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Risk and Harm: Unpacking Ideologies in the AI Discourse

We examine the ideological differences in the debate surrounding large language models (LLMs) and AI regulation, focusing on the contrasting positions of the Future of Life Institute (FLI) and the Distributed AI Research (DAIR) institute. The study employs a humanistic HCI methodology, applying narrative theory to HCI-related topics and analyzing the political differences between FLI and DAIR, as they are brought to bear on research on LLMs. Two conceptual lenses, “existential risk” and “ongoing harm,” are applied to reveal differing perspectives on AI's societal and cultural significance. Adopting a longtermist perspective, FLI prioritizes preventing existential risks, whereas DAIR emphasizes addressing ongoing harm and human rights violations. The analysis further discusses these organizations’ stances on risk priorities, AI regulation, and attribution of responsibility, ultimately revealing the diverse ideological underpinnings of the AI and LLMs debate. Our analysis highlights the need for more studies of longtermism's impact on vulnerable populations, and we urge HCI researchers to consider the subtle yet significant differences in the discourse on LLMs.

Unpacking social learning in planning: who learns what from whom?

Social learning is the process of exchanging and developing knowledge (including skills and experiences) through human interaction. This key planning process needs to be better understood, given the increase and variety of non-planners influencing planning processes. This article explores who learns what from whom through social learning in planning. We unpack social learning theoretically to be able to map it, and employ empirically-based storytelling to discuss its relevance to planning practice. We conclude that social learning can lead to positive and negative outcomes and provides a useful analytical lens to understand planning practices at the level of individuals.

Unpacking sign language interpreting as a social institution

Introduction to the Special Issue of the Journal on Translation and Interpreting Studies 17:3 (2022)

Unpacking Energy Needs

Unpacking value creation and value capture in collaborative networks for sustainability

Our study elucidates collaborative value creation and private value capture in collaborative networks in a context of sustainability. Collaborative networks that focus on innovative solutions for grand societal challenges are characterized by a multiplicity and diversity of actors that increase the complexity and coordination costs of collective action. These types of inter-organizational arrangements have underlying tensions as partners cooperate to create collaborative value and compete to capture or appropriate value on a private or organizational level, resulting in potential and actual value flows that are highly diffuse and uncertain among actors. We also observe that network participants capture value differentially, often citing the pro-social (e.g. community, belonging, importance) and extrinsic benefits of learning and reputation as valuable, but found it difficult to appropriate economic or social benefits from that value. Differential and asymmetric value appropriation among participants threatens continued network engagement and the potential collective value creation of collaborative networks. Our data indicates that networked value creation and capture requires maintaining resource complementarity and interdependency among network participants as the network evolves. We develop a framework to assess the relational value of collaborative networks and contribute to literature by unpacking the complexities of networked value creation and private value capture in collaborative networks for sustainability.

“Recovering” the political

In many European cities, urban experimentation is increasingly preferred as a method for testing and disseminating innovations that might ignite a transformation toward more sustainable cities. By both academics and practitioners, these experiments tend to be approached as relatively neutral initiatives through which plural urban stakeholders willfully collaborate, while their success is seen as above all dependent on effective management. For this reason, the political nature of urban experiments, in the sense that they entangle different and often contending stakeholders in their innovation processes, remains relatively unarticulated in both practice and the academic literature. Building on the urban experimentation literature and political theory, this conceptual paper argues that the depoliticization of experimental initiatives is especially problematic for unleashing their transformative potential, which requires revealing the existing power-relations and biases keeping the status-quo in place and negotiability of radical alternatives. From this perspective, the paper sketches out four ideal-typical trajectories for experiments as related to their (de)politicization; optimization, blind leap, antagonistic conflict and transformation. Bringing insights from political theory to bear on the urban experimentation literature, we proceed to hypothesize the implications of our ideal-types for urban experiments’ transformative capacities. The paper closes by presenting a future research and policy agenda.