Creative Next: AI Automation at Work Creative Next

AI is being used by music groups, such as our guest this episode Claire Evans, a member of the band YACHT. Their latest album, Chain Tripping, leveraged machine learning solutions for the music, lyrics, and more.
Artists are making the most of machine learning, using the technology both in the creation of their art and as a cultural touchpoint for expression, exploration, and commentary. While the Internet and more modern emerging technologies have long had a negative impact on musicians and others who create using audio, Claire Evans and her band YACHT - Young Americans Challenging High Technology - are at the vanguard of discovering how these technologies will impact art and music in the future.
 
Memorable Quotes
“Since we only really learn by doing things and making things, we figured that the most efficient way for us to get a sort of bodily understanding of what the hell AI is and what it's doing and what it means for artists and for all of us was to try to make something with it.”
“I think when we first started this project, we naively thought we could just kind of hand our back catalog to some algorithm, and the algorithm would analyze that and spit out new songs that would be new YACHT songs. And the project, the art, would be about committing to that, whatever it was. As soon as we started working on this, we realized that we're not there yet, thank God. Algorithms can't just spit out pop songs. If they could, the airwaves would be full of them.”
“If you listen to the record it sounds like an interesting experimental rock or pop record. It doesn't sound like generative, you know, plausible nonsense. It sounds like songs, and that's because there was very much a human in the loop. We used the machine learning model to facilitate the process of generating source material, and then from that source material we built songs the way that we would always build songs as humans in a studio playing music.”
“I was projecting my own meaning onto words that I didn't write. And trying to sort of cobble together some kind of meaning to the songs that made it possible for me to sort of perform and convey them with my voice. And so, it's oddly democratizing, because now the fans, the listeners, and the band, are all trying to figure out what it all means at the same time. And we were going to have as many interpretations of what it means as there are people to listen to it.”
“It also has no consideration of the body, right. It doesn't ‘know’ what it feels like to play any of these melodies on the guitar or on the keyboard. If it's physically challenging to do. All it knows is the MIDI data that it's been fed in the training process. So, a lot of these melodies sounded odd, but simple enough to play. But then when we sat down to actually play them, we found that they were extremely challenging, because they forced us to acknowledge the embodied habits that we bring with us as players into the studio.”
“I like to think of some of these machine learning models being like a camera of their individual disciplines. I mean, a text-generating model that's able to make perfect texts. Maybe that just becomes the camera of writing. And we have to completely step outside of our comfort zone to reinvent what writing means in the 21st century. And what an exciting proposition that is for an artist.”
“There's also something really interesting about the reflective quality of AI as it works today. I mean, you build a machine learning model by feeding it lots of information, trading data. And in the context of music that information is historic. It's the history of music. It's a corpus of millions of notes, or a corpus of millions of words, of song lyrics from musicians and artists that we love. Or ourselves. So this idea that we could use an emerging technology not only learn to understand it, but also maybe learn something about ourselves in the process.”
“Maybe in ten years we won't even be making mu

Musical composition is one of the earliest examples of human art and creativity. Today, new and original music is increasingly being composed by AI. Drew Silverstein, Co-Founder and CEO of Amper Music, joins the show.
Automation of sound and music, in the form of licensing stock and pre-existing recordings, is a decades-old trend that became ubiquitous with the rise of the internet. Now, thanks to machine learning and artificial intelligence, the creation of original music is increasingly being automated. Drew Silverstein, one of the pioneers at the forefront of this trend, joins the Creative Next team to explore these technologies and the trends and impacts they have on work in general and musicians in particular.
 
