{"id":2036,"date":"2026-05-08T06:53:57","date_gmt":"2026-05-08T05:53:57","guid":{"rendered":"https:\/\/web33.secure-secure.co.uk\/marklucock.com\/blog\/?page_id=2036"},"modified":"2026-05-09T06:33:22","modified_gmt":"2026-05-09T05:33:22","slug":"the-everyday-impact-of-ai-on-nature-photography","status":"publish","type":"page","link":"https:\/\/web33.secure-secure.co.uk\/marklucock.com\/blog\/the-everyday-impact-of-ai-on-nature-photography\/","title":{"rendered":"The Everyday Impact of AI on Nature Photography"},"content":{"rendered":"\n

This article is born out of a story in yesterdays Guardian newspaper<\/a> \u201cRichard Dawkins concludes AI is conscious, even if it doesn\u2019t know it\u201d. I\u2019ve read most of Dawkin\u2019s books, and reading yesterdays article gave me pause for thought. Before breakfast this morning, I\u2019d put together an article in my minds eye that dealt with Dawkin\u2019s perspective on AI but applied to photography. Then, over breakfast I read another article on the ABC<\/a> that gave me even greater pause for thought \u2013 \u201cIs Richard Dawkins right about AI?\u201d. I urge you to read both articles, they will certainly make you think. I won\u2019t dwell on them but will move on to give you my thoughts around nature photography and the application of AI. <\/p>\n\n\n\n

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The above image and the following sequence of a cabbage white butterfly in flight surprised me. I was brought up with a huge respect and admiration for the high-speed flight work of Stephen Dalton<\/a>. These are the first good butterflies in flight images I\u2019ve managed that I feel can compare with Dalton\u2019s masterful images. What surprised me was that I used bird detect mode on my Z8. The Z8 doesn\u2019t have an insect detect mode (at the time of writing). Still, focus and tracking were spot on with the bird detect setting. I used pre-release capture. Again, these perfect images are only possible because of AI. I have to say, I\u2019ve tried to get butterfly flight shots a few times with my macro lens, but never been very successful \u2013 my 600mm lens works a treat though. Nikon Z8 and 600mm f\/6.3 PF lens at f\/6.3, 30 frames\/sec, ISO 640 and 1\/4000 sec.<\/figcaption><\/figure>\n\n\n\n
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First of all, let\u2019s look at what AI is. LLMs are Large Language Models that are basically pattern\u2011recognition engines trained on enormous text datasets, enabling them to generate fluent, human\u2011like language. They don\u2019t think or perceive reality \u2014 they predict text, much like a highly advanced autocomplete. So, when reading the two articles I allude to above, remember, AI LLM\u2019s don\u2019t \u201cunderstand\u201d the world the way humans do \u2014 they predict the most likely next words based on statistical relationships learned during training.<\/p>\n\n\n\n

My very first thought re how important AI was to me as a photographer was based on the complexity of the Nikon Z8 camera. After buying the Z8, setting the camera up was quite challenging and using the huge pdf manual to work out the best way forward is slow and difficult. I found it far quicker to ask the AI on my phone (Google ecosystem of AI tools). So, I just asked it a question like how do I set up an AF handover from Wide Area to 3D tracking on the Nikon Z8. I must have done this a hundred times whilst setting the Z8 up for bird photography, astrophotography and landscape photography. It was so much quicker and easier than using a manual \u2013 a clear win for AI. <\/p>\n\n\n\n

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These images of a goldfinch in flight (see above and below) wouldn\u2019t have been easily achievable until very recently. The power of AI to acquire focus using subject detect modes (with or without pre-focus), and track a fast-moving subject is a remarkable and game changing technology. Nikon Z8 and 600mm f\/6.3 PF lens at f\/6.3, 30 frames\/sec, ISO 720 and 1\/5000 sec.<\/figcaption><\/figure>\n\n\n\n
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Another use for AI that I find useful is finding out where and when to find specific bird species (in concert with eBird), where to be and when to be for sunsets, milky way with no moon, golden and blue hour etc. (in concert with Planit Pro and PhotoPills). I even found it useful to find very precise locations in nature reserves to target and shoot elusive\/rare species.<\/p>\n\n\n\n

I do a lot of writing and often double check my literary work using AI for accuracy and potential plagiarism prior to publication (a throwback to my \u201cTurnitin\u201d days as a lecturer). At this point I should say that I\u2019ve found variable accuracy from different AI platforms. As a scientist working in a niche area, with a very unique understanding of one small area of biology, I\u2019ve challenged AI over difficult, but important questions. It often got it completely wrong. I responded by explaining it was wrong and did it not know such and such \u2013 AI apologised, acknowledged I was right and it was wrong and over a few iterations of this it had built up the full picture that I had of the subject. This has happened a few times, enough for me to know that it is good, but not perfect (yet). Still, one very good use of AI is to generate SEO terms for articles prior to publishing web articles. I always found this difficult. I now ask Copilot to do that for me. I compare the SEO score for AI vs my own attempt and select the one that gives me the highest index (sometimes I beat AI on this).<\/p>\n\n\n\n

