not that far off when you're talking

0:20:13.000 --> 0:20:17.080
<v Speaker 1>about dollars. Now, that is not cheap, right, sixty euros

0:20:17.080 --> 0:20:19.760
<v Speaker 1>per month isn't exactly cheap, but it's also not so

0:20:19.920 --> 0:20:23.280
<v Speaker 1>expensive as to price folks out, particularly if they anticipate

0:20:23.359 --> 0:20:27.680
<v Speaker 1>using the tool to create ransomware attacks that could if

0:20:27.800 --> 0:20:32.440
<v Speaker 1>they're effective, net them millions of dollars if the targets

0:20:32.480 --> 0:20:35.240
<v Speaker 1>pay up. Oh brave new world to have such AI

0:20:35.320 --> 0:20:39.120
<v Speaker 1>in it. That's also paraphrasing Shakespeare. It's not Hamlet, though,

0:20:39.200 --> 0:20:42.600
<v Speaker 1>that's from the Tempest. Well, here's the thing. There are

0:20:42.720 --> 0:20:47.040
<v Speaker 1>countless ways we could use generative AI to do great things.

0:20:47.359 --> 0:20:51.760
<v Speaker 1>The tools themselves aren't outright evil. There is no good

0:20:51.800 --> 0:20:55.600
<v Speaker 1>or evil, but thinking makes it so. It's just that

0:20:55.880 --> 0:20:58.960
<v Speaker 1>this AI can make mistakes in the form of hallucinations.

0:20:58.960 --> 0:21:03.239
<v Speaker 1>So even if you're using it for benign reasons, you

0:21:03.280 --> 0:21:07.719
<v Speaker 1>can get negative consequences. But it's also possible to weaponize it,

0:21:07.800 --> 0:21:11.159
<v Speaker 1>and that in turn could have much more widespread negative

0:21:11.160 --> 0:21:16.040
<v Speaker 1>impact on tons of people. Not great. Now, we're going

0:21:16.119 --> 0:21:18.320
<v Speaker 1>to take another quick break. When we come back, I'm

0:21:18.320 --> 0:21:22.639
<v Speaker 1>going to talk about an underlying ideology that I think

0:21:23.920 --> 0:21:29.480
<v Speaker 1>is really harmful, and it's one that Professor Michael Littman

0:21:29.560 --> 0:21:32.959
<v Speaker 1>a Brown University also feels is a big contributor to

0:21:33.080 --> 0:21:36.800
<v Speaker 1>this issue. But first, let's take another quick break to

0:21:36.840 --> 0:21:50.600
<v Speaker 1>thank our sponsors. Okay, So I alluded to Professor Michael

0:21:50.640 --> 0:21:53.639
<v Speaker 1>Littman a Brown University and said he and I share

0:21:54.440 --> 0:22:00.520
<v Speaker 1>an idea that of a contributing factor to this issue

0:22:00.520 --> 0:22:06.119
<v Speaker 1>with AI, and that relates to techno solutionism. Now, as

0:22:06.320 --> 0:22:10.800
<v Speaker 1>that kind of little hyphenated phrase implies, it's a tendency

0:22:10.920 --> 0:22:14.560
<v Speaker 1>to believe that technology can solve pretty much any problem

0:22:14.560 --> 0:22:19.520
<v Speaker 1>you can think of that. You know, with technology, we

0:22:19.560 --> 0:22:23.000
<v Speaker 1>can overcome any obstacle. If you're worried about the human

0:22:23.040 --> 0:22:26.879
<v Speaker 1>impact on the environment and the consequence is like climate change,

0:22:26.920 --> 0:22:28.840
<v Speaker 1>well there's no need to do anything about it right

0:22:28.920 --> 0:22:32.480
<v Speaker 1>now because humans are going to eventually engineer a way

0:22:32.600 --> 0:22:35.560
<v Speaker 1>out of the mess. We'll just create technology that will

0:22:35.560 --> 0:22:39.880
<v Speaker 1>not only stop climate change but maybe even reverse it. Which,

0:22:39.920 --> 0:22:43.760
<v Speaker 1>you know, maybe that's true, it might happen, but that

0:22:43.800 --> 0:22:46.040
<v Speaker 1>doesn't mean we can go on acting as if it

0:22:46.119 --> 0:22:51.560
<v Speaker 1>is already true. Right. We can't start from the assumption that, yes,

0:22:51.640 --> 0:22:53.679
<v Speaker 1>it is going to happen and everything will be fine,

0:22:54.320 --> 0:22:57.080
<v Speaker 1>because making a problem worse while we wait for someone

0:22:57.080 --> 0:23:01.480
<v Speaker 1>to innovate a solution is a terrible idea. This is

0:23:01.560 --> 0:23:03.520
<v Speaker 1>kind of like when I look around my cluttered office

0:23:03.520 --> 0:23:05.320
<v Speaker 1>and I think I really should clean up, but I'm

0:23:05.359 --> 0:23:09.480
<v Speaker 1>going to make that a future Jonathan problem instead. Meanwhile,

0:23:09.720 --> 0:23:12.000
<v Speaker 1>in the process, I'm still adding to the clutter, which

0:23:12.040 --> 0:23:14.760
<v Speaker 1>means that future Jonathan is far less likely to tackle

0:23:14.800 --> 0:23:18.639
<v Speaker 1>the issue because it's gotten worse since present Jonathan pushed

0:23:18.640 --> 0:23:22.879
<v Speaker 1>it off, and then future Jonathan is also going to

0:23:22.880 --> 0:23:27.119
<v Speaker 1>start resenting past Jonathan's immensely for good reason. Well, current

