Episode 3: Personal Identity & Data

0:01Hello and welcome to episode number three of the What So What Now What podcast.

0:05Ravi, how are you today?

0:07I'm good, thank you.

0:08Yeah, not doing too badly myself.

0:10And how are you?

0:10How's the uh the beast from the east treating you

0:14I think it's just about left the UK.

0:16Uh for those of you uh not familiar with the beast from the east, it's uh a Siberian weather storm that basically

0:22visited the United Kingdom it thought it needed to come and visit our lonely island.

0:26So we've been pretty much snowed in.

0:28But it's funny, 'cause in the UK when there's snow

0:30we run around in like hysterics, whereas most other European countries are like, hmm, yeah, whatever.

0:35Exactly.

0:36And I I I think I was quite lucky in that I escaped for this uh for this two week period.

0:40So I'm back over in the US for two weeks

0:44uh in New Jersey.

0:45So I've completely um missed the snowstorm and the snow ends and the travel chaos that's been going on.

0:53You'll come back to uh what should actually be a spring rather than like a deep winter.

0:58Yeah, exactly.

1:01Good stuff.

1:01Um today's the fifth of March and today's episode we're basically talking about personal identity.

1:07and data.

1:08But before we do that, we thought it'd be a good idea just to catch up on what we've been up to.

1:12It's been a little while since our last podcast and um that's been because we've been busy.

1:16So Ravi, what have you been up to?

1:18Yeah, so since the last pod, I think the biggest thing that I've been up to is well I went to the OptoFro Forum.

1:23So those of you that don't know what the OptoFroPro Forum is, Opto is a sports data company.

1:28And I've attended their forum for the last three years now.

1:31So this was my third forum.

1:33Um it's really good fun.

1:35So it's basically where um

1:37They promise a lot of uh football soccer uh analysts and coaches and scouts and things from clubs themselves, uh as well as people from the uh the blogging community.

1:48So this is

1:49Um my journey into Tableau was through sort um using public sports data and visiting them uh as well as doing a bit of blogging on them.

1:57So um yeah, I I've submitted a proposal for the last couple of years as well.

2:02Um but it's one of my favorite times of the year because you get to foot not only meet the people that

2:06I interacted with the sports analytics side on Twitter, but also seeing what's happening within clubs themselves.

2:13So it was really good fun this year, some really interesting ideas.

2:16And yeah, it was good fun to catch up with some people

2:19Uh they did they change the format a bit this year.

2:21They had a QA session with Devin Pula, who's um he's director of analytics at Toronto FC, who uh they won the MLS Cup this year.

2:30So MS Cup is like the big

2:32US soccer trophy that you can win.

2:35Um and they also had Luke Bourne who's who who's famously actually gone on Twitter rants about how

2:42Dayviz in sport is generally a bit bad and it's never really thought through properly.

2:47Um he has a personal vendetta against ver radars, for example.

2:51Um

2:52I mean it makes sense, right?

2:53Because if a radio chart isn't contextualized properly, it's just a shape as a polygon, right?

2:58Um everyone loves radar charts from FIFA, right?

3:01Exactly, it's FIFA, right?

3:02It's it's that sort of you you you always correlate radar charts with sports and I think uh I personally like them because

3:10If you've contextualized and explained what properly exactly what your a what each area being filled means, then it's useful and you can quickly compare different polygons.

3:20But if you're looking for more values, then absolutely not it's not the right chart choice.

3:24But yeah, it was good fun.

3:25I enjoyed it.

3:26Um great chatting with people at um clubs and things like this, and we're slowly seeing more advanced statistics in uh the European game, for example, expected goals on match of the day now.

3:38is the uh go-to quick win for the analytics community.

3:41So it's good fun.

3:42Good stuff.

3:43So sports analytics all the way there.

3:44That's fascinating.

3:46Um I've personally been uh I've been

3:49I guess being more bunkered down.

3:51I went to uh the Tableau Train the Trainer course um just over a week ago now.

3:56So I spent a week over at the Tableau London HQ and um essentially spent some time with them learning how to be a better trainer uh

4:04specifically for Tableau, but I think much of what I learnt was actually transferable across um, you know, pretty much all training.

4:10And actually speaks back to the episode where we talked about learning and you know the the ask I had for people

4:16Who teach other people to kind of you know help them along rather than just you know offer solutions for them.

4:21And uh it was really it was really interesting.

4:23There was about 10 of us there um from lots of um you know different companies uh in Europe

4:28And in fact, I think I was the only English um uh person in the class, uh which which is which is quite rare.

4:34Normally train the train is full of a lot of uh sort of London folk.

4:37So um yeah, as

4:39It was really interesting to see the different cultures.

4:41One thing I never really had appreciation of is the way different cultures um perceive and understand training.

4:49And it's really fascinating how that then sort of changes the learning experience for those for those people.

4:55And then how you as a trainer have to sort of not necessarily compensate

4:59but actually work with some of those strengths and benefits to make it sort of you know meet your uh meet your needs so that that was that was a really good experience

5:08That was uh just over a week ago.

5:11And more recently I've actually had a bit of time off.

5:13Um so I've been taking sort of sporadic time off.

5:16The beast for me's ruined my staycation plans, so uh I was meant to go away.

5:22for four days and that that didn't happen so um uh today I'm still off and all I've been doing is plowing time into Zelda on the Nintendo Switch so Amazing.

5:32Yeah the the Switch is definitely a piece of kit that I'm I'm really tempted to get into 'cause

5:37It's just really nice to have something portable as well as a console that you can put on your TV.

5:43I don't know how you what what your what are your thoughts on it?

5:45Oh it's it's sensational.

5:47Um this is not gonna be a Zelda or Nintendo Switch podcast.

5:50It can very easily turn into that.

5:52So yeah, that's that's all I'll say for now.

5:55It's a sensational console.

5:56I massively underestimated

5:59the flexibility it has three modes essentially you can either dock it to your TV and that you play through your TV you can um it has a kickstand so you can just um put the screen on a table

6:11Put the standout so it stands on its own and then you can use the controllers and almost play in like a shared experience.

6:17Or you can put the controllers into the switch itself and hold it like a traditional Game Boy.

6:21That's probably what most people are familiar with

6:23And it's amazing just being able to switch those modes, um, as and when.

6:28And it just means you can play the console for longer because when you're at home it's in the T V.

6:32When you're on the go, it's in your hand.

6:33When you're you know lunchtime and you're with colleagues, it's on the table.

