116 articles tagged with #transparency. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.
Google has released Gemma Scope 2, providing open interpretability tools for understanding the behavior of language models across the entire Gemma 3 family. These tools are designed to help the AI safety community analyze and interpret complex language model behaviors.
OpenAI researchers are developing a 'confessions' method to train AI language models to acknowledge their mistakes and undesirable behavior. This approach aims to enhance AI honesty, transparency, and overall trustworthiness in model outputs.
OpenAI is outlining its approach to handling mental health-related litigation cases involving ChatGPT. The company emphasizes handling sensitive cases with care, transparency, and respect while working to strengthen safety and support features in their AI platform.
OpenAI is collaborating with independent experts to conduct third-party testing of their frontier AI systems. This external evaluation approach aims to strengthen safety measures, validate existing safeguards, and improve transparency in assessing AI model capabilities and associated risks.
OpenAI is researching mechanistic interpretability through sparse neural network models to better understand AI reasoning processes. This approach aims to make AI systems more transparent and improve their safety and reliability.
The Ethereum Foundation has published a treasury policy document with input from key developers and researchers including Vitalik Buterin, Tim Beiko, and Dankrad Feist. The policy appears to outline governance and management strategies for the Foundation's significant ETH holdings and operational funds.
The article exposes how DeFi protocols manipulate treasury reporting through inflated dashboards that display recycled tokens, illiquid assets, and misleading accounting practices. These deceptive practices create false impressions of financial strength to build user trust rather than representing actual operational funding capabilities.
StarCoder2-Instruct introduces a fully transparent and permissive self-alignment approach for code generation AI models. This development represents an advancement in open-source AI tooling for developers, emphasizing transparency and accessibility in code generation capabilities.
The article announces the launch of The Hallucinations Leaderboard, an open initiative designed to measure and track hallucinations in large language models. This effort aims to provide transparency and benchmarking for AI model reliability across different systems.
The article explores how blockchain technology can provide resilient infrastructure and solutions during times of crisis when traditional institutions may fail or become corrupted. It examines blockchain's potential to maintain trust, transparency, and functionality across borders when centralized systems are compromised.
OpenAI experienced a significant ChatGPT outage on March 20, prompting the company to release findings about the technical bug that caused the disruption. The update provides transparency about the incident and outlines actions taken to prevent similar issues.
OpenAI is clarifying how ChatGPT's behavior is determined and announcing plans to improve the system's behavior while allowing more user customization. The company also plans to increase public input in decision-making processes around AI system behavior.
The Ethereum Foundation has published its annual report detailing the organization's core principles, vision, and resource allocation processes for 2021. The report aims to provide transparency to the community about the Foundation's role and describes Ethereum as an 'infinite garden.'
A multi-stakeholder report by 58 co-authors across 30 organizations presents 10 mechanisms to improve verifiability of AI system claims. The tools enable developers to provide evidence of AI safety, security, fairness, and privacy while allowing users and policymakers to evaluate AI development processes.
A policy research paper outlines four strategies to improve AI industry cooperation on safety: communicating risks/benefits, technical collaboration, transparency, and incentivizing standards. The research highlights that competitive pressures could create collective action problems leading to under-investment in AI safety.
The Cultural Landscape Foundation has filed a lawsuit challenging Trump's Reflecting Pool renovation project, citing concerns about transparency and compliance with federal preservation laws. The case highlights broader issues in how government manages major infrastructure projects and enforces heritage protection regulations.
Ripple's CTO Emeritus David Schwartz has publicly denied rumors that he is bound by a post-departure gag order preventing him from speaking truthfully about Ripple and XRP. The denial addresses speculation about potential restrictions on his ability to comment on the company following his departure.
Researchers have developed QualAnalyzer, an open-source Chrome extension that makes AI-assisted qualitative research more transparent by preserving detailed audit trails of LLM analysis processes. The tool processes data segments independently and maintains records of prompts, inputs, and outputs to enable systematic comparison between AI and human judgments.
Researchers analyzed AI data science systems designed for medical settings, finding that success depends on creating transparent intermediate artifacts like readable query languages and concept definitions. These intermediates help users reason about analytical choices and contribute domain expertise, despite opacity in other parts of the AI process.
Aster Chain has officially launched, positioning itself as a new blockchain platform focused on combining onchain privacy with transparency. The launch was announced from George Town, British Virgin Islands on March 17th, 2026, marking the platform's entry into the privacy-focused blockchain space.
The Free Software Foundation is advocating for open-source, community-developed AI models ("free-range LLMs") as an alternative to proprietary AI systems developed by large corporations ("factory-farmed AI"). This represents a push for democratization and transparency in AI development, emphasizing user freedom and community control over AI technology.
CryptoQuant released a report ranking cryptocurrency exchanges based on reserves, trading activity, and transparency metrics. KuCoin topped the rankings with an exceptional score of 96.7 out of 100, establishing it as the most transparent exchange for reserves according to the analysis.
The article discusses proof-of-reserves as a mechanism for crypto exchange safety, noting that while it's beneficial, the implementation and effectiveness is more complex than it initially appears. This highlights the varying levels of security and transparency across different cryptocurrency exchanges.
Blockchain technology is improving cross-border payments by increasing transaction speed, reducing costs, and enhancing transparency. Chainlink is specifically enabling secure and compliant blockchain-based cross-border payment solutions.
The article appears to discuss community-driven evaluation systems as an alternative to traditional black-box leaderboards, suggesting a shift towards more transparent and community-controlled assessment methods. However, the article body is empty, limiting detailed analysis.
