In this episode, B Crittenden and Lutie Rodriguez with guest Ariel Miller focus on recent news surrounding two popular apps: TikTok and Spotify. From biometric data collection to speech analysis on Spotify, what are these apps doing to increase audience engagement and personalization? How does that impact users’ data privacy?

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Transcript

[Musical intro, fades out]

B: Welcome to the Let's Talk series of Tech in the Arts, the podcast for the Arts Management and Technology Lab. My name is B Crittenden, and I'm the Technology and Interactive Content Manager.

Lutie: And I'm Lutie Rodriguez, the Chief Editor of Research.

B: Each month, we review trending stories and discussions with topics such as streaming, artificial intelligence, marketing, social media, inclusion, fundraising, and much more. Our goal is to exchange ideas, bring awareness, and stay on top of the trends. In this month's episode, we dive into two popular apps, TikTok and Spotify, and discuss recent initiatives, such as TikTok's incubator for Black artists and Spotify's latest personalization feature called Only You. We explore TikTok's collection of biometric data like faceprints and voiceprints, and AMT Lab contributor Ariel Miller joins us to discuss Spotify's recent patent for utilizing speech recognition technology. We hope you enjoy.

[Musical intro, fades in]

Over the past year or so, the app TikTok has made a presence in our Let's Talk episodes, specifically. And we tend to keep bringing it up over and over again and so we thought it'd be a good idea to sort of dive into it a little bit further. So we want to start off by talking about a new program that they announced in January 2021. They founded TikTok for Black Creatives, which is a three-month long initiative that really focuses on helping a group of Black creators and artists in developing their skills to help open doors for them to reach new heights in their career. The program is meant to help 100 of these artists and it also has a grant program for a selected group of creators in partnership with a multimedia company called MACRO, which represents the voices and perspectives of people of color. So, this incubator just wrapped up in early May and there are some articles that have highlighted sort of the experiences that this first group of program participants had in it.

I wanted to just mention where this came from and why this came to be in the first place because it really came out of TikTok trying to find solutions to some backlash that they have received as a platform, mostly last summer when they received some criticism from people of color on their platform, specifically, who observed censorship, content suppression, mostly coming from what we think could be algorithmic racism and targeted moderation. And so TikTok came out with a list of goals in their apology letter, and one of the things that they included was trying to create more opportunities for Black creators on the platform.

Lutie: Last summer, during a lot of the protests that were going on about racial violence, there was some sort of...TikTok called it a glitch, where it appeared that videos with the hashtag “Black Lives Matter” and, I think, “#GeorgeFloyd” appeared to have zero views. So that was something else that led them to want to create this program. But I think it's interesting…I mean, it's the case with, like, a lot of cases of algorithmic bias, where it's, like, "Well, it wasn't the intention to suppress Black creators." Or that's often what platforms say. But then you're like, "Well, it still had the result of that and it appeared to have that result," so there obviously still needs to be action taken.

B: Right, right. And I was just reading people saying that, you know, at least things are happening and they've made some more, like, specific goals for themselves. I just really also quickly wanted to talk about sort of what the program is actually doing for these creators. Apparently, more than 3,000 creators applied to the program within 24 hours of its opening in January, which is, I guess, a testament to the number of creators who are interested in this sort of thing and excited to be involved. All they had to do were be at least 18, be based in the U.S., and have at least 10,000 followers, so it wasn't necessarily accessible to every single, like, artist on the platform. They did at least have to have some sort of following, and they did try to select people who represented a pretty diverse set of focuses and interests. So, basically, what the program involved was teaching them how to develop strategies to make and fulfill goals, defining their identities, learning how to plan and understand their audiences, how to build a team, how to self-promote, so a lot of, like, lessons in marketing and branding. And there were also participants of the program who actually have said that one thing that they gained out of this was a network of other creators, both people who were participating in the program and panelists, and they did invite a lot of, like, guests on.

Lutie: Was it TikTok employees that were teaching it?

