1. technology and computing

Intelligent Lufthavn, gruppe 10
Bilag Hum­Tek Bachelor foråret 2015 Bilag 1
Interviewguide til Kenneth Fribert (Airmagine)
Teknologisk: ●
Hvor opstod idéen og hvordan er I kommet fra idé til endeligt produkt? ●
Hvorfor har I valgt at bruge denne teknologi? ●
Hvordan tror I forbrugeren vil modtage/reagere på teknologien? ●
Hvordan er teknologien testet (og udviklet)? ●
Hvilke udfordringer har i haft i udviklingen af teknologien og er der stadig udfordringer der ikke er løst? ●
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Hvordan fungere systemet? ○
Teknisk ○
Marketing Virker teknologien på alle mennesker? ○
Har I oplevet udfordringer med at identificere forbrugere? fx dværge, transkønnethed, religiøs påklædning (som burka) mm. Salg/marketing: ●
Hvad vil I bruge skærmene til? ○
Hvilken effekt forventer I det har hos forbrugere (passagerer)? ■
○
Hvilken effekt forventer I det har hos jeres kunder (virksomheder)? ■
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Hvilken effekt, hvis nogen har i registreret? Hvilken effekt, hvis nogen, har I registreret? Ser I allerede nu effekter af skærmene? Perspektivering: ●
Hvilket potentiale har teknologien? ○
Kan den implementeres andre steder? Intelligent Lufthavn, gruppe 10
Bilag Hum­Tek Bachelor foråret 2015 Interviewguide: Sarah Pink
We are working with a project where we wish to investigate our own method of interviewing through visual ethnography. In that regard we wish to interview you about our method to hear your perspective. The main focus of our project is the theme of face detection as a new technology framed in an Actor­Network­Theory perspective. ­­­­­­­­­­­­­ ●
How much does one’s experience with making film influence one's ability to make visual ethnography? ­ given that visual ethnography is invented and conducted outside of formats of filmmaking in an art paradigm (the technique of film). ●
What is the limitations of visual ethnography? What can it contribute with and when doesn't it make sense to use it as a method? Face detection is a new technology being implanted (commercially) in screens in CPH Airport in order to expose certain groups of potential buyers to targeted advertising. The technology counts how many male and female travelers are looking at the screen and how many of a certain age range is looking at the screen. It gives a picture of the average age and of if there is a majority of male or female consumers look a the screen in that instance. It measures this every 0,7 seconds. ●
So the question is whether a phenomena such as new technology and the mediation of it is possible to research through ethnography? ●
And: Can face detection (potentially: face recognition) be used as a research tool, conducting visual ethnography and thereby easing the workload of the scientist? ○
Or are ethics in leaving such a responsibility with a non­human overwhelmingly problematical? ○
Would visual ethnography as a method loose some of its value, by primarily dealing with quantitative data over qualitative data? (e.g. counting and monitorising behavioral patterns at different locations) ●
How do you use recorded representations, for example do you edit your representations into a film and if so, for whom? Intelligent Lufthavn, gruppe 10
Bilag ●
Hum­Tek Bachelor foråret 2015 Has visual ethnography ever been used to research in researchers methods? Do you find this approach to be usable? ­­­­­­­­­­­­­ Version 2 Brief introduction of your self; name, occupation ect. ●
What is a researcher supposed to know before working with visual ethnography, and are there specific pieces of equipment that you use rapidly in your own projects? ●
Do you think in storytelling when doing visual ethnography, and how do you work with this aspect ­ for example with a traditional way of storytelling on film like the three­act­structure model? ●
Planning of Visual Ethnography ○
How much thought goes into “framing”, “lighting”, “composition” and other film­technics? ○
How important is storyboarding? ○
What is your role out in field; for instance, when do you observe and when do you interact and what is “important” to film? ●
What are the some of the most typical errors and mistakes that researchers do when performing visual ethnography? ●
How do you catch the interest of the viewers of your films? ●
