SHAPE: A Framework for Evaluating the Ethicality of Influence

Agents often exert influence when interacting with humans and non-human agents. However, the ethical status of such influence is often unclear. In this paper, we present the SHAPE framework, which lists reasons why influence may be unethical. We draw on literature from descriptive and moral philosophy and connect it to machine learning to help guide ethical considerations when developing algorithms with potential influence. Lastly, we explore mechanisms for governing algorithmic systems that influence people, inspired by mechanisms used in journalism, human subject research, and advertising.Comment: An earlier version of this paper was accepted at EUMAS 202

Can Large Language Models Understand Argument Schemes?

Argument schemes represent stereotypical patterns of reasoning that occur in everyday arguments. However, despite their usefulness, argument scheme classification, that is classifying natural language arguments according to the schemes they are instances of, is an under-explored task in NLP. In this paper, we present a systematic evaluation of large language models (LLMs) for classifying argument schemes based on Walton’s taxonomy. We experiment with seven LLMs in zero-shot, few-shot, and chain-of-thought prompting, and explore two strategies to enhance task instructions: employing formal definitions and LLM-generated descriptions. Our analysis on both manually annotated and automatically generated arguments, including enthymemes, indicates that while larger models exhibit satisfactory performance in identifying argument schemes, challenges remain for smaller models. Our work offers the first comprehensive assessment of LLMs in identifying argument schemes, and provides insights for advancing reasoning capabilities in computational argumentation

Towards Dialogues for Joint Human-AI Reasoning and Value Alignment

We argue that enabling human-AI dialogue, purposed to support joint reasoning (i.e., 'inquiry'), is important for ensuring that AI decision making is aligned with human values and preferences. In particular, we point to logic-based models of argumentation and dialogue, and suggest that the traditional focus on persuasion dialogues be replaced by a focus on inquiry dialogues, and the distinct challenges that joint inquiry raises. Given recent dramatic advances in the performance of large language models (LLMs), and the anticipated increase in their use for decision making, we provide a roadmap for research into inquiry dialogues for supporting joint human-LLM reasoning tasks that are ethically salient, and that thereby require that decisions are value aligned

Online Handbook of Argumentation for AI: Volume 4

This volume contains revised versions of the papers selected for the fourth volume of the Online Handbook of Argumentation for AI (OHAAI). Previously, formal theories of argument and argument interaction have been proposed and studied, and this has led to the more recent study of computational models of argument. Argumentation, as a field within artificial intelligence (AI), is highly relevant for researchers interested in symbolic representations of knowledge and defeasible reasoning. The purpose of this handbook is to provide an open access and curated anthology for the argumentation research community. OHAAI is designed to serve as a research hub to keep track of the latest and upcoming PhD-driven research on the theory and application of argumentation in all areas related to AI

Online Handbook of Argumentation for AI: Volume 3

Editors: Federico Castagna, Francesca Mosca, Jack Mumford, Stefan Sarkadi and Andreas Xydis.This volume contains revised versions of the papers selected for the third volume of the Online Handbook of Argumentation for AI (OHAAI). Previously, formal theories of argument and argument interaction have been proposed and studied, and this has led to the more recent study of computational models of argument. Argumentation, as a field within artificial intelligence (AI), is highly relevant for researchers interested in symbolic representations of knowledge and defeasible reasoning. The purpose of this handbook is to provide an open access and curated anthology for the argumentation research community. OHAAI is designed to serve as a research hub to keep track of the latest and upcoming PhD-driven research on the theory and application of argumentation in all areas related to AI

Etudes des caracteristiques cristallographiques, thermodynamiques et microstructurales des produits de dehydratation du gypse

Available from INIST (FR), Document Supply Service, under shelf-number : T 80277 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueSIGLEFRFranc

Building premium commodity brands : an exploratory study of New World fine wine

The research explored how the four marketing!mix!elements!namely!product,!price,!promotion!and! place,!can!be!used!to!position!premium!commodity!brands!in!such!a!way!that!it!stimulates!regional! competitiveness!and!business!growth!for!producers!and!marketers!operating!globally.!!The!study! specifically!focussed!on!fine!wine!as!a!premium!commodity.!!Factors!such!as!product!innovation,! place!of!origin,!pricing!strategies,!promotional!activities!and!channel!management!and!distribution! were!considered!as!part!of!an!integrated!marketing!strategy.!! ! Eighteen! respondents,! including!wine! industry!experts,!wine!producers!and!wine!marketers! from! four!New!World!wine! producing! countries,!South!Africa,!Australia,!New!Zealand! and! the!United! States of America (USA) formed part of the qualitative study. The research and associated model aimed to identify a link between brand positioning strategies (as related to the marketing mix), brand knowledge and brand equity. It was found that making fine wine accessible to its target market and having relationships with key players in the industry are the most relevant factors in building strong New World fine wine brands that can compete effectively in the global fine wine market. To illustrate these findings the research project concluded with a conceptual framework based on the Dimensions of Brand Knowledge(Keller,1993).Mini-disseration (MBA)--University of Pretoria, 2015.nk2016Gordon Institute of Business Science (GIBS)MBAUnrestricte