Memorable Quotes
“As our technology evolves, we see AI dramatically decreasing the cost of accomplishing certain tasks and dramatically decreasing the amount of information that any one person needs to know to be successful at that task. And whether it's music, whether it's farming, whether it's creating a script, or whether it's just doing more rote business tasks, and I think what we are going to arrive at in the not too distant future, is a world in which the ability to complete a task is fully democratized and anyone can do nearly anything with the assistance of an AI.”
“The value, then, of our human input is gonna be on the creative input and the creative direction, so that, as people, how can we direct the workforce and the work effort of these machines to do something that's meaningful to us.”
“All you need to know to create unique and professional music tailored to your content are three things: the style of music you want to create, the mood you want to convey and the length of your piece of music and that's all you know. In a matter of seconds, you'll make something brand new.”
“We think our job is just a matter of tasks in a sequence that accomplish something specific that they get a goal done, whereas our career is all about helping others achieve their goals, and the manner in which we do that will change. We used to communicate via written letters only, and then it became telegraphs, and then it became phone calls, and then it became email. Now it's texts. We're still communicating. We're still conveying messages, but how we do that will change. And in the same way, in music, the jobs of the music world that exist today will certainly evolve and be very different in a matter of years, in the same way that they're very different now than they were 10 years ago.”
“So what I would say to those, both coming up in music, and those who are already successful and experienced, is to understand that technologies evolve. The way we do things will change. Be accepting of that. Be on the forefront of the adoption of those new technologies and their tools, but also be mindful at the core value in music. It's not because of the process by which it's made. It's because we're making art and people value art.”
“Whether or not we exist as a company, this is happening. AI music is here.”
“And then we said to ourselves, ‘As composers, we are experts at translating music into emotion and emotion into music.’ And so we suggested, ‘What if we could create a creative AI that gives you the same collaborative experience of working with us, but within the time and economic framework that you need?’”
“And with each evolution in technology, the barriers to expressing oneself creatively through music were dramatically decreased, the time it takes to learn to express oneself and the cost of purchasing the tools to do so. And in that manner, we see AI music and Amper as the next step in this centuries long, if not longer, progression of technological innovation democratizing creative abilities.”
 
Who You'll Hear
Dirk Knemeyer, Social Futurist and Producer of Creative Next (@dknemeyer)
Jonathan Follett, Writer, Electronic Musician, Emerging Tech Researcher and Producer of

AI is driving innovation in the field of audio production. Jonathan Bailey, the Chief Technology Officer of iZotope, a company pioneering advances with these technologies, talks about the state-of-the-art in audio software.
As recently as 50 years ago, audio production required physical tools such as a soldering iron to achieve. With the rise of the personal computer these technical requirements have disappeared, replaced by software which handles all of the work with bits and bytes. From mixing to sound repair to post-production, machine learning-powered software like that offered by iZotope continues to automate an audio engineer’s workflow and even put professional audio production within the reach of amateurs.
 
Memorable Quotes
“There's a macro trend which is actually bigger than sort of machine learning or AI, which is for the professional working in audio the last 50, 60, 70 plus years has been a transition away from the technical problem domain to the creative problem domain.”
“You have a person that has a point of view that is guiding and steering the neural network. Now, there are new network architectures where a neural network can train another neural network, and those are pretty interesting, but there's still someone behind that, right? So they're, currently and for the foreseeable future, there's going to be kind of a guiding hand who's steering and curating what these things are capable of.”
“There's a lot of buzz in the world of technology overall and I think probably a lot of snake oil and misunderstanding of what machine learning really is capable of, but on the other hand, it is a pretty spectacularly powerful technology and set of techniques that we can use in the world of music and audio.”
“By being able to encode some of the best practices and some of the learning that only an audio engineer would have, and it's like your virtual audio engineer buddy, now people can create recordings that will sound good enough that they could be uploaded directly to Spotify or SoundCloud.”
“As a team that works with ML all day long, we are just scratching the surface of what is even possible to do in terms of personalizing the experience to a specific user, in terms of continuing to enhance our algorithms in response to real-world data.”
“We can really see a future where the audio engineer sits down, they've made a recording, it's de-noised, it's cleaned up. Everything works well together, and they can start getting creative, just painting with colors rather than having to fix a bunch of problems in the content that they produce. That's the world that we're trying to push those people towards.”
“The sort of next horizon for both the world at large but definitely for audio is how can we use neural networks to generate content?”
“We have a stream of audio coming into the product and a stream of audio leaving the product, and our job is to process that audio to make it sound better or make it sound more like the user wants us to.”
“We can almost treat that representation like an image, and at each portion of that spectral representation, we can attempt to make a decision, for example, is this voice or not-voice?”
“So we've trained a neural network to be able to make point-to-point decisions, both in time and in frequency.”
“We had an idea that it might be possible to use machine learning to solve this problem.”
 
