discussion keeps the world turning this is roundtable the algorithms know you predict you and profit off you but with reckoning can we truly escape the grip of big data and stick around for our special segment heart to heart your questions are answers business tech culture or whatever stirs your soul
we're ready to dive in coming to you live from Beijing this is roundtable I'm a young for today's program I'm joined by Steve Hatherley and you should in the studio first on a day's show with every click every like every move online we're creating a trail of data a trail so rich that big data might know
us better than we know ourselves it predicts our next meal our next binge watch and sometimes even our next heartbreak in so many ways our digital lives embody the truth behind the quote if you're not paying for the product you are the product all that data we generate becomes a goldmine for companies
eager to monetize our every move you are savvy roundtable listener are probably already aware of this hidden trade -off now the awakened among us are trying to break free from the digital web that's been spun around them trying to escape the tailored information cocoons algorithm driven recommendations
and personalized pricing schemes that seem to know us too well and it's a rebellion against the invisible digital exploitation that has quietly shaped our online world but can they truly succeed in breaking free tell us you shouldn't about this moment of reckoning when people realize that they want
to break free from the grip of big data oh yeah so we can see is that young people nowadays are beginning to resist this kind of phenomenon called price discrimination it's some of them are caused by these big data algorithms and they have realized that some platforms use big data to analyze user behavior and impose
price discrimination on some of these very loyal users to maximize profits and this behavior has made young people feel a sense of injustice sparking their backlash and also this is why some college students are voicing dissatisfaction with algorithmic recommendations the you know they argue that such
kind of a recommendations overly cater to user preferences and they're creating information cocoon as you said going on while the suggested content may not always be accurate or valuable and some people find it very scary because it feels like they're watching you often times it can feel like that yeah
I guess it's frustrating isn't it because you would think logic would suggest that the more loyal of a customer you are the more loyal you are as a customer then the more benefits you would get but this is kind of the opposite isn't it it's counterintuitive the more loyal you are the more the higher
prices you will be you'll you'll be suggested whereas new users will be offered discounts from a business point of view I understand it but from a consumer point of view from a personal point of view it is very frustrating it is it's almost like you're well it is that you're penalized for your loyalty
and for the willingness to spend more and the most horrifying part is the big data with this machine learning algorithms can predict exactly the price point anyone seated here is willing to pay yeah it's a little it's a little scary isn't it it is but the fact that we're being watched that every move
is being analyzed or let's not say every move but you know there are some that we know we've given consent and there are others that maybe we've stopped but but maybe or is happening without us knowing and this is all happening and this is not particularly new news for people at this point I would think
that is correct in China Youth Daily they wanted to know how young people were feeling about this so they conducted a survey on algorithmic recommendations and they were targeting young people primarily college students 3694 valid responses that's what they got in total and this is what people had to
say 78 % believed that they needed to reduce their reliance on algorithmic recommendations almost 73 % reported having experienced big data price discrimination and almost 70 % felt that recommended recommendation algorithms should be more transparent in what they are doing so obvious frustration from the respondents
there mm -hmm and the term big data is center in this discussion what is big data although this sounds very much like a term that was all over the place 10 years ago but still provide a definition and tell us how does it make recommendations yeah so basically big data refers to the process by which platforms
collect and analyze massive amounts of user data and this data includes basically like browsing history purchase records device information personal details and more because they can analyze you through these kind of data for example maybe the price of your phone model is more expensive and some of the platforms
will recommend you more expensive products and that is how these platforms are using or analyzing the big data or information of yours to give you a specific or tailored information they're they're labeling you right essentially platforms use this data for precise targeting for instance e -commerce platforms
they might offer promotional discounts like we said to new users and a loyal user will get a higher -priced item recommended to them similarly video platforms recommend content based on a user's viewing history to match their interests there's lots of different ways that this manifests itself and on on many
different types of platforms and also algorithms are you know presents in nearly every corner of our lives it feels like this survey also report you know revealing that about 90 % of respondents were aware of the existence of algorithmic recommendations and also common platforms incorporating such algorithms
include video platforms is taking up about 90 % shopping platforms are also using algorithm or these kind of big data kind of technology and this is taking up for about 74 % people thinks that 74 % of people think these platforms are using big data and also social media is 67 % music platforms 66 % and even
lifestyle and consumption apps that's 39 % okay I can understand you know by when we're mentioning music platforms maybe they're recommending you music that you may like and that is a kind of favored function or a feature that users most of users will like well I mean it's it's not always bad we shouldn't
write vilify this it's it's not where every example is a terrible example for example music recommendations or for me I like to watch some TV shows on on a streaming platform and then after I watch I don't know if you guys are show reviewers or not you know like three stars four stars five stars I do
it too or the thumbs up or the thumbs down well what you're doing is you're feeding into the big data because you're helping the platform recommend shows to you later on based on the things that you liked or what you didn't like so there's an example of it where it's not terrible and me Mengna, excuse
me, who was a recent graduate from a university in Fujian said exactly the same thing the videos recommended to me always make me feel comfortable always make me feel happy she also referenced a ride hailing app about her daily routines suggesting that the ride hailing app knows her schedule just as
well as she does she goes to visit her friend every Wednesday or Thursday and the ride hailing app knows about this so if she gets a ride hailing app at that time the app will automatically fill in her friends address and some may see this as a as an extreme convenience other might feel like this is a little
scary it's a bit freaky well I hate to pay it depends on how you view it right for example just before the show today at around eleven thirty on Sunday on a Sunday a few weeks ago I got a coffee from a local coffee brand it's a well -known brand at eleven thirty a .m.
