Speaker 1: Welcome to tech Stuff, a production from I Heart Radio.
Speaker 1: Hey there, and welcome to tech Stuff. I'm your host,
Speaker 1: Jonathan Strickland. I'm an executive producer with I Heart Radio.
Speaker 1: And how the tech are you? It's time for the
Speaker 1: tech News for Thursday, January nineteen, twenty twenty three. And
Speaker 1: last year it seemed like the front half of every
Speaker 1: tech news episode was dominated by Elon Musk's on again,
Speaker 1: off again and then totally on again quest to buy Twitter.
Speaker 1: But so far in the honor really goes to chat,
Speaker 1: GPT and open Ai, which is the startup that's behind
Speaker 1: the controversial chat pot so. First up today, Sam Altman,
Speaker 1: the CEO of open Ai, gave an interview with Strictly
Speaker 1: VC in which he addressed some rumors about the upcoming
Speaker 1: next generation of the GPT language model a k a.
Speaker 1: GPT four. We're currently on GPT three point five. Altman
Speaker 1: warned that people are bound to be disappointed in the
Speaker 1: new language model because the hype around it has grown
Speaker 1: to a point that's just impossible to live up to.
Speaker 1: And I think Altman in general has been pretty good
Speaker 1: about acknowledging this kind of stuff. A lot of folks,
Speaker 1: including myself, have pointed out how chat GPT falls short
Speaker 1: in lots of ways, and I don't think Altman would disagree.
Speaker 1: He has been pretty forthcoming about this sort of stuff,
Speaker 1: and he's not making claims that chat GPT is flawless
Speaker 1: or even skilled at every kind of writing. So I
Speaker 1: guess it's unfair for folks like myself to say I
Speaker 1: can't even write a shakespeareance on it, even even though
Speaker 1: it can't. I mean, maybe if I kept at it,
Speaker 1: maybe if I kept tweaking prompts, I could massaw chat
Speaker 1: GPT to a point where it could produce an actual
Speaker 1: Shakespearean style sonnet. But anyway, Altman wouldn't commit to win.
Speaker 1: This next model will launch. He said it will launch
Speaker 1: when it's ready, which I also think it is a
Speaker 1: pretty responsible take, and he admitted that there were concerns
Speaker 1: about how chat GPT might be used by students to
Speaker 1: try and cheat on schoolwork. But he also pointed out
Speaker 1: that when calculators became a thing, we just we didn't
Speaker 1: just abandon teaching students how to do maths. Instead, we
Speaker 1: took calculators kind of into account. While doing so, the
Speaker 1: way we taught it started to change. That's a kind
Speaker 1: of interesting take. Now, Honestly, I think chat GPT could
Speaker 1: be useful for say, English teachers, to show how a
Speaker 1: generated essay might fall short of actual real work done
Speaker 1: by a student who's taking the subject seriously. It could
Speaker 1: be useful to explain to students the difference between real
Speaker 1: critical thinking and surface level as servation. And this way
Speaker 1: you wouldn't have to take an actual student's essay and
Speaker 1: then embarrass that student in front of the rest of
Speaker 1: the class and say, see, little Timmy over there totally
Speaker 1: doesn't understand the role that false staff plays, and Henry
Speaker 1: the fourth part two, just look at this terrible work.
Speaker 1: Shame on you, little Timmy. Instead they could say, look,
Speaker 1: here's this essay written by chat GPT. Here are the
Speaker 1: places where the observations being made are pure surface level
Speaker 1: and they don't really say anything. This is the sort
Speaker 1: of stuff you need to avoid and think about when
Speaker 1: you make your own work. And uh, I get that
Speaker 1: I'm putting a lot on teachers there, and that they're
Speaker 1: already overworked and undervalued, and that should change too, just
Speaker 1: throwing that out there now. One thing about open AI
Speaker 1: that has undeniably caused harm is the process by which
Speaker 1: the company has tried to filter out objectionable material. So
Speaker 1: in the past, even with g PT, we've seen examples
Speaker 1: of how chat bots can submit truly offensive material that
Speaker 1: includes stuff that ranges from racism and sexism and hate
Speaker 1: speech and calls for violence to description of truly horrific
Speaker 1: acts that I can't even begin to describe on this show.