B: So TikTok partnered with a company called MACRO, which is a production and media company that really centers people of color. So it was kind of a partnership between TikTok and MACRO in terms of, like, how they were leading these sessions. But they also had guest speakers, including, like, Gabrielle Union and radio host, Charlemagne the God—a number of people who are pretty at the top of their game in terms of media. And so it was all sorts of...like, they had happy hours, they did things in breakout rooms, they have a discord now. So this is, like, where it really reminded me of, like, any sort of, like, young professionals program or graduate school where you're, like, in a cohort of people who are, like, invested in their own professional development. So, yeah, I think it's cool that they're doing it. I hope that they keep doing it, because clearly it's in high demand and they were only able to really help 100 people. And some Black creators have vocalized that, like, this program doesn't really address some of the complaints that people were having. I know one artist said, like, going into the program, they had a lot of questions about the content moderation system because that's something that a lot of Black creators run into issues with. A lot of sort of the criticism is that Black creators have experienced situations where their content is taken down or censored and they don't understand why, and perhaps they see another creator who isn't a person of color who has basically posted the same exact thing and it hasn't been taken down. And so, apparently, a lot of the people who participated in this program, they wanted to better understand the moderation system so that they could work with it so that their content wasn't being removed or censored, and apparently one creator in particular reported that the moderation system is still unclear to them. They didn't necessarily, like, figure that out because of the program. But there are other pluses to it.

So, continuing on in our examination of TikTok: Lutie, did you want to share a little bit about some privacy news we have?

Lutie: Yes. So, on June 2, TikTok updated its U.S. privacy policy to allow the app to collect biometric identifiers and biometric information from users' content. And that privacy update says that that includes things like faceprints, and voiceprints. And really, there's still a lot of vagueness about what that entails—faceprints and voiceprints—and why they're doing that, why this update came. There wasn't really any information about any product enhancements they're doing that would necessitate that. So, people are a little bit concerned to put it mildly. They did let users know with, like, a pop-up that came when you logged in. So they did inform people, but they just informed people that there was a privacy update, not about any of the specifics. So users really had to go in and take the initiative for themselves about learning what that entailed.

B: My initial reaction to this is that, first of all, like, the words "biometric data" and then "faceprints" and "voiceprints" sounds very personally intrusive. And all of our data is personally intrusive, but I think the idea of someone having a record of your face as well as your voice is, like, a little bit more jarring to a lot of people, probably, than having your behavioral data.

Lutie: Right, yeah, it definitely does sound scary, especially because TikTok didn't really provide any clear reasoning about why they're doing it. There were kind of two parts to this privacy update: one that would allow TikTok to collect more information about images and audio—which other apps also do so it can help with image descriptions on social media for those using screen readers and on the audio side, TikTok has an automatic caption feature, which would, you know, explain why they're collecting that audio information. But it also identified that visual and audio collection is for enabling special video effects, for content moderation, and for demographic classification, which I thought sounded kind of strange. I don't really know what that entails. I don't know if they would use it to, I don't know, identify the breakdown of user demographics?

B: This kind of reminds me of when we were talking about Google's third-party cookie update and how there's some risk of them starting to use systems that classify people demographically in order to, like, target people for certain content. And I would imagine that this sort of thing kind of serves the same purpose.

Lutie: Yeah, I would imagine so.

B: I'm wondering, Lutie, what you think this means for arts organizations and, like, anyone in the arts and culture industry?

Lutie: Yeah, I do know, separately, that obviously TikTok is a very popular platform right now and because of that has started to be utilized more by artists and arts organizations. I mean, for artists, it's a great way to showcase any art they're making. People are on it all the time, so it's a way to be exposed to a different group of people than maybe you are in your regular networks. And arts organizations have used it to kind of get some more engagement from young people, especially I've seen a lot of, like, museum TikToks. So, just knowing about this, for maybe an artist or arts organization thinking about getting on TikTok, knowing the risks that could come with it. And TikTok does have a privacy and security hub where they try to include all that information; I would recommend reading through it.