6:37And it's it just fits so many use cases.

6:39I'm playing a very solo um game at the moment, Zelda

6:43But um I played Mario Kart and uh with a couple of people and it's it's amazing.

6:48Like and I didn't think you could have that kind of engagement with people through a console in that way.

6:53So yeah, hands off the Nintendo.

6:57Yeah, exactly, exactly.

6:58And the funny thing is you think the graphics are awful.

7:01Actually, you know, the game design is really good and it's gone to the point where I think

7:07You don't pay attention to the graphics because the game quality is that good and it's that high.

7:11It's got that Nintendo feel to it.

7:13So everything about it is just it's just really, really good.

7:17I love it.

7:18Good stuff.

7:19So um going back to our topic today, personal identity and data.

7:23So what what's the what today?

7:25What is our what is the qu like sort of what side of our podcast?

7:29Okay, so this is a topic that I've been massively interested in for I don't know how long, um largely because I'm a big uh quantified self sort of addict

7:40Uh quantified self just basically means you collect data about yourself um with a view of helping uh improve a certain aspect of your life, but sometimes you don't necessarily have to do that.

7:50You could collect it and you know improve your life many years later when something starts to change in you.

7:55life right so it's also about future historical and and the present and I wanted to sort of you know take a step back and look at how technology and data and

8:07and personal identity and data.

8:09A sort of um this really sort of busy playground of discussion at the moment where everything seems to be centered around it

8:18And I I guess the what's of this is kind of can be broken down into three areas.

8:23Firstly, you know, what's collected about you.

8:26Right?

8:26What do people know?

8:27What do companies know?

8:28What can people find out about you just using data that you yourself have created?

8:33The second is how much do you know?

8:35Like what do you know about yourself that is out there

8:38Uh and the last thing is no, does it bother you?

8:42So th those so that it's kind of like a complex topic because there's three what's in there, but they all sort of link into each other.

8:48So I I I don't know your thoughts so far

8:50Yeah it's it's sort of a nexus of what, right?

8:52So we're looking at these three different aspects that interlinked and it funnels down to you as an individual, but then at a meta level that that information about the individual individual is exactly what we're talking about

9:03Um yeah, so it it's it's interesting because I'm me m myself and my family are fairly uh we don't like

9:12We we we we like our privacy, right?

9:14Like w we've always been um advocates of keep my data to myself unless absolutely necessary.

9:20And it's sort of something that's sort of uh I guess um imprinted upon me as I've grown older.

9:25So I'm very conscious of all the different ways of collecting today, some some of the passive and some of the active levels, right?

9:33Um and I think

9:34That that sort of what's collected about you and how much you know, those are two very strong factors.

9:40And I think this is where the sort of wider discussion comes into place because I think people don't

9:45Either they don't realize or they feel like they're not explicitly told when data is being collected about them.

9:51When in reality, I I'm almost at the stage of my life where I'm thinking, uh

9:57you know all I just know all data is collected about me.

10:01Like I mean I I just I just accept that and then I

10:05Want to then make an active movement to say I wanna shut off this panel or restrict this panel.

10:12Like the

10:13the streams of data I'm giving out, I c I feel like now I know that everything can be and is being like monitored or collected, I feel like I can turn those taps slightly.

10:23But of course I don't think that taps ever fully ever gonna turn off because

10:27You know, th unless you become a hermit, um, there's there's not really much much likelihood of you disappearing off the face of the earth.

10:34Everyone has a data imprint now.

10:37Exactly, and um it's it's interesting what you say.

10:40I mean I have a very similar stance and I'm probably more liberal than most.

10:45I'm actually a proponent for having your data in services

10:49Um because and this is the big but and this is the big because if those companies can offer you better services and better um sort of

11:00uh I guess uh packages of of of stuff that they can offer you.

11:03Maybe it's Facebook and they want to offer you a way to connect with your friends or maybe it's Apple and they want to offer you um an iCloud storage solution so you can keep all your photos

11:12on in the cloud rather than on your phone to free up some space.

11:16If those things are targeted and work in a way that actually enhance your life and an important bit

11:22you're more than happy to offer your privacy as an exchange to access those things.

11:28I don't have a problem with with that particular sort of way of thinking.

11:32And the reason is this

11:34Um before these social uh networks um existed, before these services existed, I mean I don't even I don't even people can remember what was like what life was like.

11:43Um before Google

11:45Exactly.

11:46Like we as a society have opted into this way of working because it offers such epic amounts and convenience and capability to us.

11:55that we've just sort of taken for granted that all of this, all of this has to be somehow um resourced and somehow built and somehow created.

12:03Now that doesn't mean that you know companies can cross the line

12:06But I do think where there's a healthy balance between, okay, Company X, I will give you this information if you can offer me this kind of service.

12:15The best example I can give is Google Photos.

12:18Now that thing is just sensational.

12:21This might even become an advert for Google Faders if I'm not careful.

12:26It it you know, three years ago they started by saying, Hey, um, hey everyone, have unlimited uh photo storage and initially I was like, whoa there, easy now.

12:35What are you gonna start doing?

12:36You're gonna start looking at my photos and then look at this, but the offer was this, you know.

12:40Put your photos into the cloud.

12:42In a few months we'll start telling you interesting things about what's in your photos.

12:46We'll start editing it for you.

12:47We'll start making albums for you.

12:49We'll also start making it easy for you to search.

12:51We'll start putting together memories of your holidays

12:54And I have something like 80,000 photos and videos, okay?

12:58And for me, that's a sensational, that's a sensational offering.

13:03So, you know, as soon as that came out, I spent I think the best part of three weeks uploading all my stuff onto Google.

13:10And then two weeks later, it it just completely revolutionized my photo album

13:15There's no way on earth I could have done anything close to what Google has done so far with my photo management and organization.

13:22And better yet, they keep adding functionality and features to it

13:26How does this help Google?

13:27It trains their AI so that they can look at pretty much any photo or video and so they can make sense of things.

13:34They can probably build like a 3D visual map of the world using everyone's photo

13:39Okay.

13:39Now am I bothered by that?

13:41Not so much because guess what?

13:42I love Google Street View when I when I'm going somewhere and I I have no clue where it is.

13:48Now, if I happen to be in that Google Street View video and they've forgotten to mask up my face, do I care?

13:53Yes.

13:54And so there needs to be this balance of like, you know, benefit for the user, but also, you know, being careful about infringing on

14:01people's privacy and so what people don't often do is find out ways they can a control you know certain aspects of what you know these companies can and can't do with their data

14:11But then there's this other aspect which is people don't do a good enough job of actually critiquing privacy properly.

