How A.I. Will Change Conservation Photography with Allen Murabayashi

Episode 151: How A.I. Will Change Conservation Photography with Allen Murabayashi

Shownotes: ConservationVisuals.com/151

(Digitally transcribed, please forgive any typos)

Jaymi Heimbuch:
E 151 - Allen Murabayashi
===

[00:00:00] Jaymi Heimbuch: Every so often in life, you can get lucky enough to meet someone who has had a very real but very subtle impact on your life without you ever realizing it at all. And that's the case for me with Allen Murabayashi. Alan is the co-founder of Photo Shelter. Photo shelter is one of the most popular platforms out there for photographers for hosting their website to be able to not only have these, , beautiful galleries, but also to be able to license their imagery and to have a really great stock photo library.

[00:00:32] Jaymi Heimbuch: So I have been for years and years on photo shelter websites, practically every day going through photographer galleries and so on, and. I never realized, of course, 'cause I'm not out there looking up who co-founded , this tech software. I never realized how much Alan's work has influenced my daily life as a photographer and a photo editor until his name came across my radar.

[00:00:54] Jaymi Heimbuch: Recently when I read an article in Audubon magazine titled, what does generative [00:01:00] AI mean for bird and nature photography? Well, that's kind of a showstopping title right there, right? Because what does AI mean for the future of bird and nature photography? For the future of conservation photography?

[00:01:12] Jaymi Heimbuch: And as I was reading through this article, I thought, oh my goodness, I really wanna talk to the author. And turns out the author is Alan Mursi,

[00:01:20] Jaymi Heimbuch: I'm just, I'm kicking myself for not having realized his name and been following his blogging for years. Because Alan is so insightful. He has so much to say about not only this topic, but a whole lot more. And so it was a big honor when he said yes to coming on to the podcast to talk about what influence does AI have and will it have on conservation photography? And our conversation today not only ranged throughout that topic, but also things like how to continue making a living as a conservation photographer and revenue streams and so much more. It was an absolute joy to get to sit down and talk with Alan, and I [00:02:00] think you are going to love this conversation as much as I did, and get so much out of it. So without further ado, let's jump into this episode.

[00:02:08] Jaymi Heimbuch: Welcome to this episode of Impact, the Conservation Photography Podcast.

[00:02:12] Jaymi Heimbuch: And today we're gonna jump into a topic that has everybody buzzing. And that is ai, artificial intelligence, and we've got a really spectacular guest today who. Is gonna help us think more critically about the future of ai, and specifically how it can impact conservation photography, what it means to us as conservation photographers, what it means in conservation science.

[00:02:35] Jaymi Heimbuch: So, Alan, welcome to the show. Thank you so much for

[00:02:38] Allen Murabayashi: being here. Thank you so much for having me, Jamie.

[00:02:42] Jaymi Heimbuch: So before we dive into everything, I'm already eager to start asking questions, but before we jump in, for anyone who has not had the joy of meeting you, who is Alan in the

[00:02:50] Allen Murabayashi: world?

[00:02:52] Allen Murabayashi: I'm Alan Mursi. I am the co-founder and former c e o and chairman of a company called P Shelter which was a[00:03:00] is a cloud-based service for photographers to store and manage an archive their photos. We also have a. Organizational version of that product, which services most of the professional sports leagues and teams and universities and tourism bureaus, et cetera.

[00:03:16] Allen Murabayashi: So as more and more organizations and individuals have been creating and storing and distributing digital content our product kind of fills in, in the niche for managing that stuff online.

[00:03:28] Jaymi Heimbuch: Yes, I'm super familiar with photo shelter websites. As a, a photo editor, I love landing on websites that are on photo shelter because it's so easy for photographers to just make me a light box and I can just download their photos and it's awesome.

[00:03:41] Jaymi Heimbuch: So, while I'm definitely familiar with Photo shelter, I became familiar with your work more and more after reading a particular article that came out in Audubon Magazine which you wrote about AI and conservation. And it was kind of a shocking article to read because of [00:04:00] how it even start, like the whole intro of that article.