0:23:27.160 --> 0:23:30.160
<v Speaker 1>generations are doing that to future generations right now when

0:23:30.200 --> 0:23:33.840
<v Speaker 1>it comes to stuff like climate change and carbon emissions,

0:23:34.280 --> 0:23:38.359
<v Speaker 1>right we are. Even when we're inventing solutions or what

0:23:38.400 --> 0:23:41.119
<v Speaker 1>we think of as solutions to try and tackle these problems,

0:23:41.520 --> 0:23:46.920
<v Speaker 1>we're not making the problem less severe. Instead we're just like, oh, well,

0:23:46.920 --> 0:23:49.240
<v Speaker 1>we came up with this cool solution, so let's just

0:23:49.320 --> 0:23:52.840
<v Speaker 1>keep doing the problem, because this is making the problem

0:23:53.840 --> 0:23:57.840
<v Speaker 1>less bad. Carbon capture is a great example, right with

0:23:57.960 --> 0:24:03.120
<v Speaker 1>carbon capture. Ideally, you would get off of carbon emissions

0:24:03.359 --> 0:24:06.760
<v Speaker 1>in general anyway, and then use carbon capture to help

0:24:06.800 --> 0:24:10.679
<v Speaker 1>reduce the CO two load the atmosphere. But instead, what

0:24:10.680 --> 0:24:17.359
<v Speaker 1>we're doing is we're using carbon capture in connection with

0:24:17.560 --> 0:24:21.880
<v Speaker 1>carbon emissions, which means we're not easing off on carbon emissions.

0:24:21.920 --> 0:24:25.040
<v Speaker 1>In fact, in some cases, we're getting even more aggressive

0:24:25.080 --> 0:24:28.560
<v Speaker 1>with them, and we're counting on carbon capture to offset that,

0:24:28.760 --> 0:24:32.199
<v Speaker 1>so that we're still contributing to the problem. You know,

0:24:32.240 --> 0:24:34.720
<v Speaker 1>we're not moving away from it, which is why I

0:24:34.920 --> 0:24:40.080
<v Speaker 1>hesitate to really endorse technologies like carbon capture, because unless

0:24:40.119 --> 0:24:44.160
<v Speaker 1>it's coupled with an actual move to reduce carbon emissions

0:24:44.200 --> 0:24:47.520
<v Speaker 1>in general, it's not really solving the problem. It's actually

0:24:47.640 --> 0:24:52.399
<v Speaker 1>enabling the problem. It's facilitating it anyway. Techno solutionism is

0:24:52.400 --> 0:24:55.480
<v Speaker 1>also what makes it possible for someone like Elizabeth Holmes

0:24:55.480 --> 0:24:59.159
<v Speaker 1>to convince investors to pour millions of dollars into an

0:24:59.240 --> 0:25:02.440
<v Speaker 1>unproven idea. So, in case you're not familiar with Elizabeth

0:25:02.480 --> 0:25:06.000
<v Speaker 1>Holmes's name, she was the founder of Farranos, the startup

0:25:06.040 --> 0:25:08.440
<v Speaker 1>that aimed to create a device small enough to fit

0:25:08.520 --> 0:25:10.879
<v Speaker 1>on a desktop that would be able to run medical

0:25:10.920 --> 0:25:13.800
<v Speaker 1>tests on a micro drop of blood. You just need

0:25:13.840 --> 0:25:16.760
<v Speaker 1>the teeniest, tiniest sample of blood, and then you'd be

0:25:16.800 --> 0:25:19.439
<v Speaker 1>able to run one of more than one hundred medical

0:25:19.480 --> 0:25:23.640
<v Speaker 1>tests and check for everything from present conditions or diseases

0:25:23.880 --> 0:25:28.159
<v Speaker 1>to your genetic tendency to develop certain conditions. There was

0:25:28.240 --> 0:25:32.240
<v Speaker 1>only one little problem. The technology didn't work. At least,

0:25:32.240 --> 0:25:34.640
<v Speaker 1>it didn't work anywhere close to what it would need

0:25:34.680 --> 0:25:37.600
<v Speaker 1>to be in order to fulfill the dream device that

0:25:37.680 --> 0:25:40.920
<v Speaker 1>Holmes was looking to build. There were so many factors

0:25:41.320 --> 0:25:44.440
<v Speaker 1>that needed to be solved, and some of them might

0:25:44.520 --> 0:25:46.879
<v Speaker 1>not be solvable, at least not in a way that

0:25:46.920 --> 0:25:49.439
<v Speaker 1>would require you to only part with a microdrop of

0:25:49.440 --> 0:25:52.640
<v Speaker 1>blood in the process. But Holmes and her team did

0:25:52.680 --> 0:25:55.960
<v Speaker 1>their best to obfuscate that fact. They relied on existing

0:25:56.040 --> 0:25:59.920
<v Speaker 1>blood analysis technologies to make it appear as though there

0:26:00.119 --> 0:26:03.520
<v Speaker 1>device worked, while they also tried to keep things going

0:26:03.760 --> 0:26:06.080
<v Speaker 1>until a breakthrough came along. It was sort of the

0:26:06.560 --> 0:26:12.560
<v Speaker 1>fake it until you make it ideology, but coupled with

0:26:12.720 --> 0:26:17.440
<v Speaker 1>some snake oil salesmanship and some smoke and mirrors as well.