14:17Um that you know, they critique the wrong things.

14:20And we'll come to this a bit later in the so what.

14:23But you know that that that's my general stance.

14:25As long as a company can offer me a genuinely meaningful benefit

14:29For me to give them their data, I will do it.

14:31Because to me, I used to pay for photo management services.

14:33I used to pay £30, £40 a month, and none of them can do what Google's doing with my photos today.

14:39Mm-hmm.

14:40And I think and I think the the nicest the easiest way to explain Google like as a business model um

14:47Is that that that's that's your payment like you you you're you've got this service that allows you to access and index every single every single website on the internet, every single image

14:57you know, a as a start of what Google does, as a crux of what Google started off being and now it's sort of grown into this massive beast.

15:04But if we think about Google in that sort of way as

15:08we ha are using its service to find far reaching parts of the internet, then actually the trade-off there is you're paying them in your privacy data.

15:16You're paying them by saying

15:18I am using this this internet in this web browser uh at this time searching this certain thing.

15:24It's linked up I'm signed in on my um my email account so now you have an idea of who I am and

15:30what my emails are and I'm I'm building this profile that they can use to either be smarter about what such returns

15:38Mm-hmm.

15:38Or be offered that as a service saying that, okay, uh if to to a company they set you know doing SEO for like you were looking for smarter search engine optimization.

15:48they can say, well, uh how about we help you target, you know, the twenty twenty to twenty-eight year old um person looking for um information about data visualization.

15:58uh on a regular basis during his work day.

16:01That's who we'll target and within the first page results your website will will appear.

16:05Like that's that's the trade-off that exists.

16:07And

16:07That that is is exactly it.

16:09This sort of thing, if you're aware of that transaction and it's okay, fine.

16:14Like that that's that's okay, you're happy with that.

16:17But it's when they're saying, Well, actually, we point you out as a twenty-two year old um Asian uh person of Asian ho heritage

16:26who went to university in Plymouth and works in London and works for all these different clients because we can see you on the different networks, then it gets a bit tricky, right?

16:34Then it gets a bit of like, well actually you know exactly who I am and where I am.

16:38So uh Exactly.

16:40And some of that and some of that comes down to ethics, right?

16:43Like um what are the ethics of this company?

16:45And it it's funny because uh a good comparison point, uh I'm just gonna use Google as the big bad evil

16:51you know, person in this in this story and I'm gonna um people would expect this of me, but I'm gonna use Apple as a as maybe a more ethical player here.

17:01We're all laughing 'cause I I'm a big Apple fan, so uh of course I pitch Google as the

17:06Evil one and Apple is a bad one.

17:08But where I'm going with this is this.

17:13um line of um you know privacy is so important to us and it's so so fundamental to the way we work that we're never gonna infringe on your privacy.

17:22So much so that we're gonna build AI.

17:25So instead of matching your photos in the cloud, we're gonna match them on your actual phone.

17:29So nothing ever goes to the cloud, right?

17:31Okay, sounds like a great story

17:33And then they were like, oh yes, um w you know, you know when you're typing messages and new words come up all the time and wouldn't it be great if we were to correct

17:41pick these up, I know we'll invent something called differential privacy where we'll basically create so much noise that our computers won't know that it's actually you talking to us.

17:49And then when we get the information back, um, it'll be great because we'll then be able to see all these words and then do all this stuff.

17:56And guess where that's going?

17:58Absolutely nowhere

17:59Like on my phone, on my phone, photos is awful.

18:03I mean I'm I'm a big Apple fan, but my god, the worst thing on my handset.

18:08is the way it ha handles photos.

18:10It takes days to like find three people in photos.

18:15It can't do face recognition uh to save its life.

18:18You have to it has to do it overnight.

18:19It uses your battery if you if you if you don't if you don't leave it doing right.

18:24It uh it doesn't synchronize faces between your Mac and your iPhone, so

18:28your two devices will both be doing the same analysis at the same time and none of them will talk to each other.

18:34It's like it's like what's going on here?

18:36And this is the funniest thing

18:38Uh you take Google's approach where everything is done in the cloud, it means they can update it frequently at all the time, right?

18:44And you know, I see the benefits of that.

18:46At scale, exactly.

18:47Apple, if there's a problem wrong with say, oh, there's this character that, you know, makes our iPhone crashes.

18:52They have to send out an update, like an iOS update to fix an AI issue.

18:58Because because they don't do anything in the cloud.

19:00And that that it that to me is just

19:03Like, you know, I I get the point about privacy, but there's an a really good example where it just doesn't work.

19:09And so, you know, you again, I'm going back to this point about balance.

19:13There has to be a healthy balance between the two.

19:16And

19:17We're kind of getting into the so what's now and we're gonna I'm gonna I'm gonna use Facebook as a really bad example of you know where a company really has crossed the line.

19:26Um, Facebook used to be a platform where there were no photos.

19:30Do you remember those days?

19:31No, no.

19:32I mean I I got Facebook in two thousand nine.

19:34So man, I joined Facebook.

19:37I was uh the second uh York I think was the second or the third university in the UK to get Facebook.

19:44Did you join Facebook?

19:46Did you join Facebook?

19:48Sorry, go on.

19:48Yeah, did you have to like um give your dot ac dot uk thing like you know in Yes.

19:53Oh wow that that's how old school I am man Wow.

19:58I joined Facebook with my exactly with my university email.

20:02And not only that, I had to wait for an invite when I got in I could invite ten people and it was crazy.

20:08It literally took over uh communication online campus and it happened right at the beginning of our university uh year, 2006 when I started, right?

20:16So

20:16And then three months later, they introduced status updates.

20:20Because before all you could do was just be like, hey, I'm Tim, here's my profile, and you can just look at profiles.

20:25Then they introduced like a status update.

20:27I enjoyed that status up that used to be Tim and Graner is whatever.

20:32And it's like people people followed that state same um like process.

20:36And when I joined, I was like, why is everyone doing this?

20:38It's so weird

20:39It's actually and eventually they hit the they hit the nail on the head with photos, right?

20:46You can upload photos.

20:48Now they've been collecting everyone's photos.

20:51Most people, I think 90% of people, if you ask them where do they keep their photos, they'll say Facebook.

20:57Okay, not on their phones, not on a USB drive, not an external hard drive.

21:00They'll just say, oh yeah, I uploaded them to Facebook.