[00:04:03] Jaymi Heimbuch: Would you mind giving us kind of a, an overview of this article and what sparked it and how you created it?

[00:04:09] Allen Murabayashi: Yeah, I guess I should back up a little bit. You know, I've been blogging about the photo industry for about 15 years. So a bit of a, a pundit in terms of kind of watching what's happening in the industry, both on the, you know, camera, technology, hardware development side, as well as the way that photos are being used by photo professionals, whether they're editors or other photographers, but also general consumption, how culture is sort of looking at photography in general.

[00:04:33] Allen Murabayashi: So Because of kind of being in and outta the industry. A few years ago, Audubon asked me to be a judge for the Audubon photo contest. So that's how I met a lot of our mutual friends over at Audubon. And after doing that for five years I finally got off of that jury, but then Sabine, who runs the photo contest, asked me whether I'd have any interest in, in writing about AI as it relates to conservation photography.

[00:04:59] Allen Murabayashi: And it [00:05:00] was something like many of us Who have been sort of keeping an eye on what's happening in AI was I, I've been very interested in seeing the rapid development of ai particularly as it relates to what's called generative ai or the, the AI's ability to create new content, whether it's text, video, or photography.

[00:05:19] Allen Murabayashi: And that kind of took me down a bit of a thought experiment, you know, contemplating how ai could be used, but also looking at how, how. Computer imagery and other fabricated photos or Photoshop have been used to sort of fool the audience in the past. And so that became, the intro of, the article.

[00:05:40] Allen Murabayashi: And, and as a part of that article, Audubon also tried to generate. Images using Mid Journey or Dolly, I can't remember exactly which system they used, but they, they tried to generate images based on the images that that won in the past. So that was just an interesting, you know, way to kind of look at where we [00:06:00] are now and what direction we could be headed to in the future.

[00:06:03] Allen Murabayashi: Yeah,

[00:06:03] Jaymi Heimbuch: I definitely was. A little unnerved, I have to admit at how close the generated images were to the winning images. So when when you open up this issue of Audubon, you see the winning images, and then the next article or the next you know, page as you go through those images is. These images are fake and it shows the ones that were generated and the alt text from the winning images were inputted in order to generate these other versions.

[00:06:32] Jaymi Heimbuch: And the similarity of what was generated to the content of the original images was pretty trippy. I had my family on a Zoom call and I was like, you guys, you gotta look at this. And so I was showing them the, the magazine pages on our Zoom call and uh, it's, it's really surprising and. What I loved about your article was that you jumped into a lot of the, basically the pros and cons of AI inside of conservation, [00:07:00] and that this is something that we really need to keep an eye on, that it is worrying where it could go, but it's also exciting where it's being used for conservation efforts.

[00:07:11] Jaymi Heimbuch: Can you talk a little bit about the way that conservation is helpfully using AI to further research or science?

[00:07:19] Allen Murabayashi: You know, when people have been introduced to ai you know, in the past six months or so through these chat bots, chat, G P T, et cetera, and then maybe, you know, a lot of people have seen the Pope and the puffer, which I think was the first sort of viral, generative image.

[00:07:35] Allen Murabayashi: And so they kind of understand visually, That we're on this cusp of a revolution to be able to maybe just type in what we want, right? Text to image. Text to video is already a reality. Whether you think it's convincing or not is up to individual tastes. And I I also think that since so much con content consumption happens on the phone, it's really hard to [00:08:00] scrutinize an image that's, you know, two inches across.

[00:08:02] Allen Murabayashi: And so in a lot of cases when you're looking at a printed magazine and you say, well, the feathers look a little weird, the feet are a little weird. Now try looking that on your phone and scrolling, you know, 50 images per second like the way the kids do it. And that level of scrutiny no longer is there, and so the fidelity of the image no longer needs to be there.

[00:08:21] Allen Murabayashi: So in most cases, what this, you know, version three of AI or version two, depending on who you're counting on is more than capable of creating. Convincing imagery, but to me the real interesting stuff that's happening in conservation is really more on the machine learning side. And so machine learning is a subdiscipline of AI that's basically used a lot in conservation for its ability to comb through a lot of data very, very rapidly.

