Encoding Freedom: Analysis of open search technology between German hacker ethics and Asian start-up culture

• In Event: Wiring digital justice: Embedding rights in Internet governance by infrastructure - I

Abstract

Susi.AI is an open source personal assistant that has its roots in decentralized technology, peer-to-peer principles and the German hacker culture. It is devoted to values and rights of the Free Software movement: „access to source code is a fundamental right“ (Stallman, cited in Birkinbine 2020). With the recent move of SUSI.AI towards Asia, however, other cultural visions, values and notions of freedom entered the developer community. SUSI.AI is still relying on the initial hacker community, but also making use of the Google summer of code program funding open source project, for example. This indicates that free software is not entirely independent from corporate players, quite on the contrary (Birkinbine 2020, Coleman 2013). In a sense, both hands are feeding each other, but one of them is much more powerful than the other. Drawing on concepts from STS such as “vanguard visions” (Hilgartner 2015), values by design (Von Hippel 2006), and the political economy of free software (Birkinbine (2020) this presentation will pose the following questions: What visions, values and rights are driving SUSI.AI and how are they encoded in the technology? What compromises are SUSI developers willing to make to remain capable to act? And how do they handle the balancing act between free software and corporate actors? And, on a more general level, what are the wider sociopolitical implications in terms of tech development; especially in Europe where fundamental rights are framed as “core European values” (Mager 2017)? These questions will be answered based on a rich body of qualitative research materials including interviews with German, Asian and US-American SUSI.AI/ open source developers, participatory observations of open tech events in Frankfurt (CCC), Berlin and Singapore (FOSSASIA) and two joint workshops with SUSI.AI developers.

This research is funded by the Austrian Science Fund (FWF, project number: V511-G29).

Author

• Astrid Mager, Austrian Academy of Sciences