:00:00. > :00:42.This is what happens when you let an artificial intelligence get
:00:43. > :00:46.creative. In a future with mass unemployment, young people are
:00:47. > :00:54.forced to sell blood. That's something I can do. You should see
:00:55. > :00:58.the boy and shut up. This is a film whose script was written entirely by
:00:59. > :01:05.an AI chatbot, one that's been trained to mimic science-fiction
:01:06. > :01:13.movie screenplays. Well, I have to go to the skull. I don't know what
:01:14. > :01:18.-- it's a fun watch, but only if you are in on the joke. Yes, it seems
:01:19. > :01:25.writing a gripping or even coherent narrative is beyond AI at the
:01:26. > :01:32.moment. But what if you were to give it the words and let it be the
:01:33. > :01:36.director? What if you gave an AI complete creative control over the
:01:37. > :01:44.costumes, the camera angles? What if you let it chews the cast? What
:01:45. > :01:48.would happen then? -- choose. That was what Sachi and Sachi
:01:49. > :01:53.commissioned this LA -based glad to find out. It is a real experiment.
:01:54. > :01:58.Out on a limb kind of experiment for film. Now, they decided not to make
:01:59. > :02:03.a full-length feature film, but instead to embark on a more
:02:04. > :02:08.manageable project. A pop video, which is something that many new
:02:09. > :02:11.directors cut their teeth on. A French dance group gave them
:02:12. > :02:15.permission to interpret one of their songs. The lyrics would form the
:02:16. > :02:23.script, but the interpretation would be completely down to the machine,
:02:24. > :02:26.more accurately machines. A director's job is a lot of different
:02:27. > :02:30.disciplines and specialties, so given that there is no one beat
:02:31. > :02:37.artificial brain somewhere that can do that, we assembled the best and
:02:38. > :02:41.most progressive pieces of television in a collect it to do
:02:42. > :02:54.that job. And what a collective it was. The -- first up, IBM's Watson
:02:55. > :02:58.was used. The humans could ask the next AI questions about what the
:02:59. > :03:04.video should look like. For that, take to the director's chair. I came
:03:05. > :03:12.up with a series of questions you might ask somebody like me, like,
:03:13. > :03:16.who are the characters? If I said day and night that's non-sequitur
:03:17. > :03:24.and random. But it is quite creative. I can't imagine a creative
:03:25. > :03:28.type coming up with that. She is a Japanese Twitter chat bot that
:03:29. > :03:32.appears to be a 17-year-old Japanese girl and was asked a whole lot of
:03:33. > :03:34.questions about who the characters in the lyrics were, what actions
:03:35. > :03:39.they should perform and what outfits they should wear. Do you have any
:03:40. > :03:46.kind of understanding about how it came up with those answers? Day and
:03:47. > :03:49.night. Night as the main character? From what we understand, this
:03:50. > :03:56.particular AI has been programmed by having conversations with fans, it's
:03:57. > :04:01.a Twitter handle. It has millions of conversations and it is relating in
:04:02. > :04:07.a way that a 17-year-old girl relates on Twitter. Next, casting.
:04:08. > :04:11.How does the director choose the right actor for a role? Well, it is
:04:12. > :04:16.probably someone who feels emotionally connect to the work and
:04:17. > :04:20.can transmit those emotions to the audience, but really it kind of
:04:21. > :04:26.comes down to a gut feeling. That's something that computers don't have.
:04:27. > :04:32.But what computers can do is measure the Performa's brain activity using
:04:33. > :04:36.and EEG, like this. In a very unusual casting session, ten
:04:37. > :04:41.unsuspecting actors were asked to perform the song while their facial
:04:42. > :04:46.expressions and brainwaves were compared to that of the song's lead
:04:47. > :04:52.singer when she performed it. The guy with the best emotional match
:04:53. > :04:56.got the gig. They said, what will you do with that? We said the
:04:57. > :05:01.director needs that to make the joys and whoever we choose has a matching
:05:02. > :05:08.emotional intent to the scene. -- choice. Did they know at this point
:05:09. > :05:16.that the director was and AI? No. When do they find out? Michael does
:05:17. > :05:19.know now. In fact, when the cast him, we brought him down to the set
:05:20. > :05:22.and explained this process. We said it would be a little weird because
:05:23. > :05:26.we will give you directions based on artificial intelligence, as an
:05:27. > :05:31.understanding of what this song is and what your actions are supposed
:05:32. > :05:35.to be. On the day of the shoot even the camera drones followed flight
:05:36. > :05:40.parts that were based on Watson's emotional analysis of the song. And
:05:41. > :05:47.when it came to the editor, choosing the shots and cutting it together,
:05:48. > :05:50.the AI build a brand-new editor, AI. This started by creating random
:05:51. > :05:56.assortment of shots and then learned from feedback on the human sweet
:05:57. > :05:59.shop they liked. And where. After many iterations the finished video
:06:00. > :06:08.was given a visual treatment that was itself a type of neural art,
:06:09. > :06:12.adding a day and night style to the -- character's scenes. How did turn
:06:13. > :06:19.out? Good and bad, really. The result is a pop your that's not
:06:20. > :06:23.going to win any. In fact, the band, whose videos are usually very highly
:06:24. > :06:27.produced, have distanced themselves from the whole thing. And I'm not
:06:28. > :06:33.really convinced that and AI has actually been the director here. --
:06:34. > :06:39.an AI. Are you? Got a hold different lot of sAI to do different jobs,
:06:40. > :06:44.including asking what this guy should wear. But then the people at
:06:45. > :06:50.the lab I'd really saying otherwise. Are you happy with the results? Yes.
