WEBVTT - Halt! Bot or Not?

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<v Speaker 1>Technology with tech Stuff from works dot com. 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 a senior writer for how stuff works dot com

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<v Speaker 1>focusing on all things technological, and recently I did an

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<v Speaker 1>episode about artificial intelligence and how Mark Zuckerberg and Elon

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<v Speaker 1>Musk had kind of a public disagreement about the direction

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<v Speaker 1>of AI, and how other people have weighed in. Some

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<v Speaker 1>people have said that perhaps Musk and Zuckerberg are arguing

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<v Speaker 1>about something that isn't really relevant right now, and that

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<v Speaker 1>there are in fact other elements of artificial intelligence that

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<v Speaker 1>we should be focusing on instead of whether or not

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<v Speaker 1>it is certain to make our lives better or worse

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<v Speaker 1>or rule over us. But it got me to thinking

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<v Speaker 1>about a related topic, and I touched on it all

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<v Speaker 1>little bit in that episode, and that was all about

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<v Speaker 1>how do you tell when a a an entity that

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<v Speaker 1>is communicating with you is in fact a person or

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<v Speaker 1>it is a computer program that is mimicking a person.

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<v Speaker 1>So we're going to look at that, And honestly, I

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<v Speaker 1>was inspired a lot also by the fact that we've

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<v Speaker 1>got a new Blade Runner movie coming out. It's Blade

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<v Speaker 1>Runner two thousand, forty nine, which has no connection to

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<v Speaker 1>this show. By the way, they are not sponsoring us.

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<v Speaker 1>I'm pretty sure no one connected to Blade Runner two

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<v Speaker 1>thousand forty nine even is aware that I exist. But

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<v Speaker 1>I'm a fan of the original Blade Runner film and

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<v Speaker 1>I'm looking forward to seeing what happens in Blade Runner

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<v Speaker 1>two thousand forty nine. I'm a little hesitant because it

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<v Speaker 1>depends upon which interpretation of the original film they decided

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<v Speaker 1>to ultimately go with. If they went with the director's vision,

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<v Speaker 1>might not want to see two thousand forty nine, but

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<v Speaker 1>I wanted to kind of talk about the difference between

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<v Speaker 1>communicating with a person and a synthetic being. Now in

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<v Speaker 1>Blade Runner, the synthetic beings are called replicants, and they

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<v Speaker 1>are not exactly robots. They're often referred to as androids,

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<v Speaker 1>but I don't really think that's terribly accurate either. They're

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<v Speaker 1>more like genetically engineered human simulations. Like they're not fully human. Uh.

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<v Speaker 1>They have other elements that either augmented abilities and intelligence,

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<v Speaker 1>but a lower lifespan that sort of stuffy. They tend

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<v Speaker 1>to be born in the adult stage of their lives

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<v Speaker 1>and implanted with false memories, but they're meant to do

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<v Speaker 1>jobs that humans can't or won't do, and they do

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<v Speaker 1>have a tendency to resent their lot in life, seeing

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<v Speaker 1>as how in the original film they did just have

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<v Speaker 1>that built an expiration data just a few years. They

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<v Speaker 1>don't live for a few years, and then they would

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<v Speaker 1>their bodies would break down and blade Runner the story

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<v Speaker 1>follows an investigator who is seeking out specific replicants that

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<v Speaker 1>are on the run in order to quote unquote retire

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<v Speaker 1>them with extreme prejudice. So this is all set up

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<v Speaker 1>at the beginning of the movie. Now, one thing those

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<v Speaker 1>investigators or blade Runners do is ask questions of suspects,

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<v Speaker 1>suspected replicants. You know, they find someone they think that

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<v Speaker 1>might be a replicant, and then they interview that person

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<v Speaker 1>and they look for signs that that is not actually

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<v Speaker 1>a real human being, because replicants are not exactly human.

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<v Speaker 1>They're human like, but they do not process emotions the

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<v Speaker 1>same way that humans do. So blade Runners can look

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<v Speaker 1>for indications that the suspect is actually a replicant and

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<v Speaker 1>they use what is called the void comp test in

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<v Speaker 1>the movie. This is a test that includes the hypothetical

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<v Speaker 1>situation you're in a desert walking along in the sand

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<v Speaker 1>when all of a sudden, you look down and see

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<v Speaker 1>it towards it. This you reach down and flip the

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<v Speaker 1>tortoise on its back. The tortoise lays on its back.

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<v Speaker 1>It's belly baking in the hot sun, beating its legs,

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<v Speaker 1>trying to turn itself over, but it can't, not without

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<v Speaker 1>your help. But you're not helping. Why is that? Now?

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<v Speaker 1>I kind of paraphrase that scene because it actually happens

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<v Speaker 1>as dialogue between two characters. But that was the attempt

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<v Speaker 1>of an interrogator to figure out whether or not the

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<v Speaker 1>person they were talking to is actually a human being,

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<v Speaker 1>because the emotional responses would indicate whether or not it

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<v Speaker 1>was a human response, or if there was a lack

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<v Speaker 1>of that, that it was perhaps a replicant. Now, that's

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<v Speaker 1>all science fiction, but in the real world there are

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<v Speaker 1>times when we encounter bots or AI constructs and we

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<v Speaker 1>might not know at first, at least they were not

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<v Speaker 1>communicating with a real life person. In fact, the Interactive

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<v Speaker 1>Advertising Bureau reported in two thousand fourteen that thirty six

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<v Speaker 1>per cent of all web traffic is general to buy bots,

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<v Speaker 1>not people, and the security firm Imperva reported in early

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<v Speaker 1>two thousand seventeen that today that figure is now closer

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<v Speaker 1>to fifty, which means that right now there's more traffic

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<v Speaker 1>on the web being generated from bots than actual human beings,

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<v Speaker 1>And that's not exactly great. Much of the web depends

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<v Speaker 1>upon advertising for monetization. But how do you figure out

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<v Speaker 1>what the value of traffic to your website is when

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<v Speaker 1>you know there's a good chance that more than half

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<v Speaker 1>of all those page views were generated from algorithms, not

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<v Speaker 1>from human beings. Now, much of the bot traffic isn't

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<v Speaker 1>meant to be outright malicious. There might be bots that

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<v Speaker 1>are essentially trying to to scour the Internet for data

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<v Speaker 1>for nefarious purposes, but a lot of them are just

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<v Speaker 1>they're gathering information for, you know, completely innocent purposes. Really,

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<v Speaker 1>gathering information on its own is not necessarily a bad thing.

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<v Speaker 1>It's how we use the information that makes it good

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<v Speaker 1>or bad. It's kind of paraphrasing Shakespeare there. But there

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<v Speaker 1>are the various bots on social platforms and websites that

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<v Speaker 1>also interact with people, and some of them are again benign.

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<v Speaker 1>They're meant to be helpful, such as bots that can

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<v Speaker 1>answer basic customer service questions for companies. You've probably encountered

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<v Speaker 1>one of these where you were looking for some information

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<v Speaker 1>about a particular product or service and then a little

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<v Speaker 1>chat window pops up, and you get the feeling that

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<v Speaker 1>the entity you're talking to is not exactly another human

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<v Speaker 1>being on the other end. It may just be a bot.

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<v Speaker 1>Sometimes that's fine. Sometimes it's more frustrating than helpful, because

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<v Speaker 1>you find that you have to word things in a

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<v Speaker 1>very particular way for the bot to comprehend what you mean,

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<v Speaker 1>whereas a human would probably pick it up much faster.

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<v Speaker 1>But you get the idea of why that was employed, right.

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<v Speaker 1>That was meant to make things a little more smooth

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<v Speaker 1>and to remove the necessity of putting a human being

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<v Speaker 1>in charge of that at all hours of the day.

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<v Speaker 1>You can also find these sorts of automated services on

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<v Speaker 1>phone lines, including bots that call you, which is always fun.

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<v Speaker 1>There's nothing like having a conversation with a bot for

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<v Speaker 1>half a minute before you figure out something fishy is

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<v Speaker 1>going on. But other bots are meant to serve the

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<v Speaker 1>purposes of some third party, sometimes with malicious intent, such

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<v Speaker 1>as convincing you to click on a link that leads

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<v Speaker 1>to malware, and that's where we really run into obvious problems.

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<v Speaker 1>Some of the benign ones can run into problems too often.

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<v Speaker 1>There are unintended consequences if you're scouring the web for data.

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<v Speaker 1>Data is valuable and sometimes people will want to get

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<v Speaker 1>hold of it for bad reasons, even if the initial

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<v Speaker 1>approach wasn't to do anything nefarious. Now, some hackers have

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<v Speaker 1>used bots to flood a platform with complaints in an

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<v Speaker 1>effort to silence people that the hackers do not like.

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<v Speaker 1>So let's say there's this jerk face hacker who thinks

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<v Speaker 1>a Facebook page devoted to promoting women in STEM education

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<v Speaker 1>and careers is dumb. So this jerk face then creates

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<v Speaker 1>or more likely purchases bots to flood Facebook with complaint

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<v Speaker 1>reports about that specific page in an attempt to get

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<v Speaker 1>Facebook to shut the page down. Now that's a pretty

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<v Speaker 1>lousy thing to do. And to be clear, some of

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<v Speaker 1>the jerk faces are aiming at pages that the average

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<v Speaker 1>person would say is a bad one. It doesn't have

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<v Speaker 1>to be something that like I feel strongly about and

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<v Speaker 1>and in favor for. I think STEM education and careers

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<v Speaker 1>for women is amazing, and I would be very upset

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<v Speaker 1>to hear about a page that was shut down because

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<v Speaker 1>of one of these attacks. On the other hand, let's

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<v Speaker 1>say that there was a page that was promoting something

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<v Speaker 1>I really do not like. Maybe it was a page

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<v Speaker 1>that was promoting, uh, you know, racial discrimination. I would

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<v Speaker 1>think that was terrible. If someone else were to take

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<v Speaker 1>bots and direct them to that page in order to

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<v Speaker 1>shut it down, I would also think that that's not

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<v Speaker 1>so great. I don't think that a page about racial

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<v Speaker 1>discrimination should be promoted or exist on Facebook. I don't

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<v Speaker 1>think that's appropriate. But at the same time, I don't

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<v Speaker 1>think it's appropriate to use automated systems to bring that down.

