AI is Helpful and Harmful to Photography

I watched a Casey Neistat video yesterday about AI, and it made me wonder how this technology will be helpful and harmful for photography. AI is not going away. Photography isn’t going away, either—at least not anytime soon. What kind of impact will AI have on it? How do we move forward?

Let’s start with the harmful. Below are some quick thoughts on why AI is bad for photography:

Devaluation of human craft. AI images lack human story, skill, and effort, yet still compete with actual photos, diminishing appreciation for what is real. Art requires human effort; fake art is faux-art.
Job displacement. Photographers, photo editors, and even models will—and have already begun to—lose work as AI tools and generative systems become cheaper alternatives to paying people to create real pictures.
Authenticity issues. AI blurs the line between real and artificial, contributing to a distrust in images. Oftentimes, our first thought is: is this AI?
Loss of style. As computers take over what once was individual choices, everyone’s photos will start to look alike. There will be fewer and fewer new aesthetics.
Ethical & copyright concerns. AI has been trained on real works by real people without their consent or compensation. Cases currently being hashed out in courts are likely to determine that companies illegally trained their AI models, but the damage has already been done, and the little guys—that’s you and me—will not get even a penny for it, while Disney and other large companies will get large settlements.
Fundamentals skipped. When cameras and software can do everything for you, technical skills and creativity will become less important and less prevalent.
Cultural & artistic dilution. Photography’s value as a historical and artistic medium will erode when infinite machine-created images overshadow real human moments. AI will increase the total number of consumable images available by leaps and bounds, and non-AI images will be more easily lost in the massive pile of AI slop.
Energy consumption. AI takes a lot of power and resources. By 2030, it’s expected that up to 9% of all electricity generated in the U.S. will go to power AI. That’s shocking!

Now, let’s look at the positive. Below are some quick thoughts on why AI is good for photography:

Powerful tools. AI can be used to remove distractions by handling tedious tasks, freeing photographers to focus on other things. A very smart friend of mine told me once, “I’m not afraid of losing my job to AI; I’m afraid of losing my job to someone who’s better at AI than I am.”
More proficiency. AI can help you do more. What once took a team of people can be done with just one or two.
Accessibility. Photography has never been more approachable for beginners, those less experienced, those without expensive gear, and those lacking technical knowledge. And it’s only going to get easier and easier. Literally, anyone and everyone can be (and is already) a photographer.
Authenticity revolution. As AI images and AI altered photographs become more and more common, the natural response will be a yearning for what’s real. Authenticity will become even more valuable. Unedited digital photos and film photography have been gaining popularity, a trend that will continue to grow and grow as a pushback against AI.

My view is that AI is largely bad, but it can be good. It certainly can’t be ignored. So how do we navigate such treacherous waters? I don’t use AI often, but I use it sometimes. Like with most things, moderation is key. Use AI wisely, and not for everything. Let me share some recent examples of how I used AI.

The most obvious is the image at the top, which isn’t particularly good. It illustrates the topic of this article well enough, though. I was able to generate it in a few seconds with just a few words typed out. A few months back I used AI to animate a small section of my YouTube video to help tell a story. Those are pedestrian uses of the technology, and not anything to get excited over.

Pool Remnant – Rodanthe, NC – Fujifilm GFX100S II – Kodak Tri-X 400 Recipe

Where it really came in handy for me is back at the start of summer. I found a deal on an RV rental. This particular unit needed to be relocated from Miami to Boston, and it needed to get there in two weeks. Anyone willing to do it would get 75% off the rental cost. Driving up the East Coast in an RV is something that my wife and I had talked about doing for a few years, but it just wasn’t practical. Suddenly, this discount was available and we happened to have a hole in our calendar, so it was like fate. Even the airline tickets were surprisingly affordable to Miami and from Boston, especially considering that it was a last-minute purchase. The only problem is that we barely had time to pack, let alone plan an entire trip up the Atlantic coast. So I used AI to plan it for me.

I told it when and where I was starting and ending, and let it choose the whole route, including where to park the RV at night. I made some RV park reservations (AI even provided the websites and phone numbers for that), and soon we were on our flight to Miami. While not perfect, AI did a better job at planning the trip than I could have, and it did it in seconds, where it would have taken me hours and hours. I was surprised and impressed. I would definitely do that again.