and now every day at that time of day I get some sort of message from that company's app I don't know if it's a coupon I don't know what it is because I don't open it but it it knows oh well this is around the time that Steve gets a coffee I guess so let's just give him a little nudge and on the ride
hailing app I go to the same place a lot of the time to pick up groceries or to there's another place I go for fun and the the app knows so all I for it's convenient all I have to do is press the button I don't have to search for the address I don't have to copy and paste it it's already there so there
are examples is where it's really convenient and also because it is automatic it can be accurate because you don't need to type in the address anymore because they've just pasting the original or the the previous one I had this kind of experience and making this thing to me is kind of a convenient because when I
whenever I put on my Bluetooth headphones my phone immediately prompts me to open a music app or and you need to like mmm where your headphone at the certain time because they will analyze and to get all of these time data location data and also your device data into into one kind of analysis and then
you know I don't find it bothersome in some way you know because it is just telling me or it gives me a kind of a convenient vibe that I can I can just click that button and open my what I want to do I feel you shouldn't being a member of Gen Z he's usually the more welcoming one of all kinds of new
tech on on the team and also sometimes when let's say we're doing the research for the show I vividly remember a while ago before Steve you joined the team we did this topic on electric wheelchairs so I was researching on a few platforms and then I got recommendations of that stuff and I really don't
want it and and also I'm searching like you know leopard print Italian pumps as well and I wonder how these different platforms label or profile me I must sound like a very well dressed elderly person maybe next you'll get a leopard print electric wheelchair oh wow maybe in pink very stylish you know
we're talking about the good things and the bad things today but the main point here is that young people are fighting back so how exactly are young people fighting against big data and all the things that go into it so one way is that they're trying to be invisible or like going incognito to prevent
the you know platform algorithms from accurately identifying them or their behavior patterns also breaking the price confinement or discrimination imposed by this big data so some of them will just frequently change their personal information by changing their personal details and using virtual usernames
and avatars and users try to conceal their true identity also switch different devices maybe you can buy one like like use one shopping platforms on your tablet and use another platform on your phone that's maybe one way but you need to know that you don't use one account also using different browsers
right using different browsers can help prevent platforms from tracking your behavior and also try to disguise yourself it is a way I would say fake mustache I think what we need to know is that these kind of methods are just concluded by netizens and we don't have any evidence that proving that they
are effective right yeah well I'm curious to hear the digital mustache how do you describe disguise yourself go incognito that is a quite interesting one I actually saw some news on it you know one you can you can comment right a lot of products or even some plane you when you're buying plane tickets
you can comment on the airline service right so you can come you're gonna make comment in the common area or query pages and you can frequently comment it is too expensive I can't afford this and I I will just cancel the flight or cancel the schedule and then the the price of the flights maybe or just
go down a little yes go down a little bit and you and I actually saw that news that someone commented in the airline service page and the price decreased from 4 ,000 yuan to 2 ,000 yeah it's just it's just so I mean it's so ridiculous isn't it that we have to do this it sounds like we're going into James
Bond spy mode to just stop big data from knowing exactly who we are and what we're interested in and what we and when we want to buy it yeah things like comments or dislikes on on certain pages but that doesn't always work there's an article from the Verge from 2022 and they were talking about the fact
that even when users tell YouTube that they aren't interested in certain types of videos similar recommendations keep cutting keep coming Mozilla did a study on that and what they did in the study they looked at video recommendation data from more than 20 ,000 YouTube users and then the researchers from Mozilla found
that the buttons like not interested or dislike or stop recommending channel or remove from watch history are largely ineffective at preventing similar content from being recommended I've been doing all the wrong things then yeah so what's the key to this then it well I don't think that these tech companies
are just gonna willingly tell us what's the you know at the bottom of that black box but one of the things and this is from PC mag is and I'm always guilty of this when you go to a website or sign up for something do you always put your real name your real birthday your real everything well from day
one my friend recommended to use the pseudo name but sometimes you forget your pseudo name so you just come up with a fake name and you always use it see I always feel like I don't know I don't even think about I just put my real information in there I know and this is what PC mag comm says and the title
of this was how to stop companies from collecting your data they say lie online lie online whenever you can and they said you know we're not talking about you know giving a fake name to your bank or you know government agencies or something like that but when you're filling out web forms what they recommend
is that you can put in a fake birthday a fake full name a fake phone number a fake physical address when you're searching for I don't know a hot pot recipe online for example isn't when you're required to put in so much information isn't that when you're kind of pretty I wouldn't say fully committed
but you're like signing up as a VIP or a repeated user of some platform or something and here's a question I've always wondered should I I've always thought that I should put down my real birthday because on my birthday I'll get a free hot pot or whatever part you know that's why I thought it was for that perk
so I feel like oh I should probably maybe you can you know write a write down a wrong year number but for your month and day of your birthday then it's probably best to keep it real I mean I guess that's up to you right I mean every year on my birthday I every year I still get a happy birthday message