Who are the viewers (audience) of your film? ●
Where do you feel that these films are supposed to be distributed? ●
How will the future look like for visual ethnography? Praktiske ting vedrørende interview Location: CBIT? Udstyr: 550D, microport, lys Hvem interviewer: Dækbilleder: RUC, studerende Intelligent Lufthavn, gruppe 10
Bilag Hum­Tek Bachelor foråret 2015 Grafik: intro, subt Interviewguide Jonathan Moav
Skype kontakt: jonathanmoav Han har selv givet udtryk for at han hellere vil tale om Trumedia end at skrive om det (interviewmæssigt) ­­­Vi har skrevet følgende spørgsmål til ham Questions that interest us is: ­ What does face detection mean to you (Trumedia)? ­ What inspired this hybrid invention? ­ Have you heard of critique or complains from citizens concerning the new technology? ­ if yes, what matters and aspects have the interest of consumers? ­ What are the typical wishes and/or preferences from your costumers? ­ does the performance of the technology live up to expectations? Interviewguide Jesper Ryberg og Niels Christian Juul
­
Hvad er de nye reklameskærme med face detection­teknologi, der er ved at blive implementeret i Københavns Lufthavn, for dig? ­
Reklameskærmene med face detection­teknologi overholder persondatalovens § 28 og § 29, så det ikke kan betragtes som overvågning. Hvad mener du om dette? ­
Ved ens færden på nettet genereres data der bruges til at målrette reklamer til forbrugerne, hvor de nye reklameskærme målretter på hvem du er ud fra køn og alder. Hvilken forskel ligger der heri? ­
Hvilken adfærdsvirkende effekt vil det få på passagerne? ­
Hvor ser du at denne teknologi kan udvikle sig til? ­
Hvilket potentiale har den og hvad kan man forestille sig? Intelligent Lufthavn, gruppe 10
Bilag Hum­Tek Bachelor foråret 2015 Bilag 2 interviews
Jonathan Moav 1
Tidskoder er taget fra denne fil 20150512_001_interview_jonathanmoav.mp3 Hvad er Trumedia
00:08:40 – 00:09:07 Trumedia focuses on audience measurements, what are audience measurements? It is know who, I’ll call it if I am looking at it from a retail side, an airport can be retail, a store can be retail, a bank can be retail, any where that serves costumers 00:12:08 – 00:12:22 Extreme difference between the online in which we know everything and just push, push, push and we know that if we push the right thing we can better sell, to outside, the brick and mortar world where we don’t know much 00:12:26 ­00:12:56 This is where Trumedia is trying to fit in, coming in and saying know what there is a sign in a shopping mall or in the airport I will tell you that there are a lot of looking at it right now so maybe we should change advertisement to some good aftershave or something like that or for what ever reason there is a lot of women crossing next to that sign so let us put the new perfume by unknown privatliv/privacy
00:14:37­ 00:15:09 the issue of privacy, I mean you know all of us to day have smartphone and again I’ll take a smartphone as an extension of the online world, it is the online world, to day you walk into a store and you log into the Wi­Fi of the store and say ok I accept or give them some details basically they know who you are and they can, they know were you where, they know every moment of the time if your GPS on or you mobile you can be tracked every where. 00:15:28 – 00:15:55 the one thing that is very important to Trumedia is to say that the information, the information or the way we do it leaves the privacy issue out of it. I mean It is totally private … we are not invading the privacy of people we don’t know who you are. hvad kan systemet bruges til/hvordan virker systemet
00:09:40 – 00:10:03 I’ll start with the costumer… what the costumer wants to know if I knew more about my costumer or who my costumer is, it doesn’t have to be by name let’s say my costumer is man or woman maybe I could target my sales differently, because there is different needs for different genders” 00:10:22 – 00:11:10 that is one aspect of it knowing who your costumer is, again not knowing who as a person, that I am Jonathan or what ever but knowing who it is gives me Intelligent Lufthavn, gruppe 10
