Welcome to the new Tech+Art Podcast!
Join us on this adventure as we meet & speak with: artists, makers, researchers, designers and creators from all background and fields.
Our objective is to understand their creative perspective, dive into their workflow & creative process, be inspired by new ideas and their work – and stay one step ahead of cutting-edge industry developments.
Today we’re speaking with Irene Alvarado, a creative technologist working with Machine Learning at Google’s Creative Lab in New York City.
Throughout our conversation, Irene dives into the value of exploring ideas at the intersection of various fields or industries, the immense benefits that come from prototyping and making to learn; as well as the unexpected impact of new technologies and tools – not only on empowering more individuals to explore their ideas – but in increasing accessibility for all.
You can learn more about Irene and her work here:
There’s a full list of all resources mentioned at the bottom of the post!
I had always been curious about computer science. It was something that I wanted to at least minor in, if not take a couple classes in. So I took my first programming class in my second semester of my freshman year. I think naively what I didn’t know was helpful, because all of my classmates were so much better than I was and had been coding for years. It became intimidating later on, but at the beginning it was all very exciting and fun to acquire a skill that you could make something with.
I still had it in my mind that I wanted to do something in the arts as well. And so I did a double degree in computer science & history […]. And the reason why is that I felt that the engineering education was lacking because it had no context. Like you learnt how to make stuff, but you didn’t really learn why you should or the history of things; there was very little connection between what we were making and the way society worked how things worked.
[…] At some point, I bumped into this whole world of design, and interaction design and human computer interaction and started reading about the history of that. And finding people that I admired that worked in the space, and finding artists that kind of exhibited some of these traits, like the Zach Liberman’s of the world. And that’s when it hit me, ‘ok what I actually like is how technology affects people’ and the connection between those two fields. So I decided to go back to school and study HCI in grad school and I feel like I was able to finally connect all the tech part, the design part, and the context of why you build things and how you build them and how they make their way into the world.
[…] I met Golan Levin […] I think he opened my eyes to all the ways you could combine “art” and “weird stuff” that people are into with tech and design. That’s kinda the first place that I started really tying threads and doing projects that maybe sat in-between what you would call design, art, technology. I don’t call myself an artist, but I do find a ton of inspiration from the art world.
The goal of the lab is really to help think about the future of Google, the technology and the products and services. And that’s extremely expansive.
So my first year there I spent some time exploring new machine learning technologies. I worked on a project to put out a new library that would allow you to detect something called pose estimation. So it’s a technology that relies on all these advances in computer vision and despite using a camera you’re able to detect where your body parts are […]
I had noticed that there was all this technology inside of Google that didn’t really exist as a public library out there. And I worked with a few engineers and researchers to put that out in the world as an open source library that works on Tenserflow.js. […] It’s called PoseNet.
To go back to grad school as well, Golan also opened my eyes to the fact that you can be a creator who makes products and artifacts; or you can be a creator who makes tools for other people. I think I was strictly in the artifacts and products world for a long time. At the Creative Lab, I delve more into creating tools. Building blocks that others can use to make their own creative projects. […] I’ve worked on mostly machine learning interfaces and creativity, new tools that designers and creatives can use – even if they’re not technical.
And his point is that with a lot of digital technology and creative tools that are digital, it’s really hard to achieve this quick immediacy. So when you think of something like animation, it’s incredibly hard to create an animation quickly. You’d need to go into After Effects – and AE is a tool for pros – I’m not good at it and I’d have to look up a tutorial to even do something simple, like maybe moving a box from left to right. So to me, what’s interesting about Machine Learning is achieving more of an immediate connection with something you’re trying to achieve.
When I think of some of the most exciting machine learning tools – like some of the tools we’re trying to create with Teachable Machine – they’re tools that would help you think of an idea, prototype it quickly, and create an interaction that just wouldn’t really be possible with traditional programming. Maybe I want to train the computer to understand certain phrases, or certain poses or certain things – and do that quickly. Like in a matter of seconds. And then put that interaction into something else. Put it into a prototype. Put it into a physical piece. Put it into an art piece. And see the effect of that.
I think we’re at the beginning of hopefully, kind of a blossoming of tools for creatives, designers and artists to leverage all these capabilities. But ultimately, I see it as a tool. The hardest thing is to have a good idea and to have the right craft to be able to execute it well.