The AI revolution isn’t just changing how fast we work — it’s reshaping how we create, collaborate, and even define art itself. Beyond the flashy demos and new apps, the deeper question is: how do humans and AI actually build together?

For Mason Youngblood, a researcher at Stony Brook University, the answer starts with studying how collective intelligence works — not just among humans, but across networks of people, animals, and now AI systems. Mason blends biology, cultural evolution, and social science with emerging AI research to uncover how creativity scales when it’s collaborative.

On AI with Bry, Mason shared how AI is sparking a new Renaissance in art and music, why attribution and ethics must evolve with technology, and how leaders, educators, and creators can embrace AI as a co-creator rather than are placement.

Key Takeaways from Mason Youngblood’s Conversation

• AI Can Spark a New Renaissance

  Instead of replacing creativity, AI is unlocking it. From turning ideas into songs or visuals instantly, to remixing cultural artifacts at lightning speed, AI gives people a way to “pull ideas out of thin air” and focus on the creative spark itself.

• Everything Is a Remix — Accelerated

  Social media already thrives on remix culture. AI accelerates this exponentially, whether blending songs, generating visual mashups, or creating entirely new styles. Mason highlights tools like Art breeder and Data Mind Audio that empower artists to work in more organic, networked ways.

• Collective Intelligence Is the Key

  The most powerful creativity doesn’t come from a single human + AI, but from networks where multiple people and AIs interact. Research shows that realistic population structures — groups of humans and AIs collaborating — consistently generate more diverse and creative outputs.

• Attribution and Ethics Must Evolve

  As AI borrows from massive data sets, how do we reward the original creators? Mason points to blockchain, NFTs, and ethically constructed datasets as potential models. Just as music sampling required new systems for fairness, AI art and music will too.

• AI as a Creative Partner in Coding and Art

  Mason uses AI daily for generative art and creative coding. Instead of slowing down to learn new code bases, he leverages AI to bridge gaps quickly, pushing models until they “break” and then turning strange outputs into new artistic directions.

• Teaching the Next Generation to Co-Create

  At Stony Brook, Mason is preparing to teach a course where students first create art without AI, then collaborate with AI to expand it. The goal: to show undergrads that AI isn’t cheating — it’s a skillset. Learning to partner with AI creatively is as essential as learning to write essays or code.

From Faster to Collective

The next phase of AI isn’t just “faster outputs” — it’s better, more collective creativity. When humans and AIs collaborate in structured networks, the results aren’t just efficient — they’re novel.

Reinventing Creativity and Identity

AI challenges our idea of what it means to be “an artist.” For some, this feels threatening — will AI-generated art erase human originality? Mason reframes it: AI doesn’t erase art, it widens access to creativity. Even those who don’t see themselves as artists can now turn ideas into music, visuals, and stories. The bigger challenge is building systems that protect attribution while amplifying creativity.

Leading Through the AI Renaissance

Mason reminds us that creativity thrives in robust systems, not just efficient ones. Leaders and educators must design environments where AI tools complement human imagination, not replace it. That means:

● Rewarding original creators.

● Building purpose-built tools that integrate into real workflows.

● Teaching teams and students how to iterate, remix, and push AI to expand possibilities.

The Renaissance wasn’tjust about new tools — it was about new ways of thinking. The same is true today.

The Road Ahead

AI isn’t just another app on your desktop. It’s a co-pilot in the next wave of human creativity. As Mason puts it, “We need tools that interact with human creativity in flexible, iterative ways — so they complement, not replace, the artist.”

The leaders, creators, and educators who embrace AI as a partner in remixing and reimagining culture will define the next era of art, music, and meaning.

🔗Connect with Mason Youngblood

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Episode's Transcript

Please understand that a transcription service provided the transcript below. It undoubtedly contains errors that invariably take place in voice transcriptions.

Bryan (00:05.07)

All right, I think it's recording, so. Hey everybody, welcome back to AI with Bri, the podcast where we are exploring how to learn, leverage, and lead with AI. I'm your host, Bri, and if you're curious about how AI intersects with community, cooperation, and collective intelligence, you're in for a great conversation today. Joining me is Mason Youngblood. He's a researcher and scholar focused on cultural evolution.

collective behavior and how groups of humans and even animals make decisions together. Mason blends biology, social science and emerging technologies to better understand how collaborative intelligence functions and including how AI is now shaping all of these dynamics. So welcome to the show Mason. Thanks for being here.

