Philosopher and writer Simone Weil laid out a few principles on automation in her fascinating and often difficult book Need for Roots. Her view as positive, and she noted that among workers in factories the happiest ones seemed to be the ones that worked with machines. She had strict views on the design of these machines however, and her views can be summarized in three general principles.

First, these tools of automation need to be safe. Safety comes first, and should also be weighed when thinking about what to automate first – the idea that automation can be used to protect workers is an obvious, but sometimes neglected one.

Second, the tools of automation need to be general purpose. This is an interesting principle, and one that is not immediately obvious. Weil felt that this was important – when it came to factories – because they could then be repurposed for new social needs, and respond to changing social circumstances – most pressingly, and in her time acute, war.

Third, the machine needs to be designed so that it is used and operated by man. The idea that you would substitute man by machine she found ridiculous for several reasons, but not least because we need to work to finds purpose and meaning, and any design that eliminates us from the process of work would be socially detrimental.

All Weil’s principles are applicable and up for debate in our time. I think the safety principle is fairly accepted, but we should not that she speaks of individual safety and not our collective safety. In the cases where technology for automation could pose a challenge for broader safety concerns in different ways, Weil does not provide us with a direct answer. This need not be apocalyptic scenarios at all, but could simply be questions of systemic failures of connected automation technologies, for example. Systemic safety, individual safety, social safety are all interesting dimensions to explore here – are silicon / carbon hybrid models always safer, more robust, more resilient?

The idea about general purpose and easy to repurpose is something that I think reflects how we have seen 3d printing evolve. One idea of 3D-printing is exactly this, that we get generic factories that can manufacture anything. But the other observation that is close at hand here is that you could imagine Weil’s principle as an argument for general artificial intelligence. It should be admitted that this is taking it very far, but there is something to that, and it is that a general AI & ML model can be broadly and widely taught and we would avoid narrow guild experts emerging in our industries. That would, in turn, allow for quick learning and evolution as these technologies, needs and circumstances change. General purpose technologies for automation would allow for us to change and adapt faster to new ideas, challenges and selection pressures – and would serve us well in a quickly changing environment.

The last point is one that we will need to examine closely. Should we consider it a design imperative to design for complementarity rather than substitution? There are strong arguments for this, not least cost arguments. Any analysis of a process that we want to automate will yield a silicon – carbon cost function that gives us to cost of the process as different parts of it are performed by machines and humans. A hypothesis would be that for most processes this equation will see a distribution across the two and only for very few will we see a cost equation where the human component is zeroed out. Not least because human intelligence is produced at extraordinarily low energy cost and with great resilience. There is even a risk mitigation strategy argument here — you could argue that always including a human element, or designing for complementarity, necessarily generates more resilient and robust systems as the failure paths of AIs and human intelligence look different and are triggered by different kinds of factors. If, for any system, you can allow for different failure triggers and paths, you seem to ensure that the system self-monitors effectively and reduces risk.

Weil’s focus on automation is also interesting. Today, in many policy discussions, we see the emergence of principles on AI. One could argue that this is technology-centric principle making, and that the application of ethical and philosophical principles suit the use of a technology better and that use-centric principles are more interesting. The use-case of automation is a broad one, admittedly, but an interesting one to test this on and see if salient differences emerge. How we choose to think about principles also force us to think about the way we test them. An interesting question is to compare with other technologies that have emerged historically. How would we think about principles on electricity, computation, steam — ? Or principles on automobiles and telephones and telegraphs? Where do we effectively place principles to construct normative landscapes that benefit us as a society? Principles for driving, for communicating, for selling electricity (and using it and certifying devices etc (oh, we could actually have a long and interesting discussion about what it would mean to certify different ML models!)).

Finally, it is interesting also to think about the function of work from a moral cohesion standpoint. Weil argues that we have no rights but for the duties we assume. Work is a foundational duty that allows us to build those rights, we could add. There is a complicated and interesting argument here that ties rights to duties to human work in societies from a sociological standpoint. The discussions about universal basic income are often conducted in sociological isolation, not thinking about the network of social concepts tied up in work. If there is, as Weil assume, a connection between our work and duties and the rights a society upholds on an almost metaphysical level, we need to re-examine our assumptions here – and look carefully at complementarity design as a foundational social design imperative for just societies.

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