EmailContact
Skip to main content

Research Overview

GPTfake conducts independent research on AI censorship patterns, bias detection, and transparency.

Research Areas​

Longitudinal Studies​

We track AI model behavior over time to identify:

  • Gradual policy shifts
  • Silent content updates
  • Behavioral drift between versions
  • Convergence patterns across models

Bias Detection​

Analysis of political, cultural, and ideological bias:

  • Political spectrum scoring
  • Cultural bias identification
  • Regional variation analysis
  • Temporal bias changes

Policy Analysis​

Examination of AI content policies:

  • Official policy documentation
  • Actual behavior vs stated policy
  • Cross-platform comparison
  • Regulatory compliance

Technical Papers​

Deep technical analysis:

  • Response pattern classification
  • NLP-based censorship detection
  • Semantic similarity analysis
  • Change detection algorithms

Key Findings​

2024 Highlights​

  1. Rising Censorship  Average refusal rates increased 15% across major models
  2. Policy Convergence  Models becoming more similar in restrictions
  3. Silent Updates  60% of behavioral changes unannounced
  4. Regional Variation  Gemini shows strongest geographic differences

Publications​

Recent Papers​

Datasets​

All research datasets available for academic use:

  • Daily monitoring data (JSON/CSV)
  • Historical trend data
  • Prompt libraries
  • Response classifications

Collaboration​

Academic Partners​

We collaborate with:

  • Universities conducting AI ethics research
  • Digital rights organizations
  • Policy research institutes
  • Independent journalists

How to Collaborate​

  1. Data Access  Request research dataset access
  2. Joint Studies  Propose collaborative research
  3. Peer Review  Review our methodology
  4. Citation  Use our data in your research

Contact: info@gptfake.com

Methodology​

Our research follows rigorous standards:

  • Reproducibility  All methods publicly documented
  • Transparency  Open data and analysis
  • Peer Review  Academic review of findings
  • Ethics  IRB-compliant where applicable

See Methodology for details.

Impact​

Media Citations​

Our research has been cited by:

  • Major technology publications
  • Academic journals
  • Policy reports
  • Investigative journalism

Policy Influence​

Research used to inform:

  • AI governance discussions
  • Transparency requirements
  • Platform accountability
  • Regulatory frameworks

Get Involved​

Last updated on