Article with Sami Mahroum: “In my experimentation with AI-augmented policy analysis for government clients, I have found that these systems excel at what I call “sentiment-aware policy design.” While traditional tools might show that a congestion charge reduces traffic by 22%, AI systems can remind you that the term “congestion charge” polls substantially worse than “clean-air fee”; that implementation during election years multiplies political risk; and that exempting delivery vehicles creates coalition-building possibilities with small-business groups.
The point isn’t to replace human judgment. It is to make experienced insiders’ implicit political knowledge more explicit, systematic, and testable. With AI, the abstract-rationality crowd gets quantitative rigor, the bounded-rationality practitioners get political intelligence, and – crucially – both can see the other’s perspective clearly.
Moreover, when combined with web-search capabilities, AI tools can contribute near-real-time sentiment analysis. This matters because policies designed to address last quarter’s concerns might no longer fit the political terrain when they launch in the coming quarter. By the time a pension reform reaches parliament, murmurs of a recession may have changed voters’ priorities entirely.
AI-powered analysis can reveal how specific issues are being discussed across news, social media, parliamentary debates, stakeholder communications, and other channels. It can identify rising concerns and flag when a window of political opportunity has opened or closed. Such insights can help governments counter the perception that they are slow, deaf, and disconnected from everyday realities. AI cannot make governments omniscient, but it can make them more responsive and less blind to the political consequences of technical decisions.
The high-trust technocracies succeed partly because they have systematized the integration of technical excellence with political responsiveness. Now, AI offers democracies the means to do so as well…(More)”.