Speaker 1: And obviously, any company making a chat bot wants to
Speaker 1: avoid the chat bot creating these kinds of situations, even
Speaker 1: if it's just because it's bad optics. Right, if the
Speaker 1: reason is, oh, we don't want to do that because
Speaker 1: it'll hurt our investment, at least, they still don't want
Speaker 1: to do it. Now, as you may know, chat GPT
Speaker 1: generates responses to queries by referencing information from a massive
Speaker 1: database of scanned material across the Internet, and there are
Speaker 1: complex rules at play that guide chat GPTs responses, but
Speaker 1: ultimately those responses depend heavily on the repository of scanned information. Now,
Speaker 1: the problem is, and I'm sure you've realized this, the
Speaker 1: web is home to some really terrible communities, ones where
Speaker 1: truly awful material is shared and sometimes celebrated, and chat
Speaker 1: GPT cannot magically tell the difference between what is acceptable
Speaker 1: and what is unacceptable. So it needs people to essentially
Speaker 1: tell the model what isn't isn't right, and it has
Speaker 1: to be able to identify certain stuff as falling into
Speaker 1: categories of content that are forbidden and then filter anything
Speaker 1: like that out of its responses. Anyway, Open a Eyes
Speaker 1: approach was to outsource this work of tagging offensive material,
Speaker 1: identifying it meta tagging it so that chat GPT could
Speaker 1: avoid such stuff, and they went with a company called
Speaker 1: Sama s a m A. This company had also worked
Speaker 1: with Facebook in the area of content moderation, so it
Speaker 1: would hire out people to go through Facebook posts and
Speaker 1: flag any that violated Facebook's policies. Now, the way Sama
Speaker 1: hands handles this is to employ people in Kenya to
Speaker 1: do the work at a salary that breaks down between
Speaker 1: a dollar thirty two and two dollars per hour. By
Speaker 1: the way, Sama was paid around twelve dollars fifty cents
Speaker 1: per hour per case um, and the people actually doing
Speaker 1: the physical work are getting a dollar thirty two to
Speaker 1: two dollars of that time. Magazine indicates that a receptionist
Speaker 1: in Nairobi makes around a dollar fifty two per hour,
Speaker 1: So these are pretty low paying jobs and in return
Speaker 1: for this hourly rate, employees were divided into three groups
Speaker 1: to read passage after passage of just truly the worst
Speaker 1: stuff you can imagine. Each group focused on a specific
Speaker 1: kind of offensive material. There was a hate speech group,
Speaker 1: a sexual abuse group, and a violence group, and I'm
Speaker 1: sure there was plenty of overlap between these three. Employees
Speaker 1: would read and tag each passage for eight or nine
Speaker 1: hours a day, and as you can imagine, being plunged
Speaker 1: into that kind of work and being expected to meet
Speaker 1: certain deliverables right to tag a certain number of passages
Speaker 1: each day really took its toll. It was psychologically taxing,
Speaker 1: to say the least, and many employees reported being traumatized
Speaker 1: by the work, and a few of them argued that SAMA,
Speaker 1: despite what it claimed, was not providing adequate services for counseling.
