Peter Welch, a Senator from Vermont, recently introduced a new bill called the "Transparency and Accountability in Artificial Intelligence Act" (TRAIN Act), aimed at increasing transparency for AI developers. If passed, this legislation would allow copyright holders to issue subpoenas to relevant parties to obtain training records if they believe their works have been used without authorization to train AI models. Note: Image generated by AI, image licensed through Midjourney.

Recently, Deloitte released a report highlighting the significance of data privacy in generative artificial intelligence (GenAI). According to the survey, concerns regarding data privacy have significantly increased among professionals, with only 22% citing it as a top concern in 2023, compared to 72% in 2024. This indicates a growing awareness of potential risks as technology advances. Image Source Note: The image is generated by AI and licensed through Midjourney. In addition to data privacy, transparency and data sources are also important.

Recently, OpenAI's CEO Sam Altman announced his decision to leave the company's internal safety committee, which was established in May of this year to oversee key safety and security decisions in the development and deployment of OpenAI's AI models. Altman's decision has drawn significant attention as he hopes to hand this role over to third-party experts to enhance transparency, collaboration, and security. With Altman's departure, this safety committee will transform into an 'independent oversight committee' focused on safety and security issues.

Recently, the US Department of Commerce released a proposal requiring artificial intelligence (AI) companies to provide detailed reports, aimed at stricter regulation of this rapidly evolving technological field. The notice, titled 'Proposed Rules,' was published on September 9, with the intention of ensuring the safety, reliability of AI technology, and preventing potential misuse by foreign adversaries or non-state actors. Photo credit: Image generated by AI, image licensed from Midjourney. Secretary of Commerce Gina Raimondo stated at a press conference that the rapid development of AI...

Social media giant Meta is about to make significant adjustments to the way AI content is tagged on its platforms Instagram, Facebook, and Threads. Starting next week, the 'AI Information' label for content edited or modified by AI tools will be moved to the post menu and will no longer be displayed directly below the user's name. This change brings several key points: 1. Tagging Distinction: Content that is entirely generated by AI will still retain a prominent label, while labels for content that has been merely edited by AI will be hidden. 2. Sources of Transparency: Me

Anthropic has recently made public the system prompts for the Claude model, including the Claude 3.5 Opus, Sonnet, and Haiku versions. This is a significant breakthrough for the AI industry, as most vendors typically keep this information confidential. This move enhances AI transparency, as the behavior rules and personality traits of Claude are detailed through these prompts. Generative AI models generate text based on statistical predictions, and system prompts are used to guide model behavior to avoid inappropriate actions. Anthropic's aim with this initiative is to

IBM has launched Watsonx Governance to help enterprises improve AI model transparency. Watsonx Governance provides tools for managing risks and enhancing transparency. IBM's consulting services expand strategic expertise to assist clients in achieving responsible AI. Watsonx Governance is one of three new software products within the Watsonx AI platform. IBM also announced intellectual property protections for its Watsonx models.

Researchers, in collaboration with MIT, Cohere for AI, and other institutions, have launched the Data Provenance Platform to tackle the issue of AI data transparency. The platform audits and tracks over 2,000 widely used fine-tuning datasets, emphasizing the importance of data transparency. Insufficient data provenance can lead to data leaks, exposure of personal information, bias, and legal risks. The Data Provenance Platform is expected to enhance AI data transparency and improve the quality and ethical compliance of datasets.

🔍 The 'Foundational Model Transparency Index' released by Stanford University reveals that AI model developers lack information about the potential societal impacts. Meta's Llama 2 performs best in terms of transparency, but still faces issues of insufficient transparency. The research highlights the challenges the AI industry faces regarding transparency and the importance of regulation in promoting greater transparency.

Walmart has announced its commitment to responsible AI, focusing on six key areas: transparency, safety, privacy, fairness, accountability, and user-centricity. The commitment aims to help users understand how the company utilizes AI and the advanced safety measures taken to protect user data. Evaluations of AI systems ensure that sensitive information is used in a privacy-preserving manner to mitigate potential biases that could affect users. By using human-managed AI, Walmart takes responsibility for its impacts and continuously improves its AI tools based on user feedback. The company hopes to pave the way for ethical AI adoption in the retail industry through its leadership.

TikTok's latest initiative: introducing AI-generated content labels. The label requires creators to use it to inform viewers that the content is produced by AI. There are plans to rename filters and effects that use AI tools to enhance recognizability. This move aims to boost content transparency and maintain the quality of the platform's content. User experience will therefore be improved.