Disclosures & Transparency

Last Updated: August 8, 2025

⚠️ Financial Disclosure

NOT FINANCIAL ADVICE: Nothing on this site constitutes financial, investment, legal, or tax advice. All content is for informational and educational purposes only. Consult licensed professionals before making financial decisions.

AFFILIATE RELATIONSHIPS: AIConsiders.com participates in the Amazon Services LLC Associates Program and may earn commissions from qualifying purchases. These relationships do NOT influence our rankings, which are determined by objective criteria and data analysis.

Methodology Overview

How We Generate Recommendations:

  • Data Collection: Automated aggregation from public sources including reviews, specifications, pricing databases, and government statistics
  • AI Analysis: Multiple AI models (GPT-4, Claude 3, specialized recommendation engines) analyze data independently
  • Consensus Building: Recommendations published only when models reach >80% agreement
  • Human Auditing: Quality checks for accuracy, not editorial influence
  • Update Frequency: Automated weekly updates with daily monitoring for major changes

Ranking Criteria

Each category uses specific, weighted criteria:

Laptops (Example):

  • Performance benchmarks (25%)
  • Build quality/reliability data (20%)
  • Price-to-performance ratio (20%)
  • User satisfaction scores (15%)
  • Repairability/upgradeability (10%)
  • Battery life (10%)

Credit Cards (Example):

  • Rewards value calculation (30%)
  • Fee structure analysis (25%)
  • Approval requirements (15%)
  • Additional benefits value (15%)
  • Customer service ratings (15%)

Data Sources

We aggregate data from:

  • Consumer review platforms (aggregated, not individual reviews)
  • Manufacturer specifications and pricing
  • Government databases (Census, BLS, regulatory filings)
  • Industry benchmarking tools
  • Public financial disclosures
  • Academic research papers

We do NOT use: Paid reviews, PR materials, or sponsored content in our analysis.

Model Cards

Primary Models Used:

  • GPT-4: General analysis and pattern recognition
  • Claude 3 Opus: Data synthesis and ranking logic
  • Custom ML Models: Category-specific optimization

All models operate with fixed prompts and evaluation criteria. No ad-hoc human prompting influences rankings.

Limitations & Biases

Despite our efforts to minimize bias, be aware of:

  • Training data biases inherent in AI models
  • Availability bias toward well-documented products
  • Geographic bias toward US market data
  • Temporal lag between market changes and updates
  • Inability to test products physically

Corrections & Feedback

Found an error? We want to know:

  • Email: [email protected]
  • Include: Page URL, specific error, supporting evidence
  • Response time: 48-72 hours for review
  • All corrections are logged publicly

Legal Compliance

This site complies with:

  • FTC Guidelines on Endorsements and Testimonials
  • Amazon Associates Program Operating Agreement
  • GDPR and CCPA privacy requirements
  • Truth in Advertising standards