There was a time not long ago when I spent time on photography forums. I joined quite a few debates about artificial intelligence, and in these debates, some people compared new AI tools with other automated camera features. “How is AI any different from autofocus?” is a question I saw in various forms.
It’s a fair question to ask. For most of the history of photography, focusing had to be done manually. Some photographers decried the use of autofocus when it appeared as something technological that took away from the craft of photography. Today, many people say the same thing about AI – isn’t AI just another tool like autofocus that helps us make better pictures? The answer may not be obvious at first, but I believe the answer is a firm no.
Is Autofocus Like AI?
In one respect, autofocus is similar to some generative AI algorithms. After all, autofocus is an automation that moves the photographer one step away from the mechanical process of making a photo. And perhaps there is some merit to using manual focus at times to understand the physical movement of the compound lens, at least when you’re not using a lens that is focus-by-wire.
As an aside, removing automation is an interesting journey that can certainly give one a new perspective on the entire photographic process. At least, I’ve experienced this personally, as for a very long time I used only manual focus on my first camera:
But there is a crucial difference between autofocus and AI-generated images that goes beyond mere results. Yes, these days you could generate an image of a bird using AI algorithms, producing a thing that, at first glance, looks like art. But this thing, instead of being art in the sense of being a representation of a human soul, is instead a reflection of the machine that compiled it. It is a step – not unlike others taken in recent years – to replace human connection by machine-mediated interaction.
AI tools were not created by big tech companies to help you with your photography or to take some of the tedium out of creating local masks, but to replace you, sell you things, and ultimately, replace the need for human uniqueness and produce media that is the psychological equivalent of refined sugar that renders humanity powerless to resist the rise of the high-tech corporate control of society.
Of course, that’s not unique to AI. To some extent, social media and other algorithms have had this effect for some time. But AI (of all kinds, not just in the photography world) is a force multiplier that increases the efficacy of this dehumanization. It is intended to replace people’s jobs, sources of enjoyment, free time, and so on to the point where it can no longer be easily countered by human resistance. The same is certainly not true of autofocus.
Noise Reduction
There is another reason why AI is different than autofocus, and I’d like to illustrate this point with AI noise reduction. Of course, I’ve seen the results, and AI noise reduction does a pretty good job. But, I never use it in my own photography. Why? One reason is because I don’t want to support AI tools in general due to reasons I’ve already mentioned.
But there’s another reason, that to me, is perhaps more important. When I use autofocus, I know basically what autofocus is doing. I know what it means for a lens to be focused on a particular subject. Even if the autofocus has been trained using machine learning algorithms, the end result is something I could replicate myself, at least if my reaction time were a bit faster. It places the plane of focus a particular distance away from the camera.
The same is true of demosaicing algorithms (the process of combining individual color subpixels into a traditional pixel that we see on screen). Tone curves, black and white conversion, and even traditional denoising, are all processes that are basically understandable. Moreover, such processes are possible to replicate by writing a computer program by hand, with no need to input countless photos other than the one you are planning to edit.
AI noise reduction is different, because its algorithm cannot be reconstructed without knowing the millions of images used as input. The final result obtained with it is no longer equivalent to a final result obtained using basic photographic process. Rather than algorithms that operate solely on the pixels on hand, they depend upon recognizing higher-level content based on their large databases of starting images.
Instead, AI noise reduction recognizes higher-level concepts such as feather detail, eyes, hair, shapes, and may even replicate patterns from other images on the small scale of dozens of pixels. Some photographers may criticize the accuracy of some of these reconstructions (such as upscaling an image with low-resolution text, resulting in gibberish letters). But as algorithms become more powerful, and require more energy, it is inevitable that it will bring higher and higher-level reconstructions, so that missing patterns such as feather detail will be interpolated. Hints of such interpolation is already present in today’s software. Eventually, it may be possible to transform an ISO 20,000 image into one that looks like it was taken at ISO 100 with very advanced reconstruction.
This goes beyond what I consider photography. Moreover, the process of higher level construction and interpolation encourages an approach to photography in which we no longer are in control of the final result – instead, we provide some starting point, and AI adds most of the artistic touches to reach the final product. This process is relatively primitive now, but as time goes on, it will only become more apparent. On the surface, AI noise reduction algorithms are not the same as generating AI images from scratch, but given my outlook on the future, I hope you can see why I avoid them, too.
