Google Glass

When augmented reality converges with AI and the Internet of Things

The confluence of augmented reality, artificial intelligence, and the Internet of Things is rapidly giving rise to a new digital reality.

Remember when people said mobile was going to take over?

Well, we’re there. Some of the biggest brands in our world are totally mobile: Instagram, Snapchat, Uber. 84% (!) of Facebook’s ad revenue now comes from mobile.

And mobile will, sooner or later, be replaced by augmented reality devices, and it will look nothing like Google Glass.

Google Glass
Not the future of augmented reality.

Why some predictions fail

When viewing trends in technology in isolation, it’s inevitable you end up misunderstanding them. What happens is that we freeze time, take a trend and project the trend’s future into a society that looks almost exactly like today’s society.

Past predictions about the future
Almost.

This drains topics of substance and replaces it with hype. It causes smart people to ignore it, while easily excited entrepreneurs jump on the perceived opportunity with little to no understanding of it. Three of these domains right now are blockchain, messaging bots, and virtual reality, although I count myself lucky to know a lot of brilliant people in these areas, too.

What I’m trying to say is: just because it’s hyped, doesn’t mean it doesn’t deserve your attention. Don’t believe the hype, and dig deeper.

The great convergence

In order to understand the significance of a lot of today’s hype-surrounded topics, you have to link them. Artificial intelligence, smart homes & the ‘Internet of Things’, and augmented reality will all click together seamlessly a decade from now.

And that shift is already well underway.

Artificial intelligence

The first time I heard about AI was as a kid in the 90s. The context: video games. I heard that non-playable characters (NPCs) or ‘bots’ would have scripts that learned from my behaviour, so that they’d get better at defeating me. That seemed amazing, but their behaviour remained predictable.

In recent years, there have been big advances in artificial intelligence. This has a lot to do with the availability of large data sets that can be used to train AI. A connected world is a quantified world and data sets are continuously updated. This is useful for training algorithms that are capable of learning.

This is also what has given rise to the whole chatbot explosion right now. Our user interfaces are changing: instead of doing things ourselves, explicitly, AI can be trained to interpret our requests or even predict and anticipate them.

Conversational interfaces sucked 15 years ago. They came with a booklet. You had to memorize all the voice commands. You had to train the interface to get used to your voice… Why not just use a remote control? Or a mouse & keyboard? But in the future, getting things done by tapping on our screens may look as archaic as it would be to do everything from a command-line interface (think MS-DOS).

XKCD Sudo make me a sandwich
There are certain benefits to command-line interfaces… (xkcd)

So, right now we see all the tech giants diving into conversational interfaces (Google Home, Amazon Alexa, Apple Siri, Facebook Messenger, and Microsoft, err… Tay?) and in many cases opening up APIs to let external developers build apps for them. That’s right: chatbots are APPS that live inside or on top of conversational platforms.

So we get new design disciplines: conversational interfaces, and ‘zero UI’ which refers to voice-based interfaces. Besides developing logical conversation structures, integrating AI, and anticipating users’ actions, a lot of design effort also goes into the personality of these interfaces.

But conversational interfaces are awkward, right? It’s one of the things that made people uncomfortable with Google Glass: issuing voice commands in public. Optimists argued it would become normalized, just like talking to a bluetooth headset. Yet currently only 6% of of people who use voice assistants ever do so in public… But where we’re going, we won’t need voice commands. At least not as many.

The Internet of Things

There are still a lot of security concerns around littering our lives with smart devices: from vending machines in our offices, to refrigerators in our homes, to self-driving cars… But it seems to be an unstoppable march, with Amazon (Alexa) and Google (Home) intensifying the battle for the living room last year:

Let’s converge with the trend of artificial intelligence and the advances made in that domain. Instead of having the 2016 version of voice-controlled devices in our homes and work environments, these devices’ software will develop to the point where they get a great feeling of context. Through understanding acoustics, they can gain spacial awareness. If that doesn’t do it, they could use WiFi signals like radar to understand what’s going on. Let’s not forget cameras, too.

Your smart device knows what’s in the fridge before you do, what the weather is before you even wake up, it may even see warning signs about your health before you perceive them yourself (smart toilets are real). And it can use really large data sets to help us with decision-making.

