By The Copilot

What if the future of AI in media isn’t replacing storytellers, but giving them better tools to tell better stories?

This episode is sponsored by Descript.com 

In this episode of The Media Copilot, host Pete Pachal sits down with Laura Burkhauser, CEO of Descript, to explore how artificial intelligence is reshaping media production without sacrificing creativity, editorial judgment, or human storytelling.

Laura explains why Descript’s vision has never been about replacing editors, but about eliminating the repetitive, time consuming tasks that slow production. From text based video editing and AI assisted collaboration to intelligent clipping and personalized workflows, she shares how AI is becoming a creative partner rather than an automated replacement.

The conversation also examines why memory, personalization, and collaboration may become AI’s greatest strengths, how media organizations are adapting to an increasingly creator driven landscape, and why the next generation of production tools will focus less on software features and more on helping teams create great content.

Finally, Laura offers a refreshing perspective on the future of AI, arguing that the industry has spent too much time selling fear instead of showing creators how these tools can unlock more original storytelling, more creative freedom, and entirely new ways of producing media.

The conversation explores:

• Why AI should replace repetitive labor, not human creativity
• How Descript evolved from a text based editor into an AI powered production platform
• Why collaboration remains the most valuable feature in modern media workflows
• How AI memory is creating more personalized creative assistants
• Why editorial judgment, taste, and storytelling still belong to humans
• How newsrooms and media companies are producing more content with smaller teams
• Why the future of media production is conversational, collaborative, and AI assisted
• How creators can use AI to spend less time on tools and more time telling better stories

Why this matters

Artificial intelligence is transforming every stage of media production, but the biggest opportunity isn’t replacing creative professionals. It’s removing the friction that keeps them from creating. As newsrooms, marketing teams, and independent creators face growing pressure to produce more content across more platforms, AI has the potential to become an intelligent collaborator that accelerates production while preserving human judgment, creativity, and authenticity. This conversation offers valuable insight for journalists, marketers, content creators, media executives, and anyone navigating the future of AI powered storytelling.

🔗 About the 👤 Guest

Laura Burkhauser is the CEO of Descript, the AI powered audio and video editing platform used by creators, media organizations, podcasters, and enterprise teams around the world. Under her leadership, Descript continues to pioneer AI assisted media production, helping storytellers simplify complex workflows while keeping human creativity at the center of the creative process.

LinkedIn: https://www.linkedin.com/in/burkhauser/
Descript: https://www.descript.com

This episode is brought to you by Descript.

Descript makes editing podcasts and video as easy as editing a document. Record, transcribe, clean up audio, remove filler words, create clips, and more with powerful AI tools built right into your workflow.

Spend less time editing and more time creating with Descript.

Visit Descript to learn more.

About the show: To explore more conversations like this and see what’s new, visit the Media Copilot website at mediacopilot.ai. You’ll find new episodes, expanded resources, and tools designed for journalists, communicators, and media leaders navigating the fast-changing world of AI. It’s the home base for everything Media Copilot and it’s just getting started.

Enjoyed this episode?

Subscribe to The Media Copilot on Substack, Apple Podcasts, Spotify, or your favorite app. On YouTube? Tap the Like button and Subscribe to the YouTube channel. For more AI tools and resources built for media professionals, visit mediacopilot.ai.

Produced by Pete Pachal and Executive Producer Michele Musso
Edited by the Musso Media Team 

Music: “Favorite” by Alexander Nakarada, licensed under CC BY 4.0

All rights reserved. © AnyWho Media 2026

THE MEDIA COPILOT TRANSCRIPT

THE MEDIA COPILOT

AI Won’t Replace Creators

Featuring Laura Burkhauser, CEO of Descript

[00:22] Pete Pachal:

Hi, welcome to this sponsored episode of The Media Copilot, presented by Descript. I’m your host, Pete Pachal. I covered tech for a long time as a journalist, and now I have deep conversations with the media people, the builders, and the creators who are all trying to answer the question: How will we get information in the future? And how will that change the jobs and the industries whose business is information, especially media?

My guest this week is Laura Burkhauser, CEO of Descript.

Every media team right now is trying to answer a set of questions that are straightforward, but the answers are increasingly difficult. The main one is: How much AI should we bring into production?

