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AI – The Good, the Bad and the Ugly: Part 1

Introduction

I have not been posting since April. I have been swamped with a mix of teaching, grant writing, admin duties, and health problems. The time is still quite precious, but I have been desperate to do some blogging for a change.

I have recently been involved in a discussion about the reliability of AI and its use in research and education. I want to devote this series of posts to presenting my views on AI, what tools I use, how and why, and what I would like to see and not to see in the future.

These blog posts will evolve over time as I prepare my lecture for an AI-focused special session at the British Society for Plant Pathology #PPATH25 conference and other opportunities. I will also surely be testing other AI services and apps, and so my views and recommendations will surely change in the future.

Disclaimer 1: I tend to pay for apps and services I use, firstly because I believe in supporting the development of excellent tools. Secondly, because I firmly believe that if “paid means I am a customer, free means I am a product”.

Disclaimer 2: My views here do not reflect the official views or the policy of my employer. I have paid for the tools myself.

&TLDR:

  • AI revolution is happening, and its wide impacts are inevitable, “this genie is out of the bottle”.
  • There is a lot of hype about AI, both positive (“AI will solve all our problems”) and negative (“AI will take over the world”).
  • When used responsibly, AI can be very beneficial, but it needs to be used properly, with extra caution.
  • AI providers and politicians are forcing AI upon us for their own reasons, as they want it used everywhere. Given that AI is often wrong, we might see some spectacular failings in the future.

I am thinking of generative AI as a group of not-particularly-smart and often-not-reliable assistants, who have access to the largest library in the world but do not always know how to use it well.

They can help me enormously, but I need to tell them exactly what I want and then carefully check what they produce.

By the way, that’s very similar to my Master’s or (early years) PhD students.

The first post/review to follow shortly…