[00:08:50] Allen Murabayashi: So as most people know, every device we have collects some form of data. Nowadays, you know, there's thousands of sensors in your car. Your phone can. It can capture photos, but it can [00:09:00] also capture lidar. It can capture audio, it can capture video. And, and the real problem is, you know, if you wanna do something nefarious or something great with all this data, you need a way to sift through it.

[00:09:12] Allen Murabayashi: And so most of the interesting conservation stuff that I've been reading about in the past few years is really like if we look at a million photos, Can we discern any patterns in it? What can we do that's useful out of it? Ohio State University had a project where they were analyzing photos of leopards and leopard spots, and whereas the average human can't detect patterns in leopard spots 'cause they just look like spots.

[00:09:37] Allen Murabayashi: It turns out that the patterns showed genetic relationships between the animals and the machine learning was able to determine. Offspring from their parents. And again, it's something you need a massive dataset. You've gotta train that dataset. You've gotta verify these results that that machine learning is throwing out against d n A.

[00:09:57] Allen Murabayashi: But once you make those correlations, it becomes an [00:10:00] incredibly powerful. Tool. And so machine learning as it relates to sifting through data and machine vision in a lot of cases to me is the application today that gives me the most hope in terms of conservation. I don't think that the average conservation photographer is going to see their.

[00:10:22] Allen Murabayashi: Their lives threatened because somebody figures out how to generate a bird, you know, more effectively. It's just not. Mm-hmm. It's not what we're in the business of doing as, as photographers. And, and I hope, because I know you're a photo editor as well, you know, as long as we have smart and savvy photo editors in the way of.

[00:10:41] Allen Murabayashi: As gatekeepers to say we need to send a photographer out into the field to actually capture this animal out in the field. And this photographer needs to spend three years out in the field, three seasons on in the field to really understand the, the behavior of this animal. That stuff isn't gonna go away.

[00:10:59] Allen Murabayashi: We'll [00:11:00] have camera traps and other automated ways to maybe alleviate the need for a human to be out there all the way. But it's still gonna be a camera that's capturing this stuff, and a photographer who's determining how to create these shots that are very compelling.

[00:11:12] Jaymi Heimbuch: I'm so glad that you, you mentioned that because it definitely, the rise of AI in terms of creating images, I know has a lot of photographers worried.

[00:11:20] Jaymi Heimbuch: They're like, well, if you can just tell a computer to create an image and that's what's gonna be used, then who's gonna hire me to go out and take photos? And I think that if you are sort of. Someone who's doing generic stock photos of whatever, then sure, that could be a nervous thing. But for conservation photography, we're typically documenting things that you can't dream up or describe, like it's not known yet, or it's activity that is happening on the ground.

[00:11:45] Jaymi Heimbuch: Maybe that's not necessarily always the case. Maybe it's not necessarily true. Maybe there are situations where you could create scenes through AI and use that, but for the most part, we. We need photographers [00:12:00] out there still documenting what's happening and what's going on the ground. So I have this theory and I would love to hear if you think that it sounds possible or, or dumb or what, but I actually think that the rise of AI will bring a higher value to human made.

[00:12:16] Jaymi Heimbuch: Photography. You know, we saw a lot of the value behind photography plummet when stock agencies starting to started to do tons of royalty free licensing and so on. And so we saw this huge decline in in income levels for photographers. But I feel like this is actually gonna bring back a lot of the value that we've lost over time to have humans go out and make real world photos.

[00:12:38] Jaymi Heimbuch: What do you think about that? I

[00:12:40] Allen Murabayashi: think that there are genres of photography, like stock photography and product photography that will most likely go to ai just because they are fairly generic in nature. There's not a ton of intrinsic. Value in those types of images. And arguably when it comes to something like product [00:13:00] photography, you really, you spend so much time manufacturing the scene to be perfect and then Photoshopping, whatever image you have, that in some ways you might as well computer generate the thing or let in the first place, not, you know, and that's nothing against the very talented product photographers that exist out there, but there are very few.

