I attended PoliticalTech Summit 25 in Berlin. One of the speakers was Beth Goldberg and what she said led me to dig a bit deeper; here are my notes and links. …
Firstly the videos of here session are not yet available so I had to make do.
Here’s what made me sit up, I paraphrase, the drive for revenue leads to the social media companies encouraging dissent and abuse. It can be better than that!
Links
- AI and the Future of Digital Public Squares by Goldberg and [many] others (Goldberg, Acosta-Navas & Bakker 2024). See the page at the Cornell Archives for full citation inc. abstract. She signposted the paper in an article on Linkedin and preceded this with another article on Linkedin suggesting better was possible.
- In her Berlin speech, she made much of “Bridging” and the Goldberg, Acosta-Navas & Bakker 2024 references, Bridging Systems: Open Problems for Countering Destructive Divisiveness across Ranking, Recommenders, and Governance , by Aviv Ovadya, Luke Thorburn also at the Cornell Archives
- And Google Jigsaw, announce their incorporation of such principles into Google AI Perspectives on their Medium blog.
This is an extract from her linkedin article, which is a pretty effective summary,
We agreed there is vast, unrealized potential for the internet to democratize decision making and meaningful participation. We zeroed in on four ways LLMs and #genAI pose a paradigm shift for our digital public squares that could serve – or further imperil – more pluralistic societies:
- 🌐 Collective Dialogue Systems apply deliberative tech that enable people to express themselves and deliberate collectively, simplifying how we can solicit collective intelligence and find common ground.
- 📱Bridging Systems in public squares can change today’s incentive structures that reward moral outrage, redesigning to promote connection and understanding between people with different views and identities.
- 👋 Community-driven moderation affords communities the customizable tools to tailor moderation to their own needs.
- 🤖 Proof-of-Humanity Systems are critical for more sophisticated, adaptive ways to distinguish between humans and bots.
The abstract for Ovadya, Thorburn says, offering a definition of “Bridging”, italics are mine,
“Divisiveness appears to be increasing in much of the world, leading to concern about political violence and a decreasing capacity to collaboratively address large-scale societal challenges. In this working paper we aim to articulate an interdisciplinary research and practice area focused on what we call bridging systems: systems which increase mutual understanding and trust across divides, creating space for productive conflict, deliberation, or cooperation. We give examples of bridging systems across three domains: recommender systems on social media, collective response systems, and human-facilitated group deliberation. We argue that these examples can be more meaningfully understood as processes for attention-allocation (as opposed to “content distribution” or “amplification”) and develop a corresponding framework to explore similarities – and opportunities for bridging – across these seemingly disparate domains. We focus particularly on the potential of bridging-based ranking to bring the benefits of offline bridging into spaces which are already governed by algorithms. Throughout, we suggest research directions that could improve our capacity to incorporate bridging into a world increasingly mediated by algorithms and artificial intelligence.