B: And also kind of keeping an eye on it because it is, like you said earlier, it is pretty vague at the moment. And TikTok isn't necessarily being the most transparent when it comes to why they're using this and how and have not responded yet to any, like, push for more information, and so it'll be interesting to see how that plays out. I'm kind of curious to see, like, are people going to get kind of too intimidated by this idea of faceprints and voiceprints and start to, like, push back on it? Or will there be sort of a continued complacency?

Lutie: Yeah, I can't see there being a big exodus, honestly, especially because—unless you read the privacy policy yourself when the notification came up or are reading tech news—you probably don't know about it.

B: Yeah, yeah.

Lutie: So, I did want to say that the second part of the privacy update is what covered the collection of biometric information. And just to read directly from their update, it says, "We may collect biometric identifiers and biometric information as defined under U.S. laws, such as faceprints and voiceprints from your user content. Where required by law, we will seek any required permissions from you to any such collection," which is a little bit comforting. However, the update doesn't specify which laws they're looking to—whether they're state or federal—and only a few states have biometric privacy laws, so if users are in a state that doesn't have one, TikTok could automatically start collecting that biometric information without asking any permission. Which is also suspicious, because, originally filed in May 2020, there was a class action lawsuit for the wrongful collection of biometric data, which led to a $92 million settlement for TikTok. So people are a little bit concerned that this privacy policy update is just a way to quickly cover themselves from any other such lawsuits.

B: But depending on where you are, it may or may not actually mean anything.

Lutie: Right. This lawsuit was is Illinois. Yeah, I'm a little scared. [laughter]

B: I mean, not to rag on TikTok too much because, coming off of the incubator for Black creators, a lot of artists and organizations have found great success in building audiences, especially from the pandemic, but there's also just part of it, like, that we all—both consumers and creators—can try to be a little bit more aware of and cautious of in terms of knowing what is out there, and if you don't care if your biometric data is out there, then you don't have to worry about it. But, at least, you know, knowing about it is probably good.

Lutie: Yeah. I think TikTok's algorithm, related to its data collection, is what makes it an entertaining and successful app. That the algorithm, like, pins you down so well, and it will feed you the videos that it knows you’ll be interested in. So what makes it entertaining, I guess, also makes it scary.

B: Right. Like, what makes it entertaining and accurate is what makes it a little bit scary.

Lutie: Yeah, which is kind of related to Spotify.

B: Yeah. So, Spotify, which really champions personalized music streaming catered to the tastes of individual users, it was granted a patent for speech recognition in January of this year, 2021. And today, we have a special guest with us to discuss this: AMT Lab Contributor, Ariel Miller. So, hi, Ariel. Can you just give a really brief introduction to yourself?

Ariel: Sure thing. My name is Ariel, and I did research on the patent technology that you just mentioned for speech recognition. I'd like to also mention I am an avid Spotify user, so when I saw this and saw what, you know, Spotify is trying to do and move to with their business model, I had to dive right in.

B: To start off with: can you just give an overview of what this technology is and why it's being developed?