And that’s the big thing: our connected devices are always plugged into the digital layer of our reality, even when we’re not interacting with them. While we may think we’re ‘offline’ when not near our laptops, we have started to look at the world through the lens of our digital realities. We’re acutely aware of the fact that we can photograph things and share them to Instagram or Facebook, even if we haven’t used the apps in the last 24 hours. Similarly, we go places without familiarizing ourselves with the layout of the area, because we know we can just open Google Maps any time. We are online, even when we’re offline.

Your connected home will be excellent at anticipating your desires andbehaviour. It’s in that context that augmented reality will reach maturity.

Google Home

Augmented reality

You’ve probably already been using AR. For a thorough take on the trend, go read my piece on how augmented reality is overtaking mobile. Two current examples of popular augmented reality apps: Snapchat and Pokémon Go. The latter is a great example of how you can design a virtual interaction layer for the physical world.

So the context in which you have to imagine augmented reality reaching maturity is a world in which our environments are smart and understand our intentions… in some cases predicting them before we even become aware of them.

Our smart environments will interact with our AR device to pull up HUDs when we most need them. So we won’t have to do awkward voice commands, because a lot of the time, it will already be taken care of.

Examples of HUDs in video games
Head-up displays (HUDs) have long been a staple of video games.

This means we don’t actually have to wear computers on our heads. Meaning that the future of augmented reality can come through contact lenses, rather than headsets.

But who actually wants to bother with that, right? What’s the point if you can already do everything you need right now? Perhaps you’re too young to remember, but that’s exactly what people said about mobile phones years ago. Even without contact lenses, all of these trends are underway now.

Augmented reality is an audiovisual medium, so if you want to prepare, spend some time learning about video game design, conversational interfaces, and get used to sticking your head in front of a camera.

There will be so many opportunities emerging on the way there, from experts on privacy and security (even political movements), to designing the experiences, to new personalities… because AR will have its own PewDiePie.

It’s why I just bought a mic and am figuring out a way to add audiovisual content to the mix of what I produce for MUSIC x TECH x FUTURE. Not to be the next PewDiePie, but to be able to embrace mediums that will extend into trends that will shape our digital landscapes for the next 20 years. More on that soon.

And if you’re reading this and you’re in music, then you’re in luck:
People already use music to augment their reality.

More on augmented reality by me on the Synchtank blog:
Projecting Trends: Augmented Reality is Overcoming its Hurdles to Overtake Mobile.

Mood augmentation and non static music

Why the next big innovation in music will change music itself — and how our moods are in the driver’s seat for that development.

Over the last half year, I’ve had the pleasure to publish two guest contributions in MUSIC x TECH x FUTURE about our changing relationship with music.

The first had Thiago R. Pinto pointing out how we’re now using music to augment our experiences and that we have developed a utilitarian relation with regards to music.

Then last week, James Lynden shared his research into how Spotify affects mood and found out that people are mood-aware when they make choices on the service (emphasis mine):

Overall, mood is a vital aspect of participants’ behaviour on Spotify, and it seems that participants listen to music through the platform to manage or at least react to their moods. Yet the role of mood is normally implicit and unconscious in the participants’ listening.

Having developed music streaming products myself, like Fonoteka, when I was at Zvooq, I’m obviously very interested in this topic and what it means for the way we structure music experiences.

Another topic I love to think about is artificial intelligence, generative music, as well as adaptive and interactive music experiences. Particularly, I’m interested at how non-static music experiences can be brought to a mass market. So when I saw the following finding (emphasis mine), things instantly clicked:

In the same way as we outsource some of our cognitive load to the computer (e.g. notes and reminders, calculators etc.) perhaps some of our emotional state could also be seen as being outsourced to the machine.

For the music industry, I think explicitly mood-based listening is an interesting, emerging consumption dynamic.

Mood augmentation is the best way for non-static music to reach a mass market

James is spot-on when he says mood-based listening is an emerging consumption dynamic. Taking a wider view: the way services construct music experiences also changes the way music is made.

