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Related Concept Videos

Blinding01:11

Blinding

Blinding is a commonly used method of not telling participants which treatment a subject is receiving. Blinding is a critical part of a randomized control trial or RCT. It reduces the bias that affects the results. In an RCT, blinding is used in the form of a placebo. A placebo effect occurs when untreated subjects falsely believe they have received the treatment and report improved symptoms. A placebo or a dummy treatment is administered to subjects to negate the bias caused by such an effect.
Motivational Bias01:25

Motivational Bias

Cognitive bias results from limitations in thinking and information processing, leading to systematic errors in judgment. Conversely, motivational bias stems from personal desires or emotions, causing distortions in perception to align with self-interest. Motivational bias influences how individuals perceive and attribute causes to events, often shaped by personal needs, goals, and self-esteem preservation. This bias can distort judgment, leading to inaccurate assessments of success, failure,...
Social Proof00:52

Social Proof

Social proof is a form of persuasion based on comparison and conformity. People compare their behavior and actions to what others are doing and will change to conform to do what their peers do.
Confirmation Biases01:31

Confirmation Biases

The confirmation bias is the tendency to focus on information that confirms our existing beliefs and ignore information that is inconsistent with our expectations. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Have you ever fallen prey to the confirmation bias, either as the source or target of such bias?
Self-Efficacy01:29

Self-Efficacy

Self-efficacy is the belief in one's capacity to organize and execute actions necessary to manage prospective situations. This belief significantly influences how individuals approach goals, tasks, and challenges across different domains of life.Psychological and Educational ImpactsIndividuals with strong self-efficacy are more resilient in the face of difficulties. They are more likely to adopt effective problem-solving strategies, persist through obstacles, and regulate emotions such as...
Halo Effect01:27

Halo Effect

The halo effect is a cognitive bias in which an individual's overall impression influences judgments about their specific traits. This psychological phenomenon leads people to associate positive characteristics with those they perceive as generally good and negative characteristics with those they view as bad. This effect is particularly influential in social perception, professional evaluations, and decision-making processes.The Psychological Basis of the Halo EffectThe halo effect is rooted...

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Related Experiment Video

Updated: Jun 20, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Evidence-based AI: from trailblazer to trustblazer?

Thomas Luechtefeld1, Thomas Hartung2,3

  • 1Insilica Inc., Rockville, MD, United States.

Frontiers in Artificial Intelligence
|June 19, 2026
PubMed
Summary

Agentic AI offers advanced scientific workflows but needs trustworthiness for high-stakes fields. An Evidence-based Agent Stack, inspired by evidence-based medicine, ensures AI reliability through structured roles, provenance, and uncertainty assessment.

Keywords:
agentic AIe-validationevidence-based edicineevidence-based toxicologyregulatory scienceretrieval-augmented generationrisk of biassystematic review

Related Experiment Videos

Last Updated: Jun 20, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Area of Science:

  • Artificial Intelligence
  • Regulatory Science
  • Toxicology

Background:

  • Agentic AI systems excel at multi-step scientific workflows beyond single-model capabilities.
  • High-stakes domains like regulatory science require more than fluency; they demand traceability, reproducibility, and uncertainty communication for AI adoption.

Purpose of the Study:

  • To propose a framework for making agentic AI trustworthy by design in scientific applications.
  • To leverage principles from evidence-based medicine and toxicology to build reliable AI systems.

Main Methods:

  • Decomposition of end-to-end AI tasks into protocolized roles within an Evidence-based Agent Stack.
  • Integration of mandatory provenance and versioning for all agentic workflows.
  • Anchoring AI workflows in systematic review practices, risk-of-bias frameworks, and regulatory principles (e.g., TREAT, e-validation).

Main Results:

  • The proposed Evidence-based Agent Stack enables auditable, updateable, and accountable AI outputs.
  • This approach transforms "trailblazing" AI into "trustblazing" AI by ensuring reliability and decision alignment.
  • Mandatory provenance and versioning enhance the traceability and reproducibility of AI-generated scientific evidence.

Conclusions:

  • Agentic AI can be made trustworthy by design by adopting an evidence-based approach.
  • The Evidence-based Agent Stack provides a scaffold for reliable AI in regulatory science and toxicology.
  • Integrating AI with established evidence synthesis practices ensures alignment with decision accountability and regulatory standards.