Mason Youngblood (00:56.846)

Thank you so much for having me, Brian. And just a heads up to everybody, I have a stutter that'll pop up periodically during our discussion.

Bryan (01:07.37)

All good. I have had the pleasure of hanging out with Mason and working with you on a couple of projects and you definitely have some genius here and I'm looking forward to sort of unpacking it with you. So I appreciate you taking the time out of your busy day to chat with me. I wanted to sort of talk with about the Learn Leverage Lead and we'll start with the Learn segment. You know, what is...

Mason Youngblood (01:19.27)

Thanks.

Bryan (01:33.71)

Talk to us about what you're learning lately in AI and what's something you've discovered or reflected on recently that maybe AI has kind of shifted your perspective.

Mason Youngblood (01:44.908)

Yeah, I think one thing I've been thinking a lot about recently is kind of how we can move towards agentic AI systems that are as adept at problem solving and creative tasks as groups of people are. I think this is an area where there's a lot of ongoing research that kind of hasn't.

hasn't made its way into the AI world yet. Especially from my home field of cultural evolution and then other fields like cognitive science. Yeah, there's some really interesting studies being done on how on

Bryan (02:15.394)

Mm-hmm.

Mason Youngblood (02:37.044)

AI and human collaboration and like under which conditions the collective output of groups of AIs and humans are more creative and more diverse, like under what conditions the AI tools actually enhance the creativity of people. And those conditions are things like realistic.

social network structures. So not just having like a single human and a single AI, but having actually realistic population structures where multiple people and multiple AIs are embedded in a network and interact with one another. You end up with much more creative and diverse output. And there's all kinds of, all kinds of work being done along those lines that.

I've been reading a lot about interesting and I think it's really inspiring.

Bryan (03:37.871)

I agree completely. It's that question in my head of like, I don't know, I probably use the AI LLM models 50 times a day at this point. And it is just to help spark a moment of creativity. Like I know those things are things that I could do on my own, but I would need to like shift focus or just concentrate on that for a few minutes. And then I'd come up with the things myself.

but I just know I can just tap on my good friend sitting next to me and it unlocks it super quick for me so I can get back to the thing I really care about. And I still, I've said it multiple times on this podcast, I just think that AI is gonna unlock this new Renaissance era for us, like us being able to take our ideas and pull them out of thin air and into an application, an image, a video, you know, at the tap of our fingers.

is just gonna be amazing. What are some of the tools that you've been learning about lately or what's getting you excited about some of the stuff you've been able to do with your work?

Mason Youngblood (04:47.806)

I think most recently I've been most excited about, exploring the new AI tools for artists that have been popping up. think, I think that, there's a lot of kind of innovation happening there because it's still like early, earlier on than LLMs, for example. and there are a couple of really interesting,

companies like there's titles and art breeder that are kind of AI tools for artists that are built by artists and are trying to do a better job of kind of responsible attribution of the source material that's being used to train models. But they're also coming up with really interesting

Bryan (05:35.704)

Mm-hmm.

Mason Youngblood (05:43.758)

ways of using these tools. in Art Breeder, for example, it kind of has like a node based structure where instead of just having a single image generation model that you give a prompt to and you tune a couple parameters and get an image, you have a set of models and you can link them and get output and then remix that output and combine it in the same

kind of way that real artists integrate inspirations when making work. And it's kind of a much more organic way of using AI tools for art. And I think I've been very interested in that area. Also AI tools in music. So I also make art.

in music in addition to my science. And I use a lot of AI tools. And then in the last year or so, there have been some incredible tools that have popped up in music. There's this company called Datamind Audio that is doing amazing stuff with dial transfer in music, like where you can...

Bryan (06:45.614)

you

Mason Youngblood (07:04.99)

sing into a microphone or play a guitar or play a piano and transform it into any set of output sounds that you provide. Like they have a bunch of presets, but I could go out and record a bunch of birds and then pop those sounds into this tool and then transform my voice in real time.

into that species song. And it's just really incredible. mean, those kinds of things weren't possible just a couple of years ago, so.

Bryan (07:35.736)

Wow.

Bryan (07:42.947)

Yeah, I mean, I know I've definitely played with a couple of like remix tools, like take song A and song B and blend them together. And then definitely I've done a few AI generated music files for, you know, some non-commercial royalty free type AI generated music. like the future, like I almost think this we're just.

scratching the surface on the learning of what we can accomplish with this. I think like art and music is going to be, I don't know, everything's a remix. I'm sure you've seen that video potentially, everything's a remix. like, I think the AI...

