FBN recently announced Norm, an artificial intelligence (AI) advisor for FBN members. Norm may be the first purpose-built artificial intelligence platform for farmers, but it won’t be the last. AI is definitely pervasive in agriculture and other fields. This post explores questions about the use of AI in general and agriculture.
What is AI technology?
First, let’s cover some basics. AI is an abbreviation for “artificial intelligence”. According to Dr. Anastasia Lauterbach, a contributor to Laws of artificial intelligence and smart machines, AI should be considered as “narrow” AI or “general” AI. Narrow AI is focused on solving a specific task. That’s what we generally talk about when we talk about “machine learning” (ML). In ML, computers use large amounts of data to make decisions, but not just decisions, but continuously making better decisions. ML allows computers to learn from past decisions.
AI in general is what we’ve been talking about lately. According to Dr. Lauterbach, AI in general is similar, but it seeks to mirror human behavior and abilities to solve problems. What we’re seeing today in ChatGPT and other technologies is “generative” AI, a type of general-purpose AI that can generate new content that didn’t exist before. Generative AI like ChatGPT leverages information from vast amounts of publicly available data to create original content in response to user inquiries.
How can farmers use AI?
Given how much data agriculture will need to refer to in order to make informed decisions for the future, how much AI can help increase plant and animal production? you can get some ideas. How many varieties of corn should I plant this year? A human agronomist cannot analyze all the varieties and consider soil profiles, weather forecasts, pest forecasts, etc. to determine what is best for a particular field. you can’t. But an AI with the right training data can do it.
Similarly, narrow AI is already being used in applications such as sea-and-spray technology. ML-trained equipment learns how to spot weeds and distinguish them from crops, so applicators only need to apply pesticides to weeds, not over large areas.
What’s wrong with AI?
Aside from Hollywood’s doomsday predictions that AI will become so clever and determined to destroy humanity for the benefit of the planet, there are other more immediate and practical concerns. AI depends on the data you train it on. Such decisions can cause problems if the training data is corrupted or distorted by the company to increase shareholder value. Imagine a seed company figuring out what data things like his ChatGPT use to make planting decisions, and the company starting flooding the internet with false reports about their seeds. please. That data is something we (humans) would never find in a search engine, but AI has its sights set on it. . The seed company could skew AI results to favor its own products. Just as companies use search engine optimization (SEO) strategically, marketing departments will start using his AI system to skew recommendations in their favor.
Also remember that AI has to make mistakes in order to learn to be right. This means that mistakes will happen on the way to the future.
What are the legal implications of AI?
Privacy is a big concern. Imagine an AI tool that uses a farmer’s agricultural data to make decisions. Farmers using AI tools get crop recommendations based on field data they enter and data from other farmers using the platform. For farmers, it may not be immediately obvious that their data is essentially known to all other farmers using her AI platform.
Will AI respect ownership of data, copyrights, and other forms of intellectual property (IP)? Today, only humans or companies can legally create or own intellectual property. What happens when AI uses its own information to create new derivative content? Who owns the resulting IP?
It is fraudulent for a company to trick an AI into making decisions based not on accurate data, but on published false data to distort the AI’s results in its favor. I don’t know of any laws that deal with this scenario.
Finally, there are concerns that people will make decisions based on misinformation generated by AI. There are many examples of “deepfakes” on the web. These are videos of politicians and celebrities saying things they didn’t actually say, but AI can generate convincing fakes.
Conclusion
Despite the concerns, the use of AI in agriculture and other fields has a very positive impact. AI is far superior to humans at analyzing vast amounts of data in an unbiased manner. AI can recognize patterns and problems that we cannot see. As with all new technology, good things bring some bad things, but you have to deal with them along the way.