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<v Speaker 1>I would rather see an actual ground swell of human

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<v Speaker 1>support for that, not to you know, boost it with

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<v Speaker 1>a bunch of automated scripts. I don't want to give

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<v Speaker 1>the indication that the only people who ever use bots

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<v Speaker 1>are those who want to silence vulnerable or underrepresented populations.

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<v Speaker 1>There are some who use them to attempt to silence

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<v Speaker 1>voices of hate. In either case, it's dirty pool. I

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<v Speaker 1>don't think it's really a legitimate strategy. Uh, it ends

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<v Speaker 1>up hurting everyone in the long run to use bots

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<v Speaker 1>in that specific way. Butts in general, I'm not against.

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<v Speaker 1>I do think there are times when they are incredibly useful,

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<v Speaker 1>but to use them specifically to fool people into think

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<v Speaker 1>ging their actual human beings in order to achieve an

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<v Speaker 1>ulterior motive that sets me on edge that I can't

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<v Speaker 1>really see an upside to that. I can definitely see

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<v Speaker 1>it from the side of customer service or answering general questions,

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<v Speaker 1>maybe even just trying to funnel out people who have

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<v Speaker 1>a very simple issue to resolve versus those who need

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<v Speaker 1>more attention, whereas you know those people would get directed

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<v Speaker 1>towards a pathway that would lead to speaking to an

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<v Speaker 1>actual human being. I get it from that perspective. Now,

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<v Speaker 1>in a recent episode, I explained in brief what the

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<v Speaker 1>Turing test was, or at least how we interpret it.

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<v Speaker 1>The Turing test is sort of the inspiration for the

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<v Speaker 1>Void comp test and Blade Runner. Alan Turing, one of

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<v Speaker 1>the fathers of computer science, proposed the test back in

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<v Speaker 1>nineteen fifty and in the actual thought experiment that he

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<v Speaker 1>was proposing, it was a variation on a parlor game

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<v Speaker 1>called the imitation game. Now, the imitation game is one

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<v Speaker 1>where you have an interrogator that's player, and the player

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<v Speaker 1>is presented with two subjects, neither of whom the interrogator

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<v Speaker 1>can see or talk to directly. One of the two

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<v Speaker 1>subjects is a woman, the other is a man. Both

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<v Speaker 1>of the subjects can communicate with the interrogator in a

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<v Speaker 1>way that does not require face to face contact or

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<v Speaker 1>voice or anything like that. Typically it would be through

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<v Speaker 1>something like typewritten letters, because that would help disguise handwriting

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<v Speaker 1>as well. And the two subjects have the same task.

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<v Speaker 1>They have to convince the interrogator that they are female.

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<v Speaker 1>So the woman will be telling the truth, the man

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<v Speaker 1>will be lying, and it's the interrogator's job to figure

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<v Speaker 1>out who is imitating a woman and who actually is

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<v Speaker 1>a woman. Touring then suggested taking this game a step

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<v Speaker 1>further by replacing the male subject in this thought experiment

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<v Speaker 1>with a computer. The computer would also attempt to convince

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<v Speaker 1>the interrogator that the computer was in fact a woman.

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<v Speaker 1>Now would the interrogator be able to detect the computer's

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<v Speaker 1>ruse if not? Touring suggested that this would indicate some

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<v Speaker 1>form of intelligence, though not necessarily human intelligence. But you

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<v Speaker 1>could say the machine is capable of fooling a human being,

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<v Speaker 1>of of practicing deception, which I think most of us

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<v Speaker 1>would argue. The ability to practice deception does indicate at

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<v Speaker 1>least some form of intelligence. Maybe not the type of

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<v Speaker 1>intelligence that's gonna go out and teach a class on

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<v Speaker 1>quantum mechanics, but the type of intelligence that does understand

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<v Speaker 1>the concept of manipulation at least or at least is

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<v Speaker 1>able to employ the concept of manipulation, if not understand

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<v Speaker 1>it from a truly cognitive point of view. Now, the

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<v Speaker 1>other variations and refinements to the Touring test followed after

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<v Speaker 1>Touring's death in nineteen fifty four, and Touring's life was

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<v Speaker 1>very tragic. We've done an episode on Alan Touring, so

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<v Speaker 1>if you want to go back and find that in

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<v Speaker 1>our archives, you can learn all about his his death

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<v Speaker 1>and why some people rule it a suicide. I think

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<v Speaker 1>most people do, and some people say it was accidental.

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<v Speaker 1>But it is an interesting and tragic tale. Today, the

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<v Speaker 1>general interpretation of the Turing test is that if a

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<v Speaker 1>certain threshold is met, such as a greater than thirty

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<v Speaker 1>percent success rate of a computer convincing interrogators that's actually

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<v Speaker 1>a human, it has passed the Turing test. So, in

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<v Speaker 1>other words, if you're an interrogator and you've got a

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<v Speaker 1>computer terminal in front of you, and you're typing messages

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<v Speaker 1>and the the response is coming back to you. And

0:13:40.320 --> 0:13:42.800
<v Speaker 1>if more than thirty percent of the time you cannot

0:13:42.880 --> 0:13:45.280
<v Speaker 1>tell if that actually is a computer or a person,

0:13:46.080 --> 0:13:49.320
<v Speaker 1>maybe you misidentified as a person more than thirty percent

0:13:49.360 --> 0:13:52.320
<v Speaker 1>of the time, and it's actually the computer. That computer

0:13:52.400 --> 0:13:54.360
<v Speaker 1>is said to pass the Turing test, and that it

0:13:54.480 --> 0:13:57.160
<v Speaker 1>is capable of fooling you into thinking it's an actual

0:13:57.240 --> 0:13:59.640
<v Speaker 1>human being. Now, there was a case in two thousand

0:13:59.679 --> 0:14:03.080
<v Speaker 1>and four in which a chat bought called Eugene seemed

0:14:03.240 --> 0:14:07.400
<v Speaker 1>to accomplish this. Eugene's persona was that of a thirteen

0:14:07.480 --> 0:14:11.560
<v Speaker 1>year old Ukrainian boy. Critics pointed out that Eugene's limitations

0:14:11.640 --> 0:14:15.160
<v Speaker 1>as a non native English speaker with a limited knowledge

0:14:15.160 --> 0:14:17.520
<v Speaker 1>of the world due to his age and the fact

0:14:17.520 --> 0:14:20.400
<v Speaker 1>that he was from the Ukraine, meant that people were

0:14:20.480 --> 0:14:24.120
<v Speaker 1>lowering their expectations on his performance when they were chatting

0:14:24.120 --> 0:14:27.120
<v Speaker 1>with him over a computer. In other words, critics were

0:14:27.120 --> 0:14:33.600
<v Speaker 1>saying that Eugene was gaming the system by making people think, oh, well,

0:14:34.000 --> 0:14:38.000
<v Speaker 1>non native English speaker, so if the responses come back

0:14:38.040 --> 0:14:43.080
<v Speaker 1>a little weird, that explains that. And being young means

0:14:43.120 --> 0:14:46.440
<v Speaker 1>that they this kid doesn't have that much knowledge about

0:14:46.880 --> 0:14:49.440
<v Speaker 1>a lot of things in the world, pop culture, politics,

0:14:49.680 --> 0:14:53.720
<v Speaker 1>lots of stuff, so your expectations are set low, and

0:14:53.760 --> 0:14:56.600
<v Speaker 1>then you just think, all right, well, are the messages

0:14:56.640 --> 0:14:59.320
<v Speaker 1>I'm getting Are those in line with what I would

0:14:59.360 --> 0:15:02.840
<v Speaker 1>expect a thirteen year old non native English speaker to

0:15:02.960 --> 0:15:06.240
<v Speaker 1>say to me, or do they stand out as being artificial?

0:15:07.360 --> 0:15:10.040
<v Speaker 1>And a lot of this ends up being deflection as well,

0:15:10.160 --> 0:15:14.720
<v Speaker 1>where if you ask somebody a question and the computer

0:15:14.800 --> 0:15:17.400
<v Speaker 1>program doesn't have a way of responding, it will try

0:15:17.400 --> 0:15:21.480
<v Speaker 1>to deflect the question so that it doesn't indicate that

0:15:21.520 --> 0:15:27.360
<v Speaker 1>and in fact is a computer program. Well, Eugene managed

0:15:27.400 --> 0:15:30.440
<v Speaker 1>to to fool a lot of people, But again the

0:15:30.480 --> 0:15:35.880
<v Speaker 1>critics were saying, well, Eugene was kind of an outlier

0:15:35.920 --> 0:15:39.160
<v Speaker 1>in the sense that you didn't really think of Eugene

0:15:39.160 --> 0:15:44.520
<v Speaker 1>as being a native speaker with a lifetime of experience

0:15:45.080 --> 0:15:48.560
<v Speaker 1>where you could really quiz the the entity and find out, Okay,

0:15:48.640 --> 0:15:51.760
<v Speaker 1>is this actually a person or is it a computer program.

