How will advanced AI systems impact democracy?
Reviewed by Pithpith:Y5DQDQO4open to challenge →
read the original abstract
Advanced AI systems capable of generating humanlike text and multimodal content are now widely available. In this paper, we discuss the impacts that generative artificial intelligence may have on democratic processes. We consider the consequences of AI for citizens' ability to make informed choices about political representatives and issues (epistemic impacts). We ask how AI might be used to destabilise or support democratic mechanisms like elections (material impacts). Finally, we discuss whether AI will strengthen or weaken democratic principles (foundational impacts). It is widely acknowledged that new AI systems could pose significant challenges for democracy. However, it has also been argued that generative AI offers new opportunities to educate and learn from citizens, strengthen public discourse, help people find common ground, and to reimagine how democracies might work better.
This paper has not been read by Pith yet.
Forward citations
Cited by 5 Pith papers
-
An Experimental Method to Study Opinion Diffusion in Human-AI Hybrid Societies
Hybrid human-AI networks in 5x5 grids reached lower final polarization than human-only networks after eight rounds of opinion revision on polarizing topics.
-
Exploring cooperation mechanisms via reinforcement learning in network common-pool resource games
GNN-RL social planner in network CPR games achieves higher cooperation, more accumulated resources, and lower inequality than equal or proportional allocation baselines, with distilled mechanisms for regular and heter...
-
Exploring cooperation mechanisms via reinforcement learning in network common-pool resource games
A GNN-RL social planner in networked CPR games with overlapping pools achieves higher cooperation and lower inequality than baselines across four network topologies, distilled into resource-dependent and degree-condit...
-
Conversational AI increases political knowledge as effectively as self-directed internet search
Conversational AI matches self-directed internet search in increasing belief in true political information and decreasing belief in misinformation.
-
Learning with Conflicts of Interest
A game-theoretic framework and algorithms are introduced to maximize beneficial information from ML systems while minimizing biased influences arising from conflicts of interest.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.