I was recently invited by my publisher, Sage, to write a guest article for their ‘research methods community’ about a current theme in data visualisation. Perhaps unsurprisingly, this led me to look at AI and its potential role – and value – as a collaborator in data visualisation design.
In the two years since I first wrote a couple of pieces about my early sense-making of the relationship between AI and data viz (part 1 and part 2), the evolution of tools has been eye-wateringly rapid. So much so its almost impossible to reasonably find time to keep up with new applications.
What doesn’t change much though are the key elements of a data visualisation process that could benefit from such AI applications but not in a fully delegated way, rather in a collaborative role “augmenting our efforts to make tedious tasks more efficient and creative acts more ambitious”.
This piece focuses on this positive, perhaps hopeful, tone offering suggestions for ways I would appreciate enhanced support from AI and less about the now well-known – and not-insignificant risks or concerns. Due to word-count limitations I could only find room to briefly describe 12 distinct suggestions covering practical matters to do with data, creativity, design and evaluation.
You can read the article here.