That question alone leads to many more questions. Which parts of the workflow are safe to automate? How do we use these tools without flattening voice, lowering quality, or losing editorial control? And how do we avoid stacking one vendor on top of another just to record, transcribe, edit, clip, caption, summarize, and publish a single piece of media?

That last part really matters. A lot of newsrooms, comms teams, and branded content teams aren’t suffering from too few tools. They’re suffering from too many. One tool for recording, another for transcription, another for editing. The list goes on.

The promise of AI is supposed to be that you can go faster, have better quality, and have more leverage. But in practice, it can also create more complexity, especially if your workflows aren’t entirely thought out.

That’s why I’m excited to talk to Laura today. Descript is one of the companies trying to rethink what media production looks like when AI is actually built into the workflow rather than just bolted on afterward.

So this isn’t a conversation just about one product. It’s a conversation about how audio and video production are changing, how bigger teams should think about workflows, and how the interface for making media may become less about individual tools and more about what teams want to create.

[02:30] Pete Pachal:

We’re going to talk about where Descript fits into that shift, what newsrooms and media organizations should know if they haven’t used it or looked at it in a while, and what responsible AI looks like when the output isn’t just that one single piece of content.

Laura Burkhauser, welcome to The Media Copilot.

[02:46] Laura Burkhauser:

Hi, Pete. Thanks so much for having me.

[02:49] Pete Pachal:

Sure, it’s my pleasure. Let’s get into it. Let’s get into Descript.

As I understand it, it started as a very specific idea: editing audio and video via text. Now it feels more like a full production system. How would you describe the company’s evolution, and what has changed the most since generative AI became central to the product or integrated into the product?

[03:12] Laura Burkhauser:

Yeah. So Descript has been AI native since we were founded several years ago, and that’s because the concept of editing video like text is itself AI. Editing video like a document is itself AI.

The way that Descript works fundamentally, or our core feature several years ago, was that you record something like this. It’s going to be a 40-minute-long video podcast.

In the old world, you would go into a timeline and do a lot of cutting and splicing, a lot of work on audio, and cutting out all of my filler words. Well, many of them, maybe not all of them.

If you talk to sound engineers, they’ll tell you, “I know what that looks like on a timeline. I could draw it for you.”

[03:55] Pete Pachal:

And manually doing it too, literally putting little spaces and stuff.

[04:08] Laura Burkhauser:

Exactly. So Descript said, “Well, what if you could edit things like you edit a document?”

That doesn’t just mean deleting filler words or deleting things like retakes, but also copying and pasting and moving things around. That was kind of the initial idea.

Then Descript acquired a company called Lyrebird, which did AI audio generation, and brought that in as a research team to bring more AI into the product.

If you think about the things you do with a document, you can cut, you can copy and paste, and you can also write. We were one of the first products to provide text-to-voice, where you can write new paragraphs. Or, in my voice, if I use the wrong name or you pronounce my name wrong, you can actually regenerate it without having to re-record.

Those are some of the original features that we went to market with, and we immediately achieved product-market fit, especially in media.

Some of our longest-running customers are actually customers in some of the biggest, most noteworthy newsrooms that you know. That’s because, in addition to editing video like a document, we also had collaboration from the very beginning.

It’s like editing video the way you would edit a Google Doc, right? Someone in your newsroom may know the hell out of the story, but you have someone else who’s really a legal expert and understands the things that you can and can’t say. You have an editor coming in and checking the work. You have a copy editor coming in.

They all bring a different amount of expertise into this rough cut, eventually fine cut, and eventually polished step that you have toward making video.

Collapsing all of that collaboration together into a document that everyone can see, and allowing people to do things like paper edits, tremendously shortened the amount of time it took to get from recording to publishing.

That’s the foundation upon which Descript was built and why I think, to this day, we are in most newsrooms. In some, we’re wall-to-wall. Every single person on the production team has a Descript subscription.

Now, you asked what has changed because technology has changed so much since that initial promise. The biggest thing is LLMs.

[06:34] Laura Burkhauser:

What’s great is, if you’re able to edit video like a document and then LLMs come along, what are LLMs incredibly good at doing? Editing text.

Well, we understood all video as text. So having an LLM come in and be able to edit text really well kind of gives you multimodal editing for free.

