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The Persian Rug Effect: Cultivating Authentic Expertise in the AI Age

Writer's picture: Y. Osroosh, PhDY. Osroosh, PhD

Are you a biosystems engineer or an agronomist (student or researcher) overwhelmed by image processing and computer vision algorithms? Captivated by the siren song of robotics, perhaps even a devotee of ROS, you've convinced yourself that high-throughput phenotyping is impossible without becoming a computer vision guru.


Let me be blunt: this path may lead to regret. If AI has become your obsession, if you're more focused on the latest deep learning model than the delicate dance of plant-environment interactions, you're playing a dangerous game. AI is not here to help you; it's here to replace you.


Students, don't let your supervisors and departments dictate your path. Their obsession with AI is driven by grant proposals, not a genuine concern for your future. Demand more. Insist on real science, real projects that challenge you, and learning experiences that go beyond the latest AI buzzwords.


Let me tell you a story. Decades ago, I wrestled with 8051 Assembly language, a beast of a language with a syntax that seemed designed for maximum confusion. Simultaneously, I was building my own embedded systems, soldering and cursing every step of the way. Then came AVR, BASIC, Arduino, C/C++, and now even Python and Rust are trying to colonize even the most microcontroller-centric corners of the world.


Assembly language? A relic of the past, you might think. But it's not about the language itself. It's about understanding the underlying principles. You don't need to be an assembly language expert to appreciate the elegance of a well-designed microprocessor. Programming is a tool, not a badge of honor. I'm not a programmer; I'm an engineer who uses programming to solve problems.


We have this strange tendency to confuse tool proficiency with expertise. Suddenly, everyone in agriculture is a "data scientist." Newsflash: a data scientist, in my book, has a PhD and develops new data science methods. We, on the other hand, are borrowing those methods for our own purposes. We're doing "agricultural data science," not data science.


This isn't unique to data science. Researchers slap "IoT expert" on their CVs after installing a few sensors. You're an agricultural expert, period. Don't let these fleeting technologies define you. Remember who you are without the AI hype. Are you still a scientist? Still an engineer? Still a farmer at heart?


Then there's the MATLAB menace. Back in my day, it was the golden child, affordable and ubiquitous at the university. But the students? Clueless about real programming. Image processing? All MATLAB, all the time. Now, I try to get a quote for a few toolboxes for my company and nearly choke on the price tag.


Open-source was supposed to be the savior, but now it's under threat. National security concerns, the rise of AI, it all feels like a slow strangulation. And for those of you in computer vision, you're already feeling the squeeze. Your laptops are melting down trying to train models. You're resorting to synthetic data, a digital mirage. 


But here's the real question: if your goal is to develop AI algorithms, and Gemini, ChatGPT, and DeepSeek are your best friends, what's left for you to do? GenAI is already excelling in computer vision. Are you really adding value by developing yet another mediocre disease detection algorithm? 


And while you're feeding AI with your data, it's learning from you. Soon, AI agents will be doing your job, better and faster. They'll control robots, analyze images, even write your grant proposals (though I doubt they'll capture the unique flavor of academic hyperbole). 

This brings us back to the Persian rug. A true Persian rug is a work of art, handcrafted with skill and tradition. Machine-made rugs can imitate the appearance, but they lack the soul, the artistry, the centuries of accumulated knowledge. 



You, the agricultural expert, are the handmade rug. Your expertise is built on a foundation of deep knowledge, years of observation, and an intimate understanding of the natural world. AI can mimic some of your skills, but it can never replace your intuition, your creativity, your ability to connect the dots in unexpected ways. 


You, the agricultural expert, are the handmade rug. Rich in intricate patterns woven from years of experience, deep knowledge, and an intimate understanding of the natural world, your expertise is a unique masterpiece. AI can replicate some of your skills, but it can never truly replace the intuitive artistry, the creative spark, and the profound connections you forge – qualities that make you irreplaceable.

Don't let AI dictate your path. Focus on the fundamentals. Ask yourself: what can I do that AI cannot? How can I use my unique perspective to solve the challenges facing agriculture? The future of agriculture depends on your authentic expertise, not on your ability to tweak hyperparameters. 


The AI revolution can be about empowering people, instead of replacing them. But only if we remember who we are and what makes us truly valuable as agricultural experts.

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