Raiding the inarticulate since 2010

accelerated academy acceleration agency AI Algorithmic Authoritarianism and Digital Repression archer Archive Archiving artificial intelligence automation Becoming Who We Are Between Post-Capitalism and Techno-Fascism big data blogging capitalism ChatGPT claude Cognitive Triage: Practice, Culture and Strategies Communicative Escalation and Cultural Abundance: How Do We Cope? Corporate Culture, Elites and Their Self-Understandings craft creativity critical realism data science Defensive Elites Digital Capitalism and Digital Social Science Digital Distraction, Personal Agency and The Reflexive Imperative Digital Elections, Party Politics and Diplomacy digital elites Digital Inequalities Digital Social Science Digital Sociology digital sociology Digital Universities elites Fragile Movements and Their Politics Cultures generative AI higher education Interested labour Lacan Listening LLMs margaret archer Organising personal morphogenesis Philosophy of Technology platform capitalism platforms Post-Democracy, Depoliticisation and Technocracy post-truth psychoanalysis public engagement public sociology publishing Reading realism reflexivity scholarship sexuality Shadow Mobilization, Astroturfing and Manipulation Social Media Social Media for Academics social media for academics social ontology social theory sociology technology The Content Ecosystem The Intensification of Work theory The Political Economy of Digital Capitalism The Technological History of Digital Capitalism Thinking trump twitter Uncategorized work writing zizek

📣 Generative AI for Academics: coming from Sage later this year

This is your indispensable guide to navigating the rise of generative AI as an academic. It thoughtfully explores rapidly evolving AI capabilities reshaping higher education, examining challenges and ethical dilemmas across the sector.

It provides useful strategies for using generative AI in your scholarly work while upholding professional standards. This practical guidance addresses four core areas of academic work:

Thinking: How to use generative AI to augment individual and collaborative scholarly thinking that can assist in developing novel ideas and advancing impactful projects
 
Collaborating: Explore how generative AI can be used as a research assistant, coordinating teams and enhancing scholarly cooperation

Communicating: Cautioning against over-reliance, examine how generative AI can relieve communication burdens while maintaining professionalism and etiquette
 
Engaging: thoughtful and practical frameworks are offered for using these developments to support online engagement without sacrificing scholarly principles

Mark Carrigan is a digital sociologist, author and Lecturer in Education at the University of Manchester.