0:15:51.960 --> 0:15:53.680
<v Speaker 1>It's sort of beside the point. I'm not here to

0:15:53.760 --> 0:15:57.920
<v Speaker 1>argue about whether or not machines possess intelligence if they

0:15:57.920 --> 0:16:01.480
<v Speaker 1>passed the Turing test, because I did that recently already. Instead,

0:16:01.560 --> 0:16:04.080
<v Speaker 1>let's focus on the flip side of the scenario, we're

0:16:04.160 --> 0:16:08.160
<v Speaker 1>human at least I'm assuming you're a human. You might

0:16:08.160 --> 0:16:11.520
<v Speaker 1>be a bot who subscribed to text stuff. Apparently of

0:16:11.520 --> 0:16:14.280
<v Speaker 1>you out there are in that case. Thanks. I hope

0:16:14.320 --> 0:16:17.240
<v Speaker 1>you like the show. But this is all for the

0:16:17.280 --> 0:16:19.680
<v Speaker 1>humans here, this bit out here, so you bots out

0:16:19.720 --> 0:16:23.080
<v Speaker 1>there can take a break. How can we humans tell

0:16:23.120 --> 0:16:25.320
<v Speaker 1>if we're dealing with an actual person or if it

0:16:25.400 --> 0:16:29.240
<v Speaker 1>is a bot. Well, one of the ways that we

0:16:29.360 --> 0:16:34.440
<v Speaker 1>have created a means of separating bots from humans is capture.

0:16:35.320 --> 0:16:38.640
<v Speaker 1>Capture is an acronym that stands for a completely automated

0:16:38.720 --> 0:16:43.200
<v Speaker 1>public touring test to tell computers and humans apart. That

0:16:43.240 --> 0:16:44.960
<v Speaker 1>pretty much sums it up when you break it down.

0:16:45.120 --> 0:16:48.560
<v Speaker 1>It's completely automated, meaning there's no human oversight necessary for

0:16:48.600 --> 0:16:53.120
<v Speaker 1>any given implementation of the technology. It's public. It's pretty

0:16:53.120 --> 0:16:55.880
<v Speaker 1>self explanatory. It's a test that's out there in the public.

0:16:56.040 --> 0:16:58.080
<v Speaker 1>I guess I explained it even though it wasn't necessary.

0:16:58.560 --> 0:17:01.160
<v Speaker 1>That's my bad, y'all. Now, it's said to be a

0:17:01.160 --> 0:17:04.560
<v Speaker 1>turing test because it's meant to detect human versus automated

0:17:04.640 --> 0:17:08.480
<v Speaker 1>agents operating on a given web page. We talked about

0:17:08.600 --> 0:17:11.320
<v Speaker 1>the touring test just now. But h so we're not

0:17:11.359 --> 0:17:13.520
<v Speaker 1>gonna go over that again. But you know, again, it's

0:17:13.560 --> 0:17:17.560
<v Speaker 1>just just this indicator. Is there something there that implicates

0:17:17.680 --> 0:17:20.200
<v Speaker 1>this as being a computer agent not a human being?

0:17:20.640 --> 0:17:22.680
<v Speaker 1>And if it is in fact a computer agent, then

0:17:22.720 --> 0:17:24.960
<v Speaker 1>you have a gate up saying all right, you don't

0:17:25.000 --> 0:17:28.280
<v Speaker 1>get to participate in this because it's not meant for you.

0:17:28.520 --> 0:17:31.680
<v Speaker 1>When you have of your web traffic out there generated

0:17:31.680 --> 0:17:35.359
<v Speaker 1>by bots and you're trying to collect meaningful data about

0:17:35.400 --> 0:17:38.879
<v Speaker 1>real human being users, you have to have a way

0:17:39.359 --> 0:17:41.960
<v Speaker 1>to separate the two. Right. So, if I'm a web

0:17:42.000 --> 0:17:45.400
<v Speaker 1>administrator and let's say that I've got let's just say

0:17:45.400 --> 0:17:50.200
<v Speaker 1>that I'm running a sweepstakes, have created an online entry form.

0:17:50.240 --> 0:17:53.080
<v Speaker 1>I don't want someone flooding my sweepstakes with bots in

0:17:53.119 --> 0:17:56.040
<v Speaker 1>an effort to try and game the system and win

0:17:56.359 --> 0:17:59.800
<v Speaker 1>by submitting more entries than anybody else. I want to

0:17:59.800 --> 0:18:02.400
<v Speaker 1>be able to control that. So I want to have

0:18:02.600 --> 0:18:04.800
<v Speaker 1>some sort of element on there that can weed out

0:18:05.400 --> 0:18:11.040
<v Speaker 1>the automated agents out there versus the actual human beings. Now,

0:18:11.080 --> 0:18:13.879
<v Speaker 1>that last bit and capture to tell computers and humans

0:18:13.880 --> 0:18:16.119
<v Speaker 1>apart is the key to all of this. Capture is

0:18:16.160 --> 0:18:18.720
<v Speaker 1>a Guardian right, Like I was just saying, it's meant

0:18:18.760 --> 0:18:20.680
<v Speaker 1>to keep people from just writing a script to fill

0:18:20.680 --> 0:18:24.080
<v Speaker 1>out a form or make a comment on forums, really

0:18:24.600 --> 0:18:27.560
<v Speaker 1>complete any interaction on the web in an automated way.

0:18:28.160 --> 0:18:33.480
<v Speaker 1>As someone who creates content online and I get lots

0:18:33.480 --> 0:18:36.480
<v Speaker 1>of comments on various platforms, I don't want a whole

0:18:36.520 --> 0:18:42.960
<v Speaker 1>bunch of automated gobbledygook showing up under my various podcasts

0:18:42.960 --> 0:18:47.120
<v Speaker 1>and videos because then I can't tell where the actual

0:18:47.600 --> 0:18:51.240
<v Speaker 1>signal is. All I'm seeing is noise. So you want

0:18:51.280 --> 0:18:54.880
<v Speaker 1>to have some way of controlling that, and you might

0:18:55.080 --> 0:18:57.439
<v Speaker 1>use it to limit spam in the message board, or

0:18:57.480 --> 0:19:00.520
<v Speaker 1>to stop people from abusing the format of an online mistakes,

0:19:00.640 --> 0:19:04.399
<v Speaker 1>or or again to stop people from harassing others on

0:19:04.480 --> 0:19:07.760
<v Speaker 1>social platforms. Now, the necessity for cap chub is due

0:19:07.840 --> 0:19:10.800
<v Speaker 1>to a fundamental flaw of the Internet, and that flaw

0:19:10.960 --> 0:19:14.600
<v Speaker 1>is this, it doesn't take very many people to make

0:19:14.760 --> 0:19:18.960
<v Speaker 1>using the Internet a total drag. You don't want some

0:19:19.160 --> 0:19:21.840
<v Speaker 1>jerk face to use a script to create thousands of

0:19:21.880 --> 0:19:25.200
<v Speaker 1>email addresses from a web based email provider and then

0:19:25.359 --> 0:19:29.359
<v Speaker 1>use those email addresses for spam purposes or for someone

0:19:29.400 --> 0:19:31.560
<v Speaker 1>to gain the system. In other ways a single person

0:19:31.600 --> 0:19:35.840
<v Speaker 1>has the potential to impact lots of other people. So

0:19:35.960 --> 0:19:39.320
<v Speaker 1>everything's out of balance, and the force demands a Jedi

0:19:39.400 --> 0:19:44.080
<v Speaker 1>to right the wrongs or something. Now, the ideal application

0:19:44.119 --> 0:19:48.760
<v Speaker 1>of capture is some sort of test that is very

0:19:48.840 --> 0:19:53.560
<v Speaker 1>easy for humans to complete, but very difficult for computers

0:19:53.640 --> 0:19:56.639
<v Speaker 1>to complete. And that requires some creative thinking. So what

0:19:56.720 --> 0:19:59.119
<v Speaker 1>are some things that people are really good at but

0:19:59.200 --> 0:20:03.800
<v Speaker 1>computers are aren't so great at. Over time this changes.

0:20:04.160 --> 0:20:07.840
<v Speaker 1>Computer programmers get better at designing software that allows computers

0:20:07.840 --> 0:20:11.359
<v Speaker 1>to simulate more of what humans can do. And that's

0:20:11.400 --> 0:20:14.320
<v Speaker 1>not a bad thing necessarily because it pushes our development

0:20:14.320 --> 0:20:18.880
<v Speaker 1>of artificial intelligence. But for the purposes of gate keeping,

0:20:19.040 --> 0:20:22.240
<v Speaker 1>it does make it more tricky. You've gotta figure out

0:20:22.240 --> 0:20:24.560
<v Speaker 1>a new way to be able to prevent people from

0:20:24.560 --> 0:20:28.840
<v Speaker 1>abusing the system. Now, the idea for capture came from

0:20:28.880 --> 0:20:32.040
<v Speaker 1>a couple of different teams. One team was at Alta Vista,

0:20:32.280 --> 0:20:34.320
<v Speaker 1>which started to work on ways to cut down on

0:20:34.320 --> 0:20:38.480
<v Speaker 1>online abuse way back in the Ulta Vista team was

0:20:38.480 --> 0:20:41.439
<v Speaker 1>trying to find a way to prevent bots or scripts

0:20:41.480 --> 0:20:44.000
<v Speaker 1>from adding active u r l s to the search

0:20:44.080 --> 0:20:49.000
<v Speaker 1>engine platform. Meanwhile, the other team was at Carnegie Mellon University,

0:20:49.160 --> 0:20:51.680
<v Speaker 1>And actually this happened a couple of years after Alta

0:20:51.800 --> 0:20:55.560
<v Speaker 1>Vista's work, and they included some researchers who were really

0:20:56.040 --> 0:20:58.360
<v Speaker 1>eager to try and find a solution to this problem,

0:20:58.359 --> 0:21:03.600
<v Speaker 1>and they included Louis on On, Manuel Bloom, Nicholas Hopper,

0:21:03.760 --> 0:21:07.520
<v Speaker 1>and John Langford. It was the Carnegie Melon team that

0:21:07.600 --> 0:21:11.119
<v Speaker 1>coined the term capture back in two thousand three, and