In fact, I did do it again, but on a much smaller scale. I visited the Great Smoky Mountains for the first time a few weeks ago, specifically for fall color photography. I wasn’t sure where I should take my camera and what time of day might be best for those locations, so I had AI do that research for me. It was tremendously helpful, and saved me probably an hour or two of research.

Golden Appalachian Light – Gatlinburg, TN – Fujifilm X-T5 – Classic Amber Recipe

When I’m creating new Film Simulation Recipes and I’m researching films stocks, I have used AI to help with the investigation. While AI is great for research, it isn’t always right. Sometimes it gives a wrong answer. Sometimes, if you ask it the same question twice, you’ll get two very different answers. These instances of inaccuracy and inconsistency does call into question if AI is trustworthy at all. It seems to be moderately trustworthy, and requires double-checking its responses for anything remotely important.

Different AI models are better at various tasks than others, but none of them are good at creating Film Simulation Recipes—at least not yet. Initially, AI was quite terrible at this, often giving nonexistent or nonsensical settings. It’s better now, but still quite mediocre. It doesn’t have a good grasp on what the practical consequences are of camera setting adjustments. If you ask it to create the exact same look more than once, you’re sure to get two notably divergent answers. As someone once told me: AI will often give a better answer than a complete novice, but rarely a better answer than an expert. You can see the progress over the last couple of years, and I’m sure there will be continued improvements, but we’re not there yet when it comes to Fujifilm Recipes.

I think that navigating AI requires using it. If you are not at least somewhat comfortable with the technology and proficient at it, you might (as my friend worries) lose your job to someone who is better at it than you are. But moderation is still the key. Use it when it might actually be helpful. Don’t use it for everything. In fact, using it for everything might be to your detriment.

Some recent studies suggest that over-dependence on AI can reduce critical thinking skills, memory, and creativity. It might also make you lazier and feel less motivated. A quick Google search reveals headlines like AI Is Making You Dumber, Yet Another Study Finds that AI is Making Us Dumb, Science Shows AI is Probably Making You Dumber, Studies Prove It: AI Makes Us Dumb, and so many more. The key seems to be how you use it, and clearly less is more.

AI can be a powerful tool, and using it affectively can be a great benefit. It can save you a lot of time and increase productivity. It can help open some doors that might otherwise be impractical to open. But there’s also a negative side to it, and overusing it can have negative side effects on your mental health. It seems tricky to navigate. I think, though, that the technology will become more integrated and more seamless, and soon we’ll be using AI without even realizing it. Perhaps, in a few years, things will get sorted out, and it won’t be such a treacherous path. In the meantime, consider moderation as the safest route through this tricky time—not ignoring AI entirely, and not using it for everything, either.

Can ChatGPT Replicate a Recipe??

Someone pointed out to me that ChatGPT can create a Film Simulation Recipe that replicates the look of any photo that you upload. Just share a picture with AI, and it will analyze the look and produce a Recipe that matches. But can it really do that? And, if so, is it accurate?

So I gave it a try. I uploaded a picture and asked AI to replicate the aesthetic of it with a Fujifilm Recipe. Sure enough, it produced one. I also asked ChatGPT to tell me which Fuji X Weekly Recipes are the closest. Let’s examine the results.

Test 1

The top picture is the camera-made JPEG captured on my Fujifilm GFX100S II using the Nostalgic Film Recipe (a Film Dial Recipe). I uploaded it to ChatGPT and asked it to make a Recipe based on that image. The second picture was reprocessed in-camera using the settings that AI provided. Quite obviously, they are pretty far apart and are not a good match.

Some of the settings are the same. Both pictures use DR400. Both are Grain Weak (although ChatGPT chose Grain size Large). Both have Color Chrome Effect Strong and Color Chrome FX Blue Weak. Noise Reduction is -4 on both. The White Balance Shift is +2 Red & -4 Blue. All of the other settings were different—for example, the Nostalgic Film Recipe calls for the Nostalgic Neg. film simulation, while AI chose Classic Chrome. The Recipe made by AI isn’t too dissimilar to Kodachrome II, although not an exact match. I asked ChatGPT to tell me which Fuji X Weekly Recipes were the closest, and it suggested Kodak Ektar 100 and Kodak Gold 200.

Test 2

The top picture is the camera-made JPEG captured on my Fujifilm GFX100S II using the Fujicolor PRO 160C Warm Recipe (which is also a Film Dial Recipe). The bottom picture was reprocessed in-camera using the settings that ChatGPT provided. They are far apart, and are not an especially good match, although it is slightly better than the first test.