Who You'll Hear
Dirk Knemeyer, Social Futurist and Producer of Creative Next (@dknemeyer)
Jonathan Follett, Writer, Electronic Musician, Emerging Tech Researcher and Producer of Creative Next (@jonfollett)
Jonathan Bailey, CTO, iZotope
 
Join The Conversation
Website & Newsletter: www.creativenext.org
Twitter: @GoCreativeNext
Facebook: /GoCreativeNext
Instagram: @GoCreativeNext
 
Sponsors
GoInvo, A design practice dedicated to innovation in healthcare whose clients are as varied as AstraZeneca, 3M Health Information Services, and the

AI is the latest technology to spark innovation in the art world. Artist Mario Klingemann, creator of “Memories of Passersby 1” which was auctioned by Sotheby’s in 2019, talks about his work and the future of art.
Machine learning technologies like Generative Adversarial Networks (GAN) are accelerating progress in the automation of creative output. While Mario is best-known for his visual art he is shifting his attention to text-based output, which he sees as ripe for pioneering work. Art has always been interwoven with technology, and the future will be increasingly digital, leveraging smart machines that raise questions about the nature of humanity and creativity.

The impact of AI and other emerging technologies is of great interest to artists, who translate that interest into insights about where the world is heading. Transmedia artist Stephanie Dinkins shares her work and insights.
We go through our lives, ubiquitously using technologies like Alexa and Netflix, without critically thinking about the impacts that machine learning and other emerging technologies have on today and tomorrow. Stephanie’s art, as well as live event projects that create dialog and participation from experts and every citizens alike, strive to make us aware of and active in how we think about and engage with our technology - being particularly mindful about issues of representation, bias, and empowerment.
Memorable Quotes
“Not The Only One is talking a lot about ‘the would be’. So if you ask it a question it will say, ‘Take it to the would be.’ And I always marvel at that, because it seems to be offering this idea that you take it to this thing that I'm not quite sure what it's talking about, but the advice feels sound, and also feels in line with the way that my family and ancestors might answer that question.”
 
“If this is one example of this technology, are there others that represent people of color in a way? Are there others that represent different cultures and attitudes in different ways? How are they programmed, and what does this mean for the world?”
“She is a system that is representationally one thing, but perhaps is informed by coders who are not completely in line what her representation might be.”
“I've been able to step into this arena, learn by doing, and then have a voice in terms of trying to get people to think about ideas of bias and equity and ethical thinking and inclusion in the AI sphere.”
 “And long run, really being involved in the making of the systems so that at least there are a multitude of different ways of being and ways of existing in the world, to start questioning how the system are working, what data they're based on, and bringing up why that might be a problem.”
“Not The Only One is my attempt at making a memoir of my family through artificial intelligence. And the original idea was to take three generations of women from the family, have us all talk to each other, do oral histories, transcribe that information, feed it into a recursive neural network, or a chat bot system, and allow others to question it so that they get to know us and our values and ideas.”
“I also think that there's a space where we get to interrogate and question the systems and think a little deeper about not only using those systems, but changing them.”
“We need to find ways to make technologies that seem really inaccessible and perhaps not for certain communities feel like they are accessible, and find ways then to use them.”
“I've come to the conclusion that in the short run specifically, the data is going to be the thing that we need to be conscious of.”
“I feel like the story of my family is a very specific one that has some specificities that we would like to share in a certain way, and that I don't want to be lost even to a next generation. And a way to hold onto that is to build it into a system that will be going on and engaging other systems. And so I do this work hoping that will hang around, and hoping that we don't just get overrun by whatever it is makes it most expedient to get to the information or ideas that are out there.”
“We seem to be creating a world through algorithms and artificially intelligent systems that - it's gonna really form and inform the way the world functions going forward.”
“I was talking to this robot and questioning her and we were having conversations, and it became clear to me that some of the things I was looking for were not in her.”
“I happen to think that we're entering a time where artists and everyone else are going to have to be learning all the time.”
 