Ariel: Yeah, so the interesting part about this technology and where I probably tried to spend the majority of my time when looking at it with the speech recognition is looking at how they actually do that. How is the machine, the machine learner, specifically, able to take information from your voice, from sounds, then process it and figure out, basically, metadata from you? Because, specifically, with the technology...I mean, speech recognition is not anything...it's not a new concept for us in 2021. But the technology that it is and that Spotify is trying to do with it is also go beyond metadata characteristics, such as gender, age, and just kind of basic characteristics that you as a user would manually put in and figure out your surrounding areas and figure out your mood and kind of where you are at that moment to figure out, out of your listening habits, what to recommend to you for your next song, next playlists...things of that nature. The speech recognition technology, the way it works is that it starts with an audio input and it filters and formats that signal. And then it retrieves that content to break it down into those content metadata that I mentioned prior: your emotional state, gender, age, and then environment. And then it retrieves that environmental metadata to figure out the physical part of where you are and then, like, your social environment. So what I mean, I guess the difference between the physical is like if you're at a busy street and it can hear that you're outside and just that you're outside, like your actual physical location, versus maybe your social environment, maybe you're outside at a park, or maybe you're outside on a busy street, or maybe you're inside and the noise is kind of quiet and so maybe it's giving coffee vibes. Like, I don't know, just different examples of, like, what the difference between, like, your physical environment and then the social environment. And then, what the machine will then do, is normalize that content. And this is where I would love to do a little bit more research and figure out if that's the reason...if that's the “why” Spotify will be able to move to a place where they can actually pair you or give suggestions on what you should listen to next without you even, like, saying anything. I don't want to get too ahead of myself, but I was actually very excited to see…I'm a Spotify user and so I believe it was April 12 of this year that I saw the wake word became a thing, which was, "Hey, Spotify." And so this is kind of Spotify's slow transition into using the speech recognition technology. It's not at the place where it's, you know, analyzing my mood yet, but I can tell, as an avid Spotify user...like, I love Spotify. Like, it's basically my first love when it comes to streaming music, so I've been using it pretty much since I could get a student discount for it, which was back in, like, 2013. So, me and Spotify, we've been through this, long and true. I was really excited to see the wake word. A little nervous, but more so excited just because it's like, "Okay, that's different, that's new." And when you say, "Hey, Spotify" kind of like, you know, "Hey, Alexa" or "Hey, Siri," you say a name, you say a title. And I'm very impressed with its efficiency in terms of just how quick...like, I've noticed, especially with, like, Siri, you can say, like, a really long sentence and that can maybe sometimes be too much information and so then it's just like pulling words. But "Hey, Spotify," it comes on immediately. Like, there's no lag, there's no pause, there's no "Did you hear me? Did you not?" It heard you, it's ready to act, and it says literally, like, it'll show you the words of what you just said. Even if there's a "Um," there's a pause, it knows that you're talking and it knows to kind of filter those things out and get to the point of what you said.

Lutie: Yeah and with that, is that voice recognition as used in Spotify available on all operating systems right now?

Ariel: Yes, yes, yes.

Lutie: Awesome. I didn't know that.

B: Yeah, definitely going to have to try that out now because I haven't explored that yet. And I think I saw in your research that Spotify used technology from the Echo Nest to develop this and make it work.

Ariel: Right, and that was something interesting that I found as well in terms of...Echo Nest is basically the reason why Spotify is able to have the model that it has and act in the way that it's acting right now, even before the speech recognition. You know, Echo Nest was created as a two-tiered approach and so in its approach, it takes data and information to give very accurate and detailed music recommendations, and so that's kind of the reason why I feel like Spotify has been able to have the longevity that they've had as a music streaming platform, as they were probably one of the first. Echo Nest really just kind of gave birth to their ability to be very efficient and very just pristine with the selection of music that came to you. They really looked at and observed your listening behaviors and some of the new artists or songs that you replayed or songs that you liked, to the point where by the time you get a recommendation, you're already halfway intrigued because it's so aligned with what you were listening to previously. And so, in regards to, you know, Echo Nest being a big contributor to Spotify and their technology, I'd say it's a big contributor just to their overall platform and being able to move forward with some of the studies and research and really their inspiration for certain patents to kind of take things to the next level.

B: Going back, the main difference between their past methods of data tracking and data tracking now with this speech recognition technology is that now, rather than just data based on listening behavior, the data is coming from their environment as well as their emotional states. In your research, you talk a bit about how musical preferences can reflect these big five personality traits, which I thought was really interesting and I was hoping you might talk about that a little bit and how that is reflected in this technology.

