1 00:00:00,000 --> 00:00:05,051 Welcome to this course on Web Intelligence and Big Data. 2 00:00:05,086 --> 00:00:13,212 In this first lecture, I'll introduce you to the topic, as well as outlined the, 3 00:00:13,212 --> 00:00:18,848 course itself and discuss some of the logistics and evaluation. 4 00:00:18,848 --> 00:00:25,840 When talking about intelligence, one can't help but recall Allen Turing and his 5 00:00:25,840 --> 00:00:33,385 famous thought experiment introduced way be back in 1950, to test if a computer was 6 00:00:33,385 --> 00:00:38,376 actually intelligent. Turing's original test is based on a 7 00:00:38,376 --> 00:00:45,586 popular party game where a human judge is able to converse using typewritten text 8 00:00:45,586 --> 00:00:50,066 only between two people, one a man and one a woman. 9 00:00:50,066 --> 00:00:56,082 And needs to judge, based on the conversation alone, which is a man and 10 00:00:56,082 --> 00:01:02,068 which is a woman. Turing's variation of this imitation game 11 00:01:02,068 --> 00:01:07,002 was to replace one of the participants by a machine. 12 00:01:07,002 --> 00:01:13,504 And now the judge needs to determine based on the conversations alone, who is human 13 00:01:13,504 --> 00:01:18,096 and who is a machine. Turing claimed that if a machine could 14 00:01:18,096 --> 00:01:25,039 successfully fool a human judge into believing that it was not a machine and 15 00:01:25,039 --> 00:01:31,040 actually human, then that machine should be considered to be intelligent. 16 00:01:32,056 --> 00:01:38,416 An interesting variation of the Turing test is where the judge's, now a machine, 17 00:01:38,416 --> 00:01:44,395 and needs to figure out which of the parties it's talking to is a human, and 18 00:01:44,395 --> 00:01:49,614 which is another machine. Now, do you think you might have seen or 19 00:01:49,614 --> 00:01:53,093 experienced such a reverse Turing test yourselves? 20 00:01:54,095 --> 00:02:01,001 Think about the captchas which all of us encounter on various webpages. 21 00:02:01,001 --> 00:02:07,082 They ask us to type in a set of letters looking at disfigured versions of those 22 00:02:07,082 --> 00:02:11,015 words. A task which machines find quite 23 00:02:11,015 --> 00:02:15,066 difficult. So this is an example where the machine is 24 00:02:15,066 --> 00:02:20,001 trying to figure out whether we are actually human. 25 00:02:20,001 --> 00:02:24,087 And so it's the reverse hearing test in action every day. 26 00:02:24,087 --> 00:02:30,000 But there's more. As we shall soon see in this course, 27 00:02:30,000 --> 00:02:37,098 machines inside the web can pretty easily figure out based on the conversations that 28 00:02:37,098 --> 00:02:46,145 we have with each other whether we are male or female, the products we like and 29 00:02:46,145 --> 00:02:54,218 dislike, whether we are shopping or just surfing, whether we are rich or poor, or 30 00:02:54,218 --> 00:03:01,928 even scary things like our ethnicity. The surprising thing is, that this is 31 00:03:01,928 --> 00:03:06,666 happening all the time on the web, as we shall see in our course. 32 00:03:06,666 --> 00:03:09,063 So is the web becoming intelligent.