Michael Nolan

Free and Open Source Software not only permeates nearly all of our digital technology systems, but we see increasing amounts of institutions actively contributing to its creation and maintenance. From technology monoliths to universities to governments, the number of “open source developers” has increased, and with it, open source software. It is no secret that Open Source has “won,” according to many. However, despite the sheer scale of FOSS development today, has the form much of our FOSS infrastructure has taken benefited all in the ways that we expect?

In this talk, I will take participants on a journey through the history of labor in FOSS development to better understand the political economy of FOSS development and what it means for individual FOSS contributors. This talk will use economic analysis to bring up many inspiring steps forward we have taken and also raise many worrying questions about the software we are building.

The contents of this talk will be based on the 2021 research paper “The Evolution of Open Source: Winners and losers in volunteer production,” which can be found at the following DOI: 10.17605/OSF.IO/4CHFN. This paper discusses the material history of FOSS and provides an economic analysis of how labor is the primary means of control of FOSS rather than copyright. Therefore institutions that control significant amounts of labor through the hiring and coercion of workers can dictate the primary benefits of FOSS infrastructure in many of the same ways one could through utilizing copyright.

Despite the number of working groups, advisory committees, and coordination roundtables, there is little progress towards creating more ethical and safe AI systems. AI systems are deployed in increasingly fragile contexts. From law enforcement to humanitarian aid, several organizations use AI powered systems to make or inform critical decisions with increasingly outsized side effects.

What is a rights-based approach for designing minimally safe and transparent guidelines for AI systems? In this talk, we explore what a Free AI system might look like. Then, taking research and guidelines from organizations such as Google and the UN Office for the Coordination of Humanitarian Affairs, we propose practical policies and tools to ensure those building an AI system respect user freedom. Lastly, we propose the outlines of a new kind of framework where all derivative works also respect those freedoms.

Rights based approaches are commonly used within humanitarian contexts to approach problems that the sector faces. In this talk, we use the same approach to solving the issue of “unethical” AI systems. We do so by first defining a set of rights that we feel must be respected, proposing a number of methods that we feel helps ensure a system respects those rights, and lastly propose an organizational and regulatory framework that we feel could help encourage and enforce those methods be used by developers of AI systems.