Speaker 1: And this whole story reminds us that behind the surface
Speaker 1: of these AI programs, there's actually this huge human contribution
Speaker 1: to make them work. Like, yes, it's remarkable that this
Speaker 1: program is composing these texts in response to our queries,
Speaker 1: but to make that possible, a lot of people had
Speaker 1: to spend countless hours of work, and some of them
Speaker 1: doing work that was truly traumatic. The story gets even
Speaker 1: more complicated. Sama recently ended its contracts with open Ai
Speaker 1: ahead of schedule, probably because the company was already being
Speaker 1: taken to task for how they relied on poor people
Speaker 1: in developing countries to moderate content on Facebook, which included
Speaker 1: the content moderators being subjected to truly horrific content, including
Speaker 1: videos and pictures. And we're talking about violence and sexual
Speaker 1: abuse and and and child endangerment and worse, and in
Speaker 1: other words, I don't think Sama made this choice out
Speaker 1: of concern for its workers. The workers found themselves also
Speaker 1: either out of a job entirely or shifted to other
Speaker 1: lower paying work, so they've actually come out poorer for
Speaker 1: this as well. And some of them were saying like, yeah,
Speaker 1: the work is terrible. It takes a toll, but I
Speaker 1: need to provide for my family and now I'm not
Speaker 1: able to. So it's a very grim story. If you
Speaker 1: would like to read about it further, I recommend the
Speaker 1: article in time it is article it is titled rather
Speaker 1: open Ai used Kenyan workers on less than two dollars
Speaker 1: per hour to make chat GPT less toxic. And for
Speaker 1: our third story, about chat GPT. Let's talk about how
Speaker 1: some cybersecurity researchers were able to get the chat bought
Speaker 1: to create a new strand of malware, and not just
Speaker 1: any malware, but polymorphic malware, meaning it can take many forms.
Speaker 1: You can have a core structure that can then be
Speaker 1: tweaked so that you get different generations of malware based
Speaker 1: on the same core, but they can be different enough
Speaker 1: that an anti virus program would have trouble detecting new variants,
Speaker 1: thus extending the useful life of the malware. Like you
Speaker 1: can keep using this core malware over and over by
Speaker 1: making these small changes, relatively small changes, and keep sending
Speaker 1: out waves of the stuff. So this is bad news
Speaker 1: for the security side of things, Lee, but it's also
Speaker 1: important research because if the good guys don't know about it,
Speaker 1: then the bad guys can make greater use of it.
Speaker 1: The researchers said that the web based version of chat
Speaker 1: GPT is a little more challenging to use because it's
Speaker 1: meant to filter out anything that would result in the
Speaker 1: creation of malicious tools. You're not supposed to use chat
Speaker 1: GPT to do it, and it tries to prevent you
Speaker 1: from doing it. However, the team said that if they
Speaker 1: just kept restating their requests and if they made them
Speaker 1: more authoritative, they could eventually work around this barrier and
Speaker 1: convince chat gpt to do their bidding. Which is kind
Speaker 1: of concerning this idea that persistence and a change in
Speaker 1: tone will allow a user to sidestep safety parameters. That's
Speaker 1: not great, But what's arguably worse is the team found
Speaker 1: the a p I, the application programming interface version of
Speaker 1: chat GPT. This is the version that's meant to let
Speaker 1: you incorporate chat GPT functionality into other applications. That version
Speaker 1: appeared to have no such restrictions at play in the
Speaker 1: first place, So, in other words, it was essentially raring
Speaker 1: to go when the time came to make malware. The
Speaker 1: security firm cyber Arc says that it will continue to
Speaker 1: do research on this new development, and that it plans
Speaker 1: to release some of the source code of the malware
Speaker 1: that was created to the cyber security community for the
Speaker 1: purposes of education. And yeah, the bots are learning how
Speaker 1: to create cyber attacks. Now, all right, we're gonna take
Speaker 1: a quick break. When we come back, we'll have some
Speaker 1: more news. We're back now. Last Tuesday, it's past. Tuesday,
Speaker 1: I talked about how crypto is currently in a bit
Speaker 1: of a recovery phase, possibly because the crypto community thinks
Speaker 1: that the macro economic situation is improving. But there's no
Speaker 1: telling if that recovery phase is going to be sustainable
Speaker 1: just yet, and it appears that the big companies are
Speaker 1: still very much in belt tightening mode, which suggests that
Speaker 1: at least these companies expect things to be tough for
Speaker 1: a while. Yet. This week we heard Microsoft is laying
Speaker 1: off around ten thousand employees between now and the end
Speaker 1: of March. A company spokesperson indicated that marketing and sales
Speaker 1: will feel the impact more than engineering, and that gamers
Speaker 1: will also be sad to learn that Xbox and Bethesda
Speaker 1: divisions are among those that will be affected. Satya Nadela,
Speaker 1: the CEO of Microsoft, said that consumers are starting to
Speaker 1: get more frugal with their digital spending and that while
Speaker 1: the early stages of the pandemic saw an increase in
Speaker 1: digital spending, we're now seeing kind of a reversal of
Speaker 1: that trend as people start to ask do I really
Speaker 1: need this digital subscription and start to make choices in
Speaker 1: a way to kind of scale down their own expenditures,
Speaker 1: and on a related note, Amazon continues to cut costs,
Speaker 1: this time by planning to sunset a charitable donation program
Speaker 1: that has been in place since two thousand thirteen. It's
Speaker 1: called Amazon Smile, and it would let customers designate a
Speaker 1: charity one that Amazon had verified, and that charity would
Speaker 1: then receive a percentage of every eligible purchase that the
Speaker 1: customer made on the platform. So instead of going to
Speaker 1: www dot Amazon, you would go to Smile dot Amazon,
Speaker 1: and otherwise everything else would be the same as your
Speaker 1: typical Amazon experience. I actually made use of this program myself.