0:26:18.000 --> 0:26:22.480
<v Speaker 1>Now I do not know if Elizabeth Holmes really believed

0:26:22.480 --> 0:26:26.040
<v Speaker 1>her idea was possible. I wouldn't be surprised to hear

0:26:26.440 --> 0:26:29.640
<v Speaker 1>that that was the case, that she truly, earnestly believed

0:26:29.640 --> 0:26:32.320
<v Speaker 1>she could do this. Because we use technology to do

0:26:32.400 --> 0:26:35.880
<v Speaker 1>some amazing things that are so commonplace these days that

0:26:36.000 --> 0:26:41.400
<v Speaker 1>we forget that it's amazing. Like taking flight in an aircraft.

0:26:41.800 --> 0:26:44.480
<v Speaker 1>I mean, I take it for granted when I'm on

0:26:44.520 --> 0:26:46.879
<v Speaker 1>a plane unless I actually stopped to consider it, then

0:26:46.920 --> 0:26:52.439
<v Speaker 1>I think this really is astounding. Or accessing information on

0:26:52.480 --> 0:26:55.520
<v Speaker 1>the Internet through a device we carry around in our pocket.

0:26:55.840 --> 0:27:00.119
<v Speaker 1>I mean, the Internet alone is a phenomenal technology, and

0:27:00.160 --> 0:27:04.520
<v Speaker 1>then smartphones being able to tap into that technology and

0:27:04.960 --> 0:27:10.160
<v Speaker 1>make it mobile and accessible wherever we go. It's insane.

0:27:10.240 --> 0:27:12.480
<v Speaker 1>You know. As a kid, I read The Hitchhicker's Guide

0:27:12.520 --> 0:27:14.680
<v Speaker 1>to the Galaxy and I thought, man, how amazing would

0:27:14.720 --> 0:27:17.679
<v Speaker 1>it be to have a device that contained all this

0:27:17.760 --> 0:27:20.399
<v Speaker 1>information You could ask in anything you can get an answer.

0:27:20.840 --> 0:27:24.040
<v Speaker 1>And now we have that. Except it's not a device

0:27:24.080 --> 0:27:27.959
<v Speaker 1>that just has a huge storage space for all this info.

0:27:28.480 --> 0:27:34.080
<v Speaker 1>It's tapping into an evolving, ever changing technology of the Internet,

0:27:34.240 --> 0:27:36.400
<v Speaker 1>which will give us up to date answers which may

0:27:36.440 --> 0:27:40.679
<v Speaker 1>be right or wrong, but we can achieve phenomenal results

0:27:40.680 --> 0:27:43.520
<v Speaker 1>through technology. Right, You were able to do these insanely

0:27:43.560 --> 0:27:46.880
<v Speaker 1>incredible things, So why shouldn't we believe that you could

0:27:46.960 --> 0:27:50.600
<v Speaker 1>run one hundred or even more medical tests on a

0:27:50.640 --> 0:27:53.119
<v Speaker 1>device that's the size of a computer printer and you

0:27:53.280 --> 0:27:55.359
<v Speaker 1>just use the tiny drop of blood. That seems like

0:27:55.400 --> 0:27:57.880
<v Speaker 1>it should be possible based on some of the other

0:27:57.880 --> 0:28:01.520
<v Speaker 1>incredible things we can do. Right. That's the danger of

0:28:01.640 --> 0:28:06.280
<v Speaker 1>techno solutionism. We let ourselves think that because these other

0:28:06.320 --> 0:28:12.040
<v Speaker 1>incredible things are possible, then everything is possible, or at

0:28:12.040 --> 0:28:15.240
<v Speaker 1>the very least everything will be possible once we throw

0:28:15.359 --> 0:28:19.120
<v Speaker 1>enough technology at it. But as Thearnos proved, and as

0:28:19.200 --> 0:28:23.760
<v Speaker 1>AI is now emphasizing, this philosophy can lead us into trouble,

0:28:24.960 --> 0:28:28.680
<v Speaker 1>and as worm GPT proves, it doesn't really matter if

0:28:28.720 --> 0:28:32.120
<v Speaker 1>the big players in the space take steps to mitigate

0:28:32.160 --> 0:28:36.000
<v Speaker 1>the dangers of AI. First, we've already seen that those

0:28:36.000 --> 0:28:39.480
<v Speaker 1>steps aren't sufficient, that even with the guardrails, you can

0:28:39.520 --> 0:28:43.040
<v Speaker 1>go way off course. And second, someone else is always

0:28:43.080 --> 0:28:45.720
<v Speaker 1>going to be willing to go where the big companies won't.

0:28:46.080 --> 0:28:49.400
<v Speaker 1>If there's money to be made in weaponizing a technology,

0:28:50.040 --> 0:28:53.520
<v Speaker 1>someone will step in to fill that market need. AI

0:28:53.680 --> 0:28:57.520
<v Speaker 1>might be neither good nor bad, but people certainly can be,

0:28:58.040 --> 0:29:02.800
<v Speaker 1>and malicious AI is a certainty. It's not a theory,

0:29:02.920 --> 0:29:06.000
<v Speaker 1>it's not a possibility. It is a certainty, not because

0:29:06.040 --> 0:29:09.880
<v Speaker 1>AI is inherently bad, but because there are people who

0:29:09.920 --> 0:29:13.840
<v Speaker 1>will see opportunity in directing AI toward malicious goals, and

0:29:14.080 --> 0:29:17.280
<v Speaker 1>they will do that. Nothing will stop them. So let's

0:29:17.320 --> 0:29:19.720
<v Speaker 1>think of another use of AI that has proven to

0:29:19.760 --> 0:29:24.560
<v Speaker 1>have negative consequences. Facial recognition technology traces its history to

