Artificial Intelligence and Academic Professions
American Association of University Professors
https://www.aaup.org/reports-publications/aaup-policies-reports/topical-reports/artificial-intelligence-and-academic
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 to help members implement the recommendations of this
report.