Bilag Hum­Tek Bachelor foråret 2015 better way to serve you, to provide you what you need another aspect to it … today if Google or look on the internet if you do a search you will see that probably five minutes later when you look at another website suddenly there will popup of advertisements of things you were searching ten minutes before, there all these cookies or whatever they have that knows exactly where I was, what I did what ,I was looking for and then just bombarding me with information 00:11:44 – 00:11:58 you know how much it costs 30 second advertisement on the super bowl in the US, it’s several millions, but do you know actually looking at it? Maybe everybody went to the toilet at that moment and nobody was looking at that advertisement 00:16:12 – 00:16:37 it is looking at your face deciding that’s, what is your gender, what is your age group and if you are looking at the screen it will tell me how long have you’ve been looking at the screen, but it does not know, there is no pictures saved it is not a pc, it does not save any pictures it a very, very important thing for retailers and customers 00:17:12 – 00:17:39 what Trumedia does is basically. It has a sensor which is a camera that is mounted either on the screen or you could put it any where you like, most recommended is to be somewhere the height of a person so it would be at eye level or little bit higher 00:17:47­ 00:18:35 it looks at the face then detects the face it is important to say we are doing face detection not recognition. Recognizing is saying I know you, I know you are Jonathan, I know you are John, or Mary or what ever. No I detect that there is face, I would say there two eyes, a face, a mouth and a nose, I detect that and then I start doing the internal analysis of capturing multiple frames, you know every picture is a, a video or a stream of video is build out of frames like snapshots, on your TV there is 25 I call it snapshots per every second of video 00:18:47 – 00:19:07 it captures each frame and it says ok a man, woman, man, woman, it makes decision, it capturing how long your are looking at the sensor keeps it, stores it and later on sends it central location 00:23:53 – 00:24:09 Gaze time basically means how have I been looking, I would say when the system detects both eyes, I am actually looking at the screen, dwell time will include the gaze time but also would the time that I am looking at my mobile phone or talking to the person behind me. 00:50:27 ­ 00:50:46 the system can do two things one it collects the data in the last, during my entire speech, that it collects the data, sends it, stores it, analyses it a long time, this is done I would call System sikkerhed
00:43:16 – 00:43:46 I would say this that there is not. I mean if you look at it this way, if you hack the box all you will see are encrypted files of about I would say 10k small files with lists Intelligent Lufthavn, gruppe 10
Bilag Hum­Tek Bachelor foråret 2015 of numbers that don’t mean anything, there is no faces there, it is not like it is saving snapshots of your faces so you can hack and see me, there is nothing there 00:45:42 ­ 00:45:56 this information is so irrelevant to somebody other than somebody who is using it for the specific need to know who is looking at the screen 00:47:06 – 00:47:14 no they (cameras) are connected via cable to the box and the box is sitting I don’t know five meters, three meters away Udvikling
00:32:37 – 00:32:49 one of the biggest problems at working with research and development in facedetection is having a database of faces, that I know what their age are, what their age is Minority Report
00:34:24 – 00:35:15 so there is a clip there I always us in my presentations…. The system that detects according to the eyes who you are so he implants eyes of I don’t know Japanese guy and then he walks on the street and suddenly the sign of the gap cloth store hello mr. yamamoto I hope the bathing suit you bought last week fits you well… all though future is in Hollywood it is not that far, where the advertisement will be totally personalized and they will know exactly who I am and what I purchased 01:00:01 – 01:00:52 I will say that this is a critical thing, it is very important, it’s critical that the system keeps the privacy of the people that are looking at it, and again the definition of privacy each of us can have a different definition, because again some people will tell you what they do on Facebook and twitter all the time, the definition of privacy are defined very well within the EU, with I don’t know, all these laws, they basically say that if you do not record or keep in a way snapshots or the faces or you do not have the information that can recreate the person Jonathan Moav 2