0:21:11.200 --> 0:21:14.320
<v Speaker 1>it worked pretty well. Humans could get a capture right

0:21:14.400 --> 0:21:17.480
<v Speaker 1>more often than not, and computers weren't nearly as good

0:21:17.520 --> 0:21:21.000
<v Speaker 1>at it, at least not at first. Now we'll talk

0:21:21.040 --> 0:21:23.400
<v Speaker 1>a lot about captures in just a minute and get

0:21:23.400 --> 0:21:26.399
<v Speaker 1>into some more elements about telling the difference between butts

0:21:26.400 --> 0:21:29.359
<v Speaker 1>and humans, but right now let's take a quick break

0:21:29.680 --> 0:21:41.280
<v Speaker 1>to thank our sponsor. So with early capture implementations, things

0:21:41.520 --> 0:21:45.879
<v Speaker 1>were pretty simple. The capture would take on a pretty

0:21:45.960 --> 0:21:49.119
<v Speaker 1>universal form. You'd have a little box and inside that

0:21:49.160 --> 0:21:51.840
<v Speaker 1>box you would see a couple of different words or

0:21:52.000 --> 0:21:57.200
<v Speaker 1>collections of letters or other characters, often distorted in some way,

0:21:57.320 --> 0:21:59.960
<v Speaker 1>and a little field beneath it telling you, hey, tie

0:22:00.080 --> 0:22:03.160
<v Speaker 1>been what you see here? And it was your job,

0:22:03.200 --> 0:22:05.480
<v Speaker 1>as a human being type person to type in the

0:22:05.520 --> 0:22:08.000
<v Speaker 1>correct characters, and that would allow you to gain access

0:22:08.000 --> 0:22:10.800
<v Speaker 1>to whatever it was that the capture was guarding. And

0:22:10.800 --> 0:22:13.040
<v Speaker 1>the thought was that computers just weren't as good at

0:22:13.080 --> 0:22:17.280
<v Speaker 1>recognizing those characters as humans are. That if you distort them,

0:22:17.480 --> 0:22:22.560
<v Speaker 1>then the character recognition software couldn't put piece that altogether.

0:22:22.760 --> 0:22:27.760
<v Speaker 1>The weird shapes would be too far outside the norm

0:22:28.160 --> 0:22:31.399
<v Speaker 1>for the computer model. So if you had a one,

0:22:31.800 --> 0:22:35.320
<v Speaker 1>but that number one, the numeral one, it was all

0:22:35.440 --> 0:22:39.159
<v Speaker 1>wavy and staticky or something like you were, uh, you

0:22:39.240 --> 0:22:41.800
<v Speaker 1>were breaking up the shape a bit by changing it.

0:22:42.240 --> 0:22:45.680
<v Speaker 1>Computers can't really see that and conceptualize that's a one,

0:22:45.760 --> 0:22:48.480
<v Speaker 1>or at least not in the early days, so it

0:22:48.480 --> 0:22:50.399
<v Speaker 1>would just look like a weird squiggle to them, and

0:22:50.400 --> 0:22:53.360
<v Speaker 1>they wouldn't be able to complete the capture. Whereas we

0:22:53.520 --> 0:22:56.000
<v Speaker 1>human being type people, we'd look and think, that's the

0:22:56.080 --> 0:22:58.520
<v Speaker 1>worst number one I've ever seen. Some kid must have

0:22:58.560 --> 0:23:01.240
<v Speaker 1>drawn that, but we understand it is, we recognize it,

0:23:01.280 --> 0:23:03.879
<v Speaker 1>so we would type that in. That was the basis

0:23:03.960 --> 0:23:07.720
<v Speaker 1>for capture. Create a test that's relatively easy for humans,

0:23:08.240 --> 0:23:12.639
<v Speaker 1>very difficult for computers. Now, not everyone was capable of

0:23:12.680 --> 0:23:17.440
<v Speaker 1>seeing these captures. Clearly, some people have visual impair impairment,

0:23:17.680 --> 0:23:20.320
<v Speaker 1>and so they need to have some other element to

0:23:20.480 --> 0:23:24.960
<v Speaker 1>captures in order to be able to access that same content.

0:23:25.280 --> 0:23:29.280
<v Speaker 1>So there are also audible captures, which is pretty important

0:23:29.400 --> 0:23:32.880
<v Speaker 1>option to get around those visual impairments that some people have.

0:23:33.640 --> 0:23:41.040
<v Speaker 1>And uh, you might get a distorted voice being repeating

0:23:41.080 --> 0:23:44.359
<v Speaker 1>out the same sort of letters and numbers that you

0:23:44.359 --> 0:23:47.679
<v Speaker 1>would encounter with a capture. There might also be some

0:23:47.760 --> 0:23:52.240
<v Speaker 1>background noise that would include some other elements that would

0:23:52.280 --> 0:23:56.280
<v Speaker 1>make it hard for a computer program to analyze the

0:23:56.280 --> 0:23:59.160
<v Speaker 1>audio and figure out what was being said, but hopefully

0:23:59.400 --> 0:24:02.840
<v Speaker 1>humans would be able to make it out. So again,

0:24:02.840 --> 0:24:05.439
<v Speaker 1>it was all about making it more challenging for a

0:24:05.480 --> 0:24:08.959
<v Speaker 1>computer while not making it too challenging for human beings.

0:24:09.080 --> 0:24:13.920
<v Speaker 1>And sometimes that works great, and sometimes that doesn't work

0:24:14.000 --> 0:24:16.920
<v Speaker 1>so great. There are plenty of examples of human beings

0:24:16.920 --> 0:24:19.800
<v Speaker 1>who could not get through a capture because the distortion

0:24:19.920 --> 0:24:22.879
<v Speaker 1>was so great that it made the made it almost

0:24:22.920 --> 0:24:26.399
<v Speaker 1>impossible to recognize what the actual capture was supposed to be.

0:24:27.920 --> 0:24:31.240
<v Speaker 1>But the first counter to capture wasn't an advance in

0:24:31.320 --> 0:24:35.080
<v Speaker 1>computational analysis of visual or audible data. You know, there

0:24:35.080 --> 0:24:37.040
<v Speaker 1>are a lot of tricks that people figured out later

0:24:37.119 --> 0:24:42.240
<v Speaker 1>down the line, to make these visual captures easier to analyze,

0:24:42.320 --> 0:24:45.439
<v Speaker 1>things like switching all the images gray scales so that

0:24:45.520 --> 0:24:48.800
<v Speaker 1>you take out the different color gradations that could fool

0:24:48.840 --> 0:24:52.119
<v Speaker 1>a computer, and other elements along those lines. But at

0:24:52.160 --> 0:24:56.000
<v Speaker 1>first those weren't even really necessary because the people who

0:24:56.040 --> 0:24:58.600
<v Speaker 1>really wanted to get access to those systems didn't bother

0:24:58.760 --> 0:25:03.520
<v Speaker 1>programming better AI. They just went and started paying people

0:25:03.600 --> 0:25:07.120
<v Speaker 1>to fill out capture forms. Those who wanted to continue

0:25:07.119 --> 0:25:10.120
<v Speaker 1>the game giving the systems, they created a new industry.

0:25:10.240 --> 0:25:13.600
<v Speaker 1>They'd pay the people to fill out all these capture fields.

0:25:13.640 --> 0:25:16.280
<v Speaker 1>There was no need to develop any sort of AI.

0:25:16.440 --> 0:25:19.440
<v Speaker 1>People were doing what people were supposed to be doing easily.

0:25:19.480 --> 0:25:22.520
<v Speaker 1>They were solving captures. Now, the pay was super low

0:25:23.320 --> 0:25:25.679
<v Speaker 1>and the output was super high, and it posed a

0:25:25.680 --> 0:25:29.440
<v Speaker 1>threat to the capture system. Now, as an analogy, amount

0:25:29.520 --> 0:25:32.440
<v Speaker 1>imagine that you build a big fence strong enough to

0:25:32.520 --> 0:25:35.720
<v Speaker 1>keep bears out. No bears will get in this fence,

0:25:35.800 --> 0:25:38.119
<v Speaker 1>you say, and you go on your married a little way.

0:25:38.320 --> 0:25:40.320
<v Speaker 1>What you didn't notice is that there were gaps in

0:25:40.359 --> 0:25:43.680
<v Speaker 1>the fence that while the bears are far too big

0:25:43.720 --> 0:25:47.000
<v Speaker 1>to fit through the gaps, the gaps are big enough

0:25:47.040 --> 0:25:50.639
<v Speaker 1>to let rabid I don't know possums through, And so

0:25:50.760 --> 0:25:55.879
<v Speaker 1>the bears who go to employ rabid possums, paying them handsomely,

0:25:55.920 --> 0:25:58.600
<v Speaker 1>are able to access the stuff behind your fence anyway,

0:25:58.640 --> 0:26:02.360
<v Speaker 1>because the rapid possums pass right through the security. They

0:26:02.400 --> 0:26:05.200
<v Speaker 1>weren't intended to be kept out. Of course, in the

0:26:05.240 --> 0:26:08.760
<v Speaker 1>case the captures, we are talking about people accessing the system.

0:26:08.800 --> 0:26:11.239
<v Speaker 1>They were just doing so in massive numbers and for

0:26:11.400 --> 0:26:15.000
<v Speaker 1>less than ethical reasons. So the Carnegie Melon team began

0:26:15.040 --> 0:26:18.440
<v Speaker 1>to consider a new approach. That's when they developed recapture.

