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Academics’ Weak(ening) Resistance to Generative AI: The Cause and Cost of Prestige?

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Academics’ Weak(ening) Resistance to Generative AI: The Cause and Cost of Prestige?

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Academics’ Weak(ening) Resistance to Generative AI: The Cause and Cost of Prestige? - Postdigital Science and Education

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The disruptive potential of generative AI (GenAI) tools to academic labour is potentially vast. Yet as we argue herein, such tools also represent a continuation of the inequities inherent to academia’s prestige economy and the intensified hierarchy and labour precarisation endemic to universities as prestige institutions. In a recent survey of n = 284 UK-based academics, reasons were put forward for avoiding GenAI tools. These responses surface concerns about automative technologies corrupting academic identity and inauthenticating scholarly practice; concerns that are salient to all who participate within and benefit from the work of scholarly communities. In discussion of these survey results, we explore ambivalence about whether GenAI tools expedite the acquisition or depletion of prestige demanded of academics, especially where GenAI tools are adopted to increase scholarly productivity. We also appraise whether, far from helping academics cope with a work climate of hyper-intensifcation, GenAI tools ultimately exacerbate their vulnerability, status-based peripheralisation, and self-estrangement.

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The Metacognitive Demands and Opportunities of Generative AI

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The Metacognitive Demands and Opportunities of Generative AI

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https://dl.acm.org/doi/10.1145/3613904.3642902

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What are the imperatives of the upside?

Ethan Mollick

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Large Language Model−Based Chatbot vs Surgeon-Generated Informed Consent Documentation for Common Procedures

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Large Language Model−Based Chatbot vs Surgeon-Generated Informed Consent Documentation for Common Procedures

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Hannah Decker, MD1; Karen Trang, MD1; Joel Ramirez, MD1; et al

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LLM-Based vs Surgeon-Generated Informed Consent for Common Procedures

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This cross-sectional study compares large language model−based chatbot- vs surgeon-generated information on the risks, benefits, and alternatives of surgical procedures.

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Evaluating faithfulness and content selection

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Evaluating faithfulness and content selection

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https://arxiv.org/pdf/2404.01261

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Published as a conference paper at COLM 2024

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Prompting Diverse Ideas: Increasing AI Idea Variance

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Prompting Diverse Ideas: Increasing AI Idea Variance

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Date Written: January 27, 2024

Abstract

Unlike routine tasks where consistency is prized, in creativity and innovation the goal is to
create a diverse set of ideas. This paper delves into the burgeoning interest in employing
Artificial Intelligence (AI) to enhance the productivity and quality of the idea generation process.
While previous studies have found that the average quality of AI ideas is quite high, prior
research also has pointed to the inability of AI-based brainstorming to create sufficient
dispersion of ideas, which limits novelty and the quality of the overall best idea. Our research
investigates methods to increase the dispersion in AI-generated ideas. Using GPT-4, we explore
the effect of different prompting methods on Cosine Similarity, the number of unique ideas, and
the speed with which the idea space gets exhausted. We do this in the domain of developing a
new product development for college students, priced under $50. In this context, we find that (1)
pools of ideas generated by GPT-4 with various plausible prompts are less diverse than ideas
generated by groups of human subjects (2) the diversity of AI generated ideas can be
substantially improved using prompt engineering (3) Chain-of-Thought (CoT) prompting leads to
the highest diversity of ideas of all prompts we evaluated and was able to come close to what is
achieved by groups of human subjects. It also was capable of generating the highest number of
unique ideas of any prompt we studied.

Keywords: innovation, idea generation, creativity, creative problem solving, LLM, large-scale language models, AI, artificial intelligence, ChatGPT, idea space, prompt engineering

Meincke, Lennart and Mollick, Ethan R. and Terwiesch, Christian, Prompting Diverse Ideas: Increasing AI Idea Variance (January 27, 2024). Available at SSRN: https://ssrn.com/abstract=

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prompting diverse ideas: increasing ai idea variance

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Prompting Diverse Ideas: Increasing AI Idea Variance

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Unlike routine tasks where consistency is prized, in creativity and innovation the goal is to create a diverse set of ideas. This paper delves into the burge

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Scan this QR code to see the full slideshow of this year-long PowerNotes Study!

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Scan this QR code to see the full slideshow of this year-long PowerNotes Study!

