I’m sooo glad to be in Berlin for the 6th edition of this beloved INDL-6 conference, which is taking place at Weizenbaum Institut!
INDL started as a small-scale, informal, little-funded project, aiming to create linkages between academics and students interested in the transformations of labour brought about by digital technologies. We first met in Paris in Spring 2017, then in Louvain-la-Neuve (Belgium) a few months later, and in both cases, a smallish 20-people room was enough for all. Back then, we called ourselves ENDL (where E stood for “European”).
But in 2019, we partnered with Toronto-based colleagues and upgraded to INDL, moving from European to International level. We started a cycle of conferences which initially remained rather small-scaled, and for two years had to take place online owing to the pandemic crisis. Things started to change in 2022, when colleagues from Greece proposed to restart an in-person version of the conference which eventually took place in Athens. It was also the first time that we launched a call for papers, rather than just limiting ourselves to invited speakers, and the conference was a huge success, with almost a hundred participants and sessions running in parallel.
This year edition’s follows the same format, and I’m so happy to see that a large community is forming around this topic. It’s good to see some people who already attended last year or even before, together with many new faces, and numbers continuing to grow (this year, we have three instead of just two parallel sessions!).
Together with the parallel sessions, this year’s event includes three keynotes, an arts-meets-science session, and a regulation-oriented debate on due diligence processes and the technology supply chain. Weizenbaum Institut is a wonderful place and has made available funding, support, and an incredibly committed team of colleagues, students, and volunteers who are making this conference a success.
For the programme, link to the livestreaming of plenaries and main sessions, and further information, please see indl.network.
Data Big and Small 