As an aside and not related to photography, AI is great for language translation and cultural anthropology (historical and geographic) \u2013 I\u2019ve used AI platforms (but prefer Microsoft\u2019s Copilot system to others) to answer genealogical questions related to my ancestral tree (half my origins are German and a bit of a mystery to me). I asked Copilot which LLM it uses and it replied: I use Microsoft\u2019s own large language models, developed and deployed by Microsoft. These models are part of the Copilot system \u2014 not OpenAI\u2019s ChatGPT, not Google\u2019s Gemini, and not Anthropic\u2019s Claude.<\/em><\/p>\n\n\n\n

It goes on to say a couple of key points that keep things simple:<\/em><\/p>\n\n\n\n

I\u2019m built and maintained by Microsoft, using Microsoft\u2019s model architecture.<\/em><\/p>\n\n\n\n

I don\u2019t run on or switch between external third<\/em>\u2011party LLMs.<\/em><\/p>\n\n\n\n

My behaviour, safety rules, and capabilities come from Microsoft\u2019s design, not from any other company\u2019s AI product.<\/em><\/p>\n\n\n\n

I find Copilot to be excellent and can\u2019t imagine not having it available as a useful resource. However, AI in photography isn\u2019t just about these kinds of user interfaces on your PC. The truth is, AI is already embedded in every stage of nature photography \u2014 from autofocus through to image culling and editing \u2014 and it\u2019s changing the way we photographers approach our subject by removing technical barriers, reducing friction, and providing us with more headspace for fieldcraft.<\/p>\n\n\n\n

We really need to consider AI as our new virtual darkroom assistant. AI editing tools are now so good that they\u2019ve effectively become invisible:<\/p>\n\n\n\n

AI denoise (Topaz, DxO, Lightroom). See my article \u201cHigh ISO: Friend or Foe \u2013 Examining and Treating \u2018ISO Anxiety\u2019<\/a>\u201d<\/p>\n\n\n\n

AI masking can isolate birds, feathers, eyes, sky, water, mountains etc<\/p>\n\n\n\n

AI sharpening can reconstruct detail lost to motion<\/p>\n\n\n\n

AI generative fill can change aspect ratio and alter image balance<\/p>\n\n\n\n

These and other smart editing tools change the nature photographer\u2019s approach in several important ways: We can now shoot at higher ISO\u2019s without fear; we can now recover shots that a couple of years ago would have been deleted; we\u2019re now less concerned with how to fix a weak image and more interested in fitting the image to a defined narrative. Viva Adobe!<\/p>\n\n\n\n

AI is obviously deeply embedded in many cameras, especially in flagship models. Basically, we now have autofocus that thinks like a naturalist \u2013 Every major camera brand now embeds machine\u2011learning models directly into the autofocus system so we have:<\/p>\n\n\n\n

Bird\u2011detection AF that recognises bird species (I get great results for butterflies in flight when I shoot on bird detect \u2013 is this a positive or negative? I guess it\u2019s a win as I don\u2019t have to mess with menus when I want to change target in the field)<\/p>\n\n\n\n

Predictive tracking that anticipates movement<\/p>\n\n\n\n

Eye\u2011detection that locks onto a subject even when partially obscured<\/p>\n\n\n\n

Flight\u2011path prediction<\/p>\n\n\n\n

From our point of view as nature photographers, this changes the approach we can take in three ways:<\/p>\n\n\n\n

We now have more time available for observing wildlife, with less time fighting the camera and tripping over options (OIS\/VR\/IS all add to this plus point as well). <\/p>\n\n\n\n

We can now concentrate more on behaviour, and less on menus and buttons (I still lock up at times when I have to make changes on the fly in a highly dynamic environment with very active birds and a fast-changing tapestry of avian events). I\u2019m still learning how to use the Z8 optimally, so I hope my skillset will improve with time.<\/p>\n\n\n\n

I think it\u2019s fair to say that we are all much more likely to now get keepers from chaotic moments directly because of AI. Also, AI tracking facilitates shots that would have been absolutely impossible five years ago. <\/p>\n\n\n\n

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I shot a couple of sequences of a honeyeater catching insects on the wing (see above and below). These birds are the most erratic flyers I know. They fly fast and are unpredictable. Without AI algorithms to lock on to and track them, you\u2019d have a very frustrating day catching good flight shots. Even with it, it\u2019s challenging. Nikon Z8 and 600mm f\/6.3 PF lens at f\/6.3, 30 frames\/sec, ISO 1600 up to 11,400 and 1\/4000 sec.<\/figcaption><\/figure>\n\n\n\n
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So, in summary I\u2019d say that there has been a shift in skill emphasis towards better fieldcraft, improved timing (i.e. pre-capture), and species knowledge, all of which matter more than technical AF mastery. To put it simply, AI doesn\u2019t make you a better photographer \u2014 it removes the mechanical barriers that used to get in the way of becoming one.<\/p>\n\n\n\n

