*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
<https://docs.google.com/document/d/1O9XBMSMXxrdtN102xn7gQmJqew_dbFatY0d1CJLDGPY/edit?tab=t.0>
to help members implement the recommendations of this report.