0:29:24.600 --> 0:29:28.080
<v Speaker 1>the mid twentieth century. That's when some researchers were trying

0:29:28.120 --> 0:29:31.680
<v Speaker 1>to use computers to match faces with images that were

0:29:31.680 --> 0:29:35.160
<v Speaker 1>stored in a database, and at that time the computer

0:29:35.200 --> 0:29:38.960
<v Speaker 1>power and software wasn't up to the task. So lighting conditions,

0:29:39.040 --> 0:29:41.920
<v Speaker 1>the angle of the photo versus the angle of the

0:29:42.520 --> 0:29:46.560
<v Speaker 1>person's face that was being analyzed, the presence or absence

0:29:46.560 --> 0:29:51.160
<v Speaker 1>of glasses, a change in hairstyle or hair color. All

0:29:51.240 --> 0:29:56.920
<v Speaker 1>these variables and more were enough to confound computers. Unless

0:29:56.960 --> 0:30:01.240
<v Speaker 1>the sample image matched a stored image precise, the computer

0:30:01.360 --> 0:30:02.840
<v Speaker 1>was not likely to be able to come up with

0:30:02.880 --> 0:30:07.160
<v Speaker 1>a match, but decades of research and improvements in technology

0:30:07.200 --> 0:30:10.920
<v Speaker 1>would change all that. The US Department of Defense got involved,

0:30:10.920 --> 0:30:13.720
<v Speaker 1>which should already set off some red flags for y'all

0:30:13.920 --> 0:30:17.280
<v Speaker 1>if the DoD is in it. DARPA, the department that

0:30:17.360 --> 0:30:20.960
<v Speaker 1>funds R and D in technologies that ultimately could prove

0:30:21.080 --> 0:30:24.640
<v Speaker 1>useful for military and defense purposes, launched the program in

0:30:24.680 --> 0:30:28.160
<v Speaker 1>the nineteen nineties in an effort to encourage commercial businesses

0:30:28.480 --> 0:30:32.800
<v Speaker 1>to invest in developing facial recognition technology. In the mid

0:30:32.840 --> 0:30:35.640
<v Speaker 1>to late two thousands, we started seeing cameras with face

0:30:35.680 --> 0:30:40.960
<v Speaker 1>detection technology. This wasn't quite the same as facial recognition technology.

0:30:41.280 --> 0:30:44.960
<v Speaker 1>Detecting a face and recognizing a face are two different things. However,

0:30:45.200 --> 0:30:47.920
<v Speaker 1>it did involve creating tech that could parse shapes and

0:30:48.040 --> 0:30:51.240
<v Speaker 1>determine if a face was in frame, and facial recognition

0:30:51.320 --> 0:30:54.040
<v Speaker 1>tech was still in full swing, so we would start

0:30:54.040 --> 0:30:58.520
<v Speaker 1>to see those technologies converge in the background. In twenty ten,

0:30:59.080 --> 0:31:02.680
<v Speaker 1>Facebook introduce a ton of people to facial recognition technology

0:31:02.960 --> 0:31:07.040
<v Speaker 1>by implementing it on the social platform. So the way

0:31:07.080 --> 0:31:10.640
<v Speaker 1>this worked. As users would upload photos to Facebook, Facebook

0:31:10.640 --> 0:31:14.440
<v Speaker 1>would automatically analyze each photo and look for faces of

0:31:14.520 --> 0:31:18.360
<v Speaker 1>people in those photos. If the faces that Facebook detected

0:31:18.560 --> 0:31:24.320
<v Speaker 1>matched people within their database of biometric data, particularly people

0:31:24.360 --> 0:31:28.760
<v Speaker 1>who are already in your social network, Facebook would tag

0:31:29.040 --> 0:31:33.280
<v Speaker 1>those photos and put the person's name in there. Privacy

0:31:33.280 --> 0:31:35.680
<v Speaker 1>advocates worried about this. I mean, yes, if you were

0:31:35.720 --> 0:31:38.400
<v Speaker 1>doing something you shouldn't be doing. That already is an

0:31:38.400 --> 0:31:41.120
<v Speaker 1>issue because if someone puts a photo of you up

0:31:41.160 --> 0:31:44.000
<v Speaker 1>there and it tags you, you might be caught red handed.

0:31:44.040 --> 0:31:47.400
<v Speaker 1>But even under innocent circumstances, it could be bad. I'll

0:31:47.400 --> 0:31:51.440
<v Speaker 1>give you an innocent version of this. Let's say that

0:31:52.240 --> 0:31:56.080
<v Speaker 1>you and your best friend from college live on opposite

0:31:56.120 --> 0:31:58.880
<v Speaker 1>sides of the country now, and it's your best friend's

0:31:58.960 --> 0:32:03.280
<v Speaker 1>birthday and you've planned a surprise. You've flown in to

0:32:03.400 --> 0:32:05.400
<v Speaker 1>your best friend's town and you're going to go and

0:32:05.440 --> 0:32:10.240
<v Speaker 1>surprise them on their birthday. And one of the mutual

0:32:10.280 --> 0:32:12.560
<v Speaker 1>friends takes a photo of you while you're at the

0:32:12.600 --> 0:32:18.080
<v Speaker 1>airport arriving at the city, and it auto tags you

0:32:18.240 --> 0:32:20.840
<v Speaker 1>when it's uploaded to social media, and then your friend

0:32:20.840 --> 0:32:23.960
<v Speaker 1>finds out about the fact that you're in town before

0:32:24.000 --> 0:32:26.320
<v Speaker 1>you even get a chance to do anything. That would