The Fujicolor PRO 160C Warm Recipe uses the Reala Ace film simulation, while ChatGPT chose Eterna. Most of the settings are divergent. I don’t have a Recipe that’s especially close to the one made by ChatGPT, but Timeless Negative is probably the most similar. The Fuji X Weekly Recipes that AI suggested are the closest are CineStill 800T, Kodak Ektachrome 100SW, and Kodak Vision3 250D.

Test 3

The top picture is the bottom image from Test 1. I asked ChatGPT to make a Recipe that matches it, to see if it would suggest the same settings that I used to make it (which is the Recipe AI had made just a few minutes earlier). The Recipe that it came up with was not the same, and also not a great match. Instead of Classic Chrome, it wen’t with Classic Negative. While only somewhat similar, Fujicolor Blue is probably my closest Recipe. The Fuji X Weekly Recipes that AI thought were the closest are Kodak Portra 400 and Kodak Portra 160.

Test 4

I re-uploaded the first photo from Test 1, and asked the same question to see if it would suggest the same settings, or if it would change them. Unsurprisingly, it was completely different, this time choosing Astia for the film simulation (I didn’t bother to reprocess). It suggested that my Kodak Portra 400 Recipe would be the closest match.

Conclusion

I’ve said before that ChatGPT is a neat little card trick, but once you know how it works, it isn’t nearly as impressive. I’ve also said that it will only get better with time. Both of those statements still seem to be true. While AI can analyze a picture and produce some Fujifilm settings to try—which is amazing—it isn’t very accurate. It can also suggest Fuji X Weekly Recipes that might be similar, and it is a little better at that, but still not especially good.

I have zero doubts that with enough time—and it may only be a couple of years—ChatGPT will be able to analyze a photo and produce a Fujifilm Recipe that is pretty similar. It might be even closer to suggesting an existing Recipe that isn’t far off. It’s not there yet, though.

I’m certain that ChatGPT was trained on my website. When asked directly, it says that it wasn’t, but states that it was trained on various photography blogs and forums. When I asked it to name some specific ones, the very first it listed was Fuji X Weekly. So, yeah, AI did some of its learning from my website, which of course I did not consent to nor was I compensated for. I believe that this training is ongoing, and it probably will even learn from this article that you are reading right now. This is wrong, and eventually the courts will likely determine that it is completely illegal; however, by then, the damage is done, and there’s nothing that can be done.

With all of that said, I had a conversation with a friend of mine who is super intelligent (he’s a scientist) about AI and ChatGPT. He said that he is not concerned about being replaced by AI, but he is concerned about being replaced by someone who knows how to use it better than he does. I don’t think it is prudent to ignore ChatGPT completely. While undoubtably ethically sketchy, it is a tool that can sometimes be used effectively, if you understand its strengths and weaknesses. I’m not sure what that means for me specifically, other than it is good to test it now and again to see how far it has or hasn’t come. It definitely has made some progress since the last time I tested, but not a lot.

Using AI to Create Film Simulation Recipes + Urban Dreams X100V (X-Trans IV) Film Simulation Recipe

B is for Bisbee – Bisbee, AZ – Fujifilm X100V – Urban Dreams Recipe

Can you use Artificial Intelligence to create Film Simulation Recipes for Fujifilm cameras? Does AI even know what that is? If so, would those Recipes be any good? Those questions and more have been rattling around inside my head for the last few months.

Back in January I asked Open AI‘s Chat GPT what a Film Simulation Recipe was and it didn’t know—it couldn’t differentiate a Film Simulation Recipe from a Film Simulation, but only went so far as to acknowledge that Film Sims could be customized. It also didn’t know much about Fuji X Weekly. It didn’t take long for things to change.

Last week Open AI announced the new-and-improved GPT-4, and so I put it through the same test. To my surprise, it not only knew what a Film Simulation Recipe is, but could even create one! The AI also provided the reasons why it chose the settings it did, and they seemed logical. However, I noticed that some required parameters were missing, so I asked it to add those settings to the Recipe, and it did. I also asked Chat GPT to give the Recipe a name. The AI created Recipe turned out to be pretty good, and I used it for some photography in southern Arizona, but I’m getting ahead of myself. We’ll get back to this in a moment, but let’s talk about some other things first.

