AI and the Future of Digital Public Squares (2412.09988v1)

Abstract: Two substantial technological advances have reshaped the public square in recent decades: first with the advent of the internet and second with the recent introduction of LLMs. LLMs offer opportunities for a paradigm shift towards more decentralized, participatory online spaces that can be used to facilitate deliberative dialogues at scale, but also create risks of exacerbating societal schisms. Here, we explore four applications of LLMs to improve digital public squares: collective dialogue systems, bridging systems, community moderation, and proof-of-humanity systems. Building on the input from over 70 civil society experts and technologists, we argue that LLMs both afford promising opportunities to shift the paradigm for conversations at scale and pose distinct risks for digital public squares. We lay out an agenda for future research and investments in AI that will strengthen digital public squares and safeguard against potential misuses of AI.

• The paper presents four key LLM applications—collective dialogue, bridging, community moderation, and proof-of-humanity—to enhance public digital interactions.
• It integrates insights from over 70 civil society experts to evaluate benefits and challenges in applying AI to democratize online discourse.
• The research calls for an interdisciplinary agenda focusing on ethical AI use, regulation, and continuous evaluation of user trust in digital spaces.

Overview of "AI and the Future of Digital Public Squares"

The paper primarily examines the implications of deploying LLMs for enhancing digital public squares. The research delineates four key applications of LLMs: collective dialogue systems, bridging systems, community moderation, and proof-of-humanity systems. The authors integrate insights from over 70 civil society experts to evaluate both opportunities and risks presented by LLMs in restructuring digital public interactions.

Digital Public Squares: Theoretical Foundations

The paper opens by contextualizing digital public squares within a historical framework that traces their evolution from physical public squares to online platforms. The authors incorporate theories from scholars like Jürgen Habermas and Hélène Landemore to illustrate how digital public spheres have increasingly democratized dialogue and community formation.

Applications and Potential of AI in Digital Public Squares

The authors explore various AI applications, underscoring how they can be transformative.

1. Collective Dialogue Systems (CDS): These systems aim to foster scalable, inclusive deliberations. By facilitating collective feedback, CDS can empower more direct public participation in decision-making processes. However, challenges such as deciphering meaning from data and maintaining cost-effectiveness remain barriers to widespread adoption.
2. Bridging Systems: Bridging systems emphasize promoting common ground and reducing polarization, primarily through algorithmic ethnicities of bridging signals. Platforms like Meta and X have shown measurable improvements by integrating bridging signals, although these systems carry risks such as potential misrepresentation or oversimplification of complex discussions.
3. Community-driven Moderation: Here, the focus is on allowing online communities to moderate content effectively, aided by AI-enhanced tools to alleviate moderator workload, including burnout and exposure to harmful content. The potential for AI to contribute to moderation processes is balanced against concerns including community trust and biases inherent in automated systems.
4. Proof-of-Humanity Systems: The paper details the challenges in distinguishing humans from bots in increasingly AI-dominated spaces. Proof-of-humanity systems are proposed as a potential solution, albeit with considerations to safeguard privacy, ensure security, and prevent discrimination.

Implications and Future Directions

The authors argue that meaningful engagement on digital platforms can be supported through advancing AI technologies, which could result in more dynamic, participatory digital public squares. However, they warn of inherent risks such as misinformation, privacy breaches, and algorithmic biases. They propose a structured research agenda that includes interdisciplinary exploration, regulation for ethical AI use, and open-source resource development. They stress the importance of continuous assessment of user trust dynamics to facilitate AI's integration without unduly compromising traditional human-centric dialogues in public spaces.

Conclusion

In sum, the paper offers a detailed exploration of how LLMs, through strategic deployment, can significantly influence the architecture of digital public squares. While the integration of AI tools promises to enhance inclusivity and reduce polarization, it also necessitates careful design and regulation to mitigate risks associated with AI deployments. The authors make a trenchant case for continued research and dialogue among technologists, policymakers, and civil society to responsibly harness AI's potential in enhancing democratic discourse.