[07:01] Laura Burkhauser:

Then adding captioning to all of our videos, so you know what’s happening on the screen every few frames, gives you visual understanding.

A dog walks by, and we’re able to say, “dog walks by,” and store that as text. That gives you visual understanding in a real multimodal way before you can build a multimodal model, which takes hundreds of millions of dollars and hundreds of researchers.

Instead, we were able to get that to you early, a couple of years ago now, which was way ahead of the times.

Then last year, we built an agentic co-editor, Underlord. Because nobody needs an AI overlord, but couldn’t you use an AI Underlord?

Underlord can come in, take direction from you, and take the first pass at editing.

[07:45] Pete Pachal:

Hope it doesn’t ever vie for a promotion.

But that all sounds really fascinating. The bets that you placed early ended up really paying off in the AI era because of how language models work.

Are there specific features that editorial teams have really zeroed in on and that explain why it ended up being popular for them?

I imagine it probably varies a bit by the type of newsroom, whether you’re more broadcast versus publishing, but give me some thoughts on what really resonates with that crowd.

[08:20] Laura Burkhauser:

Originally, text-based editing itself was huge, and collaboration, which isn’t an AI feature, but it’s just a great feature. Being able to all edit at the same time, leave comments, do approvals, things like that.

But then, as video repurposing became more important, turning one piece of media into the 17,000 pieces of media that you need to feed every single content maw across all of the publishers, using us for clips has been really exciting for people.

We have a button that creates clips, but clips is actually the feature that forced us to build Underlord.

When we released clips, we had a bunch of different parameters you could set. You could say, “I want this to be vertical. I want the clips to be about 30 seconds. I want you to use this layout that I’ve already created with my brand stuff and look for clips about this subject.”

Those were the parameters you could add in.

Immediately, people had a bazillion other parameters they wanted to add. They were like, “I want to create clips for every single one of my channels at the same time. When you do it, I want you to actually create a social post about each of the clips at the same time. I want you to only choose clips where my guest is speaking. Don’t include me in the clips that you’re adding.”

And I’m like, well, this is so much direction that at this point we’re not talking about buttons anymore. You need a little Underlord to yell at.

That kind of led us to create this idea of Underlord, which I think people really like.

Now Underlord has memory. So you can work with Underlord once and say, “Look, when I say go out and create clips, what I actually mean are all of these types of clips, along with this definition of a publishing packet that I want you to create as part of that.”

Now every time I tell you, “Go make clips,” I want you to do those 50 different jobs that we got right once.

That totally changes your workflow for some people.

You’re right, it doesn’t work for everyone. But you can really have Underlord do the first pass at everything. Then you go in and act as a reviewer.

I think for a long time, and probably honestly forever, when we’re talking about things where voice is really important, you go in and change and shift things and add in the layer that makes it you.

But Underlord can do the perfunctory things that you might hire an intern to do.

[10:44] Pete Pachal:

Nice. So, yeah, clipping is obviously huge these days, and it sounds like that’s sort of the core of maybe your value proposition to a lot of these media companies.

But you tell me. When you boil down why someone would use your tool versus something else or a stack of things, is it that multimedia capability? That you can make more from a single piece of content more easily, both in terms of speed and maybe in terms of the intelligence behind how it does it?

[11:21] Laura Burkhauser:

It really depends on the customer.

In actual newsrooms, if you ask people what they love about Descript, it’s not one-shotting editing jobs with generative AI. It is a fully functioning collaborative editor that uses AI to speed up the parts of your job that you don’t like.

My vision for newsrooms isn’t that you should just go from recording to one-shotting everything.

A lot lives in the editorial decisions that go into the rough cut. If you think about a long-form audio podcast that you love, the obvious one might be something like This American Life, but there are a million now.

There’s so much audio that’s not just a straight show like this. You and I are doing a chat show.

[12:18] Laura Burkhauser:

Editing this is going to be pretty easy for your editor, and a lot of the magic comes from the interview that you and I are doing.

I don’t know how complex you get in your editing job, but my guess is this is a pretty quick editing job. Speed is what I would use to sell this to you. Speed and repurposing all the clips is what I would focus on if I were selling to your editor.

