I thoroughly enjoy Chairing the Crop Health and Protection Advisory Group. This recent interview, reproduced with permission from CHAP, shares my thoughts on the role of artificial intelligence (AI). In particular, I believe AI is an important tool in handling some of agriculture’s challenges, but it will be much easier if we remove the hype around it.
At the recent Advisory Group meeting, key players, working both inside and outside agriculture, were invited to discuss AI and share experiences to help sculpt the future of its adoption. This interview was conducted & the article written by CHAP’s Strategic Marketing Manager, Janine Heath, to highlight some of the insights from that meeting.
Can you explain what you mean by a need to demystify AI in agriculture?
Artificial intelligence still sounds very futuristic and has attracted a lot of hype. For many, this makes it feel out of reach and unapproachable. We need to remove this mystery and strip back to a simpler approach – AI is essentially a tool that can help to solve problems. Put like this, it is much easier to understand.
Being clear about the problem you are trying to solve is also part of making it feel more attainable. That might mean describing and making sense of large, overwhelming data sets, or understanding a web of connections that are too complex for us to easily hold in our minds.
There is enormous potential to use AI to our benefit, for example, to help us get to grips with some complex topics. For instance, it can help us to better understand a network of relationships in biological systems, which our brains alone struggle to cope with.
For non-scientists and technologists, how do we start to break AI down?
We need to highlight the many everyday examples of AI within the home or in the field to provide context. These include online shopping algorithms, digital maps, and weather prediction software. We see the benefits here, and it doesn’t feel intimidating or threatening. As a sector, showcasing examples that make life easier and then demonstrating their true impact provides a great opportunity to gain buy-in.
Do you think there’s a ‘quick win’ for AI?
Data alone does nothing, it’s when we use it to gain insight that it starts to provide value. So I think there is a really strong message to be shared around the collaborative use of data.
Data is everywhere within agriculture and the food chain, but how do we connect those pools together? How do we work together? When we start to think like this, we can identify gaps and opportunities, and find the real issues that need to be resolved in order to make these technologies work for us.
It’s clear to see why a corporate organisation would want to integrate AI, but what is to be gained for everyone else?
Yes, commercial industries can make obvious gains in terms of improving productivity and efficiency, but there is also huge potential to make wider environmental gains in areas such as improving biodiversity or soil health.
The challenge here is that this area will probably have a less financial impact for individual companies. The risk is that, despite the potentially huge non-financial impact, it might be seen as a lower priority.
We shouldn’t neglect this dimension and its value. You only have to look at the Government’s efforts towards COP26 later this year and the financial sector’s increasing focus on Environmental, Social, and Corporate Governance (ESG). I guess the question is how do we, as a society, want to drive this agenda? It does need more of a push.
Where does CHAP come in?
The CHAP Advisory Group is one of several ways that CHAP brings together a diverse range of interests and voices to stimulate discussion. We have a great track record of using these opportunities to stimulate creativity and collaboration, resulting in fresh perspectives which lead to new opportunities for impact.
Artificial Intelligence is a great example of a technology that urgently needs a diversity of perspectives to think through how we make it work for all. Through CHAP’s collaborators and partners, we can open the topic up to a wider range of participants.
More broadly than AI, it is time for agriculture as a whole to widen our horizons beyond our own sector and look at what other industries do. This fosters cross-sector learning. We can use the Advisory Group to invite ‘outsiders’ to share their success stories and challenges, allowing agriculture to find ways to build on these prior experiences rather than build everything from scratch. CHAP and its partners are therefore well placed to make the most of this cross-sector expertise and use it to help the industry tackle the many challenges on our ‘to-do’ list.