0:32:26.360 --> 0:32:30.800
<v Speaker 1>stink right, all that work and effort wasted because of

0:32:30.840 --> 0:32:36.520
<v Speaker 1>auto tagging. That's a very minor invasion of privacy that

0:32:36.880 --> 0:32:41.080
<v Speaker 1>illustrates the issue here well. For more than a decade,

0:32:41.080 --> 0:32:43.800
<v Speaker 1>Facebook kept the facial recognition tech in play, but in

0:32:43.840 --> 0:32:47.320
<v Speaker 1>twenty twenty one, the company at that point freshly renamed

0:32:47.360 --> 0:32:49.920
<v Speaker 1>as Meta, announced that it would drop the feature and

0:32:49.920 --> 0:32:52.640
<v Speaker 1>claimed it would also delete its database of images that

0:32:52.720 --> 0:32:55.920
<v Speaker 1>were used to help identify people. That database included more

0:32:55.920 --> 0:33:00.560
<v Speaker 1>than a billion photos. Why would Facebook slash Meta do this, Well,

0:33:00.560 --> 0:33:03.960
<v Speaker 1>partly it was probably because of optics, because at that

0:33:04.080 --> 0:33:06.800
<v Speaker 1>time the company was under intense scrutiny from the US

0:33:06.880 --> 0:33:11.320
<v Speaker 1>government after whistleblower Francis Hougan came forward with serious allegations

0:33:11.360 --> 0:33:14.880
<v Speaker 1>against the company and brought along hundreds of internal documents

0:33:14.920 --> 0:33:18.400
<v Speaker 1>backing up her claims. Many of those allegations related to

0:33:18.440 --> 0:33:22.640
<v Speaker 1>Meta slash Facebook's failure to protect user privacy and security.

0:33:23.280 --> 0:33:25.880
<v Speaker 1>Skeptics were actually worried the Meta would hold on to

0:33:26.000 --> 0:33:28.400
<v Speaker 1>that data and just say they were going to delete it,

0:33:28.440 --> 0:33:31.200
<v Speaker 1>but not delete it, and then just drop the facial

0:33:31.240 --> 0:33:35.200
<v Speaker 1>recognition feature off of Facebook and keep the information, especially

0:33:35.240 --> 0:33:38.480
<v Speaker 1>as it tried to build out the metaverse. Texas Attorney

0:33:38.520 --> 0:33:41.400
<v Speaker 1>General Ken Paxton actually told Meta not to delete the

0:33:41.400 --> 0:33:44.440
<v Speaker 1>facial recognition data because his office was in the middle

0:33:44.480 --> 0:33:49.320
<v Speaker 1>of an investigation into the company's biometric data collection practices. Honestly,

0:33:49.480 --> 0:33:52.960
<v Speaker 1>I don't know if or when Meta purged that information.

0:33:53.160 --> 0:33:56.040
<v Speaker 1>I don't know if it has been deleted. I tried

0:33:56.080 --> 0:34:00.000
<v Speaker 1>to look for some updates, but didn't really find much

0:34:00.160 --> 0:34:02.760
<v Speaker 1>because almost all the articles I could find were from

0:34:03.000 --> 0:34:05.720
<v Speaker 1>November of twenty twenty one, when Meta first announced it

0:34:05.760 --> 0:34:08.400
<v Speaker 1>was going to wipe the slate clean, So I don't

0:34:08.400 --> 0:34:13.280
<v Speaker 1>know if that actually happened. But beyond embarrassing or maybe

0:34:13.320 --> 0:34:17.240
<v Speaker 1>even incriminating images popping up on social media. Facial recognition

0:34:17.280 --> 0:34:20.719
<v Speaker 1>has proven to be a disruptive and traumatic technology for

0:34:20.760 --> 0:34:26.319
<v Speaker 1>certain populations, namely non white populations. So we often will

0:34:26.360 --> 0:34:30.279
<v Speaker 1>think of AI as being objective. Right. It's not a

0:34:30.360 --> 0:34:33.840
<v Speaker 1>human being. It doesn't have emotions, It has no motive

0:34:34.000 --> 0:34:37.160
<v Speaker 1>or motivations other than to complete whatever task has been

0:34:37.160 --> 0:34:39.640
<v Speaker 1>set for it. But we also have to remember that

0:34:39.680 --> 0:34:46.600
<v Speaker 1>AI didn't spring forth wholly formed. People designed AI, people

0:34:46.760 --> 0:34:51.960
<v Speaker 1>built AI, people trained AI, and in the process people

0:34:52.000 --> 0:34:55.799
<v Speaker 1>may end up building in biases in that technology, not

0:34:55.840 --> 0:35:00.280
<v Speaker 1>necessarily on purpose or with malevolent intent, but that doesn't

0:35:00.360 --> 0:35:05.280
<v Speaker 1>ultimately matter if those biases have impact on the general population.

0:35:05.360 --> 0:35:11.000
<v Speaker 1>As the technology goes live. With facial recognition technology, those

0:35:11.040 --> 0:35:15.520
<v Speaker 1>biases manifested in disturbing ways. Many facial recognition tools prove

0:35:15.600 --> 0:35:19.320
<v Speaker 1>to work pretty darn well on white people. Sufficiently trained

0:35:19.320 --> 0:35:21.960
<v Speaker 1>systems could identify a person with a pretty high degree

0:35:21.960 --> 0:35:25.520
<v Speaker 1>of accuracy, but with people of color in general and

0:35:25.600 --> 0:35:29.160
<v Speaker 1>black people in particular, it was a different story than

0:35:29.200 --> 0:35:33.000
<v Speaker 1>methodologies used by the systems would produce false positives, and

0:35:33.040 --> 0:35:38.120
<v Speaker 1>you can easily imagine scenarios where this becomes a huge problem.