[00:13:16] Allen Murabayashi: For example, you know, very few High-end watch photographers and very few high-end vodka photographers just be, there's not enough work. For them to do, and it's so specialized and good for them, they'll have, you know, may hopefully they'll finish out their career. I I, I look at some of the generative art that's been created and thrown out there on, you know, the, the various discord channels where you use Mid Journey, et cetera, and they're all impressive, you know, in terms of that a computer created at based on human analyzing, human creation.

[00:13:47] Allen Murabayashi: But, you know, it's, it's kind of akin to the difference of a college kid putting a poster on his wall. Of some famous artwork versus actually owning the artwork, right? There's something [00:14:00] you, you can create a rendering of, of art, but I'd rather have the sculpture in my home and be able to look at it, you know, from three-dimensional perspective.

[00:14:09] Allen Murabayashi: And I think that there's something, even if you could three d print it, there's something to say. No. I know the artists who created that with their hams. And people I think will. We'll always find value in stuff that's human created because we've had, we've had instruments played by computers that can play any piece perfectly, but I'd rather see a human, like, I wouldn't pay to go see a computer play a piece.

[00:14:32] Allen Murabayashi: I would pay to go see a human you know, sing a song. And with the Beyonce tour and the, and the Taylor Swift tour, I mean, it's, it's clear that there's value. People want to experience live performance. Together. And similarly with photography, I think there are certain types of photography where, of course I want to have a relationship with a photographer.

[00:14:52] Allen Murabayashi: I wanna know the backstory. And all, some people are content to just have a photo that has no meaning to them on the wall, but most people wanna know the [00:15:00] backstory. I think most people wanna know the, know peripherally who took that photo, and under which circumstances et cetera. So I agree with you.

[00:15:07] Allen Murabayashi: I think That art and photography are human creations and people will always be attracted to this stuff created by humans.

[00:15:17] Jaymi Heimbuch: It feels really reassuring to have you say, yes, there is some future to the value of the work that we do. It's not going anywhere. Okay. So that makes me, I feel like I'm gonna have a good day for the rest of the day now.

[00:15:28] Jaymi Heimbuch: What about for conservation photographers who are out there creating work? Do you have thoughts or philosophies or suggestions for how they can really. Project themselves or set themselves apart and say, I am active out in the field here is, you know, what's happening behind my photography. This is human made.

[00:15:48] Jaymi Heimbuch: Are there things that should go in metadata now? When we're uploading images online, or are there, I I know that this is a very broad, general, vague question, but I'm just curious about your thoughts on [00:16:00] making sure that photographers are taking the next best steps in an AI world to show that they are actively creating their images and that their content is not AI generated.

[00:16:10] Allen Murabayashi: I tend to think with conservation photography, it is mostly of a lo love of labor because I don't know any conservation photographers who are getting rich off of being conservation photographers. I mean, we, we can probably think of maybe five who have created art galleries and, and sell work, but for the most part, people just really care about one aspect of conservation photography and they go out and do it in, in that sense, the threat isn't necessarily.

[00:16:37] Allen Murabayashi: Ai, it's just been a shift in the way that content consumption has happened over the past 20 years. And I think when you look at you know, Instagram influencers and that ilk of content, Producers. It really comes down to creating a relationship with your audience and learning how to become a really effective storyteller and learning kind of some of the psychological ways to sort of hook people to your content.

[00:16:59] Allen Murabayashi: [00:17:00] And so, you know, I look at photographers who will spend five years working on a project and maybe think that the book is the. Is the end all, be all of that, the manifestation of their, their time of work. But I think more savvy photographers are learning how to document the journey of any project and put that out on social media and use crowdfunding like Patreon subscriber funding.

[00:17:27] Allen Murabayashi: And Instagram has some monetization capabilities and, you know, the, the, there's a ton, ton of different monetization platforms. And that to me seems at least for the next three years, at least, one way to make conservation content creation more viable. 'cause when you think about it, You know, as a conservation photographer, let's say the goal is to gross a hundred thousand dollars a year, and if you were able to create a Patreon and you were able to [00:18:00] get 500 plus subscribers on YouTube, which is now the minimum threshold for a.

