AI this and AI that – will it ever end?
Wow! Isn’t it amazing how our world can change in an instant? Remember not that long ago when AI was an up and coming “thing” but not yet a mainstream facet of our research lives? Now it seems everything is about AI or has some AI component to it. I’m not saying that it’s a bad thing nor am I loving it – I’m just stating the facts! It does worry me a bit though – but then again I’m an old fogey who is kinda set in her ways 😀
Research funding calls now seem to be centred around AI – which is great but again there is a challenge to this that I think folks are missing. If you are building tools to enable researchers – how will an LLM fit in? How do we hit pause or rather encourage the research to slow down just a little until we can convince our researchers that we need those basic building blocks before we go and build the next CN tower. Alright Michelle – what are you really trying to say?
AI and LLM can help us build and expand our data ecosystems – but if we don’t have the basics – aka documentation – how can build an effective tool and LLM? Remember the old adage used in statistics? Garbage in – garbage out? If we cannot create proper documentation for our datasets – then what will the AI models use?
AI is a great tool – but I think we need to remember exactly that – it is a tool! We can use it to enhance our current data ecosystems – but let’s not rely on it. We need to teach our up and coming students those basic building blocks – what is data, what is an attribute, what is a data type, etc…. before we unleash the AI tools that promise to make our lives easier.
Would love to hear your thoughts on this!