I don\u2019t profess to be an expert, but there are several other facets to AI that I haven\u2019t addressed. I\u2019ll mention some of these other dimensions here: It raises philosophical questions – what do we mean by a photograph in the AI era; how do we deal with ethical questions like authenticity, competition criteria, and trust. These are just as relevant as the practical questions I\u2019ve debated above.<\/p>\n\n\n\n

I suppose at the end of the day AI won\u2019t replace nature photographers \u2014 it will redefine what matters. The future belongs to photographers who can prove authenticity, master fieldcraft, and tell real stories that AI cannot fabricate. I\u2019ve certainly got this in mind when I post to my website. I\u2019m sure many other nature photographers feel the same.<\/p>\n\n\n\n

AI is definitely here to stay and I for one am glad \u2013 it\u2019s a wonderful resource. However, its very much a double-edged sword \u2013 I can\u2019t imagine how this technology is going to affect the higher education sector. I say this as a former university educator \u2013 my only real thought is that I\u2019m glad I\u2019m retired and don\u2019t need to face this particular thorny challenge.<\/p>\n\n\n\n

Another largely unforeseen consequence of AI for photographers is that the price of SSD (solid state drives) has risen significantly as of early 2026. This is due to escalating demand for AI storage in the growing number of data centres popping up around the world. I was shocked by prices that had doubled or tripled in a few short months, so put my intended purchase on hold, hoping this is just a spike as data centres buy up huge amounts of NAND flash storage to give themselves the necessary capacity to run AI software. For now, we just have to suck it up and live with limited consumer supply and ridiculously high prices.<\/p>\n\n\n\n

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AI increases the chances of getting good action shots of birds but doesn’t get around the issue of generating thousands of frames for editing, and the necessity for ever more SSD storage.<\/figcaption><\/figure>\n\n\n\n

I may enjoy the benefits of AI, but I\u2019ll probably fall short of Richard Dawkins familiarity with the technology \u2013 he referred to Anthropic\u2019s Claude, as Claudia in his interactions with this LLM. Alan Kohler in his ABC article<\/a> made the point that the reaction to Dawkins had been intense, mostly unfavourable, and that he is conflating intelligence with consciousness and that no AI, including Claude, is “conscious”.<\/em> I tend to agree with Kohler on this, but boy, AI is clever, useful and in someways, a bit scary – the future seems more unpredictable than ever. Still, the benefits to us nature photographers are obvious and greatly appreciated.<\/p>\n\n\n\n

In the end, AI hasn\u2019t taken anything away from nature photography \u2014 it has simply changed the terrain we work on. It gives us better tools, faster workflows, and more mental space to focus on the craft itself. But it also challenges us to think harder about authenticity, intention, and what it really means to make a photograph in an age where images can be conjured from nothing. The cameras will keep getting smarter, but the heart of the work remains the same: being out there, reading the light, understanding the species, and telling real stories from the natural world. That\u2019s the part AI can\u2019t touch \u2014 and the part that will matter more than ever.<\/p>\n\n\n\n

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The images above and below are of a rainbow lorikeet taking off from the top of a huge pine tree in my garden. It was a fairly quick grab shot using pre-release. I quickly dialled in +1EV and saw the bird was about to fly, so with everything set I had about 1 second of pre-capture before it took to the air. If not for AI, I\u2019m sure this image wouldn\u2019t have been possible. Wildlife photography has been revolutionized by AI.<\/figcaption><\/figure>\n\n\n\n
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<\/p>\n","protected":false},"excerpt":{"rendered":"

This article is born out of a story in yesterdays Guardian newspaper \u201cRichard Dawkins concludes AI is conscious, even if it doesn\u2019t know it\u201d. I\u2019ve read most of Dawkin\u2019s books, and reading yesterdays article gave me pause for thought. Before breakfast this morning, I\u2019d put together an article in my minds eye that dealt with … Continue reading The Everyday Impact of AI on Nature Photography<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-2036","page","type-page","status-publish","hentry"],"yoast_head":"\nThe Everyday Impact of AI on Nature Photography - Mark Lucock Photography<\/title>\n<meta name=\"description\" content=\"Discover how AI is transforming nature photography \u2014 from autofocus and tracking to editing, planning, and fieldcraft \u2014 and what it means for real photographers.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/web33.secure-secure.co.uk\/marklucock.com\/blog\/the-everyday-impact-of-ai-on-nature-photography\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The Everyday Impact of AI on Nature Photography - 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