Speaker 1: I selected a local theater, as in a stage theater
Speaker 1: here in Atlanta to be the recipient because it's a
Speaker 1: nonprofit organization anyway. Now, Amazon is saying that this program
Speaker 1: was not as effective as the company had hoped, and
Speaker 1: that was because these donations were you know, fractions, like
Speaker 1: a percentage of each eligible purchase, and it was spread
Speaker 1: across thousands of charities. No single charity received very much money.
Speaker 1: The company said that the average amount donated to a
Speaker 1: charity amounted to around two d thirty dollars. I just
Speaker 1: checked mine, and over the years that I've been using
Speaker 1: this and I have been using it for several years now.
Speaker 1: My purchases have amounted to about a thousand, seven d
Speaker 1: fifty dollars in donations to this theater. But that's stretched
Speaker 1: across years, right, So it's not like this theater got
Speaker 1: a check for almost two grand and was like, wow,
Speaker 1: what a huge donation. Now it's like, you know, a month,
Speaker 1: they might get a check for you know, a couple
Speaker 1: of bucks. So Amazon kind of has a point here
Speaker 1: in the sense that this was probably not the most
Speaker 1: effective charitable platform. It says that it will still support
Speaker 1: various causes, but it will make more focused decisions on
Speaker 1: things that quote unquote make meaningful change. The Data Privacy
Speaker 1: Commissioner or DPC in Ireland took aim against Meta again,
Speaker 1: this time finding WhatsApp five point five million euro, which
Speaker 1: is just a smidge under six million US dollars, and
Speaker 1: it was for a breach in the EU's strict privacy laws.
Speaker 1: At issue is how WhatsApp has been leveraging the personal
Speaker 1: information of users in the EU while trying to improve
Speaker 1: the company's services. So this isn't about targeted advertising for once.
Speaker 1: It's about using this personal information in a way to
Speaker 1: beef up the services own features and capabilities. Apparently WhatsApp
Speaker 1: methods just didn't go far enough to protect the personal
Speaker 1: information of EU citizens, though the Reuters report I read
Speaker 1: didn't go into really any detail about the nature of
Speaker 1: the violations themselves. Meta has been the target of the
Speaker 1: DPC several times now and has had to pay fines
Speaker 1: on multiple occasions for how and has continued to handle or,
Speaker 1: depending on your point of view, mishandle data pertaining to
Speaker 1: EU citizens. I don't know at what point things would change,
Speaker 1: because the fines, while they're substantial in the big picture
Speaker 1: of Meta's you know, financial situation, rarely amount to anything
Speaker 1: that would raise an eyebrow on on a massive corporate spreadsheet.