Mason Youngblood (08:19.286)

Mm-hmm. yeah. Yeah.

Bryan (08:24.392)

Era is going to accelerate the remixes exponentially. mean, social media already is exponentially accelerating remixes. We have a new meme popping up every day that goes viral. But, you know, the big I think the Bigfoot videos are the big thing right now. But the the the speed at which we can go is just incredible. But I think it goes back to just that creativity around like I don't think of myself as an artist in that.

Mason Youngblood (08:39.468)

Yep.

Bryan (08:54.256)

but I have all these ideas and I can pull them out with the AI, right? Like the AI is just helping me, I feel like become a creative person. I also think like, I'm curious what your thoughts are about this is I think art.

it like is going to blend into almost everything we do. Like I can imagine us walking up to the mall information signs and it being an art thing that not only had it knows Brian's walking up to it and he's a male and he looks like he's in his forties and he probably wants to know how to get to the XYZ men's department store or something like the art will interact with you and be very, personalized. Right. Like, do you see that personalization lens?

Mason Youngblood (09:37.75)

Yeah, I think so. I think I'm also, I see like incredible promise for AI in art, but I also, am extremely wary of it. I think like right now, a lot of the mainstream kind of AI art tools are tools that mainly kind of

are being used to help companies make advertisements and aren't really tools that are kind of used by like real artists to make art. And so I think we need to like move towards tools that are like really, really built to like interact with human creativity in a flexible way and kind of allow for more iteration. I mean, even things like if you code,

Bryan (10:12.088)

profit. Yeah.

Mason Youngblood (10:35.034)

in the chat GPT chat window versus using a tool like cursor. Cursor is going to allow you to be a lot more creative because it's kind of it's built to integrate into an existing.

Mason Youngblood (10:57.07)

creative workflow and I think we need a lot more tools like that that are purpose built. And I also think that we need to solve issues around like.

Bryan (11:00.173)

Yeah.

Mason Youngblood (11:18.222)

credit and attribution around image and audio models to make sure that we end up in a place where AI art tools are mainly complementing creativity instead of just replacing creativity. And I think I'm very worried about that. And I think a lot of other artists are very worried about that. So.

Bryan (11:20.664)

Mm-hmm.

Bryan (11:47.203)

And that's been something that I have definitely talked about with numerous AI people that I've encountered. It really builds into that leverage segment. if we pivot into this leverage segment, I'll get to the leverage couple of questions I have, but to unpack this leverage thing, we're leveraging AI, we're leveraging these artists' knowledge. They have created...

You know, the Andy Warhol soup cans and the, know, the Mona Lisa and all these things now are assets that, that, you know, the original person should get some reward from for their creativity and their, their inspiration to affect change in culture and,

they should be rewarded from it and not it quickly being ripped off by the AI and duplicated 5,000 times and put into a Super Bowl commercial or letting me use it or you know what I mean? how do we, have you thought about this or talked about it with some of your artist friends and stuff like that? Like what is the right way to collaborate on attribution? I know we solved it.

I think we've solved it not probably in the best way for the music MP3 revolution from moving from cassettes and CDs into MP3 downloads and views to attribute money, but it's changed the game for music in a big way too. So what's your thoughts on the best way to tease out how do we solve it or what we should be doing in this leveraged world of AIs everywhere?

Mason Youngblood (13:31.98)

Yeah, I think right now that the most promising way forward, which is being pushed by companies like titles, is using blockchain technology to handle attribution. So NFT technology, know NFTs get a bad rap because there's a lot of just.

terrible art that's labeled as an FT's but the underlying technology is really all about attribution and so I think there's a lot of promise there if done correctly and I know there's a lot of people working on that. Another way of doing it that... So in music there are a couple of companies

Bryan (14:01.678)

Yeah.

Mason Youngblood (14:24.876)

that basically hire musicians to make samples that other artists can then use freely in their own composition. historically music sampling of like the amen break, this classic drum break, involved like taking the original record and people recognize it and they know it's coming from the original artist, but that original artist is not getting paid usually most of the time.

Bryan (14:35.139)

Mm-hmm.

Mason Youngblood (14:53.774)

And these kinds of companies, basically, pay musicians a living wage to make source material that people can then remix freely. That kind of model could work for AI art as well. training models on data sets that have been ethically constructed from a work by paid artists.

Bryan (15:26.574)

Mm-hmm.

