Knowledge Tree
bias
Facts (16)
Sources
Social Epistemology – Introduction to Philosophy - Rebus Press press.rebus.community 3 facts
claimAn individual is not justified in abandoning a belief solely because someone else disagrees, if the best explanation for the disagreement is that the other person is ignorant, misinformed, biased, or mentally compromised.
claimEncouraging individuals to voice disagreement within a group reduces the likelihood of the group falling into unjustified groupthink or other biases.
claimAcademic freedom protections for students and faculty in universities exist partly to create space for disagreement, which helps prevent groupthink and bias.
A Survey on the Theory and Mechanism of Large Language Models arxiv.org Mar 12, 2026 1 fact
referenceThe paper 'Bias and fairness in large language models: a survey' provides a comprehensive overview of bias and fairness issues within large language models.
LLM Observability: How to Monitor AI When It Thinks in Tokens | TTMS ttms.com Feb 10, 2026 1 fact
claimLLM observability tracks AI-specific issues including hallucinations, bias, and the correlation of model behavior with business outcomes like user satisfaction or cost.
Why organisations must embrace the 'open source' paradigm blogs.lse.ac.uk Jan 5, 2024 1 fact
claimUtilizing training datasets from large databases decreases the likelihood of bias and guarantees the inclusiveness of resulting innovations by offering greater diversity and representativeness.
A systematic review of cognitive behavioral therapy-based ... frontiersin.org 1 fact
claimPotential bias in studies arises from sample sizes smaller than 50 participants per arm and a lack of information regarding the adverse effects of therapies, as noted by Moore et al. (2010).
Papers - Dr Vaishak Belle vaishakbelle.github.io 1 fact
referenceThe paper 'Toward A Logical Theory Of Fairness and Bias' by V. Belle was published in the ICLP proceedings in 2023.
A Comprehensive Review of Neuro-symbolic AI for Robustness ... link.springer.com Dec 9, 2025 1 fact
claimMehrabi, Morstatter, Saxena, Lerman, and Galstyan published 'A survey on bias and fairness in machine learning' in ACM Computing Surveys in 2021.
A Survey of Incorporating Psychological Theories in LLMs - arXiv arxiv.org 1 fact
claimPrompting Large Language Models to adopt specific social identities can reduce bias, as demonstrated by Dong et al. (2024a), and mirror human-like ingroup favoritism, as demonstrated by Hu et al. (2025a).
Social Epistemology - Stanford Encyclopedia of Philosophy plato.stanford.edu Feb 26, 2001 1 fact
claimHolman and Bruner (2017) demonstrate that industry can shape the output of an epistemic community through 'industrial selection,' which involves funding only agents whose methods bias them toward preferred findings.
LLM Hallucination Detection and Mitigation: State of the Art in 2026 zylos.ai Jan 27, 2026 1 fact
referenceWhyLabs LangKit is an observability toolkit for LLM monitoring at scale that provides continuous scanning for hallucinations, bias, and toxic language, integrates with model inference pipelines, performs statistical and rule-based anomaly detection, and includes production-grade dashboards and alerts.
Neuro-Symbolic AI: Explainability, Challenges & Future Trends linkedin.com Dec 15, 2025 1 fact
claimThe widespread use of Generative AI in content creation, drug discovery, and personalized learning necessitates the development of responsible and ethical frameworks to mitigate risks such as bias and misinformation.
Cross-cultural similarities and variations in parent-child value ... nature.com Nov 26, 2025 1 fact
claimIn research settings, limitations in cultural awareness increase the likelihood of researchers imposing their own cultural identity, values, practices, and understandings on others, which introduces bias and leads to inappropriate assumptions about the ideal optimal conditions for children’s development.
Call for Papers: Special Session on KR and Machine Learning kr.org 1 fact
claimThe success of Machine Learning systems has highlighted issues like explainability, bias, and fairness, which encourages the integration of symbolic or interpretable representations into AI systems.
The Impact of Cognitive Biases on Professionals' Decision-Making frontiersin.org 1 fact
measurementA 2015 systematic review by Blumenthal-Barby and Krieger found that 90% of 213 reviewed studies confirmed the presence of a bias or heuristic in medical populations.