Conclusion
Although there are many different AI algorithms, and some are benign at first glance, for me, the most crucial questions are: What is the ultimate spirit and aim behind the algorithm? And does the algorithm utilize higher-level content-aware interpolation, even if only at a very local pixel level? If yes, then I’m not interested.
As for autofocus, even if it uses a large database of images to focus more quickly and accurately, it does not change the pixels of my image in a way that I couldn’t do myself. Furthermore, it does not come with the same risk of broad societal change associated with general-purpose AI. While I still think it is useful at times to turn autofocus off and not neglect your manual focus skills, I simply don’t see autofocus and AI as having the same capacity for dehumanizing photography.
When it comes to my own photography, I find it interesting that my favorite shots are those that wouldn’t have needed AI noise reduction in the first place, let alone AI-generated “fixes.” Shoot in conditions that demand excessive noise reduction, and you’re probably capturing worse light in the first place. Yes, probably about 10% of my shots could be improved with AI noise reduction algorithms, but even then, I wouldn’t consider any of them “5 star shots.”
Would AI noise reduction save me some time when I have to resort to local denoising with masks? Probably. But I’d rather spend that time doing it myself. Spending time working on my favorite images is a rather peaceful and enjoyable process anyhow, and in this modern would, I think we could all use a little less efficiency.
I don’t agree with you. I don’t feel threatened by AI. It’s the natural evolution of our technology. I am very pleased with the AI noise reduction in Lightroom. I routinely use the AI powered ‘Subject detection’ autofocus which is a real game changer in my opinion. I don’t have a problem with using AI to remove a Coke can from my photo. I did it with the rubber stamp tool in the past and it easier and faster with the AI tool for the same outcome. I am not afraid of new technology and the future. AI will/does have risks as well as benefit, like all technology.
Thanks for sharing your perspective. I think everyone must define acceptable parameters for their art, and yours and mine certainly differ.
In terms of your last sentence and second sentence, ultimately the difference between your viewpoint and mine reduces to this: you think that the natural evolution of our technology is a balance of risks of benefits whereas I think technology has come to a point of diminishing returns and is more detrimental than otherwise. In short, I do not think a future with endless new advanced technology is a good future at all. I don’t think it will impact me personally to a great deal, but I think it will be worse for the world. Of course, that depends on how you weight the costs and benefits, and I suspect your weightings will be quite a lot different than mine.
Excellent article and very sharp thoughts, Jason. Thank you very much. I was probably very naive on this, I though these algorithms were mainly analysing the noise patterns in the image itself and removing those. I guess this is the way the first ones worked. Do you think now these AI tools really e.g recognize the feather pattern of a sparrow and replace noise with what a sparrow should look like (taken from a database) ? But then I wonder, if I unplug my PC from the net, is AI denoising going to be less „effective“ because the database cannot be accessed ?
I agree with you that generative AI is not for me, although I would be ready to accept some machine learning-based denoising if, indeed, it is denoising and not image reconstruction. But it may be hard to make the distinction in practice.
The algorithms are still mostly just analyzing noise patterns but they do so based on reconstructing patterns based on other images, so how to remove noise along a feather line will be different than how it’s removed in a smooth area, and that is in itself dependent on knowledge from other images. It’s a little more complicated than a direct database lookup, but basically, it does use knowledge from previous images to replace textures dependent on context.
If you unplug your PC from the net, the algorithm will still work the same. That is because the “database”, which is more properly the numerical weights in a very vast trained model, has already been derived from the training images. The training images (e.g. of birds and other noisy/less noisy images) were already processed on a much larger computer and then the final model (which is like a compressed database of noise-reduction strategies) is entirely self-contained in the program.
AI noise reduction is not exactly the same as generative AI in a vacuum, and it uses a very different sort of model than text-to-image generators. That being said, it is like reconstruction on a very fine scale, but it doesn’t seem (at least at this point) to interpolate with anything from other images like text-to-image programs do. But of course, it recognizes structures in the image based on data from other images.
So yeah, it’s a fine line and I still think AI noise reduction isn’t outside the realm of photography, only outside the realm of my personal photography.
