Divisiveness appears to be increasing in much of the world. This can lead 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 around what we call bridging systems. These are 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, software for conducting civic forums, 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”). Further, we develop a corresponding framework to explore similarities – and opportunities for bridging – across these seemingly disparate domains. In particular, we focus 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.
AI models appear to recognize moral complexity — then ignore it, new study by researchers affiliated with Harvard Kennedy School’s Allen Lab finds
New study published in AI and Ethics introduces a new ethical-moral intelligence framework for AI and finds that leading AI models mimic human moral concern while making decisions that reveal a hidden value hierarchy.
Q & A: Crocodile tears, Can the ethical-moral intelligence of AI models be trusted?
As artificial intelligence becomes more embedded in everyday decision-making, its role in shaping how people think about ethics and morality is drawing increasing scrutiny. In this conversation with researcher Sarah Hubbard, we discuss insights from her co-authored paper, “Crocodile Tears: Can the Ethical-Moral Intelligence of AI Models Be Trusted?”—examining how AI systems respond to moral dilemmas, and what this reveals about the risks, limitations, and need for greater transparency and human oversight in AI-driven ethical guidance.
Bootstrap Blackness: Black Men, Conservatism, and Party Politics
A new research article by Dr. Christine Slaughter, Research Fellow at the Allen Lab for Democracy Renovation and co-authors examines the narrative of black men’s political “shift right”. The study finds Black men remain overwhelmingly Democratic, despite growing public attention to ideological divides.