[00:18:04] Allen Murabayashi: Monetizing through ads there, there are ways to sort of piecemeal together income streams to sustain the type of work that you're doing. I think, and it's, it's not that it's easy to do. I've had a couple YouTube experiments out there right now. One that's going relatively well, one that's not going very well because you have to learn how to build audience and it's very, very difficult to do and it's very time consuming to do. Um, but I do think that there is a way for conservation photographers to continue doing what they want to do by learning new ways to tell the stories. And again, none of that has to do with ai. It's just, it's just trying to learn how to use the tools that we have now to engage an audience to make conservation, photography financially viable for photographers.

[00:18:47] Jaymi Heimbuch: Yeah, I think that ties in beautifully too, with. Inside of conservation photography, really knowing your audience in order to get a message across, like you have to study, who is the audience that you're actually trying to [00:19:00] reach with your work to make a conservation impact, and how do they want to be approached?

[00:19:04] Jaymi Heimbuch: How are they listening to things? Where are they at? What platforms are they on? What are their values? What are their fears? What are their biggest goals in life? All of these things so that you can build. The right kind of angle to your story that will appeal to that audience so that they will hear the conservation message that you are trying to tell inside of your photo story.

[00:19:21] Jaymi Heimbuch: And the same thing with your audience as a conservation photographer, the ones that can financially support you through your different business revenue, whether that is through tours, YouTube, Instagram, you know, article creation on a website and driving track, like whatever it may look like. If you're funding your photography through a Patreon account, like who are you trying to attract and what is it that they're really looking for?

[00:19:43] Jaymi Heimbuch: For, and so there's a lot of, just, I feel like if there is something that a conservation photographer can learn that is equally as important as the gear that you use that is equally as important as the composition, it is audience.

[00:19:57] Jaymi Heimbuch: analysis, really [00:20:00] understanding audiences, how to get at the information and testing, testing what is appealing to people, and getting feedback and, and playing with that. That went really far away from our original topic, but it's fascinating. Like it's really fascinating.

[00:20:13] Allen Murabayashi: It's totally true. And you know, when you look at something like workshops, photo workshops, photo workshops, you can't scale them in the way that a tech app could scale, because photo workshops are really, it's like your wedding planner.

[00:20:26] Allen Murabayashi: It's a one-on-one relationship, largely with your audience and figuring out how to get the person that comes on your workshop to come to the one next year as well. Mm-hmm. It's very much driven by sort of repeat audiences, and there's probably some metric that. The people that study this know whether, whether you need a third or one half of your audience to be repeat customers, to have a viable business doing that stuff.

[00:20:48]

[00:20:49] Jaymi Heimbuch: Yeah. I think that comes back to what you said earlier too, about getting really good at not only documenting the story that you wanna document as a conservation photographer, but also documenting the journey of [00:21:00] creating that story to build a relationship with people.

[00:21:03] Jaymi Heimbuch: That's a huge part, I think, of standing apart 'cause. With ai, okay. It's really cool that you can create this image, and it is just that image. There's no story behind it. There's no photographer behind it. It is this very static thing that will potentially have quite a short lifespan. Whereas if you are someone who is documenting the journey of who you are as a conservation photographer, then people can feel like they know you, feel like they support you, feel like they wanna be part of what that looks like, and then they also trust everything that you are creating and that trust builds.

[00:21:35] Jaymi Heimbuch: The desire to support that. So I think that it really goes back to you what you said earlier about that being part of almost like brand building and foundational business building, like building that audience through true stories in the field and, and really leaning into that. I know that there's a lot of conservation photographers, well just photographers in general who have been around for a really long time, and so they, they bulk and rightfully so in a [00:22:00] lot of ways at the idea of influencer culture on Instagram, but another.

[00:22:04] Jaymi Heimbuch: Way of thinking about it is, well, how can I take what works inside of influencer culture and use it to my benefit as a conservation photographer to help create more awareness and more support for these conservation issues? Like you can take what you don't like about something and transform it into something that really works for you.