Speaker 1: So um, yeah, it's It's yet another example of Meta
Speaker 1: doing what Meta does best, which is handle the personal
Speaker 1: information of its users in a way that's ultimately irresponsible. Meanwhile,
Speaker 1: Global Witness, a human rights watchdog agency that we've talked
Speaker 1: about several times on this show, revealed that Meta's Facebook
Speaker 1: allowed ads calling for violence in Brazil following an already
Speaker 1: violent series of protests in that country. All right, so
Speaker 1: first let's get some background. So in elections late last year,
Speaker 1: the leftist politician Louise Inacio Lula da Silva defeated his
Speaker 1: right wing opponent and former President Bolsonaro in a runoff,
Speaker 1: but Balsonaro took a page from the far far right
Speaker 1: playbook and refused to concede the election. Da Silva took
Speaker 1: office at the beginning of this year, and then some
Speaker 1: of Bosonaro's supporters stormed government buildings in these violent riots
Speaker 1: in an attempt to have this election overturned. The violence
Speaker 1: lasted several hours, and this prompted META to declare Brazil
Speaker 1: a high risk region, at least temporarily. Now that's supposed
Speaker 1: to mean that meta's properties, including Facebook, take a much
Speaker 1: more restrictive approach with regard to content moderation and add approval,
Speaker 1: and an effort to mitigate things like hate speech and
Speaker 1: calls for violence. But Global Witness found that just days
Speaker 1: after the riots, Facebook accepted fourteen of sixteen fake ads
Speaker 1: that Global Witness created, and these ads called for violence
Speaker 1: against the Silva and his supporters. That is definitely not
Speaker 1: a good look. Facebook should not have accepted those ads,
Speaker 1: but it was totally prepared to run fourteen of sixteen
Speaker 1: of them. Global Witness reps say that this shows how
Speaker 1: Meta fails to live up to its obligations in these
Speaker 1: kinds of cases, and it's something we've seen play out
Speaker 1: around the world, particularly in non English speaking countries. There's
Speaker 1: long been this accusation against Meta that the company pays
Speaker 1: very little attention to content moderation outside of major English
Speaker 1: speaking markets like the United States and the EU, and
Speaker 1: yet by doing this, by ignoring these other regions, the
Speaker 1: company is facilitating serious harm to come to populations by
Speaker 1: not cracking down on things like hate speech and calls
Speaker 1: for violence. Global Witness says that YouTube performed substantially better
Speaker 1: than Meta did and denied ads that had similar language
Speaker 1: and messaging in them, and just to set minds at ease,
Speaker 1: Global Witness did cancel these ads before they could actually
Speaker 1: go live, so no users encountered these ads that violated
Speaker 1: Facebook's policies and called for violence because Global Witness pulled
Speaker 1: them before they could they could go live on the site. Okay,
Speaker 1: I've got a couple more stories to get to, but
Speaker 1: before I get to those, let's take another quick break.
Speaker 1: We're back. So I've got a story about video games. Uh,
Speaker 1: it's not necessarily a positive one. So one of the
Speaker 1: ongoing issues in the world of video games involves what
Speaker 1: comes along with leaning on the games as a service
Speaker 1: business model, that is, releasing a game that has elements
Speaker 1: in it that allow a company to continue to generate
Speaker 1: revenue from players over time. So in the old old days,
Speaker 1: the way you made money if you were in the
Speaker 1: video game businesses, you sold as many copies of a
Speaker 1: video game as you possibly could. But once you sold
Speaker 1: a copy of a video game, that was kind of it.
Speaker 1: That was the end of the transaction. Then once you
Speaker 1: started getting into games that had a subscription model like
Speaker 1: M M O RPGs, there became this new way to
Speaker 1: make money. First you'd sell the game, then you would
Speaker 1: continue to make money from the game by collecting subscription fees.
Speaker 1: And this started to open up possibilities where you know,
Speaker 1: you look at this and you think, all right, we
Speaker 1: can continue to make profit from these games. We do
Speaker 1: have to also put effort in to continue to support
Speaker 1: the game, So there is an ongoing cost as well.