Relevante udpluk af Moav interview
brugt i “Artefaktets interne opbygning” samt kommende analyse af Moavs sociale konstruktioner “Call with jonathanmoav, Tue May 12 2015, 08:33:09.mp3” er brugt til tidskoder Intelligent Lufthavn, gruppe 10
Bilag Hum­Tek Bachelor foråret 2015 Trumedia business case ●
7m54 : Trumedia focuses on 'audience measurement' ●
8m45 : targeting sales for different genders ●
9m15 : goal of Trumedia : find a better way to 'serve' the customer ­ not to find out 'who the customer is' (as in his identity) diff. advertising ●
11m00 : extreme difference between online advertising and billboard­advertising ○
cost ○
response knowledge available ■
11m30 : this is where Trumedia wants to innovate privacy and data (social konstructions) ●
13m30 : privacy is very important ○
●
14m30 : Trumedia wants to leave the privacy issue 'out of it' ■
"it's totally private" ■
we don't invade the privacy of people ■
we only know if you’re a man or a woman ■
nothing is saved ■
no pictures are saved (!!) 15m05 : nothing is saved ­ basically it's taking a snapshot of your face.... not snapshot ­ snapshot is the wrong terminology. It's looking at your face.... deciding, what's your gender... what's your age group ●
15m20 : and if you're looking at a screen, it'll tell me how long have you been looking at the screen ●
15m25 : it's no pc ●
15m30 : @important ; it does not save any picture ­ it's a very very important thing... for retailers and for customers. Because if, if it was to save something, then it becomes a security system ­ then I have to put a sticker everywhere where it says: "please beware that you are being recorded" ... or that "you are being monitored" ­ and that's not what we wanna do in advertisement. ○
16m00 : @important; ­> it looses the purpose of advertisement ­ I mean, [the sticker] keeps people away from [the advertisement].. that's a very important point ●
16m10 : @camera; "what Trumedia does is basically... eeehm.. aa it has a sensor; which is a camera... that is eeeeh, mounted either on the screen, or you could put it anywhere you like ...." Intelligent Lufthavn, gruppe 10
Bilag ○
Hum­Tek Bachelor foråret 2015 16m40 : and it's there connected to the Trumedia device ... ahhhm video is captured ­ or not video is captured .. eh it looks at the face ­ then detects a face .. it detects, it's important to say the we are doing face­detection not ­recognition; recognizing is saying "I know you..." ○
17m10 : then I start doing the internal analysis ... of capturing multiple frames .. you know every picture is eeh .. or every video .. or stream of video ­ is built out of frames, like snapshots.. ○
17m40 : so it catches each frame, and it says okay ­ a man, woman, man, woman; makes a decision, it's capturing how long you're looking at the eeehm.. sensor.. keeps it... stores it... and later on it sends it to some central location ○
18m30 @no_tracking_after_out_of_frame : "now if you'll appear [in front of the camera] half an hour later, I will not know that it is the same person" ●
20m10 @object_tracking_in_frame : "you decide to tie your shoe, but you're still in the area ­ the system will continue and track you, and I will know it was you [when you look up again]" analysing factors ●
22m35 : ○
@dwell_time : will include the gaze_time, but also time spent ​
not ​
looking at screen ○
@gaze_time : how long have you been looking at the screen (while in frame) ○
24m10 : the ratio between gaze and dwell time they use as a measure of how interesting the ad were : the rating of the ad ●
31m00 : I: would the technology become more complex in the future? JM : "yes" ●
32m50 : "to be honest I would think that in, I don't know how many years, [...] you will go into every place, and it will detect who you are exactly" ○
●
33m15 : minority report like the future he imagines 34m50 .. : ○
da Moav blev spurgt om hans personlige holdning til Minority reports dystopiske univers, så satte han sig generelt i en position af modstand, med mindre folk følte sig villige til at lade sig identificere overalt. ●
36m30 : "that's why I like Trumedia ­ it says, 'okay I don't know who you are ­ I know what ​