Mason Youngblood (15:29.772)

I think that could be a way forward as well. There are, I think, a lot of really good potential models. But I think it's important that we experiment, we try different things, and we stay open-minded and kind of find what combination of approaches works best.

Bryan (15:47.501)

Yeah, yeah, absolutely. mean, bottom line, all those listeners out there is don't forget to support your local artists every which way you can, because I do see them as as some of the forefront of change making on this planet. So what other ways are you leveraging AI in some of your day to day stuff? You've got all these tools at your fingertips. How else are you applying it to some of your day to day work and research?

Mason Youngblood (15:55.374)

Mm-hmm.

Mason Youngblood (16:08.077)

Yeah.

Mason Youngblood (16:13.742)

Yeah, I'm using it all day. I use this platform called Sim Theory, which is like an aggregator that allows you to interact with all of the major models while keeping context. So if I'm doing a coding task and I'm not getting output I like for...

from Claude, can switch over to GPT-03 and keep the context of the full conversation. I really like using that platform. Yeah, it's great. And the kinds of tasks I'm using it on, like a lot of academics, it's been very helpful for my programming.

Bryan (16:49.134)

That's very cool.

Mason Youngblood (17:06.486)

So I'm using it for coding tasks. And in my art practice, I do a lot of generative art, so a lot of code-based art. And so it's really kind of unlocked a lot of new avenues.

because if you do generative art and you're interested in a new tool, if you have to sit and learn an entirely new code base to implement your idea, it can kind of really slow down that creative spark. You have an idea and then in between having the idea and implementing it is learning a new code base. The inspiration is gonna be gone. And so I've found it.

really helpful in my art practice. It's a...

Mason Youngblood (18:07.192)

creative coding, I think has really been helped a lot by AI. But it's, it's extremely important though, to if you are using AI tools for any kind of, of coding tasks, besides obvious things like making shh shh shh shh shh or that you're constantly vetting the output.

Bryan (18:11.147)

Mm-hmm.

Mason Youngblood (18:37.1)

I think it's also helpful to kind of like see where the models fail.

Mason Youngblood (18:50.444)

I think it, I've found that especially in my art practice to be very kind of helpful in creativity enhancing in a way. pushing the model until it breaks and kind of gives you output that's kind of strange and seems useless at first, but then you find an interesting way to incorporate it in a way that's actually useful.

Bryan (19:02.126)

Mm-hmm.

Bryan (19:19.104)

Absolutely. I was reading something about some of the AI being used to help figure out like some of the weird sounds we heard a couple years ago up in the...

Mason Youngblood (19:20.205)

Yeah.

Bryan (19:31.342)

North Pole region or something and they had to take all these different sound samplings and run it through the AI and they they did finally figure out it was some sort of underwater Glacier collapse or something that you know was trapped so it made some weird unique sound because it was trapped under Under this pocket of something and so I don't know I'm not doing the article justice so I'll try and find it and put it in the show notes here, but Just some of the unique ways that we're able to leverage AI and I think it does come from

pushing these models to some sort of breaking point to sort of see where is their limits. Many of people are asking, do you believe in God or what's the meaning of life from these models? And those are some interesting things to see what it says too, but you have to keep in mind the context of how it works.

Mason Youngblood (20:12.238)

You

Mason Youngblood (20:20.738)

Yeah, it's, I think those questions are always funny to ask because an LLM is just doing next token prediction. It's basically a regression models and a lot of people treat it like they're therapist. Yeah. Yeah.

Bryan (20:33.164)

Yeah, yeah, it is. It's just a fancy math algorithm. That's right. That's right. It's very, very, very true. Well, like, let's talk about the lead segment here. So, you know, how how are you helping leaders and how are you leading yourself to foster these stronger, more adaptive collective intelligence? You know,

frameworks as we've talked about here as the AI tools continue to evolve. What are some of the things you're doing day to day?

Mason Youngblood (21:06.292)

Yeah, that's a great question. So as a part of my work at, as a scientist and based at Tony Brook University, and I'm co-leading a new research group there called the Collective Creativity Lab. And we're doing a couple of studies on

how people use AI image tools to be more creative on online platforms using big data sets. As well as we're doing experiments on just the basic dynamics of human creativity and then hopefully kind of how AI tools enhance that creativity in an experimental context. so as a part of that lab, we've been

We hosted a big workshop and brought a bunch of people to Stony Brook to give talks and that was a lot of fun. I'm also doing teaching, so I'm teaching an undergrad class on AI and creativity in the fall. So how to use generative AI tools in a way that enhances creativity rather than hinders it.