0:26:19.480 --> 0:26:23.119
<v Speaker 1>This tech used images of real words and numbers taken

0:26:23.160 --> 0:26:27.920
<v Speaker 1>from old documents. The original run was of New York

0:26:27.960 --> 0:26:32.679
<v Speaker 1>Times archival texts, but eventually the teams sold this technology

0:26:32.720 --> 0:26:35.159
<v Speaker 1>to Google, which began to use it on lots and

0:26:35.200 --> 0:26:40.119
<v Speaker 1>lots of scanned books. They were trying to transcribe those

0:26:40.119 --> 0:26:43.879
<v Speaker 1>old books. The company used recapture to display scanned words

0:26:43.920 --> 0:26:47.919
<v Speaker 1>or numbers from the texts, and as more people filled

0:26:47.920 --> 0:26:50.720
<v Speaker 1>out the recaptures, Google began to use that data to

0:26:50.760 --> 0:26:52.879
<v Speaker 1>transcribe these old works, which meant that they had a

0:26:52.880 --> 0:26:57.040
<v Speaker 1>digital copy of these books that they had come into

0:26:57.040 --> 0:27:00.200
<v Speaker 1>possession of, which means anyone filling those fields out was

0:27:00.240 --> 0:27:04.440
<v Speaker 1>actually technically doing real work for Google, including all those

0:27:04.440 --> 0:27:07.600
<v Speaker 1>folks who were being employed to write out captures. Meanwhile,

0:27:07.640 --> 0:27:11.199
<v Speaker 1>bot developers were making better bots, and character recognition and

0:27:11.240 --> 0:27:15.400
<v Speaker 1>analysis software was getting better at increasing success rates with

0:27:15.520 --> 0:27:19.160
<v Speaker 1>visual captures. Now that would prompt capture designers to make

0:27:19.200 --> 0:27:22.840
<v Speaker 1>more challenging captures, and soon we reach a real problem.

0:27:22.960 --> 0:27:25.560
<v Speaker 1>The whole point of capture was that it was supposed

0:27:25.560 --> 0:27:27.680
<v Speaker 1>to be easy for a human to complete, but difficult

0:27:27.720 --> 0:27:31.000
<v Speaker 1>for a bot to complete. If it becomes tricky for humans,

0:27:31.080 --> 0:27:37.639
<v Speaker 1>you've defeated its original purpose. Now Google updated capture to

0:27:37.720 --> 0:27:40.679
<v Speaker 1>the familiar I'm not a robot check box that you

0:27:40.720 --> 0:27:43.240
<v Speaker 1>can still find on some online forms. They call it

0:27:43.280 --> 0:27:49.760
<v Speaker 1>the no capture recapture catchy. It wasn't just a check

0:27:49.840 --> 0:27:53.560
<v Speaker 1>box that needed checking. Behind the scenes, back if you

0:27:53.600 --> 0:27:56.000
<v Speaker 1>were able to stare at the back side of the

0:27:56.040 --> 0:27:59.960
<v Speaker 1>website that you're on, software was analyzing your clicking style

0:28:00.000 --> 0:28:02.359
<v Speaker 1>all so it would look for stuff like was the

0:28:02.400 --> 0:28:05.480
<v Speaker 1>box clicked right away, perhaps before or at the same

0:28:05.520 --> 0:28:08.199
<v Speaker 1>time as fields were being filled in. If so, that

0:28:08.240 --> 0:28:10.639
<v Speaker 1>indicates a bot rather than a human being. But this

0:28:10.680 --> 0:28:13.480
<v Speaker 1>approach also doesn't get around the fact that you could

0:28:13.480 --> 0:28:17.960
<v Speaker 1>employ real human beings to do this same work. So well,

0:28:17.960 --> 0:28:19.800
<v Speaker 1>it's an effective way to tell the difference between a

0:28:19.840 --> 0:28:23.919
<v Speaker 1>bot and a person. It's not necessarily effective in keeping

0:28:23.960 --> 0:28:26.679
<v Speaker 1>spam traffic away from a site if people are willing

0:28:26.720 --> 0:28:31.200
<v Speaker 1>to employ actual human beings to do it. In sen

0:28:31.240 --> 0:28:34.760
<v Speaker 1>Google killed off this version of capture on its own services.

0:28:34.800 --> 0:28:37.640
<v Speaker 1>You can still find it everywhere else, but these days

0:28:37.640 --> 0:28:43.760
<v Speaker 1>Google uses invisible recaptures. Now, this version analyzes your browsing behavior,

0:28:43.840 --> 0:28:46.640
<v Speaker 1>and there aren't a lot of details released about it yet,

0:28:46.680 --> 0:28:51.320
<v Speaker 1>but presumably Google is looking at how any given agent

0:28:51.480 --> 0:28:55.200
<v Speaker 1>on a website uses a web page to determine if,

0:28:55.560 --> 0:28:58.040
<v Speaker 1>in fact, that is an honest to goodness human being,

0:28:58.200 --> 0:29:00.479
<v Speaker 1>or if the terminator has the said to pop over

0:29:00.560 --> 0:29:05.880
<v Speaker 1>to Zeppos to look for some new kicks. So this

0:29:05.960 --> 0:29:09.400
<v Speaker 1>is still in a way of being able to differentiate

0:29:09.560 --> 0:29:13.400
<v Speaker 1>humans from machines based solely upon behavior, just analyzing the

0:29:13.440 --> 0:29:17.960
<v Speaker 1>behavior and thinking all right, well, this indicates a human being.

0:29:18.040 --> 0:29:21.160
<v Speaker 1>This is this person, This entity is navigating a web

0:29:21.160 --> 0:29:24.280
<v Speaker 1>page the way a human would versus this is really

0:29:24.320 --> 0:29:28.600
<v Speaker 1>efficient and formulaic and repetitive, and that tells me that's

0:29:28.600 --> 0:29:32.560
<v Speaker 1>possibly a machine. So let's switch over to Twitter. Twitter

0:29:32.640 --> 0:29:35.520
<v Speaker 1>has got a lot of bots on it. Twitter and

0:29:35.520 --> 0:29:39.600
<v Speaker 1>the follower numbers are kind of a type of status online.

0:29:39.960 --> 0:29:43.760
<v Speaker 1>If you have more followers than the general implication is

0:29:43.800 --> 0:29:46.760
<v Speaker 1>that you must be more important than someone who has

0:29:46.800 --> 0:29:52.520
<v Speaker 1>fewer followers, and so there's a healthy market for purchased followers.

0:29:52.640 --> 0:29:57.360
<v Speaker 1>On Twitter. You can go to several different companies and

0:29:57.480 --> 0:30:02.480
<v Speaker 1>stores and buy followers by the hundreds or thousands. So

0:30:02.520 --> 0:30:04.680
<v Speaker 1>if you're desperate to boost that number, you can pay

0:30:04.680 --> 0:30:07.640
<v Speaker 1>a service that will link accounts to your account. Now,

0:30:07.680 --> 0:30:10.560
<v Speaker 1>most of those probably do not have real, live human

0:30:10.600 --> 0:30:13.920
<v Speaker 1>beings behind those accounts, and so a visit to any

0:30:14.040 --> 0:30:16.080
<v Speaker 1>of those accounts will show you that they never seem

0:30:16.160 --> 0:30:19.080
<v Speaker 1>to say anything themselves. They'll retweet what lots of other

0:30:19.080 --> 0:30:22.600
<v Speaker 1>people are saying, but they don't actually, you know, tweet

0:30:22.640 --> 0:30:26.400
<v Speaker 1>anything of their own, or if they do, it makes

0:30:26.480 --> 0:30:28.880
<v Speaker 1>little to no sense. It might just be kind of

0:30:28.920 --> 0:30:34.400
<v Speaker 1>like garbled general you know, new a g kind of stuff,

0:30:34.520 --> 0:30:37.840
<v Speaker 1>the things that that sound like they might have some

0:30:37.920 --> 0:30:39.960
<v Speaker 1>sort of deep meaning, but if you think about it,

0:30:39.960 --> 0:30:43.360
<v Speaker 1>you realize, no, that really doesn't mean anything at all. Now,

0:30:43.400 --> 0:30:46.160
<v Speaker 1>on a one on one basis, Twitter bots are pretty

0:30:46.160 --> 0:30:48.560
<v Speaker 1>easy to spot. So let's say your you tweet about

0:30:48.600 --> 0:30:50.880
<v Speaker 1>something important going on, such as you know something's going

0:30:50.920 --> 0:30:53.000
<v Speaker 1>on in politics or whether John Snow is going to

0:30:53.080 --> 0:30:56.160
<v Speaker 1>win the Game of Thrones, and almost immediately after you tweet,

0:30:56.200 --> 0:30:59.560
<v Speaker 1>you notice a new followed notification and if it popped

0:30:59.600 --> 0:31:03.080
<v Speaker 1>up sue pretty quickly, like instantly after you posted a tweet.

0:31:03.600 --> 0:31:05.680
<v Speaker 1>That might very well be a bot running on a

0:31:05.720 --> 0:31:09.560
<v Speaker 1>script that is searching for instances of specific keywords, and

0:31:09.560 --> 0:31:13.400
<v Speaker 1>when it finds those keywords, it then prompts the bot

0:31:13.440 --> 0:31:17.920
<v Speaker 1>account to follow the account that generated the keywords, assuming

0:31:17.960 --> 0:31:21.200
<v Speaker 1>that hasn't already followed that account. And some butts do

0:31:21.280 --> 0:31:23.360
<v Speaker 1>this in order to convince people to follow them back

0:31:23.680 --> 0:31:26.000
<v Speaker 1>because lots of folks on Twitter have a follow back

0:31:26.120 --> 0:31:28.800
<v Speaker 1>policy which helps them boost up their own follower numbers.

