Postdoctoral researcher @PIK_Climate on natural language processing and climate science.
Joined February 2020
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Our work using machine learning to map out a "topography" of climate change research, with Jan Minx and @piersforster
nature.com/articles/s41558-0…
Max Callaghan retweeted
🆕 PIK-led research work in @ClimateActionSN generates the map of research on #ClimatePolicy from 85,000 individual studies. It informs existing gaps in knowledge and facilitates the summarisation of the state of knowledge for governments. #MachineLearning
pik-potsdam.de/en/news/lates…
To help users navigate this landscape, we argue that organisations like @cochranecollab and @CampbellReviews need to update their methodological guidance to help users distinguish between well-justified and ill-justified stopping criteria 12/N
There is a lot more to do on improving and evaluating stopping criteria. We set out a blueprint for some of this in the paper, but it requires lots of engagement and further work, some of which is already happening - e.g. in DESTINY destiny-evidence.github.io/w… @wellcometrust
Incidentally, if you are interested in working with us on how we can responsibly use ML to assist evidence synthesis, we have an open position at PIK. potsdam.pi-asp.de/bewerber-w… Today is the last day the position is open, but please get in touch ASAP if you need extra time to apply
We also argue that software providers (@Covidence @EPPIReviewer @asreviewlab @rayyanapp @evidencepartner @PICO_Portal) need to provide better guidance on how their ML-prioritisation tools can be used responsibly (i.e. with appropriate stopping criteria). 11/N
Some stopping criteria make transparent assumptions and use appropriate statistics to communicate the risk of missing relevant studies (like the one we developed 4 years ago doi.org/10.1186/s13643-020-0…, other promising alternatives are available :)) 8/N
Other stopping criteria do not do this, but rely on heuristics, like stopping after 50/100/200 consecutive irrelevant records. 9/N
This is unrelated to how fancy our model is. Whenever we use an ML-generated prediction, we need ways to manage and communicate the uncertainty that comes with relying on that prediction. This is a *necessary condition* for the *responsible* use of AI/ML 7/N
This means we can stop screening before we have seen all the potentially relevant documents. But to do this, and actually save some work, we need to know when to stop. This is where stopping criteria come in 😎 5/N
There is also lots of great software that allows scientists the opportunity to benefit from AI/ML for screening without needing to program: @Covidence @EPPIReviewer @asreviewlab @rayyanapp @evidencepartner @PICO_Portal , ... 3/N
While I was away on parental leave, our paper was published on the urgent need for well-justified stopping criteria when using ML to speed up screening in systematic reviews: doi.org/10.1186/s13643-024-0… 1/N
There has been so much work done on ML for screening in systematic reviews systematicreviewsjournal.bio…, and the vast majority of this work applies fancier and fancier models (the latest example being LLMs: arxiv.org/html/2401.06320v1) to promise ever greater work savings 2/N
Max Callaghan retweeted
Today, we have published a new research bulletin titled 'The impact of planning and regulatory delays for energy infrastructure'.
⚡ The research highlights how regulatory delays impact electricity prices, system emissions, and costs.
esri.ie/publications/the-imp…
ALT RESEARCH BULLETIN The impact of planning and regulatory delays for energy infrastructure An Institiúid Um Thaighde Eacnamaíochta Agus Sóisialta. The Economic and Social Research Institute (ESRI).
There's some talk of the fragility of the Labour majority, the role of Reform in the Con defeat/Lab victory, and the distortions of FPTP, but worth noting IMO that the majority of constituencies were rather left than right-leaning, quite a few very much so
Obvious caveats about the differences within parties categorised here as Left of Center, but these are all parties that are clear(ish) in their commitment to net zero. Suggests to me limited gains from a continued Tory focus on net zero costs and car culture wars