[00:22:22] Jaymi Heimbuch: I, I, I think

[00:22:23] Allen Murabayashi: the, the argument against influencer culture is that they, you know, the stereotype is they tend to have a very thin understanding of, you know, the places that they're going or the things that they're talking about, which to me, historically has been sort of the opposite of conservation photographers who I know that have a very deep understanding, but maybe aren't the best storytellers in the way that.

[00:22:45] Allen Murabayashi: Influencers are able to connect with audiences through storytelling. So I totally agree with you. There's a give and take that, you know that's available there. I'll also say, you know, going back to a little bit of the AI conversation, AI is not fooling [00:23:00] experts in conservation photography right now because most people have read that AI is trained on human created data, whether it's photos or writing, et cetera.

[00:23:10] Allen Murabayashi: The training sets that are used to train like bird photography for example, are not very. Deep. And so it's very easy to say, you know, put in a specific species of a bird and find that the rendering that it comes up with is not even close to reality. And I don't think that that's something that's gonna be resolved in the next two years because there's no financial incentive for these big companies like Dali to like figure out how to render an endemic bird from Hawaii very accurately.

[00:23:41] Allen Murabayashi: Right? And so in that sense, I think that. Conservation photographers are always gonna have a leg up, at least for the next three to five years until there is actually a financial incentive to know how to render an e e v bird properly, which I don't think there there's ever gonna be. But, you know, other, other tools that conservation [00:24:00] photographers can use.

[00:24:01] Allen Murabayashi: I mean, so the burden community is one that's always fascinating to me because of the, fervent and vigilance that birders seem to have about like, Don't tell people where we've spotted this bird and let's document everything. And I've seen 250 of the 279 species in this area.

[00:24:19] Allen Murabayashi: But, but that, that level of enthusiasm has also made things like the eBird app. Financially possible and, you know, cool things. The eBird app data is being used for another project called Bird Flow, where they predict the migration paths of birds, and then they take the prediction against observational data and figure out how to tweak the model a little bit more.

[00:24:42] Allen Murabayashi: And, and that kind of stuff can be used to. Figure out which habitats to protect, for example, like along the corridor of the migration path. Where should they go? You know, photographers should not see themselves as, all I do is go out with my camera and I take photos with my camera. We, we really should think of ourselves as[00:25:00] multimedia storytellers.

[00:25:02] Allen Murabayashi: And I don't mean like the two thousands version of multimedia where you're handing out a CD that had a music track. I'm really talking about. The addition of infographics the, the addition of, you know, more data into your presentation so that you're appealing to both this sort of visceral, like, wow, that's a gorgeous photo, as well as here's some important facts to know about the threat to this species.

[00:25:25] Allen Murabayashi: For example. There's a lot of things that, that photographers can, can use coming out of the machine learning that I think will be helpful to them in the future. Excellent.

[00:25:37] Jaymi Heimbuch: What are some of the things that, when you think about AI and the future of photography, or just the future of our natural world, what are some of the things that make you feel the most hopeful?

[00:25:51] Allen Murabayashi: I thought you were gonna start with a negative. 'cause that's, I know, that's the obvious. Uh, Hopeful. Hopeful. [00:26:00] I, again, I think that the ability for AI to kind of sift through mounds of data and figure out patterns that we haven't seen before and maybe alter. Human behavior in some ways, a result of that is exciting to me.

[00:26:14] Allen Murabayashi: So everything from, you know, discovering new drugs solving disease, using it for conservation purposes, you know, I mentioned bird flow predicting flight paths. Ohio University leopard spots. There's another project called Earth Ranger out of the Allen Institute for ai. That's used to.

[00:26:32] Allen Murabayashi: predict movement of animals when they're encroaching near human populations to figure out whether there's gonna be a dangerous encroachment and how rangers in that area might prevent things that would result in the animal being put down if they encountered humans. Skylight is another program by the Allen Institute for ai. They are using open source satellite imagery to track illegal phishing. So there's, there's just a ton of different AI informed projects [00:27:00] out there that people are working on for the betterment of society that the average consumer is unaware of, that I think are, are.

