It re-produces society and its power structures: the ‘who builds it’ gets to decide ‘for what’ and ‘how’. AI impacts our democratic processes, power dynamics, human interactions, and societal structures. This is what people refer to when they say that AI is ‘political’.
AI will definitely shape our far-off future but it’s also already shaping our society today. Having regulation is crucial, but we must also shape innovation to match our aspirations. To succeed, it is crucial to understand the nature of this technology.
It seems easy to make the argument that AI is a transformative technology, and that it inevitably triggers change. It will (and does) change the way we manufacture products, diagnose diseases, undertake creative work, as well as how we receive information and which pieces of information we get to see.
Such an AI-led transformation would come at just the right time – our society is in dire need of it. We’re due to miss all international climate goals, authoritarianism is on the rise, and violent conflicts seem ubiquitous. In the midst of all these crises, we find remarkable strides in AI development and we place great hope in it.
When we dream about AI’s transformative power we overlook though that AI is the product of a specific context and specific communities (poleis). The philosophy of technology teaches us that ‘technology is society made durable.’
AI is no exception.
It re-produces society and its power structures: the ‘who builds it’ gets to decide ‘for what’ and ‘how’. AI impacts our democratic processes, power dynamics, human interactions, and societal structures. This is what people refer to when they say that AI is ‘political’.
AI also creates durability in another way. For example, many AI systems build on the classification of objects (including people). Researchers point out that the act of classification creates categories and maintains them over time by making objects fit these categories rather than allowing for diversity or discontinuity. Today’s AI systems use past data to learn patterns and predict answers based on such classifications. By building on past data, they are firstly conducive to path dependency, i.e. durability; and secondly, depending on which past data are used, a ‘specific past’ and present can be perpetuated.
Since AI is political and has this durability effect, it’s important to keep whatever becomes durable in check. We should use the durability effect as a lever to work towards goals such as sustainability, equality, and justice.
When we look more deeply at ‘AI for what’, ‘AI by whom’, and ‘AI for who’, we come to fully understand that AI is political and requires political will and action to make it the transformative technology we need. We should take this to heart when shaping the European approach to excellence in AI....
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