If I’m selling to NPR and they’re doing a lot of really high-quality, prestige podcasts or video, there I’m talking about the depth of the editor. I’m talking about having your whole team in there.

Yes, we have AI features that make things way easier to do and save you hours and make you able to create a daily show instead of a weekly or monthly show.

But every story I’m telling is about humans doing a lot of work in the editor. And I think that’s because, to create really high-quality stuff, you just need humans doing work and making decisions.

That’s just something I stand by.

[13:13] Pete Pachal:

Right. So you have that inherently collaborative nature of the product, and now you have Underlord, which is kind of a collaborator too.

[13:20] Laura Burkhauser:

That’s exactly what I think about it as.

Underlord is another editor in Descript with you that is able to do some editing and has its own area of expertise, which is not the same area of expertise that you might have, that Steve from Legal might have, or that your copy editor might have.

Thinking about Underlord not as someone that you’re delegating work to in all cases, I think for some people it can be that, but in newsrooms, Underlord is more like a collaborator.

[13:52] Pete Pachal:

I’m glad you brought up memory. I’d like to chat a little bit about today’s models and how the features and capabilities overall are really accelerating.

I’d like to know, not just what helps Descript, but broadly what you’re excited about as things are progressing.

Memory, of course, has been around for a while, but it’s been rapidly evolving. That just seems like a key way things will evolve.

We think about memory as personalization for you, but in the case of a tool, it’s personalization to the workflow and someone’s rhythm. The way one person uses the tool might be totally different from someone else’s.

Talk a little bit about memory and how the new models are evolving. What excites you the most?

[14:52] Laura Burkhauser:

I think memory is really exciting, and I’ll tell you a little bit about how it shows up in creative software like Descript.

One of the fundamental criticisms of AI is that AI is, at its heart, a derivative piece of technology.

The way that it works is it does a good job of predicting what might be a good thing to do. And the way that it predicts is it trains on a huge amount of data.

That is a terrible way to create, right? What if everything you created was fundamentally derivative?

To some extent, I guess you could say you go through life and take in all of this data and have these experiences and work on a voice. And out of that comes, we hope, as creators, something that’s interesting enough that it stands out.

[15:50] Laura Burkhauser:

AI on its own will never do that because it’s fundamentally derivative.

However, what memory can do over time is begin to pick up on some of the nuances of the way you work, the context that you’re in, the workflow, and how you make things.

It stops being this regression to the mean of the most boring way to edit a podcast, tell a story, write a document, or paint a picture.

It can understand Laura’s voice, Laura’s priorities, the beats that Laura loves to hit in her stories, the importance of authenticity and humor in the way that she comes through. That might make you make different editing choices than you would make for Pete and his storytelling.

When Underlord can get a sense of your voice and your taste and your perspective, I think you start to get more excited about collaborating with it, the same way you would with a real editor whose job is to help your voice and your vision shine.

That’s why you see the same creative teams work together over and over again.

Great, your collaborator gets it now. You get the vision, you get the context, you get the kind of thing I’m trying to make. Let’s go make four more of these because you get it now.

That’s the excitement of memory for me in creativity.

[17:18] Pete Pachal:

Nice. It sounds like, in terms of it being a collaborator, it’s not even necessarily a collaborator just for people who are professional editors.

The whole text-based editing concept is a bit of a mental shift, but it’s making video editing capability, and just broader multimedia capabilities, possible for people who aren’t professional editors.

[17:44] Laura Burkhauser:

Exactly.

[17:47] Pete Pachal:

How do you think about that in terms of the ongoing discussion in society around AI? Is it here to help us? Is it here to replace us?

Does it help make teams more lightweight? Does it support them? Does it move certain lightweight tasks onto nonprofessionals? How do you think about all of that?

[18:15] Laura Burkhauser:

I think we need to absolutely throw out this concept of AI replacing humans, wholesale. I don’t want to hear about it anymore.

I’ve been saying this for a while. I think now it’s finally catching some steam, so I feel less sheepish saying it in San Francisco.

I do think AI will replace some labor, which is very different from saying AI will replace humans.

The way that I think about it, the way that I’ve worked with my team on it, and the way that I would encourage creative people to work on it, because you will come up with different answers than what me and my team came up with, is to list out the labor that you do to get to the product that you make.

