It was a privilege to be the keynote speaker at the BBC in Bristol last week at the Rural Affairs Committee, to tell their rural team about the research we undertake and how we are using AI to address some critical issues in data collection in the sector.
Agricultural research has some problems…that probably aren’t unique to agriculture but are exacerbated by some industry quirks!
❌Data quality is an issue and the lack of recognition in the sector that robust and validated data collection is more important than ever.
❌The audience is under-engaged in taking part.
❌Data synthesis across multiple sources is at best problematic and in many cases unworkable.
❌too much focus on quant over qual
❌assumption of the truth rather than the actual truth
Not knowing the truth about what’s happening on the ground is going to be increasingly problematic as reliance on the sector to solve everything from food security to carbon net zero grows. What are we doing about it?
✅ Grow engaged research communities
✅ Utilise AI to validate and check responses and ‘talk’ to farmers to get to the context, attitudes and beliefs, not just the hard stats.
✅ Build reductive AI models to condense the data and understand themes, sentiments and audiences.
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