0:31:28.800 --> 0:31:30.800
<v Speaker 1>You know, it's the whole hey, if you follow me,

0:31:30.880 --> 0:31:34.480
<v Speaker 1>I'll follow you quit bro quo kind of approach. But

0:31:34.560 --> 0:31:37.280
<v Speaker 1>in this case, one of the two parties is a bot,

0:31:37.760 --> 0:31:39.680
<v Speaker 1>at least one of them. Anyway, maybe they both are,

0:31:39.840 --> 0:31:43.440
<v Speaker 1>which is kind of funny and pointless. Now, once you

0:31:43.560 --> 0:31:46.760
<v Speaker 1>follow the bot, you may start seeing spam messages from

0:31:46.760 --> 0:31:49.320
<v Speaker 1>that bot pop up in your feed. Whenever it occasionally

0:31:49.360 --> 0:31:52.760
<v Speaker 1>posts two followers, it's likely trying to get you to

0:31:52.840 --> 0:31:56.080
<v Speaker 1>engage in a particular behavior. Now that behavior might be

0:31:56.120 --> 0:31:59.000
<v Speaker 1>more or less benign, such as convincing you to shop

0:31:59.040 --> 0:32:03.920
<v Speaker 1>a certain brand which is obnoxious but not you know, malicious,

0:32:04.480 --> 0:32:06.480
<v Speaker 1>Or it might be more sinisters, such as trying to

0:32:06.480 --> 0:32:08.880
<v Speaker 1>get you to do something foolish that will compromise your

0:32:08.880 --> 0:32:12.280
<v Speaker 1>computer and allow it to join like a hacker's bot

0:32:12.280 --> 0:32:15.560
<v Speaker 1>net army or something. And there's a lot of reasons,

0:32:15.600 --> 0:32:18.360
<v Speaker 1>most of them annoying, that a bot programmer would want

0:32:18.360 --> 0:32:21.560
<v Speaker 1>you to follow their butt. According to a study conducted

0:32:21.560 --> 0:32:25.640
<v Speaker 1>by researchers at Indiana University and the University of Southern California,

0:32:25.880 --> 0:32:29.880
<v Speaker 1>somewhere between nine and fifteen percent of all active Twitter

0:32:29.960 --> 0:32:33.840
<v Speaker 1>accounts are actually bots. It usually doesn't require a lot

0:32:33.880 --> 0:32:36.440
<v Speaker 1>of work to determine if a single account is the

0:32:36.480 --> 0:32:38.880
<v Speaker 1>work of an actual human being, but if you have

0:32:38.960 --> 0:32:40.880
<v Speaker 1>a lot of them, that can be a challenge. I mean,

0:32:40.880 --> 0:32:44.200
<v Speaker 1>if you've got thousands of followers, sorting through all of

0:32:44.240 --> 0:32:48.560
<v Speaker 1>those would take a real long time. So that's what

0:32:48.640 --> 0:32:52.160
<v Speaker 1>prompted developers to create apps like butt or Not, which

0:32:52.280 --> 0:32:55.320
<v Speaker 1>scour Twitter followers and look for signs of butts, returning

0:32:55.320 --> 0:32:57.200
<v Speaker 1>a report to the user to let him or her

0:32:57.240 --> 0:33:01.080
<v Speaker 1>know how many legitimate followers they have. Those apps, which

0:33:01.080 --> 0:33:04.920
<v Speaker 1>you can argue are are kind of bots themselves, look

0:33:04.960 --> 0:33:09.200
<v Speaker 1>for indicators such as each followers Twitter description uh the

0:33:09.320 --> 0:33:12.280
<v Speaker 1>u r L field, the number of tweets the account

0:33:12.320 --> 0:33:15.520
<v Speaker 1>has generated of its own, the number of followers the

0:33:15.560 --> 0:33:19.360
<v Speaker 1>account has, and so on. So if you come across

0:33:19.360 --> 0:33:23.160
<v Speaker 1>an account that follows thousands of other accounts but only

0:33:23.200 --> 0:33:26.160
<v Speaker 1>as a few followers of its own, that's a red flag.

0:33:26.240 --> 0:33:28.920
<v Speaker 1>That's saying, well, this account is following lots of people,

0:33:28.960 --> 0:33:31.120
<v Speaker 1>not a lot of people follow it. That tells me

0:33:31.440 --> 0:33:34.520
<v Speaker 1>something hinky might be going on. If the description or

0:33:34.600 --> 0:33:38.080
<v Speaker 1>you are l are empty, that's another indicator because it

0:33:38.320 --> 0:33:40.560
<v Speaker 1>shows maybe someone didn't want to take the time to

0:33:40.640 --> 0:33:45.440
<v Speaker 1>try and fool people by creating a bogus description and

0:33:45.480 --> 0:33:49.200
<v Speaker 1>a bogus u r L. There are several other criteria

0:33:49.400 --> 0:33:52.160
<v Speaker 1>that the apps look for, and depending upon how many

0:33:52.160 --> 0:33:55.400
<v Speaker 1>red flag boxes get checked, the app determines if the

0:33:55.480 --> 0:33:58.040
<v Speaker 1>account is the work of a script or if it's

0:33:58.040 --> 0:34:02.280
<v Speaker 1>an actual person. Now, on the one hand, we can

0:34:02.320 --> 0:34:04.240
<v Speaker 1>look at all these stories about bots, and think of

0:34:04.280 --> 0:34:07.680
<v Speaker 1>how irritating they are because they generate spam content, they

0:34:07.680 --> 0:34:10.960
<v Speaker 1>clog up actual communication. They create deception, whether it's an

0:34:10.960 --> 0:34:13.880
<v Speaker 1>attempt to trick you into following a malicious link or

0:34:13.920 --> 0:34:17.000
<v Speaker 1>to think someone is particularly notable due to the enormous

0:34:17.040 --> 0:34:19.880
<v Speaker 1>number of Twitter followers they have. But on the other hand,

0:34:20.160 --> 0:34:22.200
<v Speaker 1>we can think about how these examples show how we're

0:34:22.200 --> 0:34:26.040
<v Speaker 1>getting better at creating more human like agents. Now that's

0:34:26.080 --> 0:34:29.440
<v Speaker 1>not to say these agents possess intelligence, only that they

0:34:29.480 --> 0:34:33.080
<v Speaker 1>can imitate human interactions enough to raise the question could

0:34:33.120 --> 0:34:35.759
<v Speaker 1>this be a bot I'm talking to? If you have

0:34:35.840 --> 0:34:38.760
<v Speaker 1>to ask that question, then that indicates programmers are getting

0:34:38.800 --> 0:34:41.960
<v Speaker 1>better at designing bots, or that you're getting pretty bad

0:34:41.960 --> 0:34:45.840
<v Speaker 1>at recognizing humans. Some days, I certainly have that problem.

0:34:45.960 --> 0:34:49.000
<v Speaker 1>We'll talk a little bit more about machine intelligence and

0:34:49.040 --> 0:34:52.839
<v Speaker 1>communication in just a minute and kind of layout why

0:34:52.880 --> 0:34:57.560
<v Speaker 1>it's so difficult to really create a truly compelling butt

0:34:57.960 --> 0:35:00.360
<v Speaker 1>that can fool people into thinking it's a human. But

0:35:00.480 --> 0:35:10.719
<v Speaker 1>first let's take another quick break to think our sponsor. Now,

0:35:10.760 --> 0:35:15.359
<v Speaker 1>they're just elements to human communication that bots are not

0:35:15.520 --> 0:35:18.719
<v Speaker 1>great at handling, or they need a huge amount of

0:35:18.760 --> 0:35:21.239
<v Speaker 1>help in order to pull it off. So let's take

0:35:21.280 --> 0:35:25.120
<v Speaker 1>IBM S Watson for example. Now, Watson is the interface

0:35:25.239 --> 0:35:27.800
<v Speaker 1>that made the news when it competed against two former

0:35:27.880 --> 0:35:32.120
<v Speaker 1>Jeopardy champions on a special edition of Jeopardy. Watson beat

0:35:32.200 --> 0:35:35.239
<v Speaker 1>the opponents, which is pretty impressive when you consider that

0:35:35.320 --> 0:35:39.480
<v Speaker 1>Jeopardys format includes elements of wordplay includes and machines are

0:35:39.480 --> 0:35:44.120
<v Speaker 1>typically not very good at interpreting word play and subtext

0:35:44.200 --> 0:35:45.759
<v Speaker 1>and that sort of thing and getting at what the

0:35:45.800 --> 0:35:50.040
<v Speaker 1>actual meaning to a sentence is. Watson even attempted a

0:35:50.080 --> 0:35:52.480
<v Speaker 1>couple of jokes throughout the course of the game, but

0:35:53.000 --> 0:35:57.080
<v Speaker 1>they weren't really spontaneous bumb malls designed to get a

0:35:57.239 --> 0:36:01.520
<v Speaker 1>chuckle of, you know, Alex Trebek. Humor is just one

0:36:01.520 --> 0:36:04.239
<v Speaker 1>of those aspects of human communication that is difficult to

0:36:04.320 --> 0:36:09.200
<v Speaker 1>quantify and implement with machines. Typically, it requires programmers to

0:36:09.239 --> 0:36:13.080
<v Speaker 1>think ahead and imagine specific scenarios and queries to build

0:36:13.120 --> 0:36:18.880
<v Speaker 1>out appropriate or, depending upon the context, inappropriate responses. So,

0:36:18.960 --> 0:36:23.840
<v Speaker 1>for example, when Apple's personal assistant Sirie debuted, people immediately

0:36:23.880 --> 0:36:27.000
<v Speaker 1>began to test Sirie. They began to ask the digital

0:36:27.000 --> 0:36:30.360
<v Speaker 1>personal assistant all sorts of odd things and sharing the results.