Do you like doing all of that labor? My guess is you don’t.

Let’s separate it into a couple of buckets.

In the bucket of labor you don’t enjoy doing, how do you think about delegating this to AI?

You can’t always do it. I too would love to delegate putting away my clothes to AI, but unfortunately I can’t. That’s a human job, probably forever.

But how can I use AI to replace my labor with its labor here?

Then, for the stuff that I enjoy doing, how can I use AI to enhance my ability to do this labor?

[19:41] Laura Burkhauser:

I think there’s an enhancing bucket and a replacing bucket that probably follows patterns along different functions, but isn’t the same for every single person in the same function.

AI can help on both sides of the equation, but we have a choice.

We have a choice as individuals. We have a choice as organizations. We have a lot of choices for how we use AI.

I encourage everyone to use AI because I think it is foolish to say, “Hey, we have this thing that could make you so much more productive, and you’re just not going to use it on principle.”

To me, that feels like, “I don’t own a computer. I prefer a typewriter.”

Sure, as an affectation, that’s hilarious, but come on. No one actually thinks it’s a better way to work.

I think AI is going to be part of every non-affectatious life.

[20:39] Laura Burkhauser:

But I think how we use it is really going to depend on the function and on the person, to some extent.

And I don’t think it’s going to replace a single human.

[20:46] Pete Pachal:

Right. It’s more like you say, labor, tasks, whatever the word is.

To my knowledge, and I don’t have the data in front of me, the data is kind of supporting that.

I would be curious, though, about what you’re seeing, whether it’s data or anecdotes or whatever, with regard to the organizations you work with.

As they use your tool over time, do you find they’re doing more things that they weren’t able to do before? Do the teams start to get reorganized a bit?

What happens over time as people get acclimated to both the tool and working with the AI features?

[21:36] Laura Burkhauser:

Yeah, that’s a great question.

First, the way that I would talk about Descript’s customers is that we work with media teams and marketing teams.

We work with media teams all the way from a solo podcast to a national or international newsroom.

We work with marketing teams all the way from a solopreneur who is creating content to market their coaching business to some of the biggest enterprises in the world.

We work with storytellers in media and marketing. Those are our main kinds of customers.

What we find that they’re able to tell us is that, because of Descript, people who normally cannot take part at all in the media editing or storytelling part of the equation are now able to help.

But really, the story is that we can do video where we couldn’t do video before.

We hear from places saying, “We stopped doing video as a team because it was just too much. It was too much work. We were doing all text and maybe some audio, but no video.”

Now, we can do video as a content type.

Or we moved from doing video once a month to being able to do a daily show.

If we’re talking about an actual newsroom, doing a daily show is insane. The fact that you can do multiple daily shows and just have one or two editors working on that is unthinkable in the podcasting world of a decade ago.

And that’s because of Descript.

We can do it more often. We can do video where we couldn’t. We can do video more often.

[23:32] Laura Burkhauser:

And we can do video across many more channels.

We can do long-form video and all of our short-form clips. We can do video that is tailored for all of these different channels where we need to go out and meet the customer because they aren’t necessarily coming to our site anymore.

What I actually see is a lot of media companies moving toward a world where, yes, they have their own site and their own channel, but they also have a network of creators that you may never know is part of that media conglomerate.

They work with all of these podcasters or creators who are monetizing the way creators monetize, through things like sponsorships and YouTube ads, and the media company gets some portion of that.

There are these new economic models being built on a creator economy that depends on being able to create video much faster and across many more channels.

[24:32] Pete Pachal:

That sounds really interesting because it dovetails with a lot of media strategy right now. It’s taking advantage of this creator economy, the systems, and the ways that creators execute.

It’s an interesting merger. Obviously, like you say, creators are doing it, but even the bigger companies want to take that approach.

[24:57] Laura Burkhauser:

They absolutely are.

That’s critical to more traditional media companies surviving in the age of new media.

You want to keep the brand recognition that you have. You want to keep the valuable asset that you have. But you need to start going out and meeting people where they are, across all of the channels where they’re consuming news, which is not necessarily your site.

[25:19] Pete Pachal:

Of course, bigger companies, when you get to the enterprise level, have a set of concerns around liability and security and all these other things.