The playlist economy is leading to longer albums, but also optimization of tracks to have lower skip rates in the first 30 seconds. This is nothing compared to the change music went through in the 20th century:

The proliferation of the record as the default way to listen to music meant that music became a consumer product. Something you could collect, like comic books, and something that could be manufactured at a steady flow. This reality gave music new characteristics:

  • Music became static by default: a song sounding exactly the same as all the times you’ve heard it before is a relatively new quality.
  • Music became a receiving experience: music lost its default participative quality. If you wanted to hear your favourite song, you better be able to play it, or a friend or family member better have a nice voice.
  • Music became increasingly individual: while communal experiences, like concerts, raves and festivals flourished, music also went through individualization. People listen to music from their own devices, often through their headphones.

Personalized music is the next step

I like my favourite artist for different reasons than my friend does. I connect to it differently. I listen to it at different moments. Our experience is already different, so why should the music not be more personalized?

I’ve argued before that features are more interesting to monetize than pure access to content. $10 per month for all the music in the world: and then?

The gaming industry has figured out a different model: give people experience to the base game for free, and then charge them to unlock certain features. Examples of music apps that do this are Bjork’s Biophilia as well as mixing app Pacemaker.

In the streaming landscape, TIDAL has recently given users a way to change the length and tempo of tracks. I’m surprised that it wasn’t Spotify, since they have The Echo Nest team aboard, including Paul Lamere who built who built the Infinite Jukebox (among many other great music hacks).

But it’s early days. And the real challenge in creating these experiences is that listeners don’t know they’re interested in them. As quoted earlier from James Lynden:

The role of mood is normally implicit and unconscious in the participants’ listening.

The most successful apps for generative music and soundscapes so far, have been apps that generate sound to help you meditate or focus.

But as we seek to augment our human experience through nootropics and the implementation of technology to improve our senses, it’s clear that music as a static format no longer has to be default.

Further reading: Moving Beyond the Static Music Experience.

10 Lesser-Known Tools for Music Discovery

Radio, streaming services, social networks – everyone has their own way to discover new music. Meanwhile, there are dozens of entrepreneurs out there who believe they have a better way. Here are some of the best ones out there.

 

cmd.to fm

http://cmd.to/fm

cmd.to fm screenshot

How it describes itself: This is not your mothers radio. Listen awesome tunes from cmd.fm’s curated playlists.

How it works: It’s radio powered by a command-line interface. To keep it easy, it lets you click on the most essential commands. Player controls are activated by typed commands. All music appears to come from Soundcloud.

First impression: Fun! And I’m pretty sure this is how hackers listen to music. Does this make me a hacker?

 

MagicPlaylist

https://magicplaylist.co/

MagicPlaylist screenshot

How it describes itself: Get the playlist of your dreams based on a song.

How it works: You type the name of a song in a search box and it automatically generates a Spotify playlist with 30 other tracks.

First impression: It succeeds because it doesn’t let itself fail: generating a playlist from one track doesn’t create huge expectations, so it doesn’t disappoint. The playlists are not amazing, but it works as a quick way to pick a theme and have some music to listen to.

 

Cymbal

https://cymbal.fm/

How it describes itself: Discover songs the world is falling in love with.

How it works: Cymbal is a music social network that looks and feels a lot like Instagram.

First impression: Easy to use, because they make use of familiar interfaces. They make it easy to share content outside of the app, which is important in the early stages of social networks. Upon first try they really show you where the content is, so you immediately have something to check out. The onboarding process has too many steps and needs work. Ideally, you let people use the app ‘immediately’ and guide them through it, nudging them step by step to connect other accounts, etc.

As a social network, you need a certain critical mass to let users retain each other, so they should consider how to improve sharing the content outside the app in such a way that:

  1. Users will use the app, even if their friends are not on there;
  2. The content becomes so engaging that their friends will join.

 

trbble

https://trbble.com/

trbble screenshot

How it describes itself: Discover new music by listening to a song’s best part first!

How it works: trbble sources music from Soundcloud and lets users define the most important part of the song, so others can get a quick impression of it. This 30-second clip is then called a trbble. The playback and upvote count of your trbbles is displayed on your profile. So there’s an incentive for active users to provide music for passive users.

First impression: Found it hard to get used to the interface, but there’s a use case to explore. trbbles could perhaps provide a passive stream for DJs to listen through a lot of music, instead of actively skipping through tracks. I think conceptually it could be interesting, but needs to simplify its interface.

