Traditionally, people were shooting birds on Christmas Day, so in 1900, a few people thought about not shooting Christmas Day birds, but counting them instead. The idea came from an ornithologist named Frank Chapman.
But here’s the thing – it took hold. And it is still happening each year, with volunteers standing in fields in the freezing cold with binoculars and mugs of tea. But anyone who works with that kind of data will tell you where it creaks, and AI bird identification technology is starting to fix most of the creaks.
The trouble with counting by hand
Volunteers vary. That’s the first problem. An enthusiastic retiree with forty years of experience in birding would see things that the novice wouldn’t have seen, and the novice would be happy to record the sparrow when it’s actually not. There aren’t many experts around; hence, the inconsistency of the data.
Then there’s where people look. Roads, parks, town edges. Rich countries in North America and Europe have mountains of records, while whole stretches of Africa, South America and Asia are nearly blank, and that’s not because there are no birds. There just aren’t enough people with the time and the kit.
And when? Sunny Saturday mornings, mostly. Nobody’s out at dusk in a storm. Statisticians can adjust for all this, bless them, but you can’t adjust your way to data nobody collected.
eBird made it easier, not easy
This situation changed in 2002, when Cornell Lab of Ornithology and National Audubon Society started the eBird initiative. It is a checklist that everyone can post on the Internet. Later came apps like Merlin, from the same lab, which can suggest a species from a photo or a snatch of birdsong.
That helped beginners a lot.
Even so, somebody had to be there. Awake, outside, phone in hand. People remained the bottleneck.
Letting the machine sit and watch
Here’s the obvious next move.Add to your garden something which will not require you. A camera that can name birds by itself logs each visitor and pings your phone. It doesn’t get bored at six in the morning and it doesn’t stay in because it’s drizzling.
It watches the same spot for years, which is something volunteers, being human, almost never manage.
And it helps newcomers. If the software gives a decent first guess, a complete beginner can contribute usable records on day one.
Why gardens beat research stations
Research stations are expensive and there’ll never be enough of them. Gardens, though, are everywhere. A Birdfy smart feeder that recognizes 6,000+ species on one balcony rail doesn’t look like much of a scientific instrument.
Now picture ten thousand of them, across school yards, allotments and farm gates, each seeing its own little slice. That’s a network no funding body could afford to build.
There’s a human side too, and I think it matters as much as the data. Someone who would never call themselves a scientist starts contributing. A retired teacher. A kid with a hobby. A family who bought the gadget because it looked nice. Suddenly the natural world is partly their business.
What might actually happen by 2030
I’d stay away from big promises, but a few things look believable. Migration arrival dates could be tracked far more closely. Falling numbers of common birds might show up while there’s still time to do something. Sick birds turning up at feeders could work as an early warning when something like avian flu spreads.
None of it happens on its own, mind you. The records need shared formats and somebody checking them. My own guess is a mix, with machines doing the bulk and human experts looking over the strange or rare sightings.
The catches
AI still stumbles with rare species, young birds and parts of the world where there’s little training data. Bias doesn’t disappear, it just moves house, because the people buying connected devices tend to be better off and sit inside good wifi.
Cameras outside homes raise privacy questions too. And who owns the records? Some companies share with researchers, others keep everything inside their own app. Worth asking before you pay for anything.
Picture it in a garden
Imagine a bird feeder designed intelligently, hanging from a branch of the tree using solar power. Every visit gets logged without you lifting a finger.
On its own that’s a nice hobby gadget. If its owner shares the records with an open database, it turns into one small sensor in something far bigger. Whether a particular device can do that depends on the maker, so ask.
Where this leaves us
Citizen science started with people in thick coats counting birds for a single day. By 2030 it could be thousands of quiet devices counting all year, with people doing the parts they’re good at, like checking, questioning and caring. The tools are nearly there. What’s left is a decision to share what they see.
