One of the challenges in data-to-text NLG is creating good summaries and insights when the input is flawed (incomplete, incorrect, or inconsistent). One of my PhD students has been working on this problem, and it is a hard one! But a good solution would be hugely valuable for society. I may be able to offer a PhD studentship in this area, contact me if interested.
I’m excited by the potential of adding conversational capabilities to data-to-text systems, so that users can provide context, ask follow-up questions, etc. I think this is essential to my vision of using NLG to humanise data and AI!
Salesforce has announced that it is buying the NLG company Narrative Science, which will become part of the Tableau team which provides business intelligence tools. This highlights that NLG is being taken very seriously in the business intelligence world, and indeed BI looks like it could be a “killer app” for NLG.
Anya Belz and I are looking for a research fellow to work on a new project on reproducibility of human evaluations of NLP systems. This is a great opportunity for a researcher who wants to improve the scientific quality of human evaluations in NLP!
In 2016, I was shocked by the poor scientific quality of research in neural NLG. Fortunately, the situation is better in 2021! However, progress has been less than I had hoped, I think in part because the “leaderboard” culture does not encourage good science.
I’m looking for a PhD student to work on using AI and NLG to help cancer patients who are managing their condition at home. The student will be jointly supervised by people at Aberdeen’s Medical School. I think this is a very exciting PhD, and a chance to work on ideas that could make a real difference to people’s lives!
Why would anyone use a Bayesian model instead of a neural model in clinical decision support? Perhaps because the Bayesian model is much easier to justify and adapt to a changing world. Explaining Bayesian models is also a really interesting research challenge, and one of my colleagues has funding for a PhD student in this area.
I think NLG can help humanise and democratise data and AI reasoning. If so, this would provide huge benefits to society in a world which will increasingly by driven by data and data-based reasoning.
A few observations (not recommendations!) about what it is like to work as a researcher in university and corporate contexts.
I would like to see more PhD students and postdocs “getting their hands dirty” by collecting real-world data, working with real-world users and experts, and conducting real-world evaluations with users. Its not easy, but engaging with the real world does help scientific and technological progress.