Speaker 1: It's not like, you know, we work one day and
Speaker 1: then we just make passive income for the rest or
Speaker 1: our lives. That's that's a myth, but it did open
Speaker 1: up these opportunities, and that's when we started to see
Speaker 1: other ways to make money on ongoing titles, and that
Speaker 1: involved some stuff like being able to pay for upgrades,
Speaker 1: cosmetic upgrades for your character so that they could look
Speaker 1: a specific way and have a specific style. And most gamers,
Speaker 1: I don't think object to this, like the idea of yeah,
Speaker 1: you know, if you want, you can pay a dollar
Speaker 1: and you get this new skin for your character and
Speaker 1: it looks really cool, and I think most gamers are like, yeah,
Speaker 1: I can, you know, I don't care about that, so
Speaker 1: I'm not going to spend the money, or yeah it's
Speaker 1: a dollar, I'll spend a dollar and help support this
Speaker 1: game and plus get this cool skin. Most people don't
Speaker 1: have objections to that. But then you have the darker
Speaker 1: side of this, where you know, they offer up items
Speaker 1: or outfits or just you know, elements. They give players
Speaker 1: an advantage in return for some cold hard cash that
Speaker 1: you buy something that boosts your character performance, either temporarily
Speaker 1: or permanently, and a lot of players refer to this
Speaker 1: as the pay to win style right where you you
Speaker 1: can get an advantage on better players just by spending
Speaker 1: money and it it has a really bad rep in
Speaker 1: the video game world. Generally speaking, it's it's heavily frowned
Speaker 1: upon because people who put in the time and who
Speaker 1: genuinely love the game will find themselves frustrated with folks
Speaker 1: who just have more discretionary income and who are spending
Speaker 1: more on the title in order to get the advantage.
Speaker 1: And that's very frustrating, because we deal with that enough
Speaker 1: in real life, y'all. But anyway, along with these monetization
Speaker 1: strategies come concerns that the games, you know, gamify stuff
Speaker 1: so that players are kind of lured into spending money
Speaker 1: that otherwise they wouldn't, or there might be elements of
Speaker 1: gambling at play, such as the purchase of a lootbox.
Speaker 1: So a lootbox doesn't guarantee you a specific item within
Speaker 1: the game. It gives you a chance of getting different items,
Speaker 1: and the more common items tend to have a larger chance,
Speaker 1: and the more rare items tend to have a smaller chance,
Speaker 1: So it becomes kind of like a gamble. And a
Speaker 1: lot of countries have looked into this and even gone
Speaker 1: so far as to call it gambling and outlawed loot boxes. Well,
Speaker 1: now the EU is kind of looking in on this too,
Speaker 1: as well as other elements of of games as a
Speaker 1: service that could have a negative impact on gamer's mental health.
Speaker 1: So this doesn't mean that the EU is going to
Speaker 1: vote against loot boxes or or make those you know, illegal,
Speaker 1: or regulate them in any way. We haven't gotten to
Speaker 1: that step yet, but they have adopted this report that
Speaker 1: is looking into these kinds of things, which could be
Speaker 1: the first step toward such an outcome. So I imagine
Speaker 1: there are some video game companies out there that are
Speaker 1: watching this with some anticipation because if the EU does
Speaker 1: come to the conclusion that stuff like lootboxes amount to
Speaker 1: gambling and that this has to be regulated, and that
Speaker 1: maybe that also creates restrictions on who can buy the games,
Speaker 1: that's going to have a massive impact of the industry. Um. Yeah,
Speaker 1: So it's it's again an ongoing issue that is still
Speaker 1: kind of shaking out in different places around the world.
Speaker 1: Maybe in five or ten years we're going to see
Speaker 1: dramatically different strategies for monetization to avoid these kinds of
Speaker 1: I guess what Obi wan Kenobi would call imperial entanglements,
Speaker 1: although human in a bad way, whereas I think like,
Speaker 1: maybe we do need to rain this in a bit,
Speaker 1: because I think it is get a bit predatory. And finally,
Speaker 1: a group of academic researchers have proposed that social network
Speaker 1: should employ a new approach to their recommendation algorithms. These
Speaker 1: are the sets of rules that determine what content to
Speaker 1: promote to each user at any given time. Now, it's
Speaker 1: hardly controversial to say that, as of right now, recommendation
Speaker 1: algorithms tend to promote harmful material, or at least material
Speaker 1: that is more likely to create larger divisions between different
Speaker 1: populations of people, such as people who have different political leanings.