 

A Song a Day

http://www.asongaday.co/

A Song a Day screenshot

How it describes itself: Music from humans, not robots, delivered to your inbox every day. Because people are cool.

How it works: Give your email address, select which genres you like, and maybe select a curator. From that point you’ll receive new music recommendations, every day, in your inbox.

First impression: What I really like about the way it’s designed is that at every moment in the sign-up process, you can either give your preferences or say screw it, just send me some music. Simple and does what it says. I could imagine this having some growth potential.

 

Rising.fm

http://rising.fm/

Rising.fm Screenshot

How it describes itself: Music charts powered by Soundcloud.

How it works: It looks at data from “social media sites” and has a simple ranking algorithm to come up with charts. It’s basically an easy way to discover popular and trending music on Soundcloud.

First impression: Works well for the default tags and very popular search phrases, but if you go a bit more obscure, you get no results (eg. psytrance, goa). Even ‘trance’ returned just 6 results of which 3 were not trance. Perhaps it’s just not tracking the right blogs for that.

 

22tracks

http://22tracks.com/

22tracks screenshot

How it describes itself: 22tracks is a brilliantly curated playlist service, run by 120 expert and influential DJs from Amsterdam, Brussels, London and Paris.

How it works: The service appoints curators for genre-based playlists in each city. The curators are mostly local DJs, journalists, etc. with many being known within their scenes worldwide. Each playlist consists of 22 tracks and is updated regularly. You can save tracks to your own 22 track playlist.

First impression: Very cool concept, and so simple. They seem to monetize through brand partnerships, but I imagine they should be able to monetize part of their userbase at a low price point (between $1 and $4 per month) for additional mobile features like offline syncing, personalization, and perhaps exclusive premiers.

 

Chew.tv

https://chew.tv/

Chew.tv screenshot

How it describes itself: DJs everywhere. Right here.

How it works: DJs can livestream their DJ sets on the platform, but you can also rewatch sets later. You can find all kinds of electronic music on the site, basically: if you can imagine it, they’ve got it.

First impression: Fun. Takes me back to when I would put Boiler Room sets on my TV all day long. This is a bit more personal, as you can follow DJs and also engage with other listeners through the chat function. In terms of music discovery, it would be nice to have some type of dynamic tracklist, but having a phone with Shazam handy has done the trick for me so far. And else you can always just tweet a DJ to ask about that track you must find!

Check out my interview with Will Benton from Chew.tv.

 

Wonder

http://wonder.fm/

Wonder screenshot

How it describes itself: Wonder is a platform that simplifies indie music discovery — a place to hear what’s new as soon as it’s released.

How it works: Wonder uses some ranking mechanism to find trending tracks on Soundcloud and then presents 99 one of them to the user. Some research suggests that after the algorithms surface tracks, some human curation is involved.

First impression: Wonder is a great way to find hot new tracks before they make it to the charts. I personally enjoy Primary and Whitelabel off-shoots more, which represent hiphop and dance music respectively. Very high quality tunes. Throw out your radio.

 

Muru

http://murumusic.com/

Muru screenshot

How it describes itself: Create your own music journey.

How it works: You pick a genre as departure point, another genre of where you want to go and then the app creates a playlist that builds from the former to the latter. You can adjust the tempo, energy, popularity, and vocal-drivenness of the tracks in your playlist, as well as the length of the playlist.

First impression: There’s quite a bit of work to be done. For one, it’s currently iOS-only, and you have to connect to Spotify. The authorisation process is a bit of a pain in the butt when first launching the app, especially if you just want to try it. I’d move the ‘Connect to Spotify’ step to after playlist creation. That way you already have commitment from the user. To avoid disappointment, the necessity for Spotify should be communicated upon launch. I also wasn’t able to find the genres I prefer, because they’re not available in the app yet.

There’s plus points too: the app’s design is neat and the playlists it creates are interesting. This is in part by the concept of genre journeys: you immediately start to wonder how the app is going to transition from Blues to EDM.

Our changing relationship with music and its new practical function

back in my day music players

Music executives need to understand how shifting context and function have changed music consumers and their expectations.

Guest contribution by Thiago R. Pinto.
Portuguese version.

