“How Is AI Different From Autofocus?”

1 week ago 5

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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.

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