[00:27:07] Allen Murabayashi: Really exciting, and it's the reason for photographers to sort of keep an eye on. Of course there's all of the, the bad sides of AI using for fraudulent purposes that are, that are equally as scary, if not more so. But you know, I will say AI in its current iteration, especially when it comes to generative ai, we're like just in the beginning stages of it.

[00:27:31] Allen Murabayashi: And humans are great at creating new technologies. We're really bad at predicting where they will go and how other humans will adopt it, even in, you know, five years. So I'm hesitant to say that, generative AI will be this in three years. You know, I'm not a futurist and I don't think there are really any great futurists out there who are predicting how this is gonna go.

[00:27:52] Allen Murabayashi: But you know, it's something to keep an eye on as a photographer 'cause I think it will provide Different sets of tools[00:28:00] for conservation photographers in the future.

[00:28:02] Jaymi Heimbuch: Yeah. I really love hearing all the examples for how it's in use now. I know that a lot of the, the really scary negative stuff is the topic of conversation as it should be.

[00:28:12] Jaymi Heimbuch: But then I, I really enjoy also thinking about, okay, but what's some of the good that we can latch onto? 'cause you don't wanna throw the baby out with the bath water, right? You wanna be able to say, Hey, there's some really great things that are happening. And I think that it's gonna take an incredible amount of responsibility and diligence on everyone's part to make sure that this goes well.

[00:28:31] Jaymi Heimbuch: But it is also exciting to hear that, you know, it's not as if conservation photographers are gonna lose out on being photographers anytime soon. We we're needed.

[00:28:41] Allen Murabayashi: The, the most obvious example that photographers use every day is subject detection. Where AI is helping us just get photos and focus, and I will say with the latest generation of camera that I have, that has, you know, improved auto focus, my keeper rate has gone up significantly, [00:29:00] significantly.

[00:29:00] Allen Murabayashi: So even that little improvement technological improvement and integration into a, basically a consumer device that, you know, it's paid off in spades as far as I, I'm concerned.

[00:29:10] Jaymi Heimbuch: Excellent. Excellent. Alan, I feel like there has been a void in my life that I have not been following your work for as long as you've been blogging.

[00:29:19] Jaymi Heimbuch: I feel like I would be so much smarter and more informed had I known all about you, you know, 10 years ago. So I'm curious, like where is your work now where people can learn from you? Like read your writing, find out what, what you're up to, and basically just get involved in what it is that you're talking about.

[00:29:38] Allen Murabayashi: Ironically, I, I, I've stopped blogging. I've ah, no, started focusing a lot more on doing nonprofit work in the music education sector. So, you know, life changes life priorities. So I find myself doing much more volunteer work nowadays. And then I also happen to be from Honolulu.

[00:29:59] Allen Murabayashi: So [00:30:00] I work with different high school programs there, teaching them about. Problem solving and entrepreneurship which is all very, you know, it's in a classroom and we try to be in person as much as possible, so it doesn't require me to to write anymore. So the, I mean, to be invited to your podcast to talk to you, it's like the best, best way to, to get access.

[00:30:18] Jaymi Heimbuch: Awesome. Well, I may end up having listeners ride in with questions or something and then rope you back into another interview 'cause it's been an absolute joy. And I will say too, for the record, we have had quite a few tech hiccups during this, like with dropped calls and you have been an absolute rockstar in picking up from where you left off.

[00:30:35] Jaymi Heimbuch: And I'm so grateful for you to just stay in the flow of this conversation because it's really fascinating. I think it's really important. It's something that has people nervous and. Kind of confused and not really sure where we're headed. And so it's been really wonderful to get to just hear all of your thoughts on this.

[00:30:52] Jaymi Heimbuch: Thank you so much.

[00:30:54] Allen Murabayashi: It's been a pleasure. Thanks for having

[00:30:55] Jaymi Heimbuch: me. Awesome.