This was a joint briefing with The Alan Turing Institute.
ChatGPT is a language model developed by OpenAI that generates human-like text through deep learning. These language models are trained on a massive corpus of text from the internet and can respond to a wide range of questions and prompts with remarkable fluency and accuracy, making them a popular tool with a variety of applications, with ChatGPT amassing over 100 million users since its launch in November 2022.
However, the use of large language models also raises important questions about the limitations and ethical considerations of relying on AI-generated text. There are limitations to the information they can provide and the accuracy of their answers. Additionally, the increasing use of language models raises concerns about accountability, bias, and the impact on jobs that involve writing or content creation, such as journalism.
Some organizations and institutions have begun to regulate the use of language models, with some academic journals having banned the use of language models as co-authors on papers, citing the need for human authorship and accountability. It’s important to consider the potential benefits and challenges of language models and regulate their use in ways that protect both consumers and the wider public.
The Science Media Centre and The Alan Turing Institute put together a panel of experts to discuss the positive and negative impacts of ChatGPT and AI-generated text, including how it works, the limitations and ethical considerations surrounding it, and the real-world implications of its increasing use.
And who better to write this invitation than ChatGPT itself, showcasing the very technology at the centre of the discussion.
Speakers included:
Prof Mike Wooldridge, Professor of Computer Science at University of Oxford, and Director of Foundational AI Research at The Alan Turing Institute
Dr Mhairi Aitken, Ethics Research Fellow at The Alan Turing Institute
Prof Maria Liakata, Turing AI Fellow at The Alan Turing Institute and Professor in Natural Language Processing at Queen Mary, University of London