Don’t Park Overnight at Boothill – Tombstone, AZ – Fujifilm X100V – Urban Dreams

I wanted to find out how Chat GPT knew how to create a Film Simulation Recipe. Obviously the software has never used a camera, so where was it getting its information? I asked, and the software deflected, telling me where I could find further information on Fujifilm cameras and Film Simulation Recipes. To my surprise, Fuji X Weekly was listed as a potential resource. I wasn’t satisfied with the answer, so I kept asking, rewording the question, until the software admitted that it gathers information from (among other things) websites, such as Fuji X Weekly, One Camera One Lens, Dan Bailey, and Ted Forbes. I was a little surprised on the last two, especially Ted who I’m pretty certain doesn’t use Recipes or out-of-camera JPEGs. Maybe it just threw out some names associated with Fujifilm gear. My conclusion is that the software searches the web for resources and attempts to make sense of what it finds, and it borrows heavily from the work of others (but, thankfully, doesn’t outright copy).

I had Chat GPT make a total of seven Film Simulation Recipes for the Fujifilm X100V. Not once did it provide me with all the necessary parameters on the first try, and I had to ask it to add the missing fields. It always chose Auto White Balance (once it did not provide a WB, so I had to ask it to do so), and only provided a White Balance Shift once on the first try; for the other six Recipes, when I asked it to provide me with a WB Shift, it never ventured beyond +/- 2 for Red and Blue. In fact, only once did the software suggest that any setting go beyond +/- 2, so I think it takes a conservative approach, perhaps not understanding why anyone would want to go wild with the JPEG options.

On the first try I was provided with Color Chrome Effect and Color Chrome FX Blue settings: Off on both. For the next five attempts Chat GPT didn’t list either option, so I had to ask, and it chose Off each time. With the final Recipe attempt, it listed Color Chrome Effect set to Strong, but didn’t list Color Chrome FX Blue; when I asked it to give me a Color Chrome FX Blue setting, it (surprisingly) stated that Color Chrome FX Blue isn’t an option on the Fujifilm X100V. I think the software struggles to understand what these settings do and why someone would choose them, and also struggles to understand what specific settings are available on each Fujifilm model.

Cienega Bridge on Old Highway 80 – Vail, AZ – Fujifilm X100V – Urban Dreams Recipe

Two settings that the software never provided on the first try are Grain size and Clarity. It would list Grain strength (Off, Weak, or Strong) but never size (Small or Large). When asked about size, it suggested Large four times, Small twice, and Standard once (there is no Standard option). With Clarity, it typically suggested a positive number, and only gave me a negative number once, zero once, and Off (which I suppose is the same as zero) once. As with the other settings, it never ventured beyond +/- 2.

I asked it to mimic the look of a certain film stock, and Chat GPT provided a Film Simulation Recipe that (in my opinion) wasn’t a great match. I then asked it to mimic the look of a different film that just so happens to be the same exact emulsion just sold under a different brand name (to see if it would provide similar or identical settings), and the second Recipe was much different than the first. It’s clear that the AI isn’t analyzing pictures from film to create its Recipes, but instead finds descriptions of the stocks and suggests which Fujifilm settings could logically match the descriptions. “Vibrant” means Velvia and “soft” means PRO Neg. Std, which makes sense to a point; even though one film can produce many different aesthetics based on how it was shot, developed, printed and/or scanned (among other things), I believe you’d be hard pressed to find a single emulsion that could be emulated by both Velvia and PRO Neg. Std, but that’s what the software did.

I also asked Chat GPT to create a Recipe that I already have a Film Simulation Recipe for. I wanted to see if it would just copy my Recipe, but thankfully it didn’t. It was actually significantly different. For now, at least, the software isn’t outright plagiarizing anyone (that I’m aware of), and I hope it stays that way. Finally, using a different account, I asked Chat GPT to create a Recipe with an identical request to one of the seven, just to see if it would give me the same answer, and it didn’t. I repeated this test once more, and it once again provided a different result. While it tries to come across as “intelligence” it appears to be more like a roll of the dice.