21:03Now, over the last decade, Facebook's

21:07Photo recognition capabilities and photo management capabilities have gone exponential.

21:12No no least because they acquired Instagram

21:15Like the world's biggest photo platform.

21:17But what they've been doing in the background is they've been building facial recognition software into this.

21:23And the thing is that facial recognition software has the ability to go back in time and look at stuff you uploaded a decade ago, right?

21:31So something really scary happened to me and I I was really quite uh partly offended, but basically what Facebook did is it realized that I tagged certain people in my albums a lot

21:42And it was using those tags because we all spent time tagging people, right?

21:46As a way of training the the facial recognition algorithm.

21:49And then I uploaded a photo.

21:52of those people about you know five six seven years later because I I stopped using photos uh on Facebook I uploaded a photo and it automatically said hey is this this person is this this person

22:03Is this this person?

22:04And I was like, uh, I didn't ask it to do this.

22:07I like I didn't I didn't ask it to go through and look at these photos.

22:10And I was like, how does it know who these people are?

22:12So I had a little quick Google

22:14And it turns out that in the back end, Facebook is not only doing this and offering you the capability, it's actually doing face recognition all the time anyway.

22:23So even if I don't tag you or you don't uh expli explicitly give yourself the permission to be tagged, it's still tagging you anyway and it's keeping that somewhere.

22:32Just in case you decide to join, upload a photo and it can go to you, hey, hey, hey, hey, are these 20 photos of you will help you build a photo album and help you choose a profile photo

22:42And that I believe is crossing the line because you should be given the explicit uh you know ask, do you want to be tagged on Facebook?

22:51Or do you want me to tag and look at these photos?

22:54I'm not just uploading content for my own benefit and yes, I'm uploading it onto their service.

22:58But just a simple ask would help that ethical sort of line be a little bit less fuzzy.

23:04Yeah, I agree.

23:04I mean I I've been on Facebook for a good good chunk of years now.

23:08I I had it for a coup of a couple of years and then I left it.

23:10Um and

23:12Since then I it's it's taken a massive nosedive, right?

23:15Because there's so much going on in terms of how they use your data in your profile and how they optimize your feed.

23:21Like all these you've s read the news article that how Facebook have used, you know, your um

23:26your emotion y they've tried to see if they can alter your emotions by structuring your feelings in such a way where to see if you're happy or sad but and you know in the terms and conditions which no one obviously reads

23:37Um it says that they give they're able to do this.

23:39Like it's absolutely fine for them to run psychological experiments.

23:43Now talking again about photos, one of the one of I wrote a really interesting article about um a Tinder recently

23:49So Tinder, the dating app.

23:51So if you connect your Instagram to your Tinder, what Tinder will do is it will analyse all of your pictures.

23:59and then put you in touch with someone who has been to similar places as you.

24:03So if you've taken a picture in Times Square, uh it will find you someone and ma like try to match you with someone who's also been to Times Square or like if you've been to Rome recently.

24:13They will see that oh this person was a roam for the last two weeks.

24:16How about let's let's, you know, give them pictures of this and it's it's fascinating, right?

24:21It's it's one of these things where you're like

24:23This is really, really, really optimizing it.

24:26Because Tinder started off as you're here, someone's like five meters away, you're in slight left, slight right.

24:34Whereas now it's like

24:35Okay, let's be smart about this.

24:36Like give let's give you something to talk about off the bat, like where you don't have to read their profile or whatever.

24:42So it's fascinating.

24:43I I mean I wonder this is a massive side note, but

24:46That the uh th there are loads of academic papers about um an analytics on Twit and Tinder.

24:51And it's it is fascinating.

24:53Like people have done analysis on when people's propensity to swipe based on their location.

24:58based on what they w where they are at the time, if they're a hotel room where they're more more likely to swipe than if they're, you know, at their own home.

25:05Um and then also like a men versus women like

25:08women apparently swipe about twenty s twenty percent of the time whereas men swipe like sixty to eighty percent of the time.

25:14Like it's it's stuff like this and it's it's amazing to read because it's like this is they must have so much data

25:21um just fueling the the service that they can say, right, how can we make the smarter better, easier for our users?

25:28But I think this is a that's a maybe a good example of well, we're we're helping you, right?

25:32Like you've seen the dating adverts for like um

25:35uh at a match.

25:36com where they're like we we we don't just match you on your uh like five things you like we just match you on exactly who you are like as a person.

25:43Yeah the more information you give us the better we are feeding your

25:47the people that work for you.

25:49Um Ravy, you know the advert very well.

25:56Um

25:57Yeah, so you know it's it's that sort of thing which is a good trade off where you're saying, Well I'm giving myself to you as for the service and I'm getting something back

26:05Now another aspect to this is advertising, right?

26:09So advertising is probably one of the biggest uh benefactors of

26:15A lot of open data.

26:16So being able to do targeted advertising optimizes the cost of the advertiser and allegedly is better for the consumer as well because they're only seeing stuff that they're interested in

26:26And they're not, you know, um the the provider of the advert isn't wasting pixels or whatever.

26:31Now one of the most fascinating debates we have

26:35coming forward is um the the the sort of this paradox between the ad blockers and the ad block people.

26:43So like how how are ad blockers

26:46reacting to, you know, um ads, you know, ad companies saying, right, okay, um this portion of adverts are okay, but then we block all this sort of spam.

26:55And that that's happening, right?

26:56Like they're trying to find this not right balance of saying we can we can allow you to we'll allow consumers to see these adverts, but we'll block all of these adverts.

27:06And this conversation is ongoing between, you know, Adblock Plus and whatever you use on your browser and everyone else.

27:12And I think that's fascinating.

27:15Yeah, it's an interesting one because there's there's a n there's a recognition that you know uh and it goes back to the genesis of the internet.

27:22The internet was never meant to be monetized.

27:24Like the the whole point of the internet is just a network

27:27Yeah, and and and you know, markers and companies turned up and they said, Hmm, I wonder if we can make a living out of this.

27:34And newspapers are finding out, you know, the hard way that they can't

27:37So you know, uh like as soon as Google and the likes of, you know, Facebook and Google turned up and they took, you know, advertising eyes away from print and onto the digital

27:48or screen, you know, you know, these these companies sort of started really struggling.

27:53And to go back to your point, it's a very interesting balance because people understand that the internet works like this

28:00you know journalists you know content isn't made out of nothing even us on this podcast you know when we where I host where I host the podcast and the way the website is done you know that there is an economics around that and it's not free

28:13But the internet was built with this mantra and expectation that everything is free.

