If you’re a gardener, you should be aware that relying on AI can be dangerous. Running the AI data centers are detrimental to the environment, consuming 10 times the normal electricity compared to other search engines (UNEP, 2024). And what’s the point if it’s inaccurate? We’ve had numerous issues with AI spouting nonsense to all our wonderful customers and we don’t want your gardens, landscaping projects, or interior decorating ruined because of it. In this article, we’ll go over how to spot AI and what to use instead.

AI is transforming the plant industry at an exponential rate and not for the best. Sure, you can get information about plants, gardening techniques, and more using Chat GBT or a AI-run plant app but how accurate is this information? AI pulls its data from various sources across the internet, from downloaded books to “even those funny Reddit threads” (Climate Vault, Dec 2024). We’re sure you can recognize a red flag here: AI pulls information from ANY data online. AI can be trained to select data from certain sites but it can’t differentiate between reliable and unreliable sources. This leads to false information being shared on plant apps, the Google search settings, and even AI-generated images as fact. We can’t tell you how frequently misinformed customers come in because of AI. We have a good rule of thumb to keep in mind when it comes to AI identification: if it’s too good to be true, that’s because it probably is.

Too Good To Be True

Have you been recommended home remedies to care for sick plants? Or have you been shown images of plants that seem unreal, like deep blue leaves or neon magenta flowers that glow? These are all examples of AI displaying “too good to be true” facts and images. Gardeners in the know are aware there’s no such thing as a fully blue colored plant, that’s impossible because plants absorb light from blue and red light waves and reflect the green wavelength. Some plants appear blueish or even purple yet are never the color displayed by AI, exemplified below. Another sign (and poor recommendation) of AI is through plant apps’ advice. As we mentioned before AI absorbs and relays information from collected data all over the internet, including from memes (online jokes), unprofessional advice from Reddit and other websites, and non-scientific sources. AI in plant apps thus recommends that knowledge be treated as fact when it comes to identifying or recommending products to treat sick plants. Customers come in all the time with spotted leaves on houseplants and outdoor plants and through a plant apps “advice” been recommended inappropriate care, like supplying fertilizer when it’s a fungal issue. The fertilizer might help the plant bounce back but doesn’t eliminate a fungus, only a fungicide will do that. AI will also recommend homeopathic “remedies” for plants based on this collected data, like using honey to stimulate root growth on cuttings or using dish soap to treat for insect eggs. Sounds too good to be true right? You are correct, these claims are advertised as cheap but aren’t rooted in science and are often pulled from untrustworthy data. Honey has been shown to have limited effect, but very minimally, and rotting often occurs before root take a hold. And using dish soap on plants will kill your plants before killing insect eggs. Seasoned gardeners and plant people would be suspicious of these recommendations but those new to the lifestyle may be caught unaware and taken advantage of. 

How to Spot AI Via Images

AI learns and thus it becomes increasingly difficult to differentiate real photos and AI-generated photos. Realistic but not perfect, thankfully there are still techniques to spot AI in photos:

Strange Details: Focus on the details of a photo you question. Are plant leaves melding together? Or do flowers seem way too bright? Almost glowing? No matter how small the detail something will be wrong with its appearance, indicating AI-usage. Data is collected and generated into a new image yet AI isn’t tuned enough to make it appear natural. Another great detail to look at is if a blossom appears identical to another in the picture, AI is essentially just copying and repeating the same feature in one photo. 

Too Perfect: Aesthetics are important when it comes to internet images. Things must be perfect and AI tends to make things too perfect. AI-generated photos tend to lack realistic details, forgetting about the tiny hair like roots of a potted plant or a certain leaf pattern, instead giving an airbrushed appearance to the photo. Or the background environment might be incorrect for the plant featured in a photo, like tomatoes being displayed in a cold setting. Too perfectly aesthetic are red flags and their source, information, or appearance should not be trusted. 

These are only techniques to handle photos, however. Rely on the professionals, like academics and scientists, for plant knowledge. 

How to Spot AI: Discovering the Source

There’s a final trick up our sleeves for discovering what images or data snippets are AI-generated or not and it involves a little extra work. Are you familiar with the reverse image search?

Google Image Search: Have you ever downloaded a plant picture and are suspicious of its authenticity? Introducing the Google Image search. Simply open up a tab in Google, click the little camera in the search bar, upload that mysterious picture and you should be able to trace its origin. If the image comes from an academic source, a college, a published research magazine, or an established agricultural company chances are the plant displayed in the said photo is the real deal. If the image is tracing back to a single source and it’s on a shady website or a single page on Amazon chances are not only did you stumble upon an AI-generated image but it’s being used in a scam. Distrust the photo immediately and continue to rely on the professionals. 

The Professionals: Who to trust

The best sources for plant advice ALWAYS come from professionals: academics, scholars, and scientists. Academic websites, university & college websites, scientist-run online journals and blogs, and more are all excellent places to source plant information and research. Science is evidence-based, meaning scientists study topics through experimentation. To think about the reliability of science is to think about the reliability of the car. “Most of us trust our cars, ” says Naomi Oreskes, a professor of the history of science at Harvard, “The modern automobile is the product of the collected work and wisdom and experience of every man and woman who has ever worked on a car. And the reliability of the technology is the result of that accumulated effort (Oreskes, 2017).” Real people analyzing trusted research, not just general data, is why science and thus academia should always be trusted and referenced. AI has no peers to check it and keep it real, though in time that may change. But in the meantime stick with the professionals.

We Ricksters use Colorado State University Extension as our main source for information. There are hundreds of free articles on whatever subject you could imagine. And there’s even a Q&A panel where you speak with real researchers, not an AI-driven help bot! To check them out, click these links:

Colorado State University Extension Page: CLICK HERE!

Colorado State University Extension Q&A: CLICK HERE!

Another great source of FREE information is the library! A librarian may not be a gardener but they’re trained in the art of finding trustworthy sources and good material. Use them or the library’s search features to hunt down trustworthy authors and information. 

From college websites to libraries, there are numerous trustworthy sources for your plants. And even though AI is learning every day and becoming better, no one can do it like the pros. Plus, AI is bad for the environment, and using it is not cool. It uses thrice as much power as normal search engine, uses rare earth materials, and produces crazy amounts of electronic waste. Happy gardening and happy researching!

Sources:

“​Industry News from 3BL Media: The Impact of AI on Carbon Emissions.” My Green Lab, December 4, 2024.

“AI Has an Environmental Problem. Here’s What the World Can Do about That.” UNEP. Accessed July 7, 2025.

Oreskes, Naomi, “Why Should We Believe In Science,” TED Radio Hour, February 24th 2017, 13 Minutes.

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