you are, and I will try to provide you with something to fit you with" security of the system ●
42m20 : "if he would hack the box ­ all he will see are encrypted files of about 10k [bytes]... small files, with little numbers" Intelligent Lufthavn, gruppe 10
Bilag ○
Hum­Tek Bachelor foråret 2015 @comment; the data is saved on "the box" where the screens send their data to, to get analyzed ●
43m40 : "[the box] is an embedded device that has it's own software on a chip [...] there is no way to access it [...] and even if you hacked it, it's encrypted, and there is nothing there" ●
45m30 : "all I want to know is when are people passing by, and what is their demographic, in order to be able to (a.) know how to sell my advertisement to the advertiser [...]" ●
46m55 : "[the box] is even not communicating [(for safety)], it's dropping something, and somebody is picking it up ­ in order not to have a connection so that somebody can 'tap' it.. in a way" system structure ●
46m : "[the camera] is connected with a cable to 'the box', and is sitting like [...] 5­3 meters away" ●
46m20 : "the box is doing all the analysis ­ and then what comes out, I would say, out of 'the other end' [of the box], would be through some kind of secure line, will be this small file, with this minimal information that I mentioned earlier" ●
48m10 : "the information [from the box] goes to some central database, in which it is analyzed, converted to something I call 'readable' ­ and then the customer can get his information, and have his reports [...] and it will show something like 'so and so people where doing this at those hours'," ○
and he continues to talk about reports also showing the gender percentages, average age etc. pr time ­ ○
48m47: "and you will get distribution along time, so they will have access to some reporting system, within the airport security or whereever, that will allow them to see the information in a way where they will understand the results" ●
49m20 : "the system can do two things: one, collect the data which I mentioned [...] ­ this is done in one stream or pass, ​
but ​
there is another, I would call it stream or pass, in which [...] I call it a small pc or a small player which has an hdmi port, or a streamer[...] there is an application somewhere where somebody drags and drops clips ​
or ​
[the Trumedia way] which is done locally between the player which is behind the screen, and the Trumedia device [(the box)], which is, I don't know probabley 1m away [...]. The player can, I would say, ask Trumedia 'tell me, who's in front of, give me a snapshot right now of the situation (not a physical snapshot), but give me a status of what is happening right now... and then the Trumedia device will say ­ at this moment I see three people, two men and one woman, and then the player [...] it can say [...] 'to this audience I would like to play this advertisement'" Intelligent Lufthavn, gruppe 10
Bilag ○
Hum­Tek Bachelor foråret 2015 51m15 : "then the ad has played for 30 sec's, then again the ​
asks ​
Trumedia 'who is there right now'[...]" ○
51m30 : this is done at the local level ­ the information does not go out ●
53m : it's not Trumedia who controls the 'player' ­ it's some other firm ●
56m : they do not [(the Content Management Firm)] need the data, all they need to do is react to what the system tells them ­ they don't have the data" ○
57m12 : "all they need to know is just a snapshot of what's happening right now" ●
58m00 : the system would not allow you to ask every second for a snapshot ●
59m50 : Jonathan Moav defines 'not privacy' as if it were possible to 'recreate the face' (pixels of the face) from the data ●
1h30 : I do face detection not face recognition ●
1h52 : "I don't want to know who you are" ●
1h4m10 : Trumedia doesn't save frames in temporary files ­ they work on realtime data (in the 'box') data analysis ●
1h10m40 : [right now] we are enabling the customers to additional [...] surrounding information ○
●
(not implemented yet) 1h16 : we don't connect the demographic from one camera to another, right now surveillance ●
1h18m40 : do you know how many cameras [in the airport] that are looking at you and collocting your information? .. and another camera that is looking at you and not collecting anything ­ you have to put things into perspective ●