Has that been a challenge at all, trying to address all those things they want to do, like SSO or whatever?

[25:36] Laura Burkhauser:

Every startup loves going enterprise. It’s everyone’s absolute favorite thing to do.

As a product manager, it is always hard for me to say, “Yeah, I don’t want to go build agent memory because I would so much rather build SCIM,” which is a permissioning solution for companies that need to let some teams have access to some things and some teams not have access to other things.

If you had asked me two years ago, I would have been pulling my hair out about that problem.

I think we’ve mostly crossed the chasm there and are able to offer mature enterprises all of the wonderful features that they would love.

We’re also very careful about things like data retention. An enterprise company is obviously very private about their data.

Making sure that we’re able to meet customers where they need to be met when it comes to things like data privacy, permissioning, and all of those other wonderful enterprise features is important.

[26:49] Pete Pachal:

If you don’t mind getting into the weeds a bit, I’d like to ask about some of the features that ended up being surprisingly important.

As I edit things and do my amateur-hour stuff on podcasts or whatever, depending on your passion for the material, you can end up being kind of a perfectionist about things like chapters or show notes.

Particularly with AI features, the promise is always that it gets you a certain percentage of the way there and then the human takes it from there.

Has there been something where, surprisingly, people really needed it to be 95% there where you thought 70% or 80% would be enough, and then you worked to perfect that?

There’s a lot of iteration on some of these creator features, I imagine, depending on the feedback you get from customers. Is there anything that stands out or was surprising?

[27:56] Laura Burkhauser:

That’s a good question.

I’m always humbled by customers. It’s one of the things that I love about this job.

You have an idea of what people will use a feature for and how it’s going to land, and then the data always humbles you. The interviews always humble you.

I’ve been surprised by many features.

For me, maybe something that was surprising was when I was an amateur podcaster. I actually found Descript through podcasting.

I started a podcast with my friend, and we used Descript to edit it. I was like, “My God, I think I have to work at this company. This is the coolest thing I’ve ever used.”

[28:42] Pete Pachal:

You didn’t tell me you were a professional at this.

[28:47] Laura Burkhauser:

I am definitely not.

But one of the features that I loved was Remove Filler Words because, if you can’t tell, unless Pete has kindly removed all of my filler words, I use a few filler words.

[28:58] Pete Pachal:

I like to keep it real.

[29:16] Laura Burkhauser:

Exactly.

So I was removing all my filler words, and then as soon as I joined Descript, I found out that there is a huge camp of podcasters who are pretty against removing filler words and actually pretty against a lot of the automated editing, just-one-click, don’t-think-about-it kinds of buttons that we created, like removing pauses.

They’re like, “Look, when you get further into the editing game, you will realize the value of a pause and the value of a filler word, and of retaining the integrity of the sentence the way that the person created it.”

You don’t always do that. You never want to embarrass your guest. Do you hear me, Pete? You never want to embarrass your guest.

[29:50] Pete Pachal:

Wouldn’t dream of it.

[30:10] Laura Burkhauser:

You do want to get rid of some of them, but it takes judgment.

The more you talk to people who have been in the editing game for a long time and who are really working on S-tier kinds of content, the things that you love and have a ton of admiration for, the more you realize how much judgment goes into even something like that.

Which “ums” do you remove?

Automation can be really helpful for a lot of kinds of content. But that’s where I don’t lean a ton on automation when I’m talking to an experienced editor because it just doesn’t ring super true to them.

[30:34] Pete Pachal:

It reminds me of when Ben Affleck had that thought a couple of years ago about AI not having taste.

I wholeheartedly agree with everything you said there about integrity. Sometimes you want it out, sometimes you don’t, and that could even be in the same piece of media.

By way of transitioning to looking forward, do you think we’ll ever get there with AI?

Could it look at a conversation and think, “A pause right there would be great,” and then leave something in and apply a certain amount of taste to it?

This is getting pretty advanced, but who knows? New models come out every week.

[31:17] Laura Burkhauser:

I think yes. And that’s what we’re aspiring to build.

But again, I think that taste is not generic.

When we talk about taste, we talk about it as either you have it or you don’t. I think that’s true up to a certain bar, and I think we can get AI up to that bar.

But then the question is: Is it interesting?