0:35:38.239 --> 0:35:41.120
<v Speaker 1>For example, let's take law enforcement as there have been

0:35:41.160 --> 0:35:44.960
<v Speaker 1>several notable cases in which facial recognition technology has played

0:35:44.960 --> 0:35:48.600
<v Speaker 1>a part in authorities targeting the wrong person. If law

0:35:48.680 --> 0:35:52.080
<v Speaker 1>enforcement depends upon a tool to match a person's face

0:35:52.200 --> 0:35:55.879
<v Speaker 1>against a database of suspects and they get a hit,

0:35:56.360 --> 0:35:58.960
<v Speaker 1>you can understand why they would want to question that person,

0:35:59.480 --> 0:36:02.200
<v Speaker 1>why they would immediately assume this is a person of interest.

0:36:02.719 --> 0:36:06.560
<v Speaker 1>But if the technology produces false positives, that just means

0:36:06.600 --> 0:36:09.719
<v Speaker 1>that innocent civilians end up getting harassed by law enforcement.

0:36:10.120 --> 0:36:12.760
<v Speaker 1>And when those civilians belong to a population that already

0:36:12.800 --> 0:36:17.920
<v Speaker 1>faces disproportionate aggression from law enforcement, this exacerbates an already

0:36:18.000 --> 0:36:22.360
<v Speaker 1>critical social problem. Something that needs to get better is

0:36:22.440 --> 0:36:26.800
<v Speaker 1>being made even worse. As such, numerous communities have pushed

0:36:26.800 --> 0:36:29.640
<v Speaker 1>back on law enforcement's use of this technology, and in

0:36:29.680 --> 0:36:33.239
<v Speaker 1>some jurisdictions it's not a tool that police or other

0:36:33.320 --> 0:36:37.799
<v Speaker 1>law enforcement are supposed to use. There are laws in

0:36:37.840 --> 0:36:41.240
<v Speaker 1>certain areas where law enforcement is not allowed to depend

0:36:41.280 --> 0:36:45.520
<v Speaker 1>upon facial recognition for the purposes of identifying a suspect.

0:36:46.800 --> 0:36:49.040
<v Speaker 1>Knowing it has this law should be enough to just

0:36:49.040 --> 0:36:51.759
<v Speaker 1>disqualify it for its use in investigations, and yet we

0:36:51.800 --> 0:36:56.360
<v Speaker 1>still see it being used in lots of places, sometimes clandestinely.

0:36:56.920 --> 0:36:59.880
<v Speaker 1>It's not great. By the way, the companies that make

0:37:00.360 --> 0:37:04.359
<v Speaker 1>these law enforcement tools often build up their own databases

0:37:04.719 --> 0:37:09.560
<v Speaker 1>by scraping social networks for images. Facebook's facial recognition tool

0:37:09.760 --> 0:37:13.840
<v Speaker 1>was an incredible resource for these companies. Here you had millions,

0:37:14.040 --> 0:37:18.319
<v Speaker 1>in fact more than a billion images tagged with identities

0:37:18.360 --> 0:37:21.360
<v Speaker 1>of people in them, and many of them posted on

0:37:21.360 --> 0:37:24.440
<v Speaker 1>accounts that allowed the general public to go to that

0:37:24.680 --> 0:37:28.319
<v Speaker 1>account and see those images. So building up bots to

0:37:28.560 --> 0:37:33.120
<v Speaker 1>crawl Facebook and collect images and cross reference those against

0:37:33.280 --> 0:37:36.520
<v Speaker 1>people's names to build out a database, that was a

0:37:36.600 --> 0:37:41.280
<v Speaker 1>logical step for these companies. Now that technically violated platform policies,

0:37:41.280 --> 0:37:44.239
<v Speaker 1>but didn't stop the companies from doing it. And on

0:37:44.320 --> 0:37:47.360
<v Speaker 1>top of all that, this reliance on facial recognition technology

0:37:47.440 --> 0:37:51.799
<v Speaker 1>also requires heavy surveillance to really work properly. I mean,

0:37:51.880 --> 0:37:54.400
<v Speaker 1>you might have a great photo of your suspect, and

0:37:54.640 --> 0:37:58.319
<v Speaker 1>maybe your facial recognition system is reasonably accurate, so if

0:37:58.360 --> 0:38:01.080
<v Speaker 1>you were to get another picture of this person, you

0:38:01.080 --> 0:38:03.280
<v Speaker 1>would get a match. But you still have to figure

0:38:03.280 --> 0:38:05.560
<v Speaker 1>out where your suspect is in order to get any

0:38:05.600 --> 0:38:08.319
<v Speaker 1>other images, and to do that you need access to

0:38:08.360 --> 0:38:11.280
<v Speaker 1>a lot of camera feets you need cameras in lots

0:38:11.280 --> 0:38:14.560
<v Speaker 1>of places and systems to scan images from those cameras

0:38:14.560 --> 0:38:18.160
<v Speaker 1>to look for matches. A reliance on facial recognition pretty

0:38:18.239 --> 0:38:22.480
<v Speaker 1>much necessitates increased surveillance, which again becomes an invasion of

0:38:22.520 --> 0:38:26.919
<v Speaker 1>privacy and security for innocent civilians, suspect or otherwise. This

