In this Substack post back in March, Andy Hall made the case for generative AI to create 'political superintelligence':
The more I work with and study AI, the more I believe it can give every human being on the planet access to a sort of political superintelligence, if we shape it right. And that intelligence, in turn, can make governments smarter and more effective, representatives more faithful, and institutions more responsive than anything we’ve built in over 2,000 years of experimenting with democracy.
Hall's post is worth reading in its entirety, but I want to explore a related point - will generative AI mean the end of rational ignorance for voters? Rational ignorance is the idea that it may be better for voters to not know what decisions policymakers are making on their behalf. That's because it's costly (in terms of time and effort) for voters to keep track of how the decisions that policymakers (and politicians) make on their behalf will affect them (economists call those monitoring costs). The benefit that a voter would receive by becoming informed of what policymakers (and politicians) are doing is relatively small, because their ability to change an election (and therefore policy) is very small. When the monitoring costs are greater than the benefits of being better informed, then voters would be better off not paying the monitoring costs. That is, voters would be better off not paying attention to what the policymakers (and politicians) are doing - the voters would be better off remaining rationally ignorant. This theory of rational ignorance was introduced in the 1950s by the late economist Anthony Downs.
Where does generative AI fit into this? Generative AI could meaningfully lower the monitoring costs for voters, as it gives the opportunity for voters to ask for quick summaries of policy proposals that may affect them. This will be even more effective as generative AI understands more about users' preferences. Moreover, agentic AI offers voters even greater opportunity to investigate what policymakers (and politicians) are doing, at relatively low cost.
When the monitoring costs decrease, then the rationale for voters to remain rationally ignorant weakens. We might expect voters to become more engaged with what the government is doing on their behalf, and to be more active in engaging with government to make their preferences known. Or, at least, maybe voters will delegate these activities to their favourite agentic AI model.
There are, of course, some reasons for caution. Generative AI might reduce the cost of obtaining political information without reducing the cost of checking whether that information is accurate or unbiased. Moreover, an overly sycophantic generative AI that knows the voter's preferences might reinforce the voter's existing views rather than challenging them. So, perhaps generative AI simply moves the monitoring costs from monitoring the government to monitoring the generative AI?
Hall makes the point that political superintelligence has the potential to increase the quality of governance. If generative AI enables voters to become better informed at low cost, it could strengthen political accountability. Policymakers (and politicians) who know that voters can easily scrutinise their decisions may be less willing to act against voters’ interests, or may face greater consequences when they do.
We may not have political superintelligence yet, and large numbers of voters may still be rationally ignorant. However, it may not be long before we start to see some substantive changes in the political process, driven in part by the emergence of generative AI.
[HT: Marginal Revolution for the Andy Hall post]