[31:47] Laura Burkhauser:

Is it authentic? What is the taste? Taste to what end?

That’s where it’s all about who’s driving the car.

I do think it will get better. I think there are also going to be limits.

When it gets that good, will it get that good in a way that works with the business? Will it get that good in a way that is cost-efficient and works across all tools?

It’s not just intelligence that is the bottleneck here, but certainly the level of intelligence is a bottleneck.

I think taste is eventually a solvable problem, but it won’t fundamentally change the fact that taste plus an excellent human will still outperform generic taste every time.

[32:39] Pete Pachal:

Yeah, that makes total sense.

I’d love to chat a little bit about the general trends in AI these days. There’s been a bit of a backlash here and there.

I know that’s a generalization, but people are getting booed at graduation speeches. Whether it’s generational, I don’t even quite know how to think about the various dimensions of this, but there’s no doubt there’s a phenomenon out there.

Thinking about the people you talk to and creatives, who have always had a segment that has been skeptical of AI, how do you hear all that criticism?

What do you think is fair? What isn’t?

And what do people, particularly at AI companies, get wrong about how they talk about AI, particularly to this demographic of creatives, writers, editors, et cetera?

[33:34] Laura Burkhauser:

I think the way people talk about AI in San Francisco is absolutely insane and so alienating and inaccurate.

People are always inaccurate, but it feels self-defeatingly inaccurate in a way that, if you have any kind of connection to reality, if you have relatives who don’t live here that you respect and talk to, you’re just like, “What? I’m sorry?”

Why is the leader of every lab walking around saying, “Someone should stop me. My God, I’m building this really dangerous thing that’s going to ruin democracy and kill everyone. Someone should stop me,” and then is surprised that people are like, “I’m super freaked out. You should stop building this. This is a bad thing.”

It’s like, you’re giving us the talking points, dude.

Stop telling us that you’re building bad things. You’re freaking everyone out.

I just don’t understand it. I kind of understand it. You want to feel like, “Wow, everyone should give me more money because I’m building this thing that’s so amazing that it might kill us all.”

I still think that’s questionable. Please stop doing it.

You’re not watching this podcast. You’re very busy. But maybe someone can show this person a clip.

Stop doing it. Stop saying that.

[34:50] Pete Pachal:

I think their comms teams are listening to this podcast, so hopefully that’ll get through.

[34:55] Laura Burkhauser:

Yeah. Stop doing that.

I got started in consulting, and we used to have to take trainings on change management.

Whenever there was going to be a big change, they’d say, “You’ve got to identify the burning platform and you’ve got to identify the beach.”

The burning platform is the reason why you absolutely have to change. We cannot stay the same. It’s not going to work.

The beach is the party that you get to have when you finally jump off the burning platform. This is the thing you get people excited about.

No one is selling the beach right now.

No one is telling us why we’re excited about AI.

To the extent that they are, they’re using language that makes capital owners excited, like “more productivity.”

But to someone doing the work, when they hear “more productivity,” they hear, “Wow, sounds like I’m doing a lot more work in the future.”

Or you have people talking so far into the future that it doesn’t feel credible and isn’t credible, like, “There won’t be any work in the future.”

That’s scary, too far away, and probably not ever true in anyone listening to this lifetime.

I just think we’ve gotten it totally wrong about getting people excited about this stuff.

[36:18] Pete Pachal:

So then, zeroing in on the creative set, your customers, how do you think about that in your messaging?

How do you talk about AI with customers or even just people in general?

[36:32] Laura Burkhauser:

In the creative world, it’s even worse because you have this Twitter feed of some of the lamest stuff you’ve ever seen with AI-generated video.

Then you have a bunch of people in the tech world being like, “My God, Hollywood’s dead.”

Anyone who actually makes video is looking at this dog surfing and is just like, “I’m super unimpressed by this dog surfing video. Am I insane?”

Why is Hollywood dead because you made a pretty mid video of a dog surfing?

This is bad.

[37:05] Pete Pachal:

Yeah. It’s a standalone thing that, on its own, might be interesting and curious.

Show me the movie where that’s somehow integrated and it’s flawless, and maybe we’ll talk.

[37:17] Laura Burkhauser:

Yeah, and maybe we will.

