Purportedly AI-Generated Papers Are Alleged to Have Manipulated Scopus Rankings in Top Philosophy Journals

Three reportedly fake journals published by Addleton Academic Publishers allegedly manipulated Scopus rankings by extensively cross-citing each other and using AI-generated papers filled with buzzwords. These journals, placed in the top 10 of Scopus's 2023 CiteScore philosophy list, reportedly featured fake authors, affiliations, and grant numbers, in turn allegedly pushing legitimate journals to lower tiers, affecting academic evaluations and awards.

Risk classification

• Primary risk domain: 4 Malicious actors
• Primary risk subdomain: 4.3 Fraud, scams, and targeted manipulation

The publishers and authors used AI systems to engage in academic fraud and cheating, generating fake papers to artificially boost journal rankings for personal and institutional advantage.

Additional risk subdomains

• 6.3 Economic and cultural devaluation of human effort: The flood of AI-generated papers displaced legitimate, human-authored journals in academic rankings, devaluing honest research effort.
• 3.2 Pollution of information ecosystem and loss of consensus reality: The academic literature database was polluted with automatically generated nonsense papers, undermining the integrity of scientific consensus.

Causal factors

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

The incident was caused by human actors who intentionally deployed AI text-generation tools to produce fake academic papers and game the Scopus ranking system.

EU AI Act risk tier

• Risk tier: 3 Limited Risk

Limited Risk: The report describes the use of AI to generate text and academic papers, which falls under transparency obligations for AI-generated content.

AI system and alleged parties

• AI system: unspecified
• AI purpose: Technical Text Generation; Writing Assistant
• Behaviour type: unknown
• Alleged developer: Fake publications, Auricle Global Society of Education and Research, Addleton Academic Publishers
• Alleged deployer: Fake publications, Auricle Global Society of Education and Research, Addleton Academic Publishers
• Alleged harmed parties: University job candidates, University hiring committees, University faculty, Scopus, Academic journals

Harm severity

Severity ratings are based on this scale.

Highest direct severity in any category: Minor. 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 Minor
• Environmental: direct Negligible, indirect Negligible
• Malicious content: direct Negligible, indirect Negligible
• Differential treatment: direct Minor, indirect Minor
• Civil rights: direct Negligible, indirect Negligible
• Democracy: direct Negligible, indirect Negligible
• Privacy: direct Negligible, indirect Negligible
• Psychological: direct Negligible, indirect Negligible
• Epistemic: direct Minor, indirect Substantial
• Child sexual exploitation and abuse: direct Negligible, indirect Negligible

Financial

Reported: The report does not explicitly quantify direct financial losses, but notes that the manipulated rankings affect academic awards and promotions.

Indirectly caused: Honest researchers may have lost out on financial awards or promotions due to their journals being pushed to lower tiers.

Inferred additional harm: Unquantified financial losses likely occurred for multiple academics globally who missed out on promotions or research grants due to distorted metrics.

Differential treatment

Reported: The report explicitly describes unfair outcomes where honest journals and researchers were pushed to lower evaluation tiers.

Directly caused: The ranking system unfairly penalized legitimate journals by ranking fake AI-generated journals higher.

Indirectly caused: Researchers publishing in legitimate journals received lower evaluation scores, affecting their career progression relative to others.

Epistemic

Reported: The report explicitly describes epistemic harm through the fabrication of academic papers, literature reviews, citations, and grant numbers.

Directly caused: Five journals published hundreds of AI-generated papers using templates and fake data, which were indexed in the Scopus database.

Indirectly caused: The integrity of the Scopus database and academic metrics was compromised, leading to a loss of trust in automated academic rankings.

Inferred additional harm: Other academic databases and fields may be similarly compromised by undetected AI-generated papers, eroding the shared truth of scientific literature.

People affected

• Occurrences reported: 1
• People reportedly harmed: 20
• People reportedly exposed: 20

Potential causes

Management

• Flawed Promotion Policies: Management prioritized quantitative metrics over qualitative research reviews.
• Negligent Editorial Oversight: Publishers failed to verify editorial board members, including dead scholars.

Technology

• Automated Paper Generation: AI tools were used to generate low-quality templated academic papers.
• Vulnerable Ranking Algorithms: Proprietary Scopus algorithms failed to detect artificial citation spikes.

Data Inputs

• Fake Author Affiliations: Fabricated institutions and domains were used to register fake authors.
• Coordinated Cross-Citations: Systematic cross-citing inflated citation metrics for Addleton journals.
• Fabricated Grant Data: Fake grant numbers from nonexistent institutions were input into papers.

Human Factors

• Blind Trust in Metrics: Decision-makers relied blindly on Scopus scores without manual verification.
• Indifference to Alerts: Faculty showed indifference when alerted to the presence of fake journals.
• Academic Pressure to Publish: Pressure for awards and promotions incentivized gaming citation metrics.

Process and Methods

• Automatic Ranking Use: Automatic use of Scopus lists for hiring and promotion evaluations.
• Opaque Metric Algorithms: Lack of transparency in SJR and SNIP algorithms prevents external auditing.
• Inadequate Journal Screening: Scopus vetting processes failed to filter out coordinated citation rings.

Information quality

• Classification confidence: High
• Reason for confidence: The report provides clear, empirical evidence of academic metric manipulation using AI-generated papers, detailing the specific journals, publisher, and the mechanism of cross-citation. The impact on university evaluations is explicitly described.
• Ambiguities identified: The specific AI tools used to generate the papers are not named, and the exact number of researchers financially impacted by the distorted rankings is not quantified.
• Alternative interpretations: None. The evidence of systematic citation manipulation and templated paper generation is highly robust.

Researchers identified that three philosophy journals manipulated Scopus rankings using AI-generated papers and cross-citations. While this compromised academic evaluation metrics at institutions like Jagiellonian University, it has negligible direct national security implications.

• Overall national security impact: Negligible
• Scope: Multiple nations
• Primary target: No clear primary
• Other affected: Poland
• Alleged perpetrator: Addleton Academic Publishers

Threat characteristics

• Imminence: Long-term. Represents a strategic, ongoing concern regarding the integrity of academic publishing and automated metrics rather than an active security crisis.
• Autonomy: Human-controlled. AI tools were used as assistants by human actors to generate text, with humans managing the submission and citation manipulation process.
• Novelty: Evolved capability. Represents an advancement in academic fraud, scaling existing citation-gaming techniques through automated AI text generation.

Impact by dimension

• Physical security: Negligible. No physical systems, kinetic weapons, or critical infrastructure were targeted or affected by the academic journal manipulation.
• Information security: Negligible. The incident involves academic database manipulation rather than state-sponsored disinformation campaigns, intelligence compromise, or mass surveillance.
• Sovereignty: Negligible. No state authority, border control, electoral systems, or core government decision-making processes were impacted.
• Economic security: Negligible. While the manipulation distorted academic metrics for hiring and promotions, it occurred within philosophy journals and did not threaten strategic industries or national technological advantage.
• Societal stability: Negligible. The manipulation of academic rankings does not pose a threat to social cohesion, civil liberties, or population safety.