0:38:27.000 --> 0:38:30.560
<v Speaker 1>is one of the reasons why police and their relationship

0:38:30.680 --> 0:38:34.879
<v Speaker 1>with things like ring security are a big issue right

0:38:34.960 --> 0:38:40.360
<v Speaker 1>because if police have access to citizen cameras, then the

0:38:40.400 --> 0:38:43.480
<v Speaker 1>citizens have become an accomplice to creating a surveillance state,

0:38:44.080 --> 0:38:48.880
<v Speaker 1>and the law enforcement is leveraging that and then mixing

0:38:48.920 --> 0:38:53.280
<v Speaker 1>that with facial recognition, you get a pretty oppressive approach

0:38:53.320 --> 0:38:56.120
<v Speaker 1>toward law enforcement. And I haven't even touched on how

0:38:56.160 --> 0:38:59.359
<v Speaker 1>someone with an agenda could misuse this technology for their

0:38:59.400 --> 0:39:02.400
<v Speaker 1>own purpose. We have seen plenty of examples where an

0:39:02.480 --> 0:39:07.280
<v Speaker 1>organization that employs intrusive surveillance often discovers and I'm sure

0:39:07.800 --> 0:39:09.799
<v Speaker 1>this is a shock to all of you out there,

0:39:10.280 --> 0:39:14.759
<v Speaker 1>but they discovered that sometimes their staff will take advantage

0:39:14.880 --> 0:39:19.800
<v Speaker 1>of this technology and act upon it for themselves. Maybe

0:39:19.800 --> 0:39:23.000
<v Speaker 1>they use it to track down an X, or to

0:39:23.200 --> 0:39:27.120
<v Speaker 1>stalk someone, or to harass somebody that they do not

0:39:27.400 --> 0:39:33.359
<v Speaker 1>like this happens. In twenty thirteen, doctor George Ellard confirmed

0:39:33.960 --> 0:39:38.200
<v Speaker 1>that his office in the NSSAY uncovered cases in which

0:39:38.239 --> 0:39:41.920
<v Speaker 1>an employee had illegally made use of the agency's technologies

0:39:41.920 --> 0:39:45.960
<v Speaker 1>to spy on women with whom he had a relationship,

0:39:46.000 --> 0:39:48.160
<v Speaker 1>either in the past or in the present, and that

0:39:48.239 --> 0:39:53.439
<v Speaker 1>included listening in on phone calls and reading emails, a

0:39:53.480 --> 0:39:58.080
<v Speaker 1>flagrant violation of privacy. My point is that while the

0:39:58.239 --> 0:40:01.360
<v Speaker 1>NSSAY intended this technolog for the use of protecting the

0:40:01.400 --> 0:40:05.160
<v Speaker 1>interests of the United States, the people working at the

0:40:05.280 --> 0:40:10.640
<v Speaker 1>NSA are people, and some people can't resist the temptation

0:40:11.000 --> 0:40:15.960
<v Speaker 1>to abuse technologies that give them these abilities. Some, like

0:40:16.080 --> 0:40:19.080
<v Speaker 1>the case in twenty thirteen, will find that not only

0:40:19.200 --> 0:40:22.200
<v Speaker 1>is it possible for them to do this, they can

0:40:22.239 --> 0:40:25.680
<v Speaker 1>get away with it without detection for years, which means

0:40:25.719 --> 0:40:29.080
<v Speaker 1>then they do it a whole bunch. So, even if

0:40:29.080 --> 0:40:33.319
<v Speaker 1>facial recognition technology were flawless, which it is not, and

0:40:33.400 --> 0:40:37.959
<v Speaker 1>even if it didn't disproportionately harm certain communities, which it does,

0:40:38.640 --> 0:40:41.239
<v Speaker 1>there's still the issue of it being a technology that

0:40:41.280 --> 0:40:44.600
<v Speaker 1>folks can abuse. And sure, technically you can say that

0:40:44.640 --> 0:40:47.520
<v Speaker 1>about anything, right, you could abuse a pair of scissors

0:40:47.520 --> 0:40:51.040
<v Speaker 1>and use them as a weapon. So any technology can

0:40:51.080 --> 0:40:54.560
<v Speaker 1>be abused, but these AI technologies make it easier to do,

0:40:55.480 --> 0:41:00.839
<v Speaker 1>make it far more intrusive, make it scared available, so

0:41:00.880 --> 0:41:04.520
<v Speaker 1>you can end up abusing lots of people on a

0:41:04.560 --> 0:41:08.120
<v Speaker 1>grand scale and potentially to get away with it. And

0:41:08.239 --> 0:41:11.040
<v Speaker 1>meanwhile there are real people who get hurt in the process.

0:41:11.640 --> 0:41:13.160
<v Speaker 1>Now a thing in the future, we're going to look

0:41:13.200 --> 0:41:15.680
<v Speaker 1>back on this time as one in which Pandora opened

0:41:15.719 --> 0:41:18.640
<v Speaker 1>up the pesky box, and we spend a whole lot

0:41:18.640 --> 0:41:21.960
<v Speaker 1>of time and effort and agony getting stuff back in

0:41:21.960 --> 0:41:25.799
<v Speaker 1>that box, or to build guardrails around the box so

0:41:25.840 --> 0:41:29.440
<v Speaker 1>that the stuff can't do as bad at a job

0:41:29.480 --> 0:41:32.520
<v Speaker 1>as it would otherwise, and we'll just find out that,

0:41:32.680 --> 0:41:35.319
<v Speaker 1>just like with the myth, once that lid's open, that's it.