Part I

So, the music industry has changed. If you haven’t been living in a cave for the past 15 years you probably noticed. For those who need to catch up, here are the 3 main points that summarize it:

  • increased access to the means of production;
  • increased access to information;
  • democratization of distribution channels.

But some things remain unchanged by this digital revolution. Royalties distribution, for example. The correct distribution of copyright royalties is still a headache for composers, musicians and labels. Despite music having been practically dematerialised and living on networks where everything is trackable. Companies like Kobalt are trying to change this game, but we still have a long way to go until we get this right. This is an issue that deserves its own article, so I’ll leave it for now.

Among the lasting habits that have been practically untouched along these 15 years, my personal highlight goes to a mantra I hear in every conference, article and talk about music. It goes something like this: people’s emotional/behavioural relationship with music hasn’t changed. We still love music the way we always did.

Part II

A couple of weeks ago I was reading a report published by Vevo where in its introduction Erick Huggers, Vevo’s CEO, once again repeats the mantra:

vevo report

Well, I don’t know where Huggers and others are looking, but I can’t believe that they still don’t see something that it’s in everyone’s face. This relationship has changed! C-H-A-N-G-E-D. I would write it upside down if I could.

Before we move on with the subject, I just want to make one thing clear: yes, music still moves crowds of people. Yes, it is more listened than ever. And yes, artists still have a lot of influence. However that doesn’t mean people still relate to music the same way they used to.

Probably there is no other cultural activity that is so universal, that permeates, affects and shapes human behaviour as much as music, said Alan P. Merriam in The Anthropology of Music. However, music’s own definition evokes a variety of philosophical, cultural and even political questions. Musicologists suggest that its definition is directly related to the social context and function of certain behaviours in a particular culture. In my opinion, these two words — context and function — define a fundamental element, so many times forgotten, of the discussion: the formation of our musical preferences.

The changes in the way we build our tastes and preferences are the things that should be analyzed, so that we can understand why today music has a new function and also why we can no longer blindly support ourselves on arguments like the one above by Huggers, especially if it is presented in an music industry context. To understand context, function and how today these issues have altered people’s relationship with music, we must go back in time.

Part III

Music always had context and function. In the early days, when we were still just tribes, music used to have spiritual functions. Variety didn’t exist, neither was music entertainment. One’s tribe music was all that there was to listen to and it was directly related to celebration of the tribe’s beliefs. In other words, music was attached to religion. In this context, forget about music preference. People will listen to what the Chief says.

We evolved into more complex societies where we began to be divided into social classes. There were the nobles, the bourgeois, and the clergy. Then came everyone else. At this time the culture each one of these groups had access to, was a fundamental tool for social distinction. For the rich there were good instruments, good musicians, and concert halls. There was classical music. For the rest there were rudimentary instruments, self-taught musicians and taverns. There was folk music. In that context, musical preference was a status symbol and it showed to which social class one belonged.

2 hippies at a festival
Music had a fundamental roll in the formation of the hippie culture, being a tool for the creation of a collective identity.

During the 20th century the development of consumer societies gave new meaning to all goods produced. Especially after World War II, we started living in a society where for the first time supply was greater than demand. At this point there were a great number of companies offering very similar products and services. The technical differentiation between these goods gave space to brand personality construction and so we began consuming products not only for their quality but also because we identify with them. We started to use consumption as a way to build individual and collective identities.

In this process, cultural goods — specially music — were extremely important. Musical preference was a key element in defining ones personality, particularly among the youth. It was what defined which group a person belonged to, which ideology he or she followed, and in what values he or she believed in, independent of what was his or hers social-economical background. In that context, music preference was about identity.

Part IV

We arrived at the beginning of the 21st century and all these functions — spiritual, social and identity building — still exist. The difference is that now they’ve lost strength and no longer are the pillars that define our musical preference. The 3 key elements of the digital revolution (access to the means of production, access to information and democratization of distribution channels) created a new context to music consumption having a direct impact in the way new generations are building their musical preferences.

Never before in history have we had access to so much music, for such a low cost and at such a high speed. The access difficulty, which in my opinion was a key element in keeping our preferences so narrow, was eliminated from the equation. At 15 (in 1998) I had a proud collection of roughly 100 CDs as a result of the musical choices I made. Today a teenager with the same age has access to humanity’s music library only a few clicks away.