0:36:31.120 --> 0:36:33.560
<v Speaker 1>If you create any sort of system. One of the

0:36:33.600 --> 0:36:36.440
<v Speaker 1>first things you're going to find when you allow people

0:36:36.520 --> 0:36:38.920
<v Speaker 1>to access that system is they're going to try and

0:36:38.960 --> 0:36:41.080
<v Speaker 1>break it, or they're at least going to try and

0:36:41.120 --> 0:36:45.160
<v Speaker 1>explore what the limitations are within that system. And they're

0:36:45.160 --> 0:36:48.879
<v Speaker 1>not necessarily doing this malicious with malicious intent, but rather

0:36:49.040 --> 0:36:52.000
<v Speaker 1>that you know, we're humans, were curious. We want to

0:36:52.040 --> 0:36:56.320
<v Speaker 1>know how how far do things go? Are they really

0:36:56.719 --> 0:36:59.400
<v Speaker 1>limitless or are you going to run up against an

0:36:59.440 --> 0:37:02.000
<v Speaker 1>invisible all if you keep going in one direction long enough.

0:37:02.800 --> 0:37:06.560
<v Speaker 1>The same thing is true about personal digital assistance. So

0:37:07.719 --> 0:37:11.000
<v Speaker 1>in some cases where people were asking weird things of SIRIE,

0:37:11.200 --> 0:37:15.359
<v Speaker 1>serious responses were particularly hilarious, indicating that someone over at

0:37:15.360 --> 0:37:19.799
<v Speaker 1>Apple had anticipated some of those shenanigans because SIRIE wasn't

0:37:19.840 --> 0:37:24.560
<v Speaker 1>coming up with these wacky responses on its own account.

0:37:24.760 --> 0:37:28.880
<v Speaker 1>It was referring to a database of responses that people

0:37:28.920 --> 0:37:34.400
<v Speaker 1>had been compiling ever since they started working on the project. So,

0:37:34.920 --> 0:37:38.360
<v Speaker 1>if you are working on a personal Digital assistant project

0:37:38.360 --> 0:37:40.719
<v Speaker 1>and you think, oh, someone's gonna say I love you

0:37:41.239 --> 0:37:44.680
<v Speaker 1>eventually to this, I want to have a response to

0:37:44.800 --> 0:37:47.520
<v Speaker 1>come back that isn't just I'm sorry. I don't understand

0:37:47.520 --> 0:37:51.520
<v Speaker 1>that every time the digital assistant says, I'm sorry, I

0:37:51.560 --> 0:37:59.560
<v Speaker 1>don't understand that is an overall, like outright admission of limitations.

0:37:59.600 --> 0:38:02.319
<v Speaker 1>So you will try avoid that as much as you can.

0:38:02.440 --> 0:38:04.360
<v Speaker 1>Make it kind of a joke instead. But it means

0:38:04.400 --> 0:38:07.680
<v Speaker 1>thinking ahead, and it means the humans are thinking ahead.

0:38:07.960 --> 0:38:12.640
<v Speaker 1>It's not a machine. Uh So, here's an example. One

0:38:12.680 --> 0:38:15.480
<v Speaker 1>of the early queries that got widespread traction was I

0:38:15.520 --> 0:38:18.960
<v Speaker 1>need to hide a body, and Siri would respond originally

0:38:19.239 --> 0:38:24.080
<v Speaker 1>with various sites where you could, you know, possibly dump

0:38:24.160 --> 0:38:26.960
<v Speaker 1>a body and get away with it, like nearby reservoirs

0:38:27.040 --> 0:38:30.680
<v Speaker 1>or quarries. It's pretty grim, but darkly humorous, and it

0:38:30.719 --> 0:38:33.960
<v Speaker 1>showed that someone had been thinking those things through by

0:38:34.000 --> 0:38:36.680
<v Speaker 1>the way, that joke became very serious. In two thousand twelve,

0:38:36.880 --> 0:38:39.840
<v Speaker 1>a Florida man stood accused of murdering a friend of his,

0:38:40.080 --> 0:38:44.560
<v Speaker 1>a roommate, and on his phone the suspects phone was

0:38:44.600 --> 0:38:47.640
<v Speaker 1>a screenshot of a query to Sirie, the one about

0:38:47.640 --> 0:38:51.560
<v Speaker 1>where to hide his roommate, and prosecutors used it as

0:38:51.600 --> 0:38:54.280
<v Speaker 1>evidence in the trial. But it turned out the screenshot

0:38:54.320 --> 0:38:56.960
<v Speaker 1>that used wasn't really a query that the man had

0:38:57.000 --> 0:39:01.239
<v Speaker 1>made himself, because his iPhone was as an iPhone that

0:39:01.280 --> 0:39:05.239
<v Speaker 1>was running on Verizons service, and the screenshot was from

0:39:05.280 --> 0:39:06.960
<v Speaker 1>an iPhone that was running on a T and T

0:39:07.160 --> 0:39:11.200
<v Speaker 1>S service. Uh. Also, it turned out that the phone

0:39:11.280 --> 0:39:14.279
<v Speaker 1>he was using, the suspect was an older model of

0:39:14.320 --> 0:39:18.160
<v Speaker 1>iPhone that didn't even support SIRIE. However, he was later

0:39:18.239 --> 0:39:20.960
<v Speaker 1>found guilty of his crime, though the Serie connection was

0:39:21.040 --> 0:39:25.879
<v Speaker 1>again dismissed for those multiple reasons. Later on, Apple would

0:39:26.120 --> 0:39:30.319
<v Speaker 1>replace that joking response with a referential but less morbid joke,

0:39:30.440 --> 0:39:33.440
<v Speaker 1>which was quote I used to know the answer to

0:39:33.520 --> 0:39:37.319
<v Speaker 1>this question end quote, So, in other words, acknowledging that,

0:39:37.360 --> 0:39:39.800
<v Speaker 1>in fact, there used to be another response without actually

0:39:39.800 --> 0:39:45.080
<v Speaker 1>giving it because of you know, these very grim, macabre

0:39:45.239 --> 0:39:48.680
<v Speaker 1>reasons in real life. But let's say you wanted to

0:39:48.680 --> 0:39:53.680
<v Speaker 1>create an artificial entity that could respond with humor dynamically.

0:39:54.000 --> 0:39:56.920
<v Speaker 1>It wouldn't require you to pre program in responses to

0:39:57.080 --> 0:40:00.920
<v Speaker 1>different questions you'd have to anticipate. This would let you

0:40:00.960 --> 0:40:03.840
<v Speaker 1>have a bot that could convincingly stand in as a

0:40:03.960 --> 0:40:07.239
<v Speaker 1>human without the danger of the bot encountering something you

0:40:07.280 --> 0:40:10.000
<v Speaker 1>didn't expect and having no response to it, or to

0:40:10.160 --> 0:40:14.080
<v Speaker 1>misinterpreting the interaction with an actual human being, or if

0:40:14.080 --> 0:40:16.680
<v Speaker 1>it did misinterpret it that it could follow up in

0:40:16.680 --> 0:40:20.440
<v Speaker 1>a very human way. So if I make a joke

0:40:20.880 --> 0:40:24.360
<v Speaker 1>to my coworkers and I do it well, my coworkers

0:40:24.440 --> 0:40:27.719
<v Speaker 1>understand what the meaning of the joke was, what the

0:40:27.800 --> 0:40:30.919
<v Speaker 1>intended meaning of the joke was, and there you get

0:40:30.920 --> 0:40:34.319
<v Speaker 1>that response. If the joke doesn't go well, I can

0:40:34.400 --> 0:40:37.120
<v Speaker 1>follow it up by explaining the joke or explaining what

0:40:37.200 --> 0:40:40.320
<v Speaker 1>I had tried to do with the joke, which doesn't

0:40:40.360 --> 0:40:43.480
<v Speaker 1>make the joke funny, but at least informs the audience

0:40:43.560 --> 0:40:46.480
<v Speaker 1>as to what it was I was thinking. Machines would

0:40:46.520 --> 0:40:47.960
<v Speaker 1>have to be able to do that too, and this

0:40:48.040 --> 0:40:50.960
<v Speaker 1>is hard to do. Machines would need to be able

0:40:51.000 --> 0:40:53.840
<v Speaker 1>to interpret not only the literal meaning of any statement,

0:40:54.160 --> 0:40:58.239
<v Speaker 1>but the potential intended meanings as well. So I would

0:40:58.280 --> 0:41:02.200
<v Speaker 1>have to incorporate the concept of novelties, introducing something new

0:41:02.239 --> 0:41:05.319
<v Speaker 1>and unexpected into the interaction. It's a subversion of our

0:41:05.360 --> 0:41:08.920
<v Speaker 1>expectations that tends to lead to humor. So, for example,

0:41:08.960 --> 0:41:11.760
<v Speaker 1>Douglas Adams, who is one of my favorite authors, once

0:41:11.800 --> 0:41:15.600
<v Speaker 1>wrote a sentence describing a fleet of spaceships, and the

0:41:15.680 --> 0:41:19.640
<v Speaker 1>sentence goes like this, The ships hung in the sky

0:41:19.960 --> 0:41:24.200
<v Speaker 1>in much the same way that bricks didn't. Now that's

0:41:24.200 --> 0:41:27.520
<v Speaker 1>a great sentence. It gets across the humor and intent

0:41:27.640 --> 0:41:29.840
<v Speaker 1>to the reader. You know that if you were to

0:41:29.840 --> 0:41:32.560
<v Speaker 1>see these spaceships in the sky, they would look completely

0:41:32.640 --> 0:41:36.720
<v Speaker 1>out of place. They might even be remotely brick shaped.

0:41:36.800 --> 0:41:40.400
<v Speaker 1>But mostly it's the idea that if bricks could hang

0:41:40.440 --> 0:41:43.520
<v Speaker 1>in the air, those ships would look like that, except

0:41:43.560 --> 0:41:47.680
<v Speaker 1>obviously bricks can't hang in the air, And in one sentence,

0:41:48.000 --> 0:41:51.560
<v Speaker 1>Adams is able to convey with humor the mind bendingly

0:41:51.680 --> 0:41:56.440
<v Speaker 1>weird experience of seeing these spaceships in the Earth's sky.