from a shampoo company that I bought shampoo from once like seven years ago and I thought you know it makes me feel pretty good actually like they care or something but this is what they say and again this is from PC bank if you can't figure out why an app or a website needs the information that they're
taking from you it's not a good idea to give them your real data again that's not my opinion that's from the website PC Mac and also your phone number like in China everything's through the phone yes so if you write a wrong phone number down then what's the point of even signing up mm -hmm and also that's
why a lot of young people they're trying to use another direction of their scheme okay you want analyze me then analyze a cheaper me that creating persona like that I like that yeah sometimes you know by selecting and purchasing cheaper products on online shopping platforms you can create a value conscious
persona you know I've heard that on some platforms even if you enter the same keywords right the search results might defer because you know the platforms may estimate that you are a consumer likely to purchase higher priced products based on your previous spending habits so the more you buy the higher
the prices of the products that appear might be so you may just click on more cheaper products and then they may recommend you cheaper results when you're searching on it yeah right but I mean what but what are you supposed to do for example young's looking for a really nice pair of shoes online or something
but what do you what are you supposed to do you can't go with your fake persona or do you search the nice shoes and then say I hate these in the comment section or these are too expensive I don't know it just it's so frustrating because it just feels like so much work for us where there shouldn't be
any work involved at all right so but also I like to ask maybe it's more of the people who've had this reckoning or feeling like this but are all people rejecting the effect of big data are there some people who maybe enjoy living in the comfort of tailored suggestions tailored digital suggestions I
think we had a little bit discussion about this the answer is of course no because not everyone completely rejects this big data and this convenience that brought by big data you know some young people are not fighting against big data itself but against the unfairness and privacy invasions it may bring
and they hope to enjoy the convenience of big data while retaining control over their own data avoiding being manipulated by algorithms and also I was trying to think from another perspective because what we've been mentioning the way that people counter these big data are all the solutions that users
can do on their end and the root of the issue likely lies with the software developers you know themselves and the changes need to happen on their side otherwise it's like just I'm simply refusing to accept it but they doesn't mean that these apps aren't still collecting my data and to support what Yushin was saying
going back to that survey from China Youth Daily you know asking the question are you on set are you wholly unsatisfied with this and the answer again is no sixty point three percent of respondents said they're satisfied with the content recommended by algorithms almost seventy percent said that it
makes it easier to find content of interest almost sixty percent said that it improves information retrieval efficiency it's easier and faster to find information that they're looking for then the numbers go down a little bit increasing opportunities to encounter new things went down to almost forty
four percent useful learning resources went down to almost twenty seven percent but what we can what we can take away from those numbers is there are benefits there are benefits and not everyone is against this yes and also for those who are against it and I read so many articles on this and I've been
paying attention to this in this phenomenon in recent years and just kind of feels like we folks are what is that term eating cake and having it to yeah you want your cake you need it to or something like that yeah on the one hand we benefit from all these hyper personalized content that makes our digital
experiences more engaging and relevant and on the other hand you know it's the same personalization can create all these problems that we've just named so now the question becomes how much of this trade -off we're willing to accept and whether we can find a balance between enjoying the perks while being
mindful of the downsides and it's a paradox of the digital age where our desires for convenience entertainment and relevance can sometimes come at the cost of privacy manipulation fairness and diversity of thought may I say hmm so when in light of all of this what do you think how can we approach algorithms
in a rational and reasonable way first of all you know I actually read some privacy policies of various apps before you really I did wow because I found it scary so I actually read through all of these policies and they didn't mention or include any clauses about you know listening to users conversation because we
I had encountered that kind of comfort situation also we don't have hundred percent solid evidence to prove they are listening to us because there are big data algorithms are incredibly extensive for example if a platform detects that your you're frequently send its link to a particular user it might determine
that this person is your friend and if that friend searches for something that you've been talking about and this app could still deliver accurate recommendation to you even without your granting it any specific permissions that's how the big data works so sometimes this is an unavoidable situation and it
really depends on how you perceive it hmm I mean there are other things that you can do by the way you might be the only person on planet earth to read that was ever read through those things but yeah you can you can do other things as well but protecting your personal privacy obviously is one under understanding
I guess those rights those those terms you know if you nobody usually reads the whole thing but if you want to scroll down to the data part you can read that and know exactly what the app is going to be taking from you and decide not to use it and find how inconvenient it is sometimes without well breaking
free from big data's grip or grasp is an uphill battle as all we can feel it and one that goes beyond individual choice governments and corporations have so much power to shape how algorithms control our lives until we see real regulation transparency and accountability the fight against digital exploitation will remain an ongoing
struggle with many still caught in the system that we feel we can barely understand
