The theme of Artificial Intelligence at Surf Research Week

There was considerable focus on AI, and its implications for research and research support, at the Surf Research Week in Utrecht this week (10 May 2022). Here’s a brief set of bullet points on the discussions I noted:

Surf Research Week – Image from main conference hall

There’s too much focus on the negative examples of AI. How can we do more to demonstrate the positive benefits? And ally that to greater transparency in how AI functions.

Also, how can we intelligently reflect on the applied uses of AI? AI should not be viewed as a panacea for all social and research challenges; we need to gain the critical insight to understand when it is (and is not) the right methodology to be applied.

AI changes the nature of how research projects are organised. Also: if AI permits researchers to make discoveries about things they were not even aware of, should we even think of AI itself as a collaborator in research projects, rather than a methodology that we use?

In any case the need for collaboration between people with different knowledge becomes even stronger with AI. There are wide-ranging skills that are needed to deploy AI within a project – not just in technical terms, but in terms of data science and management, and embedding the ethical context. In particular, ensuring an ethical footing for AI projects with potentially profound social implications should involve the right philosophical expertise. The related need for management and archival skills in curating and documenting the datasets that underpin AI.

And also efficiencies and expertise provided by high-quality software engineering can drastically time and money when it comes to deploying the computer power needed for AI. A familiar discussion arose – should AI expertise be situated locally or nationally? Should it be generic or focussed on specific subject areas?

The tension within the AI community between acceleration and regulation. On the one hand, global challenges desperately required the novel ideas that AI can provide – let’s move quickly! On the other hand, we need standardisation to be able to deploy AI in a sustainable and regulation to provide the necessary ethical context. Let’s get this sorted out.

Are they distinctions between AI algorithms and datasets that area developed within the research community, and buying AI as a service from third parties? What does the latter mean for issues such as reproducibility, ethics? What are the implications for university procurement departments if a whole university wants to use AI as a platform.

(Thanks to SURF for organsing the event, and to the panellists and workhsop speakers who contributed so many ideas Emily Sullivan (Tu/E), Nanda Piersma (HvA), Maarten de Rijke (University of Amsterdam), Damian Podareanu (SURF), Antal van den Bosch (Meertens Institute) Sascha Caron (Nikhef) Matthieu Laneuville (SURF)

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