28:17That's why you can just go to any website without any sort of block and that's why net neutrality in America is

28:23It's causing so many waves because it's starting to break down that that barrier.

28:27And ad blockers are, you know, they're an interesting thing because

28:32the the the the the competition between marketeers versus ad blocking is getting really gruesome.

28:38It's like a it's like a hustle and tussle.

28:40One of the one of the smartest things I love about marketeers is their ingenuity to get around things like ad blocking.

28:47And I think two two year two, three years ago, this new concept called uh fingerprinting came into the for are you familiar with this?

28:57Yeah, yeah, yeah.

28:58So it basically creates that identity, right, and then it follows you around.

29:01Yeah.

29:01Exactly, exactly.

29:02So what what Magetears did for those who aren't familiar is that they said, okay, fine.

29:07You want to run ad blockers?

29:08Okay, no problem.

29:10We're not going to look at cookies.

29:12We're not going to do anything to do with that.

29:15All we're going to do is we're going to put maybe a pixel on this page.

29:19Or maybe, you know, the a like button like Facebook and Google does.

29:22Those like buttons are actually tracking uh entities that track where you go and they're on everything, right?

29:27So they're pretty much tracking you everywhere

29:30And what we're gonna do is we're gonna say we're not gonna even look at your IP address.

29:35What we're gonna say is if we look at your browser and the way your browser is set up.

29:40Okay, you're gonna have a certain combination of bookmarks, favorites, um uh font settings, window size, uh because your you know your screen has a specific dimensions

29:53Your IP might be localized within a certain geographic location.

29:58The three previous sites you might have visited might have been Facebook

30:02The Verge and uh Papoli.

30:04So therefore, we reckon with a one in a million chance accuracy that this is you, Tim.

30:10And guess what?

30:11It works.

30:12Yeah.

30:13And this is what they're doing now.

30:15They're not using cookies.

30:16They're not using all this other stuff.

30:18They're just using fingerprinting running in the background of so many websites.

30:22And a great resource for anyone who's curious of how brutal and well this this this mechanism works is um the I recommend an app for Google Chrome or any browser called Google

30:32Ghostary.

30:33Have you heard of this?

30:33Yeah, I use Ghost Ry.

30:35Yeah, so Ghostary is great because what it does is it surfaces and tells you which ad trackers are running on the page that you're currently on.

30:42And you go to something like I go to The Verge and I have ad ads enabled on The Verge because I love the website.

30:48They do great journalism, tech journalism, and I follow it.

30:51So I submit myself to the ads.

30:52And the ads are actually nice.

30:54They're not like awful

30:56But my god, the list of trackers is ridiculous.

31:01They have something like forty seven trackers on that page.

31:04And it's phenomenal.

31:05They're coming, you know, these are Google or Facebook, you know, the big you know, Twitter, all that kind of stuff.

31:10But then you have ad agencies and you know marketing agencies and that all goes into this sort of big pool of information that they then use to say, okay, this is Tim, so this is Ravi.

31:22So I I've just loaded up uh lifehacker.

31:24com and there are twenty-four trackers on here.

31:27Amazon Associates, Facebook Connect, Adsense, Google Analytics, Google, IMA, Publisher Tag, SafeRame.

31:34Mote, Nexus, Census, Quantcast, Rubicon, yeah, like twenty-four different trackers on this one side.

31:40This is the homepage as well.

31:41I've not even clicked on an article.

31:43And you're going there to hack your life.

31:44Exactly.

31:45And I'm like trying to figure out how to and it's funny because Lifehacker like Hi Lifehacker really did like they told me about Muta Mutoron, the one uh sorry not Mutoron, uh MuBlock

31:54the um the the the ad blocker I used um they told me about ghostry they c told me about HTTPS anywhere like these sites it's really ironic that these sites that tell you about all these things to get around are also doing the same thing

32:08You know, it's it's Yeah, so and a nice segue from there is if you've got so much passive tracking

32:18Is Google are Google and Facebook listening to me on my microphone?

32:21Like is my microphone always turned on?

32:24Oh my word.

32:25This this debate really uh angers me.

32:28Um

32:29Because I I I'll burst the myth right here, right now.

32:32Lots of people think that Facebook, uh Google is listening to them on their phone and their microphone, and they think that's why their battery dies really quickly.

32:40Um that is a huge myth.

32:41They don't do any such thing.

32:43What they do do is something even scary in my opinion, because you know what?

32:47If they listen to me and

32:49uh they got some information about me and then showed me adverts.

32:52I'd actually think, oh that's plausible, that's nice, because I have an Amazon Alexa in my house and it's always listening so that when I say hey Alexa, it's gonna fire up.

33:00Okay

33:01But the thing is, these companies are doing something much, much more scary.

33:06And I had a debate with a friend of mine, and I said to them, like, you know, you do realize that, you know, even if you weren't on Facebook

33:14they can they can still buy your data, they can still find out who you are and they can probably find out why you're not on Facebook and they probably target you with ads saying come on Facebook and then when you get on Facebook they'll be like okay you know this person has actually joined.

33:27Good work.

33:28Good work, Laver.

33:28Let's track this journey and now target if seventy thousand other people who are also not on Facebook with the same method, because we need now know this one works.

33:37Yeah, exactly, exactly.

33:38And here's the thing, uh a really simple example, and um lots of people don't think about this.

33:44They think, oh yes, you know, my bank data, my finances, all very nice, safe and secure.

33:50Wrong

33:51Those companies sell your data to guess what?

33:53Credit reference agencies.

33:55Credit reference agencies are in the business of letting other companies know

33:59the kind of people that are good to lend money to, good to do business with, and also just in the business of telling people about the kind of people exist in the world.

34:08Anyone who wants to buy it.

34:09Yeah, they sell that data and they you know they make a good attempt to de-anonymise it, but that's fine because if you're Facebook and Google and you've been tracking people for as long as you've been tracking them

34:21You can pretty much de-anonymize anything given the right amount of s data as a starting point.

34:27And the best analogy I can give is a puzzle.

34:30Okay.

34:31If I give you a puzzle and it has uh sorry if I give you pieces from a puzzle, let's say there are five pieces.

34:37Now two of those pieces are the top left and the top right corner.

34:41And one piece goes in the middle, right?

34:43You know this is a very small puzzle because by giving you the corners, I've already given you some perspective of like how big or small this puzzle is, right?