Ariel: Yeah, I found that very interesting, as well. Their previous research, done by Spotify's research and development team, they looked at the Big Five inventory, which is what you were referring to. And the Big Five is just, you know, your openness, your conscientiousness, your extroversion, agreeableness, and then your emotional stability. And the importance or the significance of that research is that that was something that they were able to do and monitor only to a certain degree, because that's what...it necessitated the need for users to manually input information in those metadata characteristics that I kind of touched on earlier in terms of, like, your age, your gender, where you are, what's going on. It really required you. You were kind of the middle...the user is the middleman to some of that information. And I think, from that research, they definitely wanted to cut the middleman out. You know, in terms of just research purposes and trying to make everything efficient, you kind of want to eliminate as many steps as possible. And so, having speech recognition and them having that patent, it allows for them to take metadata characteristics from your surroundings—like you said, it's from your environment—so that you don't have to worry about, "Okay, well, is Ariel female? Is Ariel a student? Is Ariel from this part of the country or that part of the country?" We can now have our machines pick up on certain cues about certain environments and certain areas and make that decision or make that determination for itself. And, on one hand, that's, like, cool, but in my opinion, it's freaky cool. Because it's like, to a certain extent, I mean, I kind of like that I'm able to be the middleman and kind of give the cue to Spotify. I love it and I can...even over the years, I think Spotify is one of those apps that really helped me understand, like, how my data is being tracked or how, like, what an algorithm is, basically. You know, we all use social media, or at least I use social media, but I didn't understand the term "algorithm" with social media more than I did with Spotify because I see based on what I'm actually listening to you and then what's popping up and then what comes next or the level of personalization that Spotify is able to do. I'm just, like, on one hand, like, "Wow, like, you really know me. You get me. Like, it's great." Then on the flip side, it's like, "We're getting very intimate in terms of, like, you're going to be listening to me." So now it's like, I just say something and now you're just like, "Oh, Ariel, you're having a sad day. Let's go to that song that you like to listen to when you're sad." And, you know, convenience versus creepiness. I don't know, just seeing the research that they've done with the Big Five inventory and seeing how that really inspired them to push forward and try to figure out ways to get around that and find other ways to measure those five key components.

Lutie: So, as we talked about earlier in the show, TikTok recently added into its privacy policy the ability to collect biometric information from its users, like faceprints and voiceprints. This new speech recognition technology from Spotify also kind of opens the door to Spotify being able to collect that kind of biometric data from its users if it wanted to. So, I'm just curious about your thoughts about possible privacy concerns with these new features on Spotify.

Ariel: Yeah. I'd be lying if I said I wasn't concerned. And then also, I do identify as a millennial and I think it's very interesting, just the kind of common attitude that my generation has with this sort of topic in terms of privacy for our information. I think we all kind of understand, like, if you're going to be on the internet, like, it's...what privacy? Like, somebody's going to get their hands on it some way or another. And so, on one hand, while we can all kind of be okay with that, looking at the improvements and updates of Spotify, I think that that just goes to show, with the speech recognition and kind of like what I said before, like, it already knows so much about me and because I love Spotify so much and I see it in real time, like, how it's happening, I've kind of already made the decision for myself that, "Alright, I'm okay with that." And because I know what's going on, it makes it easy for me to kind of...not get ahead of it, but it's like, okay, if I play this artist 10 different times, like, I know to expect the next newest release. I know what to expect in terms of what Spotify is going to do next. And I think that is...when we talk about speech recognition and them including that in the business model, I think that's where a lot of the concern comes from. It's like, "Okay, so what are you going to do next?" Like, yes, you're going to be recommending song to me. I feel like they've done a good job of kind of trying to answer that question and make it all about, "It's just purely so we can continue to give you convenience as you're listening and personalize your, you know, your listening experience." And that's well and dandy but also too, there's something very intrusive about it. Like, you're literally taking information of where I'm at, like, what if I don't want you to know where I'm at?

This is where it kind of seeps into that whole government regulation part and just, like, what are the boundaries? What are the constraints in terms of like how far you can use this information? All that to say, it's definitely something that I'm concerned about. I think it's 50/50 for me in terms of, like, I'm 50% excited and like, "Wow, that's actually kind of amazing. Like, look at our technology. Look at it go. Look at its improvement." But then on the other hand, for me, it definitely continues to raise that awareness of, like, yeah, this is great. But, like, are we also creating a monster? Are we feeding a bigger monster that we still haven't figured out how to tame? Like, we're still trying to find regulations and solutions, so as this thing, like, we all see that it's going to continue to advance. And at this rate, it's skyrocketing, but if it gets to a point where we ourselves as humans and the people who are programming and coding these things don't have a handle on it, like, what does that look like then? And people might say that it gets morbid or you're over-exaggerating, but I think it is a fair question.

