*Artificial Intelligence and Academic Professions * American Association of University Professors https://www.aaup.org/reports-publications/aaup-policies-reports/topical-repo... Executive Summary Educational technology, or /ed-tech/, including artificial intelligence (AI), continues to become more integrated into teaching and research in higher education, with minimal oversight. The AAUP’s ad hoc Committee on Artificial Intelligence and Academic Professions—composed of higher education faculty members, staff, and scholars interested in technology and its impact on academic labor—was formed under the assumption that faculty members are best positioned to understand and improve teaching and learning conditions, including the development and implementation of institutional policies around educational technology. To learn more about the experiences and priorities of AAUP members, the committee conducted a survey with a sample of five hundred members from nearly two hundred campuses across the country, collected during a two-week time period. Respondents emphasized the importance of improving education on AI, promoting shared governance through policies and oversight, and focusing on equity, transparency, and worker protections. Based on those responses, the committee identified the five key concerns listed below and described more fully in the findings section of this report. 1. Improving Professional Development Regarding AI and Technology Harms * Despite the widespread use of ed-tech, there is an overall lack of understanding about the relationship between AI and commonly used data-intensive educational technologies. * Untested and unproven technologies are adopted uncritically 2. Implementing Shared Governance Policies to Promote Oversight * AI integration initiatives are spearheaded by administrations with little input from faculty members and other campus community members, including staff and students. * High levels of concern arose around AI and technology procurement, deployment, and use; dehumanized relations; and poor working and learning conditions. 3. Improving Working and Learning Conditions * Preexisting work intensification and devaluation are the main reasons respondents give for using AI to assist with academic tasks. * Implementing AI in higher education adds to faculty and staff workloads and exacerbates long-standing inequities. * AI raises concerns around bias, discrimination, and accessibility because of the untested and uneven impacts on students and student learning. 4. Demanding Transparency and the Ability to Opt Out * Faculty members and staff lack choice and meaningful avenues to opt out of both AI-based tools and other ed-tech. * Few institutions have created transparent, equitable policies or provided effective professional development opportunities on AI use. 5. Protecting Faculty Members and Other Academic Workers * Academic workers across job categories are worried about increased reliance on contingent appointments and declining wages. * Respondents expressed concern about academic freedom and intellectual property rights. The report provides details on the survey’s findings about these concerns and addresses them with recommendations to improve higher education—both broadly and narrowly as it relates to emerging technologies. Faculty members can work to implement these recommendations on their campuses by incorporating guidelines in faculty handbooks and collective bargaining agreements. The recommendations can inform strategy for organizing and policymaking related to AI in higher education institutions and organized labor more generally. The ad hoc Committee on Artificial Intelligence and Academic Professions has provided a resource guide <https://docs.google.com/document/d/1O9XBMSMXxrdtN102xn7gQmJqew_dbFatY0d1CJLD...> to help members implement the recommendations of this report.