Speaker 1: The purpose of the algorithm is not too so discord.
Speaker 1: It's not to watch the world burn, it's not to
Speaker 1: create chaos. The purpose for the algorithm is simply to
Speaker 1: keep users engaged, and more importantly, to keep them on
Speaker 1: the respective platform for as long as possible. Keep them
Speaker 1: stuck to your product, because that's how you make money.
Speaker 1: You want them to stay on Facebook or Twitter or
Speaker 1: YouTube or whatever for as long as you possibly can.
Speaker 1: It's unfortunate that the stuff that tends to sow discord
Speaker 1: is particularly good at keeping people glued to these platforms.
Speaker 1: So I guess what you can say is that the
Speaker 1: algorithms themselves are not immoral. They are a moral they
Speaker 1: There's no moral judgment given to the kinds of content promoted.
Speaker 1: The algorithm is just looking for a result, doesn't care
Speaker 1: how it gets at the ends justify the means well.
Speaker 1: The researchers suggest that perhaps by purposefully designing algorithms that
Speaker 1: promote content to build bridges between people rather than fament animosity,
Speaker 1: could still keep engagement levels high while simultaneously mending fences
Speaker 1: between different populations. That if the content that's promoted supported
Speaker 1: stuff like actual discussion and some old debate rather than
Speaker 1: accusations and dehumanizing portrayals of the other side, we might
Speaker 1: see less divisiveness outside of the online world as well,
Speaker 1: because a lot of the outside world is taking its
Speaker 1: cues from what's happening on the online world. And the
Speaker 1: argument is that if we could make some conscious steps
Speaker 1: to improve things, we could see the benefits well beyond
Speaker 1: the native platforms. This is a nice thought. I would
Speaker 1: love to see it happen. The cynic in me worries
Speaker 1: that it wouldn't work, but the optimist part of me
Speaker 1: would love to see some real effort made into something
Speaker 1: like this, because the worst scenario is we could try
Speaker 1: it and it doesn't work, right, Like, that's the worst
Speaker 1: thing that could come out of it, Whereas the best
Speaker 1: thing that could come out of it is that we
Speaker 1: could actually see online communities become less polarizing, and that
Speaker 1: perhaps this could also extend to other areas of our lives,
Speaker 1: and that may be This would mean we would start
Speaker 1: to recognize where we are in agreement, as opposed to
Speaker 1: only pointing out where we have massive differences and then
Speaker 1: just escalating that to the point where people start to
Speaker 1: be harmed in the process. So I'm skimming on some
Speaker 1: of the details here, but you can read the whole paper.
Speaker 1: The whole white paper is available online. In fact, it
Speaker 1: has its own you know, kind of vanity U r
Speaker 1: L and it's bridging dot systems. And that's it for
Speaker 1: the news today, Thursday, January three. I hope you are
Speaker 1: all well. If you have any suggestions for topics I
Speaker 1: should cover in future episodes of tech Stuff, please reach
Speaker 1: out to me let me know what those are. You
Speaker 1: can do that in a couple of ways. You can
Speaker 1: go to Twitter and send me a tweet the handle
Speaker 1: for the show is tech Stuff H. S W. Or
Speaker 1: if you prefer to leave me a voice message, you
Speaker 1: can down the I Heart Radio app. It's free to download,
Speaker 1: it's free to use, and you just go over to
Speaker 1: the little search feature There you type in tech stuff.
Speaker 1: They'll take you to the tech Stuff page in the app,
Speaker 1: and there you're gonna see a little microphone icon. If
Speaker 1: you click on that, then you can leave a voice
Speaker 1: message up to thirty seconds in length and let me
Speaker 1: know what you would like to hear in future episodes,
Speaker 1: and I will talk to you again really soon. Yeah.
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