B: Definitely. I also think, just from the user's perspective, there are a lot of simple questions that I'm not sure Spotify has an answer to at this point. Like, who is listening? Which...you know, it's a machine, but you know. Who has access to the data? When are you listening? Are you ever not listening or are you constantly listening? And are you only listening when the app is open? And then, for how long is that data stored? And can I have access to it?

Lutie: Are they always queuing up playlists for you, even when you don't have the app open?

B: Just a lot of questions that come up that, at least from what I've seen, there isn't necessarily transparency around it.

Ariel: I agree. I think they're doing a really good job of kind of tiptoeing around that. It's really just about, "No, we can give you your next song. We can...you know, you don't have to type anything in. You don't even say much. We can just press play without pressing play." And it's like, "That's great. But, like you just said, like, so does that mean, you're always listening?" Or who's listening? Like, just, again, the boundaries of it.

B: Yeah, yeah. And they're certainly not unique in that. Lutie and I talked about how TikTok's latest privacy news was quite vague. It leaves people with a lot of questions and concerns. I think it'd be good to wrap up by, I guess, addressing where they are in the process now. Like, in terms of timeline, where are we in the rollout?

Ariel: Yeah, yeah. And that's kind of where I go back to the "Hey, Spotify." The big deal that is that, as we're sitting here talking about their vagueness in terms of, like, what speech recognition really looks like, I think, "Hey, Spotify" is kind of their way of easing their users and people into the technology. They're still working on it. They're still working out kinks. It's something, from what I can tell, I don't think it's something we're going to see tomorrow. But I would give a strong prediction that, definitely, within the next two years, if that, at the latest. Just because I think "Hey, Spotify," especially when it released, there was mention of that being kind of the...not the beta test, but just, again, something to kind of ease you into it and get it into your regular habits, if you will. And so, when it does get to the point where it's like, yeah, Spotify can know what you're up to, know what you're going to say before you say it, you're not as weirded out as we are right now. And it's funny, because I kind of...I compare that. I feel like it's a parallel to Alexa and all of our other AI assistants. You know, it's in your house and it's always on and it's always ready and it's always listening. You know, it's interesting to see kind of how, like, Spotify is definitely going in that direction, and so you start with a wake word and then you go to, you're just there, you're my friend waiting to go. And, you know, as a consumer, again, convenient, cool. But also, like, there's a reason why we have signals and cues, because at least then you knew that I need to say, "Hey, Alexa," I need to say, "Hey, Spotify," I need to say, "Hey, Siri," before you just start listening to me. Now, the curtain is gone. There is no door to open, there is no door to knock.

B: Right, right.

Lutie: I definitely think what you said about easing into it is true. The level of data that social media collects now, any app, if that would have happened when people first started using smartphones and social media and apps, I don't think we would have been okay with it, but it's been a gradual process, so....

Ariel: The timeline is gradual, and right now, they are at, "Hey, Spotify." They're in their wake word process.

B: Well, thank you so much. This was great. I'm kind of excited to check out my Spotify app now and talk to it for a while.

Ariel: Thank you for having me on. I'm really flattered.

B: So another area of Spotify that we wanted to examine today comes out of sort of a recent feature that they've just come out with. For any of our listeners who are streaming their audio content on Spotify, you may have seen their new Only You feature, which is essentially a hyper-personalized area within Spotify now that is essentially creating, like, personalized experiences for each user based on their in-app behavior and their in-app listens. So, some examples of the type of playlist sets that they have are your audio birth chart, which is, to clarify, not based on your actual date of birth. It's just kind of using that language to create three different, like, artists: one that shows your emotional side, one that shows your most listened to. It also gives you the opportunity to create your dream dinner party. And then something—which I think is kind of cool, personally—it's a feature called Made for Two, which allows you to invite another Spotify user to create a playlist with you, and the technology basically, like, mixes your two tastes to create a mix for you and the other user that's, like, catered to the two of you. So you could invite a friend to make a mix with you and then, like, listen to it together and it'll be, like, personalized to that pair of people. I know a lot of people have a lot of opinions about Spotify. We've talked about Spotify a lot in our Let's Talk over the last year. But, I do think Spotify is an excellent example of a company that has realized how reactive audiences are to personalization and customization and has really catered to that.