Bryan (22:34.574)

Mm-hmm.

Mason Youngblood (22:35.18)

I'm really looking forward to that class. It's my first time teaching it. And I think that for undergrads who are kind of entering a world where generative AI will be a core part of their lives, but it's kind of in the academic setting viewed as analogous to cheating. think kind of, kind of.

Bryan (23:02.509)

Yeah.

Mason Youngblood (23:04.906)

Yeah, like working with them to develop the skills to use them in ethical, responsible, interesting, creative ways will be a lot of fun. I'm really looking forward to

Bryan (23:19.181)

Yeah.

Mason Youngblood (23:23.246)

And then, yeah.

Bryan (23:23.274)

I'm in that age of old enough to know that there were certain papers I had to write out by hand versus type up and print and the teachers thought I was cheating because I was printing the Word document or something like that. So there is this hesitation and flux of how do we adopt this into our lives, right? Like I remember pre-cell phone, post-cell phone, pre-smartphone, post-smartphone. So all these inflection points that we have and it's

It is interesting because we do have to embrace and teach the younger generation how to detect the difference between real and fake, whether it's an NFT blockchain authentication vehicle or that we've got to vet this against historical papers to validate this is real. Even some of the things that my kids say about Minecraft or other things are like...

Mason Youngblood (24:02.68)

Mm-hmm.

Bryan (24:20.738)

you know, how are we helping them distinguish between reality versus imaginary? So it's so, so true. That sounds like such an interesting course. Do you have it fully fleshed out or what is some of the structures or themes that you might be able to share with us?

Mason Youngblood (24:38.838)

Yeah, yeah. I'm about halfway there, but one of the big projects in the first half of the course, students will have to make some kind of artistic work without the use of AI. And in the second half, they will have to collaborate with an AI agent on

iterating on and improving that artwork. a kind of like starting at a baseline of just, of just making a thing and then how can I use AI to enhance this thing? And I think that's going be a lot of fun.

Bryan (25:12.482)

Mm-hmm.

Bryan (25:23.638)

And it's so interesting because I don't feel like we have artificial general intelligence yet. And I think we're years away from super intelligence because I do feel like it's like I have these younger kids right now and it feels like I have the smartest seven year old that knows everything about everything I could possibly ever ask it. But I still can lead it to exactly where I want it to go. And it's not it's not

Mason Youngblood (25:32.128)

yeah, definitely not, yeah.

Bryan (25:53.583)

properly counterbalancing or thinking creatively and truly collaborating with me in the way that like you and I could, you know, and I know you and I have had a few whiteboarding sessions where we've been able to go back and forth and push back on the idea and challenge it and rethink it and then reach a consensus and then drive forward. And I think the AI is, unless you really...

properly say, play devil's advocate with me on everything I say. Like there's the balance between full collaboration, yes boss, versus no, that's complete. Here's the complete opposite view. How do you tone that dial in the model each time you have that chat is a really important function of how to get the right results out of the AI you're trying to deal with.

Mason Youngblood (26:39.5)

Yeah, how to actually push it to...

Mason Youngblood (26:48.014)

reduce a diversity of outputs that you can then choose from and iterate on. It's challenging. Yeah.

Bryan (26:53.122)

Mm-hmm.

Yeah.

This has been an amazing deep dive. I hope you potentially come back Mason, maybe in the later part of this year and tell us how the first semester went of your new class and appreciate you laying out.

Mason Youngblood (27:11.438)

would love to.

Bryan (27:12.5)

a few tips and tricks. I've never heard of sim theory and I'll make sure all the links that you mentioned are in our show notes and stuff. it's been a very insightful and collaborative conversation here. So I know.

Mason Youngblood (27:21.08)

Perfect, thank you.

Br

yan (27:28.82)

AI is not just about these algorithms, but it is trying to really amplify how we think and work and grow together as a community. some great insights into this. Mason, how can people get in touch and learn more and connect with you?

Mason Youngblood (27:45.298)

Yeah, so you can just hop on my website. It's masonyoungblood.com and it has my email. Some of the projects I've been working on. You can check out my work there.

Bryan (27:57.44)

Awesome, so check out masonyoungblood.com and for those listening, don't forget to follow the show. Please, please, please leave us a quick review and share this episode with somebody outside your normal circle that might be interested and curious about some of the intelligence and AI stuff that we've been talking about on today's show.

Again, I'll put everything in the show notes and until next time everybody, please keep learning, keep leading. The future doesn't wait.