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AI Literacy Framework for Equity WRDS Student Success Grant: Funded

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AI Literacy Framework for Equity WRDS Student Success Grant: Funded

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Project Title: Toward AI Equity: Developing an Interdisciplinary AI Literacy Framework

Brief Description: The goal of this project is to create an Interdisciplinary AI Literacy Framework that addresses the inherent inequities in Gen AI. We will host focus groups with interdisciplinary faculty from across CHESS to capture data about their local or contextual AI Literacy frameworks, which may be formal or informal at this point.

Significance:  The significance of this project is both its scope and localized context. Our field has developed a beginning, and we would argue rudimentary, AI Literacy Guide for students. This guide is the closest we can find to an AI Literacy Framework. We recognize that every discipline has its own genres, goals, and outcomes, and we believe we can complicate our own notions of AI Literacy in important ways by creating dialogue and discourse around it with other disciplines. Because our participants will represent a broad swath of CHESS disciplinary perspectives, what we learn and create will be highly contextual to our college.  Again, the goal lies on our belief that, regardless of use and adoption, students and faculty should be aware of the impact these tools have had and are having throughout academic disciplines, discourse and professional sectors, and by collecting data from faculty across disciplines we can begin to understand how to address, at a foundational literacy level, how to equip students with the AI literacy skills they need to critically navigate GenAI contexts.

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The AI Literacy Frame: A Framework in Progress

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The AI Literacy Frame: A Framework in Progress

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In Fall 2024, after spending a year with AI in first-year writing, the need to create an Interdisciplinary AI Literacy framework is more prescient than ever. This framework addresses the ethical, ecological, critical thinking, collaborative, transparent and humanistic needs of students, faculty and administrators before arriving at the threshold of AI use.

Equipping users with necessary AI Literacy will address the growing equity disparity among AI users; access to tools like CoPilot, Gemini, ChatGPT and other platforms does not necessarily mean equitability among these platforms usage. To use an analogy; giving someone the keys to a car before teaching them to drive the car does not mean everyone will be capable of driving the car in the same way.

Creating an AI Literacy Framework by speaking with educators, students, and administrators from multiple disciplines will provide the necessary language and Interdisciplinary expertise to articulate values, habits and outcomes to equip users with the required AI Literacy to engage and succeed in an increasingly AI driving culture and society. The key here is to do this from humanities lens; ensuring the crucial role of thinking, communication, process, and the human skills offered by programs like Writing Studies Departments and other humanities programs are at the heart of this work.

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Summer 2024: Charlotte Adopts CoPilot and all Niners obtain full access to CoPilot AI

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Summer 2024: Charlotte Adopts CoPilot and all Niners obtain full access to CoPilot AI

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Charlotte formally adopts Microsoft CoPilot as our University's AI platform. Based on data collected during the Pilot and this decision, the team's thinking begins shifting to AI Literacy and the need for equitable frameworks for AI use, underscoring the need for increased collaboration around AI, AI Literacy, Interdisciplinarity and Equity beyond access.

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PowerNotes Pilot Launch: An Ethical Foundation 

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PowerNotes Pilot Launch: An Ethical Foundation 

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Why PowerNotes?

Student Privacy

PowerNotes does not share personal data with OpenAI

Support

PowerNote Support Staff dedicated to our Pilot

Equitable Access

All Students in the Pilot would have access to the same and most up to date version of ChatGPT

Pedagogical Goals

Emphasis on critical reading skills, research skills, ethical, transparent and collaborative use of AI Tools.

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Trends Continued in Spring 2024

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The quantitative data about how students were using the AI Tools in FYW provided valuable insights into the integration of AI Tools into all aspects of students' unique, self-determined writing processes. The "Glass Walls" of AI Use proved invaluable as students incorporated AI into brainstorming, research, ideation, peer review and other aspects of writing while continually acknowledging the ways they were using the tools transparently instead of secretly.

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Hallways Leading Room to Room: Collaboration and Interdisciplinarity

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Hallways Leading Room to Room: Collaboration and Interdisciplinarity

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A key piece of the Literacy Framework: Using AI Tools Transparently and Collaboratively; like building with glass walls in order to see inside process and thinking.

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Visit Charlotte’s Center for Teaching and Learning for more AI resources!-2