Lutie: I have to say—I was not expecting this. I mean, I've come to expect my Spotify Wrapped at the end of every year and have started to prepare myself for it.

B: Yeah. Same. For anyone who doesn't know, Wrapped is, like, basically, a year in review for users' listening data. So it'll say, "In 2020, you listened to this many hours of podcasts," or "These are your top listened to songs" or "your most listened to artists."

Lutie: This one came as a shock and I honestly felt a little bit more creeped out by it than the usual ones, mainly because one of mine was telling me what song I listen to most at night. [Laughter] I'm like, "I'm aware. I don't really want this app telling me what I listen to at night." I don't know. I think this is the first time that there was, like, a timestamp to my listening.

B: Yeah

Lutie: ...which they obviously have. But to have it presented to me felt a little strange.

B: No, it is strange. I think some people are a little bit creeped out by it, you know, like you are. But at the same time, these features—both Wrapped and now Only You—create a huge response. Like, during the 2020 Wrapped season, Spotify's stock jumped up 16% and the app rose rapidly in the App Store ranking. So people are very responsive to this, whether they're creeped out or whether they're having a positive response to it. And I think, either way, one thing that is actually really brilliant of Spotify is that not only do they give you this data, it's like visualized and designed in a way that people are excited to share it and they're able to easily share it on social media. So it almost has, like, a viral-like quality to it that makes other people also want to see what data exists about their own behavior in Spotify. And I think that has a lot to do with the visualizations and the ability to share it easily on social media.

Lutie: No, I think what you said about it being viral is definitely true because for the few days around when these types of features come out, Instagram Stories are, like, covered with people sharing theirs. And this Only You thing makes me think even more that Spotify is attuned to this because people like sharing things that are unique about themselves, which is what this one was centered around.

B: Yeah, and I think artists and organizations can definitely look to them in terms of the success they've had in customizing and personalizing experiences for their audiences because people are very responsive to it and very excited about it, and I think this model, while it won't look the same for everyone, is something that we can all be inspired by, I think.

Lutie: Yeah, I was just thinking a little bit about how that could be implemented by an arts organization. And, yeah, like, just thinking about, like, a symphony, for example: maybe they had one concert that was, you know, most popular out of the whole season. They could come out at the end of the year and be like, "Our patrons loved X performance," or maybe, like, "We had the most new attendees at X performance." So it's kind of more difficult to have that, like, extremely personal, like, "This is what you listen to," but I think people like hearing about, like, demographic information about attendees.

B: Yeah, definitely. You know, even something like incorporating some sort of voting system into your programming. Or, now that so much, like, performing arts content has been digitized and can be streamed, we can absolutely kind of be looking at how we can be using data to customize and personalize audiences' experiences on our streaming platforms.

Lutie: I mean, also, symphonies have Spotify profiles, so...something fun to share on social media.

B: Yeah, and people are responsive to playlists.

Lutie: People love playlists. Yeah. Just to shout out the LA Phil: I think their digital stuff during the pandemic was some of my favorite and, for each performance, they had a playlist on Spotify to go along with it. And it wasn't just the pieces performed in that concert, it was kind of, like, “inspired by.”

B: No, that's a great example. This was a good examination of two apps that people are using a lot these days, both sort of some questions or concerns some people might be having, specifically, like, privacy and security related, and some interesting features that are kind of examples of some potentially positive things that are being done with these apps. So, thanks for the discussion, Lutie.

Lutie: Yeah, of course.

Thanks for listening to the AMT Lab podcast. Don't forget to subscribe and to leave a comment. If you would like to learn more, go to amt-lab.org. That is A-M-T dash L-A-B .org. Or, you can email us at amtlabcmu@gmail.com. You can also follow us on Twitter or Instagram at Tech in the Arts, or on Facebook or LinkedIn at Arts Management and Technology Lab. You can find the resources that we referenced today in the show notes. Thanks for listening. See you next time.

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