Ethics & Disclaimer

⚠️ CRITICAL DISCLAIMER - READ CAREFULLY

MedResearch AI is a RESEARCH TOOL, NOT a medical device, diagnostic system, or clinical decision support tool.

NOT FOR CLINICAL USE: This platform does not diagnose, treat, cure, or prevent any disease
NOT A SUBSTITUTE: AI-generated content does not replace professional medical judgment
EXPERIMENTAL VALIDATION REQUIRED: All hypotheses must be validated through rigorous scientific methods
NO MEDICAL ADVICE: Do not use platform output for patient care decisions
RESEARCH PURPOSES ONLY: Intended for hypothesis generation and literature analysis in research settings

Core Ethical Principles

Our commitment to responsible AI development and deployment

Human-AI Partnership

AI is a collaborative partner, not a replacement for human expertise. Our systems augment researcher capabilities while preserving human oversight, critical thinking, and final decision-making authority.

Transparency & Explainability

Every AI-generated hypothesis includes full provenance tracking: PMID citations, confidence scores, reasoning chains, and uncertainty quantification. No "black box" decisions.

Data Privacy & Security

GDPR-compliant data handling with military-grade encryption. User research remains confidential. We do not train AI models on user-generated content without explicit consent.

Bias Mitigation & Fairness

Continuous monitoring for algorithmic bias. Multi-source evidence aggregation reduces single-database biases. Ethics validator flags potential equity concerns in research proposals.

Regulatory & Legal Status

Not a Medical Device

MedResearch AI is NOT classified as a medical device under FDA (21 CFR Part 860), EU MDR (2017/745), or equivalent regulations. The platform is intended solely for scientific research, hypothesis generation, and literature analysis by qualified researchers.

Research Software Exemption

Our platform operates under the research software exemption. All AI-generated hypotheses are exploratory projections requiring experimental validation before any clinical application. Output is not intended for direct patient care.

Data Protection Compliance

GDPR-compliant (EU General Data Protection Regulation 2016/679). Our infrastructure includes:

Right to access, rectification, erasure (Articles 15-17)
Data portability and processing restrictions (Articles 18-20)
ISO 27001-aligned security protocols
Zero-trust architecture with end-to-end encryption

Prohibited Uses & Limitations

❌ Clinical Decision-Making

Do not use AI output for diagnosing, treating, or managing patients

❌ Regulatory Submissions

AI hypotheses require independent validation before FDA/EMA filings

❌ Medical Advice

Platform output is not a substitute for licensed medical professionals

❌ Unvalidated Publication

All AI-generated claims must be experimentally verified before publication

❌ Automated Drug Development

Human oversight required for all drug discovery and safety assessments

❌ Patient Data Analysis

Do not upload patient health information (PHI) to the platform

Accuracy & Reliability Limitations

AI models may generate plausible but incorrect hypotheses (hallucinations)
Evidence quality depends on source database completeness and publication bias
Novelty scores are computational estimates, not guarantees of scientific impact
Cross-domain transfers require domain expert validation
Feasibility assessments are projections based on limited data

User Responsibilities

Scientific Validation Required

Users must conduct independent experimental validation of AI-generated hypotheses through appropriate in vitro, in vivo, or clinical studies before making any scientific claims.

Critical Review of AI Output

Apply expert domain knowledge to evaluate AI suggestions. Do not blindly accept AI recommendations without thorough critical analysis and literature cross-referencing.

Proper Attribution & Transparency

When publishing research informed by MedResearch AI, disclose AI tool usage in methods sections and acknowledge platform limitations per journal guidelines.

Ethical Research Practices

Ensure all downstream research complies with institutional review board (IRB) requirements, ethical guidelines, and relevant regulations (e.g., ICH-GCP for clinical trials).

Data Security & Confidentiality

Do not upload proprietary, confidential, or patient-identifiable data. Users are responsible for maintaining data security and complying with institutional policies.

Limitation of Liability

TO THE MAXIMUM EXTENT PERMITTED BY APPLICABLE LAW, Infosphere Technologies and its affiliates, officers, directors, employees, and agents ("Provider") shall not be liable for any direct, indirect, incidental, special, consequential, or exemplary damages arising from:

Use or misuse of AI-generated hypotheses or research suggestions
Errors, inaccuracies, or omissions in platform output
Research failures, regulatory rejections, or patent disputes arising from platform use
Loss of data, profits, revenue, or business opportunities
Personal injury or death resulting from actions taken based on platform content

Warranty Disclaimer

THE PLATFORM IS PROVIDED "AS IS" AND "AS AVAILABLE" WITHOUT WARRANTIES OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, NON-INFRINGEMENT, OR ACCURACY. Provider does not warrant that the platform will be uninterrupted, error-free, or free from harmful components.

Indemnification

Users agree to indemnify and hold harmless Provider from any claims, damages, losses, liabilities, and expenses (including legal fees) arising from: (a) user's breach of these terms, (b) misuse of AI-generated content, (c) violation of third-party rights, or (d) any research activities informed by platform output.

Questions or Concerns?

For questions about ethical AI use, data privacy, regulatory compliance, or to report potential issues with platform output, please contact:

Commitment to Responsible AI

We are committed to continuous improvement of our AI systems, ethical guidelines, and safety protocols. User feedback helps us identify risks, mitigate biases, and enhance transparency. We welcome constructive input from the research community.