Student Reportedly Files Complaint Over Professor's Undisclosed Use of Generative AI at Northeastern University

A student at Northeastern University reportedly filed a complaint after discovering that a professor had used generative AI tools, including ChatGPT, to produce course materials despite university policies discouraging undisclosed AI use. The student alleged hypocrisy, citing a syllabus that barred unauthorized AI use by students. The professor acknowledged having used AI-generated materials and expressed regret over not reviewing them more carefully. No tuition refund was reportedly granted.

Risk classification

• Primary risk domain: 5 Human-Computer Interaction
• Primary risk subdomain: 5.1 Overreliance and unsafe use

The incident represents a clear case of human overreliance on AI systems, where professors trusted chatbots to perform tasks requiring human empathy, grading, and teaching expertise.

Additional risk subdomains

• 6.3 Economic and cultural devaluation of human effort: Students expressed that outsourcing instruction and feedback to AI devalues the human effort and connection they pay high tuition for, and raises concerns about disrupting the pipeline of future teaching assistants.

Causal factors

• Entity: Human
• Intent: Unintentional
• Timing: Post-deployment

The risk was caused by the human decision of professors to overrely on AI tools for grading and teaching, leading to an unexpected negative outcome of student backlash and loss of trust.

EU AI Act risk tier

• Risk tier: 2 High Risk

Risk Level 2: High Risk. The report describes AI being used in educational and vocational training systems, specifically for grading student essays and generating course materials, which directly affects student evaluation and access to education.

AI system and alleged parties

• AI system: ChatGPT, Gamma, Perplexity (Gamma, OpenAI, Perplexity AI)
• AI purpose: Writing Assistant; Automatic Skill Assessment
• Behaviour type: Assistant
• Alleged developer: Perplexity, OpenAI, Gamma.app
• Alleged deployer: Rick Arrowood
• Alleged harmed parties: Rick Arrowood, Northeastern University students, Northeastern University, Ella Stapleton

Harm severity

Severity ratings are based on this scale.

Highest direct severity in any category: Negligible. Severity is scored from Negligible to Catastrophic in each harm category, for harm the reports describe as caused directly or indirectly by the AI system.

• Physical: direct Negligible, indirect Negligible
• Infrastructure: direct Negligible, indirect Negligible
• Property: direct Negligible, indirect Negligible
• Financial: direct Negligible, indirect Negligible
• Environmental: direct Negligible, indirect Negligible
• Malicious content: direct Negligible, indirect Negligible
• Differential treatment: direct Negligible, indirect Negligible
• Civil rights: direct Negligible, indirect Negligible
• Democracy: direct Negligible, indirect Negligible
• Privacy: direct Negligible, indirect Negligible
• Psychological: direct Negligible, indirect Negligible
• Epistemic: direct Negligible, indirect Negligible
• Child sexual exploitation and abuse: direct Negligible, indirect Negligible

People affected

• Occurrences reported: 4
• People reportedly harmed: 2
• People reportedly exposed: 500

Potential causes

Management

• High Faculty Workloads: Heavy workloads pressured professors to use AI as a shortcut.
• Inadequate Faculty Training: Universities failed to train faculty on AI risks and limitations.
• Lack of Admin Accountability: Management failed to address student complaints with restitution.

Technology

• AI Hallucinations and Errors: AI generated distorted text, weird images, and errors in slides.
• Algorithmic Flaws in AI Tools: Chatbots outputted nonsensical or low-quality educational content.

Data Inputs

• Unvetted Prompting Inputs: Professors fed rubrics or raw topics to AI without refinement.

Human Factors

• Overreliance on AI Automation: Professors trusted AI outputs without reviewing them for accuracy.
• Lack of Human Oversight: Instructors failed to proofread slides or read student essays.
• Perceived Academic Hypocrisy: Professors banned student AI use while using it themselves.

Process and Methods

• No Disclosure of AI Use: Educators hid AI use in grading and course material creation.
• Inadequate Output Review Processes: Lack of verification steps before publishing AI-generated materials.
• Outsourcing Empathy to AI: Using AI for sensitive communications, causing student backlash.

Regulatory Environment

• Lagging Institutional AI Policies: Universities lacked clear rules on acceptable AI use for faculty.
• Inconsistent Integrity Rules: Rules restricted student AI use but ignored faculty AI usage.

Information quality

• Classification confidence: High
• Reason for confidence: The reports provide clear, detailed, and consistent accounts of multiple independent incidents of AI overreliance in higher education, including specific names, universities, and administrative responses.
• Ambiguities identified: The exact number of other students affected in the same classes is not specified.
• Alternative interpretations: Some might view this as a standard productivity tool dispute rather than an AI safety incident, but the systemic overreliance and ethical concerns justify the safety classification.

The incident involves university professors using generative AI tools for grading and course material generation without disclosure. While it highlights ethical concerns and student dissatisfaction regarding educational quality, it presents negligible national security implications across all assessed categories.

• Overall national security impact: Negligible
• Scope: Single nation
• Primary target: United States
• Alleged perpetrator: University faculty

Threat characteristics

• Imminence: Long-term. Represents an ongoing societal adaptation and policy challenge rather than an active national security crisis.
• Autonomy: Human-controlled. AI tools were used as assistants to generate materials, with humans retaining final control and responsibility for deployment.
• Novelty: Established threat. Overreliance on generative AI for writing and content creation is a well-documented and common phenomenon.

Impact by dimension

• Physical security: Negligible. No physical threat, kinetic attacks, or critical infrastructure impact indicated in the incident reports.
• Information security: Negligible. The incident involves educational administrative issues and does not represent an information warfare or intelligence compromise.
• Sovereignty: Negligible. The incident is confined to higher education administration and does not threaten state authority or core government functions.
• Economic security: Negligible. The incident concerns tuition disputes and educational quality, with no significant impact on strategic economic or technological security.
• Societal stability: Negligible. While students experienced dissatisfaction regarding course materials, it does not threaten large-scale societal stability or human rights.