34:50Yeah

34:51Now, if I give you five pieces and none of them go together and there are no corners, you have no clue how big this puzzle is because you don't have enough information in there

35:00But imagine if you have enough bits of the puzzle, right?

35:04Because you've been on the internet and collecting data for so long.

35:07You can suddenly start even squinting and just guessing, ah yeah, this is a puzzle about X

35:13Or this is a puzzle about why.

35:15And without even looking at the whole picture, you can just go, oh yeah, Tim goes to this website.

35:19Oh yeah, he's a he's a 30-year-old male in this place.

35:22Okay, move on.

35:23And and and actually actually if you think about it, this is this is uh the the mind logical process of Tim and Gwena and you know that's nothing compared to a supercomputer.

35:31Exactly, yeah.

35:3220,000 different scenarios in 10 minutes, right?

35:35Like you'd be like, is it this one?

35:36No, let's go let's iterate through.

35:38And this is what machine learning actually means.

35:40Yeah, it's you can just figure it out until it gets it right

35:44Let me just sit there with my quantum computer and just uh let crunch a million records until I find you and then I'll move on to the next person.

35:54I think credit agencies is my it's my favorite example as well about you know the fact that every it everyone knows everything about you from your finance and spend data and who you are, where you're spending money and like your income, whatever, right

36:04Because finance companies, that's their role, right?

36:07That's their job to figure all that out.

36:09Um and if you then think about so i if anyone is interested in finding out what Xperia knows about you, search mosaic.

36:16So the the mosaic scores and codes uh what um Xperian have and do sell to other companies.

36:23Um I've worked with bits of this data before and it's like you can basically they have groups and it's like um

36:30It's as granular as this is a Caucasian middle um middle income family who have three cars and um

36:40two children.

36:41That like that's that's the level of like granularity goes to.

36:44It's like this is the profile of this person.

36:46Now now chuck in IP address data, chuck in

36:50um anything you might know about them as a person and you can probably say it's one of these families here.

36:55So this is this is who you are.

36:56And then you can just say, well that's enough for me to go forward and be like

36:59Just spam them, th it will stick with one, not two, so then you've got your person.

37:04So this is how it all works.

37:06It's super fascinating and scary at the same time.

37:08But I think this is where uh legislation at GDPR is gonna come into play because

37:13The the sort of path from A to B with this sort of crunch to find out who the person is, that's gonna be that's gonna have to be very, very restricted and controlled.

37:23So they're gonna have the people gonna have to have these people called data controllers

37:27in their companies who have to be aware of every single transaction of data going on both internally and externally.

37:34And it's funny because the the legislation is when it came out everyone was, ah yeah it's just European companies

37:39But if you read it, it's like, well, actually is anyone that provides an uh a service to s a citizen of Europe, which is b uh basically every global company ever.

37:48Yeah.

37:49It's like is there someone in uh Europe using Apple?

37:52Yes.

37:52Okay, Apple are liable.

37:54Is there someone who use Amazon?

37:55Yes.

37:55Amazon are liable.

37:56Like all of these big companies, they can't just move their headquarters and be like, oh we don't pay tax yet

38:00Like they will get stung by this and it's uh something crazy like um ten five to five or ten percent of revenue or twenty million euros, whichever's higher.

38:09So you're gonna get hit.

38:10Like if you don't pay a whole about how you're presenting your personal identifiable data, you're gonna get hit hard

38:17And and and I mean uh GDPR is is interesting but uh I I have a B in my bonnet about the EU.

38:26Um if you go to the EU website, you know

38:28It's got a big GDPR countdown, 80 days, 11 hours and one minute, 58 seconds as I look at it now before GDPR kicks in, right?

38:38And I've gotta be brutally honest, these guys have no clue about days.

38:43and privacy.

38:44The things and policies, I mean it's the EU we all have to thank for the massive banner that comes up on the top of a website that says

38:51Did you know this website uses cookies?

38:53Like and it's it's it's it just misses the mark every time

38:59They miss the angle, they miss the mark, and they never really get down to the nitty-gritty thing.

39:04Like nothing about GDPR is gonna stop Facebook.

39:07from doing background face recognition on my photos.

39:10All it's gonna do is make it even less apparent to me as a customer that they do this.

39:16And okay, you can throw all this regulation and, you know, put in all these fines, but I guarantee you the EU will not be able to even keep up with the amount of infringements this thing is gonna cause.

39:25And so I always I I I always kind of

39:28I hate regulation when it's delivered by like an entity like the EU because more often than not, they miss the mark.

39:34They don't actually know sort of

39:36what's going on.

39:37I think governments actually have a much better capability of doing it this themselves and I'm looking forward to our government actually coming into play and maybe adding a little bit of GDPR plus, you know, like and then just making it a little bit smarter.

39:50Um but you know one uh one other thing I I also just like to to to highlight to people and you know we talk about companies investing in you know big m computer farming all this data and there's it's this perspective

40:04People always think of themselves as an entity, as a one-time entity, right?

40:08So when I get something through my letterbox uh from Pizza Hut, the reason they're sending that to me is because they want me to buy pizza today.

40:16No

40:16That's not why they're sending you a pizza through the mailbox.

40:20The reason they're sending you a pizza h flyer through the mailbox is because

40:24In your lifetime as an individual doing business to them, you're worth hundreds of pounds, maybe even thousands of pounds.

40:32Look at Amazon.

40:33The lifetime business that I offer them is well into the tens of thousands now.

40:40Okay

40:41This is what companies are actually going for.

40:43They're actually spending all of this money just to look get your lifetime business.

40:48And that's why some of these companies will spend maybe two to three hundred pounds per person on acquisition.

40:55Because if you nail that acquisition and they have good retention capabilities, you're gonna generate them thousands of income over decades.

41:03And then then th this is what they're going for.

41:05Yeah, this reminds me of a child with um George Matthew

41:08Um so George Marthy was the ex um president of Ultrax and now he is working for Kesbury, which is a drawing company.

41:15And I was sort of doing like

41:16I find it so weird that Ulteryx promoted ads will put turn on my timer like do you not see who I am?

41:21Like I've literally got Ulteryx in my profile and I'm still getting it.

41:24He's like, okay, yeah, but um

41:26It's just your profile.

41:27You're just a guy that works with data.

41:29Yeah, okay.

41:30Um but he was like, well how much does would this cost?

41:32I was like, okay, it's gonna cost

41:34I don't know, a thousand.

41:35He was like, no, it cost me five to ten dollars a month to put that advert there.

