Responsible Use of AI in Evidence Synthesis

Our commitment to transparent, auditable, and research-grade AI assistance

AI Assists, Humans Decide

Artificial intelligence enhances efficiency while human researchers maintain full control over final decisions and interpretations.

Uncertainty is Surfaced, Not Hidden

Confidence scores and transparency indicators help researchers understand when additional verification is needed.

Provenance is Preserved

Source traceability and verbatim quotes ensure all extracted information can be verified and audited.

Outputs are Inspectable and Auditable

All AI-derived content remains under user control and can be exported, reviewed, and deleted as needed.

Alignment with RAISE Principles

Evidence Table Builder is designed in accordance with the RAISE (Responsible AI for Science and Evidence) principles, ensuring that AI tools serve as trustworthy partners in evidence synthesis rather than opaque black boxes.

Our approach prioritizes:

  • Transparency: Clear disclosure of AI involvement and processing methods
  • Accountability: Human researchers retain ultimate responsibility for research quality and validity
  • Reproducibility: Structured outputs that support methodological rigor and peer review
  • Bias Awareness: Active identification and communication of potential limitations and uncertainties

For Cochrane and Evidence Synthesis Communities

We understand the unique requirements of systematic review organizations and have designed our tool to align with Cochrane and similar standards. Our implementation supports:

  • PRISMA-compliant reporting and disclosure requirements
  • Source traceability for audit and verification purposes
  • Confidence scoring to guide human verification workflows
  • Exportable outputs for integration with existing review management systems
  • Independent evaluation and validation study participation

Our Commitment

Evidence Table Builder is built for researchers who demand the highest standards of methodological rigor. We believe AI should enhance, not replace, human expertise in evidence synthesis. Our tool is designed to be:

  • A catalyst for efficiency without compromising scientific standards
  • A transparent partner that surfaces uncertainty rather than hiding it
  • A research-grade tool suitable for publication and regulatory environments
  • A platform that respects researcher autonomy and data sovereignty

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