Part V

The platforms in which we consume music have also changed. The introduction of the iPod started transforming music consumption into a private experience which allowed people to try out new music genres without worrying about their social image.

Listening to music on the metro
Music consumption habits were strongly impacted by the introduction of digital portable devices and headphones.

Through the ease of access and popularization of new platforms, music started being ubiquitous. The frontiers to experimentation were then opened and brought new tastes and the permission for listeners to break up the social identity chains of each genre allowing the free flow between a variety of different styles of music. It was the beginning of the process that freed music from its function as an identity building tool. At this point a new function for music emerges: the practical function.

Part VI

Music started to be used according to the activities and tasks that listeners were performing during their daily routines. Like this, music preference that before was an almost immutable passion built through context, today looks like a chameleon changing from moment to moment.

We are living the age of “I love this music, but at the right moment”, we see the creation of a generation of eclectics that use music in very practical ways, a generation where the mood related to an activity is more important than genre. Need to study? Downtempo or classical. Going to the gym? EDM or hip-hop. Time for cooking? Indie folk or jazz. Going to a party? Techno or trap. In other words, the experience is not in the music itself, but in what we do while while listening to it. In this context it is interesting to realize how we can look at today’s music services with new eyes. Last.fm is a great example.

Last.fm was one of the first social networks to use music to establish connections between users based on their music preferences. It identifies all tracks and the related artists played by its users and utilizes this data to build a personal music history. The initial goal was that from this list of most played artists the user’s musical preferences would arouse. If a person listens to Beethoven, Mozart and Bach a lot then classical music must be his or her preference.

But following the aforementioned argument, that music today has a practical function in people’s life, we can not accept this conclusion so fast. Classical music today is consumed a lot by people while they work and, in this case, we have to also consider that classical may not be their preference, but just the genre that follows her main daily activity: work. If the tasks we perform during the day are what are going to define what we will listen, and not our musical preference for a specific genre, than we can say that today, Last.fm does not present the musical preferences of its users, but a list of the activities they engage the most in.

While in Last.fm’s case we can consider that this data is generated “accidentally” as a service sub product, to Spotify the perception of the new practical function of music was fundamental to the development of its UX.

Spotify was one of the first major services to understand that to this new generation of listeners, the stars of streaming services are not songs and artists, but playlists and moods. Spotify’s user experience is built around these two elements, because the company understood that its users do not solely use the service for contemplation, but use music as a fuel for another activity. It was the first time I saw a service put together moods and genres side by side, presenting a perfect mirror for this profound change in music consumption behaviour.

By focusing on moods and playlists, Spotify helps its users to quickly find a perfect selection of music to whatever activity he or she is engaging in, without having the headache of searching through 30 million songs to find the perfect ones for the moment.

Spotify workout playlists

Spotify mood playlists
Spotify and its long list of mood and activity playlists.

Part VII

Now that we‘ve gone through the new practical function of music, how it changed the formation of our musical preferences, how it changed our relationship with music and finally how we can have a new look on services and business strategies, I want to go back to the focal point to this article which is the mantra “we still love music the same way we always did”. I’ll once again quote Vevo’s CEO Erick Huggers to present my counterpoints:

“Music creates transformative experiences. It has the power to connect people in personal and meaningful ways unlike any other medium.”

No, it is not music that creates the experience. Music is the background that helps to set the mood. The activity which people are engaging in is what connects people (with themselves or others). It is the Saturday lunch with friends, the picnic at the park, the music festival with 40.000 people in the middle of the desert.

“For music fans, it’s an essential part of how they live their day-to-day lives.”

I believe this statement is true only if we understand that music is an essential part of this new generation of listeners, because it gives the key to the activities they will engage in and not because — like in the past — it was used to build their personal and collective identities.

“Finding the songs and melodies that speak to them directly and reflect their unique personas isn’t so much a desire, but a need.”

Global Spotify Listener Loyalty by Genre
A Spotify chart presenting the most loyal fans by music genre. Knowing a little bit about metal it‘s obvious that its fans are the most loyal ones. What’s important to notice is how all the other genres are pretty even, showing that people are not attached to them.

