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Messaging Maneuvers: Generating and Evaluating Strategic Counternarratives with Large Language Models
No full textAs Large Language Models (LLMs) become increasingly embedded in content moderation and public communication, their potential to both generate and evaluate strategic counterspeech demands close study. Our work introduces a novel pipeline for producing contextualized counterspeech aligned with the BEND maneuver taxonomy, and evaluates the quality and effectiveness of generated countermessages by using an LLM-as-a-judge guided by Tree-of-Thought prompting. We compare automated LLM-as-a-judge evaluations against human surveys grounded in cognitive science. We analyze their alignment across multiple dimensions that help us assess the overall persuasiveness of the BEND aligned counterspeech. LLM-as-a-judge and human feedback have strong alignment in particular to messages human raters find dismissive or distortive. This indicates the LLM-as-a-judge is well aligned for detecting manipulation, incoherence, and threatening behaviors. There is also significant perceived persuasiveness alignment for explanatory messages, which suggests that these types of messages have the potential to change people's attitudes and behaviors
Optimal Electricity Tariff Selection Considering Renewable Energy Sources, Electric Vehicles and Controllable Home Appliances
Get PDFThis paper investigates the capabilities of a decision support system for optimal electricity tariff selection considering renewable energy sources, electric vehicles, and controllable home appliances. The developed model is based on a standard mixed-integer linear programming (MILP) approach, which considers different scenarios for a typical smart home. The tariff selection strategy is applied over a selected week to reflect varying electricity tariffs in Portugal. The model accounts for time-variant energy consumption at a 15-minute resolution, consistent with smart meter recordings and real-world electricity pricing structures. The proposed system enables residential users to make informed decisions by optimizing electricity costs while considering the flexibility of energy resources within smart homes. By simulating various operational scenarios, the model demonstrates the effectiveness of MILP in identifying the most cost-efficient tariff plans under dynamic consumption patterns. The results highlight the potential for such a tool to support energy cost reduction, improve demand-side management, and contribute to smarter energy usage
Navigating the Digital Product Passport Landscape: From Implementation Challenges to Future Opportunities
Get PDFDigital Product Passports are a central instrument for enabling a digitized circular economy. They provide transparency over processes and life cycles. Almost every sector must deal with them as they become mandatory in the following years. Yet, they are still in their infancy. Much theoretical-conceptual work emerges while consolidating research, but it is still missing. We tackle this gap with a review of Digital Product Passports. We could identify eleven often-used technologies for data collection, curation, and sharing with the passports. Furthermore, we present several challenges clustered into nine categories ranging from conceptual challenges via the architecture to the operation and ecosystem aspects. Moreover, we close our study with six paths for future research
Between Stigma and Support: How Esports Students and Teachers Experience and Negotiate Societal and Parental Attitudes Towards Esports
Get PDFAlthough esports are gaining traction in formal education, their legitimacy remains contested. Previous research has explored institutional developments, but fewer studies have examined how legitimacy is experienced and negotiated by students and teachers. Through reflexive thematic analysis of interviews with twelve students and two teachers in a Norwegian upper secondary esports programme, we identified three key themes: ‘They care but don’t quite get it’ (parental attitudes), ‘If it were football, they’d clap’ (societal perceptions) and ‘We have to make it make sense’ (legitimation strategies). The study contributes to esports research by demonstrating how students and teachers strive to align esports with institutional and cultural norms and by identifying key equity concerns related to recognition, gendered access and the symbolic framing of esports as a meaningful activity
Is AI Agreement Reassuring? It Depends on What Patients Believe About AI
Get PDFPeople often consult online information when choosing a doctor prior to their first visit. As AI increasingly supports medical decision-making, we examined how incorporating an AI agreement cue in a doctor's online profile influences patients’ perceptions of credibility and their intention to visit. In a user study (N = 415), participants reviewed a doctor’s profile indicating 90% diagnostic agreement with either AI decision support systems or human experts. The results show that neither the AI nor the expert agreement cue significantly influences credibility perceptions or visit intention. However, among participants with low or moderate beliefs in the positive machine heuristic, or low beliefs in the negative machine heuristic, the AI agreement cue reduces perceived competence, trustworthiness, and intention to visit. These findings highlight how beliefs about AI shape user responses to the AI agreement cue and offer implications for effective self-presentation strategies for healthcare professionals collaborating with AI
Introduction to the Minitrack on Technological Advancements in Digital Collaboration with Generative AI and Large Language Models
Get PDFThe Dark Side of Biometric Technologies: How Shared Control of the Body Elicits Job Insecurity
Get PDFTechnological advancement is associated with job insecurity, which refers to threats to the stability and continuity of work. The recent emergence of biometric technologies, which can collect, store, and analyze physiological and behavioral human data, have led to a new form of managerial control over workers: shared control of the body. Biometric technologies have the potential to infringe upon human rights and elicit job insecurity, but the mechanisms through which this occurs are not well understood. In this conceptual paper, we propose three pathways of how shared control of the body elicits job insecurity. First, shared control of the body threatens job autonomy, which elicits job insecurity. Second, perceived creepiness mediates the relationship between shared control of the body and job insecurity. Finally, shared control of the body erodes inherent and meritocratic dignity, which elicits job insecurity. We contribute to scholarly discussions regarding technology agency, surveillance, and human wellbeing