:06:51. > :06:55.The exercise we went through the vibe a lot of great learning. The
:06:56. > :07:03.output itself with the video, it could be better, as a human. But for
:07:04. > :07:07.a first attempt a worthy effort. As the director, behind the scenes I'd
:07:08. > :07:10.like, that super intimidating, because it won't be long before this
:07:11. > :07:19.technology evolves where that editor that we've created becomes
:07:20. > :07:22.absolutely able to interpret like, oh, that shot's running and it has
:07:23. > :07:25.emotion, I should use that. And if that cuts to the concept of this
:07:26. > :07:32.emotional expression it will understand how one crates with
:07:33. > :07:34.another. All of a sudden we will have really emotional cutting from
:07:35. > :07:44.artificial intelligence. It's going to happen.
:07:45. > :07:53.Like most American cities, LA is a driving city, but it can take ages
:07:54. > :07:58.to get across town because of, well, take a look at this. So if you're a
:07:59. > :08:01.parent who has to take their kids somewhere, two or three hours before
:08:02. > :08:06.picking them up again, it might not be worth your while coming home in
:08:07. > :08:11.the meantime. So what you do if you are a parent who is too busy to
:08:12. > :08:13.ferry their kids around the city? Kate Russell has taken a pop, skip
:08:14. > :08:23.and drive to check this out. He would be a teenager? Lots of
:08:24. > :08:29.homework, hectic after-school activity schedule, Dean ferried
:08:30. > :08:33.around by time poor parents. -- being ferried. Hang on a minute,
:08:34. > :08:39.that looks pretty good for the teenager at least! Juggling work
:08:40. > :08:44.commitments with school runs and extra curricular activities can be a
:08:45. > :08:48.nightmare. For some parents are taxi is the only option. But how did know
:08:49. > :08:56.your children are safe getting into a car with a stranger. That is the
:08:57. > :09:01.question Hop, Skip, Drive set out to answer. Three of us created the
:09:02. > :09:06.company. We all have kids, we have six kids between us. Every kid
:09:07. > :09:11.activity known to man is participated in. We just couldn't
:09:12. > :09:15.manage it any more. Carly loves to dance, and she's pretty good at it.
:09:16. > :09:22.We originally lived somewhere different. Then we moved here and we
:09:23. > :09:26.couldn't get her to class on time, coming from work, all the way back
:09:27. > :09:31.here and so we put in a local dance studio, which wasn't the same. Hop,
:09:32. > :09:36.Skip, Drive says it runs background checks on all its drivers, including
:09:37. > :09:40.fingerprinting. They also told us applicants must have at least five
:09:41. > :09:47.years childcare experience. Really it is caregiving. So for my son,
:09:48. > :09:50.Jackson, the caregiver will Parker, go into the school, sign him out,
:09:51. > :09:54.there is a booster seat for him because he is not eight and I can
:09:55. > :09:59.track the ride as a parent the whole way. Rides are scheduled ahead of
:10:00. > :10:03.time, with clearly branded cars and drivers and have a secret password
:10:04. > :10:06.to give to the children on pickup, so everyone can be sure they are
:10:07. > :10:10.getting in the right car. What happens when they pick you up? First
:10:11. > :10:16.I get a text message on my phone and then they come up to the door, they
:10:17. > :10:21.tell me the password and we go in the car and make conversation. For
:10:22. > :10:23.the drivers, many of them mothers themselves, it's a much more
:10:24. > :10:29.rewarding job than just driving a taxi. How is it driving lots of
:10:30. > :10:36.different kids? What approach to you use? It depends. It depends on the
:10:37. > :10:41.child. My main objective is just too obviously be friendly and some kids
:10:42. > :10:46.just get in and they have their headphones on and they have their
:10:47. > :10:51.music trading, you know, and they just need to chill out. -- music
:10:52. > :10:56.playing. Because they have just come from school or at times. At other
:10:57. > :11:04.times the kids are really chatty, so I just have to take the emotional
:11:05. > :11:08.temperature. Now Carly can go to the dance studio she loves and Jennifer
:11:09. > :11:12.can manage her life more easily. I don't have to leave work early every
:11:13. > :11:18.day, because you know that's good I need to earn to pay for dams. Hop,
:11:19. > :11:21.Skip, Drive plans a careful expansion into more regions in the
:11:22. > :11:26.future. They also added carpooling to reduce the cost and this should
:11:27. > :11:31.help ease congestion around school drop-off points as well.
:11:32. > :11:37.That's it for the shortcut of Click for this week. Much more in the
:11:38. > :11:42.full-length version on iPlayer online and on Twitter. Thanks for
:11:43. > :11:43.watching. See you soon.