I frankly think that we will start to see generative AI technology in video and in movies in Hollywood. We probably already are.

I think we’ll see this technology come in, and it’s going to be boring.

It’s going to be the way that Pixar changed the way we all do animation, with a pretty boring, to most people, behind-the-scenes change in how animation happens.

No one thinks about that. They’re just like, “Wow, Monsters, Inc. was such a good movie. I really liked that story. It made me cry.”

That’s what gets people excited.

It’s not the technology that people are using. It’s actually making really cool, admirable, exciting art.

When I look at the box office right now and see a movie doing super well that was made for under a million dollars and has already made something like $250 million at the box office, this is exciting to me.

This is a beach.

What if the beach for AI and creativity is that you are empowering people to make really exciting, original storytelling for under a million dollars and get distribution?

More stories get told. More original stories get told.

We’re not going to see just a bunch of $500 million superhero movies in the theater. We’re going to get to see original storytelling and be able to take more bets on early-stage filmmakers.

I’m excited about that beach. These are some of the stories you can tell.

At Descript, because we don’t do a lot of this generative, “there’s no real human in this ad” stuff, we do recorded media.

[39:01] Laura Burkhauser:

A lot of how I talk to people is that I say: Struggle with your art, not with your tools.

We’re not trying to replace the art here. We’re trying to help make it easier for you to make it.

You’re still going to need to struggle with that storytelling, but not with the tools that it takes to build that story.

[39:20] Pete Pachal:

I usually like to end these conversations on things you’re hopeful about and maybe concerned about as we go forward, but I feel like you’ve answered a lot of that in what you just said.

I’d be curious to jump off your last point about making things more accessible because I feel like that zeroes in on a trend in toolmaking.

You see this in a lot of different creative apps. Basically, it feels like everything is slowly moving away from discrete buttons, menus, and hard-to-find features.

If not overtly a chatbot, it’s becoming more conversational. You tell the tool what you want, and it figures out what it needs to do.

How far does this idea go?

Putting aside Descript for a moment, what does interacting with software look like in three to five years?

[40:14] Laura Burkhauser:

That’s a great question and one we talk and debate about all the time at Descript.

I don’t think buttons are going away, but I do think chat is still on the ascent.

I’m a big believer in voice. The way that I talk to Underlord is that I dictate to it.

As you can tell, I’m a bit of a rambler. It’s hard for me to get it into five words. That’s the difficulty with writing for me.

[40:44] Laura Burkhauser:

It’s sitting down and writing what I think succinctly.

So I turn on the microphone and just kind of ramble to Underlord and let it know what I want it to do with the video, and it does it.

[40:54] Pete Pachal:

I feel like the AI question of the moment is, “What do you use to dictate?” as opposed to, “What’s your phone, iPhone or Android?” from the previous era.

That’s the pro move.

[41:02] Laura Burkhauser:

Totally. I use Wispr Flow. I love it.

But I don’t think buttons are going away.

Buttons and dials are important for people who need control and want to get in there and set things the way that they want them.

I’m excited about UI on the fly, where the computer is smart about generating the right buttons and dials at a moment’s notice.

[41:32] Laura Burkhauser:

If it’s easier to turn a dial and I’m talking to you and I’m like, “Hey, I need more confetti in this shot,” maybe it generates more confetti in the shot and also gives me a confetti knob.

It’s like, “Okay, I put in more confetti, but if it’s not right, just turn the knob or dial to the right amount of confetti.”

You would never need a permanent confetti knob, but because it’s so trivial to generate software in the future, it can actually just generate that knob for you at a moment’s notice to give you the control.

Buttons and knobs are really useful for high-level control, which you’re always going to need for precision editing.

[42:05] Pete Pachal:

Nice. Yeah, I think some people might need a confetti knob. A lot of people edit wedding videos, so that could be a thing.

Laura, this has been fantastic. I want to say thanks so much for dropping by The Media Copilot and sharing your thoughts.

There’s a lot to absorb, but this has been great. I really appreciate you coming on.

[42:40] Laura Burkhauser:

Pete, thanks so much for having me. A really great conversation, and I look forward to chatting again soon.

[42:46] Pete Pachal:

For sure.

The post AI won’t replace Creators. It will replace the work they hate. appeared first on The Media Copilot.