The Two-Lane Road to Hell Is Paved with Good Intentions: Why an All-or-None Approach to Generative AI, Integrity, and Assessment Is Insupportable

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Bibliographic Details
Title: The Two-Lane Road to Hell Is Paved with Good Intentions: Why an All-or-None Approach to Generative AI, Integrity, and Assessment Is Insupportable
Language: English
Authors: Guy J. Curtis (ORCID 0000-0002-4174-6955)
Source: Higher Education Research and Development. 2025 44(8):2151-2158.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 8
Publication Date: 2025
Document Type: Journal Articles
Reports - Evaluative
Education Level: Higher Education
Postsecondary Education
Descriptors: Artificial Intelligence, Technology Uses in Education, Integrity, Higher Education, Educational Assessment, Cheating, Academic Achievement
DOI: 10.1080/07294360.2025.2476516
ISSN: 0729-4360
1469-8366
Abstract: A 'two-lane' (All-or-None) approach to the use of generative artificial intelligence (genAI) is the idea that there should be two categories of assessments in higher education--Lane 1/None: where the use of genAI is prohibited, and Lane 2/All: where "any" use of genAI is permitted. This idea has been thoughtfully detailed and continues to be debated. Although this idea is generally well-intentioned, in this comment piece I argue that, if implemented, it will promote an impoverished approach to education and educational assessment. One argument often invoked in favour of an All-or-None approach is that genAI use may sometimes be undetectable. Contract cheating (e.g., students outsourcing assessments to ghostwriters) is sometimes undetectable, yet an argument that there should be an All-or-None approach permitting contract cheating in some assessments is clearly absurd. An All-or-None approach to genAI and assessment is also absurd. A middle lane, where genAI use in assessments is allowed with some limitations, is essential.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1503562
Database: ERIC
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