1h19m50 : [comparatively to other surveillance] this is mega­privacy ●
1h20m40 : we will follow the rules/laws of privacy ●
1h2120 : anonymity is part of the way we [Trumedia] work Niels chr juul interview
Overvågningsteknologier/overvågning MVI_9385 00:03:28 ­ 00:03:59. Hvis det er implementeret smart, så opdager de det ikke (passagerne). Det betyder ikke noget for folk, de bliver i forvejen overvåget i Kastrup Lufthavn. Deres mobil og bærbar bliver tracket, og får dem til gaten, så man bruger i forvejen en masse overvågningsteknologi i lufthavnen. Intelligent Lufthavn, gruppe 10
Bilag Hum­Tek Bachelor foråret 2015 MVI_9385 00:10:13 ­ 00:12:16 Det er ikke specielt nyt (face detection). Ses i andre lande. Overvågningskamerarer. Fx med hooligans, hvor man kan pille dem ud til en Brøndby­FCK kamp. MVI_9386 00:00:06 ­ 00:00:20 Lufthavnen er jo sådan et meget nedskaleret, de vil jo kun kigge på køn og alder. Jeg havde hørt at man vil gøre sådan, at reklamerne vil følge den enkelte person. MVI_9386 00:01:40 ­ 00:01:51 Det er jo ikke anderledes end Google og Facebook, der overvåger vores internet­vaner. betydning MVI_9385 00:08:02 ­ 00:09:40 Al teknologi er blevet brugt og misbrugt. Manhatten­projektet. Udnyttelse af atomkraft og atom brintbombe. Store menneskelige konsekvenser. Teknologien er der jo "bare", så skal vi lade være med at opfinde den, den næste generations teknologi, fordi nogle vil misbruge den? Der er vel ikke en ondskabsfuld anvendelse indbygget i al teknologi. MVI_9386 00:02:20 ­ 00:02:45 Det er jo ikke anderledes end Google og Facebook, der overvåger vores internet­vaner. MVI_9386 00:00:43 ­ 00:01:15 Selvfølgelig, det kan det sagtens (reklame til den enkelte). Spørgsmålet er om det er hensigtsmæssigt, giver det mere bad will end good will. MVI_9386 00:05:35 ­ 00:06:22 Igen, den måde i beskriver face detection på, hvor de finder ud af noget med køn og alder, så er det ligeså diskret som de første Google ads. Mange siger også bare fint, så får jeg relevante reklamer i stedet for de ikke så relevante. Det er da en god tjeneste ved at gøre det her. Og det er da personaliseret og her snakker vi om noget der kun er stereotypiseret ud fra køn og alder. Det ville jeg da stille spørgsmålstegn ved om er nok til segmentering. MVI_9386 00:06:25 ­ 00:07:15 Nogle af de ting man også detekterer er race, ved at stereotype en fra Asien, som måske kan være adopteret og boet i DK hele sit liv. Så vil der være nogen der ikke "overholder" denne stereotyp­regel. MVI_9386 00:08:22 ­ 00:08:55 Det er vel det samme som det vi oplevede med Google (hvad skærmene med face detection er). Det er bare taget ud i den fysiske verden, som vi i Intelligent Lufthavn, gruppe 10
Bilag Hum­Tek Bachelor foråret 2015 forvejen oplever i den virtuelle vderden. Nogle gange bliver folk provokerer og andre gange tænker de, det er sgu da meget rart. Teknologi som lege kammerat MVI_9386 00:09:03 ­ 00:09:30 Jeg er jo nok så nysgerrig, hvad har de sat teknologien til at kunne og ikke at kunne. Jeg vil prøve at drille den. Kan jeg smile, kan jeg prøve at lave om på mit ansigt, kan jeg holde hånden op for mit ansigt. Få teknologien til at tilte en gang. MVI_9386 00:10:17 ­ 00:10:25 Det er jo bare fordi jeg er interesseret i teknologien, så vil jeg altid prøve at se hvad de har sat den op til, hvad kan den og hvad gør den ikke. tracking MVI_9385 00:03:28 ­ 00:03:59. Hvis det er implementeret smart, så opdager de det ikke (passagerne). Det betyder ikke noget for folk, de bliver i forvejen overvåget i Kastrup Lufthavn. Deres mobil og bærbar bliver tracket, og får dem til gaten, så man bruger i forvejen en masse overvågningsteknologi i lufthavnen. MVI_9386 00:02:58 ­ 00:04:40 Etablering i taxfree­område. Lovgivning. Beskyttelsesregler, EU, amerikansk..? Hvad gælder lovgivningsmæssigt? Ikke det samme som på "ambassade­grund". teknologiens misbrug MVI_9385 00:08:02 ­ 00:09:40 Al teknologi er blevet brugt og misbrugt. Manhatten­projektet. Udnyttelse af atomkraft og atom brintbombe. Store menneskelige konsekvenser. Teknologien er der jo "bare", så skal vi lade være med at opfinde den, den næste generations teknologi, fordi nogle vil misbruge den? Der er vel ikke en ondskabsfuld anvendelse indbygget i al teknologi. Bilag 3 Plantegning
Intelligent Lufthavn, gruppe 10
Bilag Hum­Tek Bachelor foråret 2015