Conditions for the successful application of artificial intelligence (once more)

01/18/24 • 23 min

The successful application of artificial intelligence depends on a set of preconditions. Some are obvious. For example, to be successful AI needs to be able to access some digital representation of its environment, either through sensors mapping the world or through the input of existing data. Where these representations are difficult to come by or data are scarce, as in many areas of politics, AI will not be successful. Other preconditions are not so obvious. For example, for AI to produce helpful results, the underlying connections between inputs and outputs must be stable over time. This points to two problems: unobserved temporal shifts between variables and the dangers of relying on purely correlative evidence without support of causal models.More important still, especially with respect to democracy, is that normatively speaking the past must provide a useful template for the future. Change is a crucial feature of societies, especially the extension of rights and the participation of previously excluded groups. Over time, many societies strive to decrease discrimination and increase equality. In fact, many policies are consciously designed to break with past patterns of discrimination. AI-based predictions and classifications based on past patterns risk replicating systemic inequalities and even structural discrimination.Few problems in politics and in democracy more broadly share these characteristics. This limits the application of AI in society and, accordingly, its impact on democracy.
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Artificial intelligence and democracy (once more)

AI has become a pervasive presence in society. Recent technological advances have allowed for broad deployment of AI-based systems in many different areas of social, economic, and political life. In the process, AI has had - or is expected to have - a deep effect on each area it touches. We see examples in discussions about algorithmic shaping of digital communication environments and the associated deterioration of political discourse; the flooding of the public arena with false or misleading information enabled by generative AI; the future of work and AI’s role in replacement of jobs and related automation-driven unemployment; and AI’s impact on shifting the competitive balance between autocracies and democracies. With these developments, AI has also begun to touch on the very idea and practice of democracy.
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Artificial intelligence and self-rule (once more)

One tenet of democracy is that governments should be chosen by those they will serve. Such self-rule is a normative idea about legitimizing the temporal power of rulers over the ruled and a practical idea that distributed decision making is superior to other more centralized forms of decision making or rule by experts. AI impacts both the ability of people to achieve self-rule and the perceived superiority of distributed decision making over expert rule in complex social systems, highlighting potential limits to self-rule in several ways.
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