Knowledge Tree
safety
Facts (24)
Sources
Building Trustworthy NeuroSymbolic AI Systems - arXiv arxiv.org 4 facts
claimThe authors propose the CREST framework for achieving trustworthiness in Large Language Models, which stands for Consistency, Reliability, user-level Explainability, and Safety.
claimGroundedness serves as the foundation for both explainability and safety in AI systems, as a lack of grounding in provided instructions can lead to unintended consequences.
claimThe authors of the paper 'Building Trustworthy NeuroSymbolic AI Systems' argue that NeuroSymbolic AI is better suited for creating trusted AI systems than statistical or symbolic AI methods used in isolation, because trust requires consistency, reliability, explainability, and safety.
referenceSarkar et al. (2023) reviewed the explainability and safety of conversational agents used in mental health contexts to identify potential improvements.
Virtue Epistemology - Stanford Encyclopedia of Philosophy plato.stanford.edu Jul 9, 1999 3 facts
referenceChristoph Kelp published 'Pritchard on Knowledge, Safety and Cognitive Achievements' in the Journal of Philosophical Research in 2009, which analyzes Duncan Pritchard's views on knowledge, safety, and cognitive achievements.
referenceChristoph Kelp published 'Knowledge and Safety' in the Journal of Philosophical Research in 2009, which discusses the relationship between knowledge and safety.
referenceJoseph Adam Carter published 'Anti-Luck Epistemology and Safety’s (Recent) Discontents' in Philosophia in 2009, which discusses anti-luck epistemology and safety.
A Comprehensive Review of Neuro-symbolic AI for Robustness ... link.springer.com Dec 9, 2025 2 facts
claimThe reasoning for learning paradigm enhances interpretability, sample efficiency, and safety in learning, particularly in domains where logical consistency is critical, such as knowledge graph completion, autonomous systems, and medical diagnostics.
referenceGaur, M. and Sheth, A. outlined the requirements for building trustworthy neuro-symbolic AI systems, specifically focusing on consistency, reliability, explainability, and safety.
How Open-Source AI Drives Responsible Innovation - The Atlantic theatlantic.com 1 fact
claimThe development of AI systems raises concerns regarding safety, fairness, transparency, and accountability.
Medicinal plants: bioactive compounds, biological activities ... frontiersin.org 1 fact
claimEkor (2014) discusses the increasing utilization of herbal medicines, highlighting the associated challenges regarding adverse reactions and the monitoring of safety.
Neuro-Symbolic AI: Explainability, Challenges, and Future Trends arxiv.org Nov 7, 2024 1 fact
referenceSharifi et al. (2023) proposed a neuro-symbolic deep reinforcement learning approach to improve the safety of autonomous driving policies.
Sleep Deprivation and Deficiency - How Sleep Affects Your Health nhlbi.nih.gov Jun 15, 2022 1 fact
claimGetting enough quality sleep at the right times helps protect mental health, physical health, quality of life, and safety.
The Impact of Cognitive Biases on Professionals' Decision-Making frontiersin.org 1 fact
referenceM. P. Stiegler and K. J. Ruskin published 'Decision-making and safety in anesthesiology' in Current Opinion in Anaesthesiology in 2012.
Ethnobotanical study of food plants used in traditional medicine in ... link.springer.com Nov 26, 2025 1 fact
claimThe empirical use of Spondias dulcis and Aframomum alboviolaceum during pregnancy warrants caution due to a lack of robust scientific evidence regarding their safety.
Nanomaterials in the future biotextile industry: A new cosmovision to ... frontiersin.org Dec 1, 2022 1 fact
referenceIntelligent textiles are designed to integrate technologies that offer users greater functionality, such as health monitoring, safety, security, and lifestyle tracking, as described by Sayol (2015).
LLM Observability: How to Monitor AI When It Thinks in Tokens | TTMS ttms.com Feb 10, 2026 1 fact
claimDatadog allows end-to-end tracing of AI requests, capturing prompts and responses as spans, logging token usage and latency, and evaluating outputs for quality or safety issues.
Papers - Dr Vaishak Belle vaishakbelle.github.io 1 fact
referenceVaishak Belle and P. Barcelo authored the paper 'A Uniform Language for Safety, Robustness and Explainability', published in JELIA in 2025.
Stress, Lifestyle, and Health – Introduction to Psychology open.maricopa.edu 1 fact
referenceWhile some stressors are inherently more threatening than others, such as objective threats to health or safety, cognitive appraisal still plays a role in augmenting or diminishing an individual's reaction to those events, according to Everly & Lating (2002).
A Scoping Review of Indicators for Sustainable Healthy Diets frontiersin.org Jan 12, 2022 1 fact
measurementThe scoping review identified 143 health indicators across the 103 articles, categorized into the following concepts: health outcomes (26), nutrient adequacy (22), nutrient density (16), moderation (12), diversity (9), safety (1), multiple concepts (47), diet quantity (4), and other (6).
Building trustworthy NeuroSymbolic AI Systems: Consistency ... onlinelibrary.wiley.com Feb 14, 2024 1 fact
referenceThe CREST framework, introduced in the paper 'Building trustworthy NeuroSymbolic AI Systems: Consistency...', demonstrates how Consistency, Reliability, user-level Explainability, and Safety are built on NeuroSymbolic methods.
Survey and analysis of hallucinations in large language models frontiersin.org Sep 29, 2025 1 fact
referenceOpenAI published the GPT-4 System Card in 2023, detailing safety and system information.
A framework to assess clinical safety and hallucination rates of LLMs ... nature.com May 13, 2025 1 fact
procedureThe framework relies on a 'baseline' experiment configuration, using the same input data points as the new experiment, to achieve a meaningful clinical comparison of efficacy and safety.
Epistemological Problems of Testimony plato.stanford.edu Apr 1, 2021 1 fact
claimCharlie Pelling's 2013 article 'Testimony, Testimonial Belief, and Safety' examines the relationship between testimony, testimonial belief, and the concept of safety in epistemology.