Red Brick and Good Cakes – Bisbee, AZ – Fujifilm X100V – Urban Dreams Recipe

Based on this test, I believe that AI is about 60% of the way there to being a useful tool for creating Film Simulation Recipes. It struggles to know which parameters to provide. It doesn’t understand the nuances between camera models. It seems to take a rather predictable and conservative approach to creating Recipes. While I think it tries to be logical with its choices, it is basically just taking a guess and giving random settings, which might produce good results sometimes and might not other times. The amazing thing, though, is that just a couple months ago the AI didn’t even know what a Film Simulation Recipe was, so it has made significant strides in a short period. I think eventually—and it might not even be that far out—the software will be able to analyze an image and provide settings for your Fujifilm camera that will be a reasonably close match to that image. For now, though, AI isn’t a particularly good way to get a Recipe.

I promised that I would get back to the first Film Simulation Recipe that I asked Chat GPT to create for me to use on my Fujifilm X100V. I asked the software to create a Recipe that would be good for an urban environment at night. It provided me with everything except for Grain size, White Balance Shift, and Clarity, so I asked it to give me those settings, too. Then I asked it to name the Recipe—it gave me five choices, and I went with the first: Urban Dreams.

I found Urban Dreams to be a pretty decent and versatile Recipe. I didn’t get a chance to use it much in an urban environment at night, but the results were good in the few opportunities that I did have. It seems to do well in sunny daylight, dreary overcast, nighttime, indoors, outdoors, landscapes, street, still-life, portraits, etc., so this could be one’s go-to Recipe for everyday photography. It reminds me a little of Kodachrome 200, a high-ISO slide film introduced by Kodak in the mid-1970’s and discontinued in 2006. It’s not completely “right” for Kodachrome 200, but can be surprisingly close sometimes, and this Recipe is probably the closest to it that I’ve seen.

Dusk on Highway 90 – Benson, AZ – Fujifilm X100V – Urban Dreams Recipe

This Urban Dreams Film Simulation Recipe is compatible with most X-Trans IV cameras: the X-Pro3, X100V, X-T4, X-S10, X-E4, and X-T30 II. For X-Trans V and newer GFX, you can use this Recipe, but it will render slightly different (try it anyway). For the X-T3, X-T30, X-Trans III, and older GFX, simply ignore Clarity and consider Sharpness set to 0; the results will be very similar (only slightly different).

Classic Chrome
Dynamic Range: DR400
Highlight: -1
Shadow: +1
Color: +2
Noise Reduction: -2
Sharpness: -1
Clarity: +2
Grain Effect: Strong, Large
Color Chrome Effect: Off
Color Chrome Effect Blue: Off
White Balance: Auto, 0 Red & +2 Blue
ISO: Auto, up to ISO 6400
Exposure Compensation: +1/3 to +1 (typically)

Example photographs, all camera-made JPEGs using this Urban Dreams Film Simulation Recipe on a Fujifilm X100V:

Oleander Blue – Tucson, AZ – Fujifilm X100V
Colorful Triangle – Bisbee, AZ – Fujifilm X100V
Gunfight at the O.K. Corral – Tombstone, AZ – Fujifilm X100V
Boothill Visitors Leaving – Tombstone, AZ – Fujifilm X100V
H.B. Cook 1882 – Tombstone, AZ – Fujifilm X100V
Tattered Flag – Tombstone, AZ – Fujifilm X100V
Gunslinger – Tombstone, AZ – Fujifilm X100V
Wells Fargo – Tombstone, AZ – Fujifilm X100V
Courthouse – Tombstone, AZ – Fujifilm X100V
Bisbee Afternoon – Bisbee, AZ – Fujifilm X100V
Under the Trestle – Vail, AZ – Fujifilm X100V
Just not Straight Ahead – Bisbee, AZ – Fujifilm X100V
Studebaker – Bisbee, AZ – Fujifilm X100V
Studebaker 2 – Bisbee, AZ – Fujifilm X100V
Blue Truck – Bisbee, AZ – Fujifilm X100V
Uphill to Downtown – Bisbee, AZ – Fujifilm X100V
Object Limited – Bisbee, AZ – Fujifilm X100V
Cafe – Bisbee, AZ – Fujifilm X100V
Outdoor Breakfast – Tucson, AZ – Fujifilm X100V
Coke and Produce – Tucson, AZ – Fujifilm X100V
Lit Lamp – Tucson, AZ – Fujifilm X100V
Saloon & Steaks – Tucson, AZ – Fujifilm X100V

This post contains affiliate links, and if you make a purchase using my links I’ll be compensated a small amount for it.

Fujifilm X100V in black:  Amazon   B&H  Moment
Fujifilm X100V in silver: Amazon   B&H  Moment

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