Who You'll Hear

The digital design profession has undergone tumultuous change over the last decades, lessons from which inform the future of AI-driven computational design. Daniel Harvey, Head of Product Design & Brand at The Dots Global, is our guest.
Design has evolved since the rise of the Internet and mobile computing, resulting in unintended negative consequences in our world such as the appropriation of social media technologies by evil actors, and the pernicious influences of bias and other invisible forces. In extreme cases our tools even contribute to the culmination of the most horrific of outcomes, such as the genocide in Rohingya. We explore how these complicated dynamics provide a glimpse into the future of design and technology.
 
Memorable Quotes
“When we're ripping off the same Silicon Valley apps, or the same sort of business models we end up inheriting, intentionally or not, all their weird, f****d up, white tech world biases too.”
“There is this fantastic service that you can take the content of a job description, put it into that, and it will  remove the gender bias from it.”
“As design does evolve, and as tools evolve, and as patterns evolve, I think we could get to a point where design is less about sort of pixel level craft, it's about more higher level value.”
“One of the things that I'm most excited about is  the reemergence of niche networks.”
“Facebook was used as a platform to promote  hate in Myanmar which led to an unconscionable number of real deaths, a massive refugee crisis.”
“You can have the most diverse and inclusive team in the world, but if you're looking at the same three or four big tech companies as examples to swear by, you're never going to really see the benefits of that diversity.”
“What's still not happening is you don't have one sort of common tool that's pointing to the same common assets and  common design libraries or pattern libraries.”
“Because of this proliferation of advertising as the default business model, we're just accustomed to it now, and we're willing to accept it when it does creep back in.”
“When you have voracious growth of a community, of an audience, and then you start to put advertising on top of that, the inevitable metric becomes daily active users. And the inevitable experience of using the product is, we'll cram advertising more and more into every part of the experience.”
“If you start to grow your skill sets in other areas, it's just an extra superpower.”
“There's a real problem with so much sameness in design today.”
“The scale of these platforms is what invariably leads to their potential for damage.”
 
Who You'll Hear
Dirk Knemeyer, Social Futurist and Producer of Creative Next (@dknemeyer)
Jonathan Follett, Writer, Electronic Musician, Emerging Tech Researcher and Producer of Creative Next (@jonfollett)
 Daniel Harvey, Head of Product Design & Brand at The Dots Global (@dancharvey)
 
Join The Conversation
Website & Newsletter: www.creativenext.org
Twitter: @GoCreativeNext
Facebook: /GoCreativeNext
Instagram: @GoCreativeNext
 
Sponsors
GoInvo, A design practice dedicated to innovation in healthcare whose clients are as varied as AstraZeneca, 3M Health Information Services, and the U.S. Department of Health and Human Services. www.goinvo.com 
 
Design Museum Foundation, A new kind of museum, they believe design can change the world. They’re online, nomadic, and focused on making design accessible to everyone. Their mission: bring the transformative power of design everywhere. You can learn about their exhibitions, events, magazine, and more. www.designmuseumfoundation.org

BIF, As a purpose-driven firm, BIF is committed to bringing design strategy where it is needed most - health care, education, and public service to create value for our most vulnerable populations. www.bif.is