41:39I was like, right.

41:39And he was like, well, now if if I convert one person from that advert and put them into the funnel,

41:45of our sales team and then we sell a license.

41:48Like bear in mind that UltraX license is a three grand a year, three to five grand a year over the span of three years

41:54This like George is like, well I'm I'm I'm not laughing, right?

41:57Because I'm spending such a a little amount of time on my return on investment is ridiculously high.

42:02So there's no reason for me not to.

42:04It's the same thing with pizza, right?

42:06Like uh you you put something through a door and it the return on investment of that the cost of putting that through your door and then say

42:13If you put it through 100 doors and ten people buy a pizza, then pfft done.

42:16Oh, you're sort of you've got more business, so you've got more income.

42:19And then another thing I'll add here is loyalty cards

42:23Like we've all got those stamped loyalty cards at a coffee shop or a pasta place we go to quite regularly and you just want that, you know, I'll get ten and then I get one free.

42:32It's like, well actually you've

42:33You've spent what f if it's five pounds of the past so you buy ten is fifty pounds and you're getting one free, okay, you're s you're basically saving like that much is not much at all.

42:43But you will go for that because you just see I wanted that return on investment

42:47Yeah, exactly.

42:48And the other thing here is um and you know we we're very deep into the so what's at this point.

42:53I f I forgot to mention that when we actually started the scene.

42:56But but the other thing is um

42:59When you're looking at data, so we're talking a lot about it being collected and you know some some companies are very good.

43:06Take Google and take Facebook for example.

43:09They'll let you download your data

43:11And as a citizen you think, oh how empowering this is.

43:14You know, this is great that I can download my data.

43:17What I'll say to people is have you ever tried doing that, okay?

43:20Number one, most companies don't have a good mechanism that will actually allow you to do that, even though they claim that that's possible.

43:27A good example is RunKeeper.

43:29And I try and download my data of RunKeeper.

43:32It's the most unmaintained service that sometimes it works, sometimes it doesn't.

43:36And support will openly tell me, yeah, it's not working at the moment.

43:39Um come back later, basically.

43:41Alright, fine.

43:42I won't do that.

43:43I'll use their APR, I'll get the data

43:45Number two, uh download your data off uh Google Takeout, right?

43:49Google Takeout, very simple to use interface.

43:52The easiest interface I think I've come across for downloading the data that a company has about you in one file swoop

43:58However, I don't recommend you try it because you're gonna get back gigabytes that you will have no clue what to do with.

44:05Okay

44:05Number one, most of them are in formats that most humans don't understand.

44:09Like JSON or XML or whatever.

44:12Like

44:13Like thank thanks Google, thanks for all this data, but I I literally have no clue how to process it or even read it or even understand it for for a matter of fact unless, you know, it's like a

44:22Geek tool built for geeks but no one else, basically.

44:25But you know the features there, so EU, thank you very much.

44:28We'll we'll carry on dancing in the sunlight

44:30Um and then number three, you j you just you just have no idea the scale of what you're asking when you say download all my data.

44:41I did this, it took

44:43seven days for Google to generate the uh the the download.

44:47The download had to be split up into forty-seven segments, each two terabytes big.

44:53Okay?

44:56I'm so thankful I have a computer that's capable to take all of those zip files, open them and dump them somewhere.

45:03Yeah, exactly.

45:04Because I like I uh you have no hope if you're an everyday consumer, just no hope

45:09And and this is the thing.

45:10The download feature when you don't make it easy for people to understand what you actually hope for them i is is not good enough

45:17Companies need to be displaying this information in easy to digest ways.

45:21So being able, for example, to let you browse sections of your data just on the service itself so that you can say, actually I want to know what you have about me.

45:28Then you get a list.

45:29Okay, here's everything we have.

45:31Here are the timelines we have stuff for.

45:32Here's like a density diagram that shows you how much data we have about you during this period of time.

45:37It has location.

45:38And Google does this sometimes in the Google Maps.

45:41uh uh app you can go to the history tab and it shows you a history of everywhere you've been it's kind of scary but it's it's a bit like moves but you know that's a really good way of displaying to you okay look we have a pretty good awareness of everywhere you've been and this is the kind of level of detail that we have it at

45:55And if you see that and you go, I don't like this, then the you know the switch off location tracking should be right there at the bottom of the page because you've you've seen it and you don't like it, so you want to switch it off

46:05And that's the kind of, you know, level of um integration between privacy, but also surfacing this information to people that we really need.

46:13And doing it in a way that's digestible by everyday people.

46:17Maybe everyone's data literary skills will go up, so JSON files and all these XML files will be, you know, palatable to everyone.

46:24But I highly doubt that's gonna be anytime soon.

46:27I gu I guess we're r uh we're we've just stumbled into the now, right?

46:30The the sort of the ha the once people are more I I think the data literary point is is key here.

46:36If once people are more aware and how uh understand exactly how their data is collected as well as use

46:42And also that they can also use it, they can get benefits from it.

46:45Um then it becomes a bit more palatable and but I think

46:50Making sense of it is is key, right?

46:52Like making sense of the world you live in as well as the the parameters you have and the controls you can put in place.

46:59to um block your privacy.

47:01For example, it's I know people that are like, well, I'm gonna pay uh fifteen, twenty pounds a year for a VPN service so that wherever I go, I'm not able to be tracked as a

47:11This is Tim and Geno or this is Rapid Mystery.

47:15Yeah.

47:15Right.

47:17Because uh because it's like you know, when you when you join uh an uh your internet service provider, when you join public Wi-Fi, all of these things are

47:25planting something on getting something out of your device and free Wi-Fi isn't free because they're getting that information out of you, right?

47:31Like they're Yeah, yeah.

47:32I think I think I was working at a client once and we talked about like, well you just use hot Wi-Fi hotspots because you can track someone's journey around

47:39um just uh just the the actual shopping center.

47:42It was a shopping centre cloud.

47:43And we were like, we just you can just have it ping the router and you can see at this point this person's here, at this point this person here, and the transaction fee is their data, the service they require

47:53we're getting back is free Wi-Fi.

47:56So the the the scary thing about free Wi-Fi and this is why I always use a VPN whenever I'm connected to free Wi-Fi is that marketing companies

48:06use that as a way of discovering your IP address and then they store that information and train their marketing um you know their

48:15cookies and and trackers to then track those IP addresses.