I’m pretty much okay with text-generative AI, since basically they work as a more profound search engines that can analyze and gather data from various sourses, so you don’t need to spend too much time googling too much. But as for AI they put even in modern smartphone cameras I’m so pissed. Like, one day I wanted to make a shot of a vintage silk blazer, it was a bit wrinkled and it was probably when first time I’ve noticed that camera tries to ‘smooth’ out those wrinkles (doing shitty job, lightly speaking). And I can’t even turn this effect off! (Like, there is a tumbler in the settings, but it won’t save my ‘choice’ for some reason).
The interesting thing is that one of the reasons you have to spend so much time Googling is because the very existence of Google’s methodology caused a massive growth in creating endless websites, often with duplicate and low-quality information. So, one can say that the introduction of mass automation with advertising at Google was one of the main causes of people having difficulty finding things, and now AI is the solution to the problem created by a previous technology.
ChatGPT (or whatever generative AI you might be using) is not a “more profound” search engine. It will make stuff up.
Although I do not like AI in general I use DXO pure raw on a daily base for my M4/3 system including AI noise reduction (even for low ISO pictures). The results are in general the same or better than photo’s taken with my FX system (without DXO). As long as the ISO’s are not extreme it makes M4/3 (with it’s advantages) much more useful. As soon as I see something unnatural I stop.
A lot of sensible things have been said here. I do use AI-NR and in the case of pixelated small faces it makes often horrendous choices…. But in short time these choices will improve for sure. To me AI-NR is one of most innocent uses of AI.
It will be necessary to add a message if and how AI was used in the process making things.
So everybody knows what we are looking at.
At the moment Google has made progress with a Qbit-computer that can be 250.000 times faster than the regular one we all know.
Combine that with AI and the largest pile of data in the world and indeed one must fear from the power and possibilities that may arise. “Do no evil” is their old marketing slogan tha t already lost its meaning.
I do think in a vacuum, AI noise reduction is benign. However, one of my greatest concerns is that using AI noise reduction is contributing to a social phenomenon where the emphasis also is placed on pure production of imagery. That does not mean that the said imagery is bad or that it isn’t photography; on the contrary, it can be quite good. But it does seem to be a reflection of something that doesn’t quite sit right with me. Perhaps it is relative and others would consider high fps in a similar regard. But even so, the relative nature turned to an absolute can still be a useful device to understand the nature of photography, so I still think it can be worthy to understand it.
Great article, and I agree with every single point you mention! I am all for the advancement of technology – but it has come to a point where the inclusion of “enhancements” through tools that supplant the photographer – such as eye-tracking focus, overwhelming FPS, supplanting parts of the image, etc. – have diminished the value of the photographer. As an example, I will cite that I will stick with my Nikon D850 and PS 2022 DSRL (which does not support AI)
From my point of view, no matter how much some people hype AI, for me it is “the biggest cheat in the entire history of photographic art”, therefore it has nothing to do with real photography. If the unbridled development of technology means that I have to accept all these supposed “advantages”, I prefer to stay back and enjoy my photography thanks to myself and not to the “ultra-algorithms” hidden inside a camera or in the latest editing program.
I think your choice is interesting. In some ways, beyond the absolute values of specific technologies, there is also value in choosing a given point of technology and sticking with it. Beyond the direct impacts on photography, a slower approach also helps you have well-defined and invariable parameters, whose variability could otherwise distract from creative side of photography.
I don’t think that recent technological advances diminished the value of photographers – I think they just changed their role.
If you look back 150 years, a photographer was a good part technician – without extensive knowledge of camera technology, no one was even able to take a picture (just imagine handing a random person a large-format camera today…). Also, just owning a camera was something that made you “valueable” as a photographer back then!
Nowadays, a child with a smartphone and absolutely no technical knowledge about photography can take a picture that’s sharp and correctly exposed. But we still need photographers – not for their ability to take technically good photos, but for their ability to create aesthetic, creative, artistic, inspiring, … pictures.
And I believe if we ever reach a point where AI is truly creative and can generate original content, we will have a lot more serious problems than the obsolescence of photographers…
> And I believe if we ever reach a point where AI is truly creative and can generate original content, we will have a lot more serious problems than the obsolescence of photographers…
I do think the worse possibility is that AI doesn’t need to be truly creative to basically satiate the desire for media consumption in the present.