0:41:56.600 --> 0:41:59.719
<v Speaker 1>Computers would have a real hard time replicating that, at

0:41:59.800 --> 0:42:03.360
<v Speaker 1>least on purpose. A computer program that put rough sentences

0:42:03.400 --> 0:42:08.600
<v Speaker 1>together using a basic syntax and vocabulary could potentially make

0:42:08.680 --> 0:42:12.879
<v Speaker 1>weird and funny sentences, but these would be mostly random

0:42:12.920 --> 0:42:16.080
<v Speaker 1>and frequently meaningless, and you wouldn't be able to hold

0:42:16.120 --> 0:42:20.040
<v Speaker 1>a context from sentence to sentence. To make something that

0:42:20.080 --> 0:42:25.960
<v Speaker 1>has meaning requires aspects of intelligence that computers don't yet possess. Watson,

0:42:26.280 --> 0:42:29.960
<v Speaker 1>with its jokes, was running on a massively powerful computer

0:42:30.040 --> 0:42:34.239
<v Speaker 1>system with two thousand, eight hundred eighty processing cores, and

0:42:34.320 --> 0:42:37.200
<v Speaker 1>that doesn't even approach the power necessary to create real

0:42:37.360 --> 0:42:43.080
<v Speaker 1>humor spontaneously. To detect and generate sarcasm, and entity must

0:42:43.160 --> 0:42:47.160
<v Speaker 1>understand context and other cues and machines aren't very good

0:42:47.200 --> 0:42:50.320
<v Speaker 1>at this, though we've seen some advances in contextual tracking.

0:42:50.719 --> 0:42:54.160
<v Speaker 1>For example, Google's Personal Assistant can follow a line of

0:42:54.280 --> 0:42:57.600
<v Speaker 1>questions about the same subject without you having to restate

0:42:57.680 --> 0:43:01.000
<v Speaker 1>the subject with each question. If I asked my Google

0:43:01.040 --> 0:43:04.480
<v Speaker 1>Home what when the next Braves game is, it would

0:43:04.520 --> 0:43:07.200
<v Speaker 1>give me an answer. Let's say it's day after tomorrow. Well,

0:43:07.239 --> 0:43:09.320
<v Speaker 1>I could follow that up with what will the weather

0:43:09.360 --> 0:43:12.319
<v Speaker 1>be like then? And the system would understand that by

0:43:12.480 --> 0:43:14.920
<v Speaker 1>then I mean the day of the game, So the

0:43:15.000 --> 0:43:18.760
<v Speaker 1>day after tomorrow. I might also ask what's the fastest

0:43:18.800 --> 0:43:21.799
<v Speaker 1>way there, and it will know that by there I

0:43:21.840 --> 0:43:24.560
<v Speaker 1>mean the stadium, and that I am probably am asking

0:43:24.560 --> 0:43:27.880
<v Speaker 1>how to get from my current location to that stadium

0:43:27.960 --> 0:43:31.160
<v Speaker 1>and the most efficient way possible. The subject is stored

0:43:31.200 --> 0:43:34.120
<v Speaker 1>in temporary memory, I don't have to keep asking specific

0:43:34.239 --> 0:43:37.920
<v Speaker 1>questions about the game or the stadium. But that's still

0:43:37.960 --> 0:43:42.680
<v Speaker 1>a long way off from actually understanding context. So one

0:43:42.800 --> 0:43:46.160
<v Speaker 1>test for bots might be for us to have it

0:43:46.239 --> 0:43:49.080
<v Speaker 1>tell us a joke. If it's clear that the bot

0:43:49.160 --> 0:43:51.920
<v Speaker 1>can create a brand new joke, one that has not

0:43:52.080 --> 0:43:57.400
<v Speaker 1>been pre programmed, one that is spontaneous and novel and

0:43:57.480 --> 0:44:00.680
<v Speaker 1>created by the bot itself, and it makes sense and

0:44:00.800 --> 0:44:04.520
<v Speaker 1>it is funny. We've reached a point where telling bots

0:44:04.600 --> 0:44:08.759
<v Speaker 1>and humans apart is going to be tremendously complicated, but

0:44:08.880 --> 0:44:11.920
<v Speaker 1>right now we're nowhere near that. The jokes that we

0:44:12.000 --> 0:44:15.759
<v Speaker 1>hear bots tell, for the most part, are ones that

0:44:15.760 --> 0:44:18.200
<v Speaker 1>have been created by human beings and just stored in

0:44:18.239 --> 0:44:20.680
<v Speaker 1>a database, and the body just pulls them out and

0:44:20.719 --> 0:44:24.320
<v Speaker 1>then recites them. It's not creating them. It's just pulling

0:44:24.920 --> 0:44:29.200
<v Speaker 1>a massive data from a cell in a giant spreadsheet

0:44:29.239 --> 0:44:31.399
<v Speaker 1>and saying, all right, this is the joke I'm gonna

0:44:31.440 --> 0:44:35.080
<v Speaker 1>tell us. The joke that's in sell see four and seventeen.

0:44:35.400 --> 0:44:38.960
<v Speaker 1>That's the joke for today. That's not creating a joke,

0:44:39.040 --> 0:44:42.120
<v Speaker 1>it's just reciting one. If we can get to a

0:44:42.160 --> 0:44:44.719
<v Speaker 1>point where they can create jokes, that's a big jump

0:44:44.719 --> 0:44:49.000
<v Speaker 1>in computer intelligence and maybe a brand new audience from

0:44:49.040 --> 0:44:53.360
<v Speaker 1>my type of humor I'm always looking. Well, that pretty

0:44:53.400 --> 0:44:57.360
<v Speaker 1>much wraps up this episode. Really, the key to determining

0:44:57.360 --> 0:45:00.200
<v Speaker 1>whether or not it's a bot or a hu Man

0:45:00.480 --> 0:45:04.799
<v Speaker 1>is testing whether or not it's capable of handling novelty.

0:45:05.480 --> 0:45:09.480
<v Speaker 1>Most bots are fairly limited in the scope of things

0:45:09.480 --> 0:45:11.560
<v Speaker 1>they can handle, and if you step outside of that,

0:45:11.640 --> 0:45:14.840
<v Speaker 1>you see those limitations pretty quickly, and that then it

0:45:14.840 --> 0:45:18.080
<v Speaker 1>becomes apparent. But every year we're getting a little bit

0:45:18.080 --> 0:45:24.000
<v Speaker 1>better at handling wider spectrums of experiences with bots, so

0:45:24.040 --> 0:45:26.480
<v Speaker 1>that it becomes more and more complicated to tell them

0:45:26.520 --> 0:45:30.720
<v Speaker 1>apart from human beings. Uh. In most cases it's probably

0:45:30.920 --> 0:45:33.360
<v Speaker 1>a moot point. It's not really necessary depending upon what

0:45:33.440 --> 0:45:36.200
<v Speaker 1>it is you're trying to do, But in some cases

0:45:36.760 --> 0:45:38.359
<v Speaker 1>you really do want to know whether or not that's

0:45:38.360 --> 0:45:40.560
<v Speaker 1>a human being or a machine. On the other end,

0:45:41.200 --> 0:45:44.799
<v Speaker 1>if you guys have any stories about funny times where

0:45:44.840 --> 0:45:46.920
<v Speaker 1>you were chatting with something that you thought was a

0:45:46.960 --> 0:45:48.520
<v Speaker 1>human and turned out to be a bot, Like I've

0:45:48.560 --> 0:45:52.319
<v Speaker 1>got friends who have received robo calls and didn't know

0:45:52.560 --> 0:45:55.880
<v Speaker 1>until about half a minute in or maybe a minute in,

0:45:56.000 --> 0:45:59.279
<v Speaker 1>that it was a robot. Those are great stories. I

0:45:59.280 --> 0:46:02.000
<v Speaker 1>have specifically love the ones where if you ask the

0:46:02.160 --> 0:46:06.360
<v Speaker 1>entity are you a robot? It tries to deflect but

0:46:06.560 --> 0:46:09.920
<v Speaker 1>does not actually answer the question. Those are the best.

0:46:10.560 --> 0:46:12.400
<v Speaker 1>But you can get in touch with me, let me

0:46:12.440 --> 0:46:16.120
<v Speaker 1>know your experiences. The email address is tech stuff at

0:46:16.160 --> 0:46:18.440
<v Speaker 1>how stuff works dot com, or you can drop me

0:46:18.480 --> 0:46:21.279
<v Speaker 1>a line on Twitter or Facebook. The handle for the

0:46:21.280 --> 0:46:25.040
<v Speaker 1>show at both of those is tech stuff hs W. Remember,

0:46:25.520 --> 0:46:28.760
<v Speaker 1>normally you can watch me record shows live at twitch

0:46:28.800 --> 0:46:32.560
<v Speaker 1>dot tv slash tech stuff. I record on Wednesdays and Friday's.

0:46:32.760 --> 0:46:36.399
<v Speaker 1>Today's episode is a little bit outside the norm. There

0:46:36.480 --> 0:46:38.839
<v Speaker 1>is no one currently watching me live, so when I'm

0:46:38.840 --> 0:46:42.000
<v Speaker 1>doing my dance like I am right now, no one

0:46:42.080 --> 0:46:45.600
<v Speaker 1>can see. But most days you can see, and I

0:46:45.680 --> 0:46:48.520
<v Speaker 1>do the dance then too. So join me at twitch

0:46:48.520 --> 0:46:50.799
<v Speaker 1>dot tv slash tech stuff to watch the show live.

0:46:50.840 --> 0:46:53.600
<v Speaker 1>You get to see all the elements of the show

0:46:53.680 --> 0:46:57.720
<v Speaker 1>come together, and I will talk to you again. Really

0:47:03.280 --> 0:47:05.680
<v Speaker 1>for more on this and thousands of other topics, is

0:47:05.719 --> 0:47:16.240
<v Speaker 1>that how stuff works dot com.