0:41:35.800 --> 0:41:38.799
<v Speaker 1>Now we just have to cope. Hamlet might say what

0:41:38.920 --> 0:41:43.520
<v Speaker 1>a piece of work is AI, and then I don't know,

0:41:43.600 --> 0:41:47.080
<v Speaker 1>you'd probably be all moody or something. Maybe that's just

0:41:47.160 --> 0:41:53.040
<v Speaker 1>how I feel. Anyway, That is sort of my perspective

0:41:53.400 --> 0:41:56.960
<v Speaker 1>on really techno solutionism in general, but AI in particular.

0:41:57.640 --> 0:42:01.480
<v Speaker 1>And again I don't wish to say that AI is

0:42:01.880 --> 0:42:07.120
<v Speaker 1>inherently bad or that it's useless, just that there is

0:42:07.160 --> 0:42:12.160
<v Speaker 1>a lot of potential for negative use cases, intended or otherwise,

0:42:12.760 --> 0:42:18.319
<v Speaker 1>and that even if we address the unintended consequences, we

0:42:18.400 --> 0:42:22.160
<v Speaker 1>still have the issue of people building out tools that

0:42:22.480 --> 0:42:26.319
<v Speaker 1>were malicious from start to finish. And it doesn't matter

0:42:26.320 --> 0:42:29.359
<v Speaker 1>how many good tools we have out there. If these

0:42:29.440 --> 0:42:34.880
<v Speaker 1>bad tools end up enabling a new era of malicious attacks,

0:42:35.320 --> 0:42:36.920
<v Speaker 1>we're going to have to come up with new ways

0:42:37.000 --> 0:42:40.680
<v Speaker 1>to protect ourselves against such things. And it's going to

0:42:40.760 --> 0:42:45.520
<v Speaker 1>be ugly. And it also really raises scary questions about

0:42:45.560 --> 0:42:50.319
<v Speaker 1>AI's use and weaponization on more grand scales, right like

0:42:50.400 --> 0:42:54.080
<v Speaker 1>on a military level, which is an ongoing concern. Again,

0:42:54.600 --> 0:42:58.600
<v Speaker 1>I think pretty much everyone out there anticipates that this

0:42:58.760 --> 0:43:02.440
<v Speaker 1>is a four on conclusion that AI will be deeply

0:43:02.480 --> 0:43:08.520
<v Speaker 1>incorporated into military operations beyond what it already is doing now.

0:43:09.200 --> 0:43:12.160
<v Speaker 1>Because if you don't do it, someone else will, which

0:43:12.200 --> 0:43:14.640
<v Speaker 1>means everybody has to do it. If you don't do it,

0:43:14.680 --> 0:43:18.640
<v Speaker 1>then you end up being you know, victim to someone else.

0:43:19.239 --> 0:43:24.480
<v Speaker 1>So that it's kind of that mutually assured destruction philosophy

0:43:24.640 --> 0:43:28.319
<v Speaker 1>of the Cold War, except it's with AI, and I

0:43:28.440 --> 0:43:30.799
<v Speaker 1>don't see a way around it, which is a very

0:43:30.880 --> 0:43:35.160
<v Speaker 1>cheerful way to conclude this episode. Maybe I'm being far

0:43:35.239 --> 0:43:37.839
<v Speaker 1>too cynical and pessimistic. I would love to find out

0:43:37.840 --> 0:43:39.640
<v Speaker 1>that that's the case. I would love for that to

0:43:39.680 --> 0:43:44.200
<v Speaker 1>be true. So I hope that all of my fears

0:43:44.200 --> 0:43:47.640
<v Speaker 1>and misgivings are misplaced. I would love to be wrong

0:43:47.680 --> 0:43:49.799
<v Speaker 1>in this case. There are times when I don't like

0:43:49.840 --> 0:43:51.480
<v Speaker 1>to be right, and this would be one of them.

0:43:51.920 --> 0:43:58.719
<v Speaker 1>So here's hoping. Until then, I suggest everyone out there

0:43:58.760 --> 0:44:01.880
<v Speaker 1>continue to do what I always advocate, use critical thinking

0:44:02.560 --> 0:44:07.839
<v Speaker 1>paired with compassion to conduct yourself so that you can

0:44:08.040 --> 0:44:13.719
<v Speaker 1>avoid problems for yourself and for other people, and hopefully

0:44:14.640 --> 0:44:17.359
<v Speaker 1>end up making the world a little bit better in

0:44:17.400 --> 0:44:19.719
<v Speaker 1>the process. Yeah, you don't need to go out and

0:44:19.760 --> 0:44:22.200
<v Speaker 1>save the world. You just, you know, need to use

0:44:22.239 --> 0:44:26.040
<v Speaker 1>some critical thinking and compassion to behave in a way

0:44:26.120 --> 0:44:30.520
<v Speaker 1>that is more beneficial than harmful. That's the goal. Whether

0:44:30.600 --> 0:44:33.200
<v Speaker 1>we succeed or not, sometimes that's not up to us,

0:44:33.600 --> 0:44:36.560
<v Speaker 1>but we can do our part. In the meantime. I

0:44:36.600 --> 0:44:39.160
<v Speaker 1>hope you are all well, and I'll talk to you

0:44:39.200 --> 0:44:49.520
<v Speaker 1>again really soon. Tech Stuff is an iHeartRadio production. For

0:44:49.640 --> 0:44:54.480
<v Speaker 1>more podcasts, from iHeartRadio, visit the iHeartRadio app, Apple podcasts,

0:44:54.600 --> 0:45:01.240
<v Speaker 1>or wherever you listen to your favorite shows.