No argument there! That’s certainly true. But I’m not taking about media consumption – AI that could really generate original thoughts would be a serious threat to humanity. I know, that’s Sci-Fi for now, and I doubt it will ever become reality, but you never know…
Indeed. That last possibility is truly the most scary one. And I am betting it will be possible in my lifetime…
I remember a quote from a professional photographer about the ever-improving AF-capabilities, saying that what made him a better photographer than others wasn’t his ability to take sharper photos.
And I think that sums it up pretty well. AF is just a tool to technically improve your photos, it doesn’t affect the creative process of photography – except that the realisation of some ideas becomes easier.
For me, the same goes for noise reducing, be it “AI” or not. Yes, it does make changes to your picture on pixel level, but it doesn’t change the overall composition and message of a picture. It’s just a technical improvement.
Other AI tools do affect the overall look of your picture, and that’s where I personally draw the line. Adding objects, sky replacement etc. – that’s something completely different.
The use of such AI tools may be a valid art from in itself, but it just isn’t photography anymore.
I think that’s an understandable assessment. And of course, the sort of AI that is used in noise reduction is more like traditional machine learning (perhaps with some hybrid approaches) compared to language models and generative image models. However:
(1) I do think there is more to it than the general overall composition and message. All sorts of subtle little details in a photo contribute to a great photo and thus the line is a bit more blurred on whether advancing machine-learning reconstruction will really change such details in subtle ways. It may not add things that were never there, but it can reconstruct details that were never there based on other images, so the line is fine indeed.
(2) As mentioned, the other reason why I am hesitant about AI denoising is the tangential issue of promoting an ecosystem where software enhancements go beyond what is possible in image capture with purely physical equipment. And of course, such an ecosystem tends to promote other tools as well.
I mostly agree – that’s why I prefer ‘AI’ denoise models that do not create ‘new’ details but just preserve and maybe enhance existing details while removing noise. I think Lightroom does a pretty good job at that, especially if you set it at a rather low value.
But you are right, the further the technology advances, the more difficult this distinction will become…
And I also agree with what you said about pictures needing AI noise reduction not being your favourite pictures anyway – I usually feel the same, with very few exceptions.
However, I often use my pictures for purely documentary purposes, and there some limited AI assistance in improving photos with technical issues can be really helpful.
Good points, thanks! I generally agree with you about AI denoising. If it wasn’t a good composition before, it won’t be after denoising.
I’ve only used DXO PureRaw 2 extensively. The newer models are a little cruncher, and Topaz straight up seems to be using Gen AI to create detail that couldn’t be interpolated.
I’ve taken plenty of wildlife photos that benefited greatly from AI denoising. My Fujifilm 150-600 is f8 at the long end, and often requires 12,800 ISO to get high enough shutter speeds for BIF. I suppose I could take a leaf out of Jason’s book and just not shoot in bad light, but Osprey seem to hunt regardless of the lighting conditions, and we can’t all wait for perfect weather.
Jason, it would be an extra $20k or so to allow those results with a full frame camera (Z8 and 800mm 6.3 or so).
I agree that AI denoising is often a tool for the margins, but it’s nice to shoot events and not worry about trading enough light for enough DoF constantly as well.
I haven’t used anything but Lightroom’s AI noise reduction recently, but from tests I’ve seen, I think you’re right about Topaz using generative AI to create detail. I used Topaz a while ago but never liked its noise reduction very much since it often gave artifical-looking results, and AI generated detail will (for now) often contribute to this impression.
My ideal noise reduction software would just retain the details I can still make out in a picture with my own eyes and brain. Of course, that way you will always loose detail when using high ISO, since some stuff just gets lost in the noise, but that’s part of the game (and part of the reason why I carry my heavy equipment with me).
I’m ready for an authenticated image format that cannot be manipulated.
If you could – just go ahead and delete this comment.
Where I personally draw the line is using AI to add things that were truly never there in the original. I do use AI to remove things sometimes. I left my bag in an otherwise awesome shot, for example. And the end result is that even I can’t tell. So it reflects my intent.
However, if it were for a contest I would not present it as if I didn’t use AI, if that were the rules.