48:18So they don't acquire your IP address um your device IP address and MAC address from your home because they that you know your your ISP doesn't sell that data

48:27Where they'd get that from is these free hotspots that you get, you know, or around and you know companies do sell that.

48:34That's why it's a free Wi-Fi.

48:35Someone has to pay for it

48:37And they're paying for it by selling the uh the MAC addresses and IP addresses that are coming from that specific router.

48:44And then that gets put into an algorithm, it then uh geolocates you because guess what?

48:49If you keep walking past Starbucks

48:50You don't know it, but your phone's pinging the Wi-Fi every single time you walk past.

48:55So these companies have really good situational awareness of where you go.

49:00where you work and all of those uh that that sort of thing.

49:03So I mean I'm not prop I'm not promoting VPN services to everyone, but I think if you're connecting to public Wi-Fi hotspots

49:10quite often it's a really good idea to get VPN, not least because it's also a really common way to get hacked because people go into those cafes with imitation networks that say their Starbucks or say their Costa

49:23You log on thinking you're logging on to the real thing, but what they've done is basically injected themselves between you and the internet and they're just watching you do everything you're doing.

49:32And there's actual devices you can buy with Raspberry Pi, which are about 30 quid off Amazon of all the places that will do this for you.

49:39It's crazy.

49:43Another thing I'd recommend people do is there's this challenge that was run, I forget the name, let me just Google it a second.

49:52It's called the the uh privacy paradox

49:56And it's actually another podcast.

49:57I'll put it in the show notes.

49:59And what they did was they basically had a three or four episode sort of journey.

50:05into privacy.

50:07And what I'll say about this, what about it is this.

50:10I mean they're quite sensational.

50:11It's an American podcast.

50:12It's called Note to Self.

50:13And they did this thing called the Privacy Paradox in partnership with another organization

50:18But you can subscribe to it now.

50:19You send them your email, and what they'll do is they'll send you over five days, they'll send you an email saying, today, try this, find out this about your privacy.

50:27Go to this setting on your phone and look at the options

50:29or any of these ticked, that means these apps have access to A, B, C, and D.

50:33And I remember listening to it and I was quite chuffed with myself because I had a very good awareness of stuff that was

50:39was going on.

50:40There's even a couple of things in there that were like really irked me.

50:43I was like, oh I really didn't know that that bit of information.

50:46So I highly suggest people

50:48And check it out.

50:49It's gonna be in the show notes or you can just Google Privacy Paradox It'll be the top hit.

50:53And um listen to the the five episodes

50:56um uh uh in the podcast.

50:58I think it's a really informative and really interesting way of looking at the topic because

51:04I don't think everyone has an issue with privacy.

51:07I think people just don't know when they're being taken taken to town and just simply knowing what companies know about you

51:14Sometimes we'll give people a peace of mind, but in other places it will allow them to take more control by using either apps that you know look after their privacy better or something as simple as VPN services

51:26Or even getting a phone that supports privacy in a much more sort of stable way, both Android or iPhone, you know, it doesn't have to be necessarily Apple.

51:35I think that's like an a really useful step that you can take because it's such a big topic, right?

51:40Yeah, absolutely.

51:40And and also given that, you know, once because we're more mobile, we think that we're maybe

51:45We're doing we're giving away less data because you're like, well, it's fine with my mobile phone, but in fact you're giving away more because you've got iads and stuff on there as well.

51:53And it's just you have to be really aware of

51:55all of the different things you're giving away.

51:57I think once once this that that literacy as well, as well as the day literacy comes comes forward and people are more aware and more diligent about what they're doing, uh then we sort of move forward and we

52:10Exactly, exactly.

52:11And then the last thing I'd recommend to do before we start to close out the podcast is

52:17You try and collect your own data yourself.

52:20You have no real understanding or perspective unless you start downloading

52:25data yourself something as simple as going on to online banking downloading your statements um for the last maybe decade and just put it into one excel

52:33uh chuck it into some visualization tool and just see what kind of story someone could tell just looking at your bank statement and that's the i that's the kind of picture your bank tells other people about you.

52:45That's where the credit rate r reference um ratings.

52:48come from or something as simple as your running data you know you start running from one place and you finish in one place how often is that the start the finish line your home right you think about that before you share it out on these platforms

53:00Again, as a very simple thing, but if you go running enough, uh as Strava recently found out, you start revealing things like secret military base

53:08That you're not supposed to reveal.

53:10Because people are running around these military bases with Strava on their phone and they do this nice community thing.

53:16I say, hey, here's a map of where everyone runs in the world.

53:19Zoom into someplace and you're like, hmm.

53:21There's not supposed to be something here, but it looks like people are doing laps around something.

53:24Do you do laps or something?

53:26Imagine that.

53:28Imagine that.

53:29Where could this be?

53:30Um so just something as simple as you know downloading your data will give you an awareness of you know what what you have.

53:37I have something on my blog called TabTQS and one of the best demos I do in 10 minutes is of Google

53:42I download location data from Google and I show people the columns that Google has.

53:47It has something like accuracy of your location, direction, speed, accuracy of speed, elevation, accuracy of elevation.

53:55They're doing really sometimes good work and also really, you know, scary work to get even more precise about what they know about you.

54:02So by doing that you'll see you'll see this information and and I think you'll be better placed

54:08Okay.

54:08Okay.

54:09It's a good put place to end the in the end of the pod.

54:12Absolutely.

54:13And before the bumper double bill

54:15It is a quite a long episode and we didn't stick to our time limit, but so it's a good topic.

54:21Um I I I I am absolutely you know failing today.

54:24At the very beginning of the podcast, I forgot to highlight that we have a website

54:29We do, we have a website and a Twitter handle now.

54:31And a Twitter handle, and they're both the same thing.

54:343wattpod.

54:36com is the website and 3Wattpod is the Twitter handle.

54:40So

54:41You can now find our podcast on there.

54:43You can also still find us on SoundCloud, iTunes, I believe Pocket Cast as well now.

54:49I'm a big Overcast user, so I listen on Overcast

54:53We love your feedback.

54:54Some of you have been sending us emails, some of you have been tweeting us directly, tagging us in tweets.

54:59We love that.

55:00We'd love to hear more feedback, both uh you know, critical and um positive

55:04So please send it in and we'll continue to sort of adapt and uh change the podcast as we go along.

55:10Uh but that's been it.

55:11That's been episode three and uh Ravi we'll probably be back in a couple of weeks, right?

55:15We will, yeah, yeah.

55:16And um till then, take care everyone, and uh we'll see you soon.

55:19Cool tegasy