Human+Machine: the key to success in the greenhouse

Added on 28 August 2023

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Human+Machine: the key to success in the greenhouse

The perception of people regarding AI and robots is multifaceted and can vary greatly. Some individuals view these technologies with optimism, recognizing their potential to enhance productivity, improve efficiency, and create new job opportunities. They see AI and robots as tools that can assist and collaborate with humans, automating repetitive or dangerous tasks, and freeing up time for more creative and complex work. On the other hand, there are concerns about the impact of AI and robots on employment. Many fear that automation could lead to job displacement and unemployment, particularly in industries where tasks can be easily automated. This perception stems from the idea that machines can replace human workers, potentially leading to economic inequality and social disruption. It is important to note that while AI and robots can indeed automate certain jobs, they can also create new employment opportunities in emerging fields related to AI development, robot programming, and maintenance. The key lies in adapting to the changing nature of work, upskilling, and embracing the potential for humans and machines to collaborate effectively in a rapidly evolving technological landscape.

By now everyone has one or two scary stories about ChatGPT and AI and how they can potentially ruin our lives. The Deep Fake, new alternatives to the Nigerian Prince emails and the new wave of cyberbullying to name a few. Yet, the main question is if these tools and algorithms going to take our jobs away. Indeed this new industry is going to create new and different jobs but you can expect a customer service person who is now replaced by a chatbot, overnight to become an AI engineer and software coder.

In our industry, repetitive tasks and mind-numbing efforts will be automated as it has been the case for the past two decades. You barely can find a greenhouse that does not have a sorting machine these days. We used to do this by hand not too long ago. There will also be some tasks that will be done by these algorithms that are considered high cognitive decision making and in some cases, the algorithm might in fact offer a better solution compared to a human "if" the training data that was used to build the algorithm is much larger, much more diverse and far more informative than the knowledge and experience of the human who is going to us it.