Here is the big issue. Music for new generations is not about reflecting their unique personas, but a mirror of the activity he or she is performing. Music was once a question of loyalty and identity. Today it’s a good consumed according to moments. So the musical preferences of these listeners is much more flexible and no longer the reflection of their identities.

Part VIII

Whether this new perspective is something bad or good for music is not up to me (or especially to this article) to say. What is important here is that this revolution cannot be stopped. It is a continuous process of gradual transformation where the individual is in charge. It is a self regulating revolution where it is not up to industries and businesses to control it, but to really understand its culture, values, rules and players. We should not perceive this new listener from a conservative viewpoint or as an enemy to the music establishment. We should analyze it from an evolutionary standpoint where the listener is the transformation agent in a radical change in the social consumption relations.

Futurism is a science that usually gets its predictions wrong because it is done in large by people who look at technology and numbers (and because it is just damn hard to see what’s coming). Technology can change people’s behaviour, but only if it is the right time for it, in the right context. Numbers can sometimes be misleading. If you only look at the big numbers you might miss the small ones which are the real indicators of transformation. The real challenge in futurism is to predict how our behaviour is going to change. Borrowing from Tom Vanderbilt’s excellent article:

“When technology changes people, it is often not in the ways one might expect.”

Technology changed the way we listen to music and as a result we changed the way we feel about it. We should start considering that people are no longer loving music, but that they just like it. Or are even just using it. But what is more important is that only when we understand these changes, will the music industry be able to create services, products and business models that are in tune with this new listener.


This is a guest contribution by Thiago R. Pinto. 

5 Bots You’ll Love

Since launching its chatbot API last April, Facebook’s Messenger platform has already spawned 11,000 bots. Bots are popular, because they allow brands to offer more personalized service to existing and potential customers. Instead of getting people to install an app or visit your website, they can do so from the comfort of their preferred platform, whether that’s WhatsApp, Messenger, Twitter or something else.

Bots, basically automated scripts with varying levels of complexity, are ushering a new wave of user experience design. Here are some of my favourite bots.

AutoTLDR – Reddit

AutoTLDR bot

AutoTLDR is a bot on Reddit that automatically posts summaries of news articles in comment threads. tl;dr is internet slang for “too long, didn’t read” and is often used at the top or bottom of posts to give a one-line summary or conclusion of a longer text. It uses SMMRY‘s API for shortening long texts.

The key to its success is Reddit’s digital darwinism of upvotes and downvotes. Good summaries by AutoTLDR can usually be found within the top 5 comments. If it summarizes poorly, you’re unlikely to come across its contribution.

Explaining the theory behind AutoTLDR bot.

Subreddit Simulator – Reddit

Subreddits on Reddit center around certain topics or types of content. Subreddit Simulator is a collection of bots that source material from other Reddits and, often quite randomly, create new posts and material based on that. Its most popular post is sourced from the “aww” Subreddit and most likely sourced two different posts to create this:

Rescued a stray cat

Check out other top posts here. Again, the reason why it works well is because of human curation. People closely follow Subreddit Simulator and upvote remarkable outcomes, like the above.

wayback_exe – Twitter

Remember the internet when it had an intro tune? wayback_exe takes you back to the days of dial up and provides your Twitter feed with regular screenshots of retro websites. By now, it’s basically art.

It uses the Internet Archive’s Wayback Machine, which has saved historic snapshots of websites.

old site 1

old site 2

pixelsorter – Twitter

If you’re into glitch art, you’ll love pixelsorter. It’s a bot that re-encodes images. You can tweet it an image and get a glitched out version back. Sometimes it talks to other image bots like badpng, cga.graphics, BMPbug, Lowpoly Bot, or Arty Bots. With amazing algorithmic results.

 

Generative bot – Twitter

Generative bot

Generative Bot is one of those bots that makes you realize: algorithms are able to produce art that trumps 90% of all other art. It uses some quite advanced mathematics to create a new piece every 2 hours. Seeding your Twitter feed with occasional computer-generated bits of inspiration.

Want more inspiration? We previously wrote about DJ Hardwell’s bot.

What are your favourite bots? Ping me on Twitter.