Amplifying Limitations, Harms and Risks of Large Language Models
Michael O'Neill Mark Connor
We present this article as a small gesture in an attempt to counter what
appears to be exponentially growing hype around Artificial Intelligence (AI)
and its capabilities, and the distraction provided by the associated talk of
science-fiction scenarios that might arise if AI should become sentient and
super-intelligent. It may also help those outside of the field to become more
informed about some of the limitations of AI technology. In the current context
of popular discourse AI defaults to mean foundation and large language models
(LLMs) such as those used to create ChatGPT. This in itself is a
misrepresentation of the diversity, depth and volume of research, researchers,
and technology that truly represents the field of AI. AI being a field of
research that has existed in software artefacts since at least the 1950's. We
set out to highlight a number of limitations of LLMs, and in so doing highlight
that harms have already arisen and will continue to arise due to these
limitations. Along the way we also highlight some of the associated risks for
individuals and organisations in using this technology.