Audio text meaning

From 2 August 2026, the EU’s landmark AI Act will require firms such as OpenAI, Google and Meta to apply machine-readable labels to material produced by ChatGPT, Gemini and similar systems, indicating whether content is machine-generated or has been manipulated. The legislation also charges the European Commission with guiding the development of a voluntary code of practice to support the effective roll-out of this labelling duty. Early groundwork for the code has been laid through expert studies examining technical methods to mark content by type. Preparatory studies At a technical workshop on 4 September 2025, AI companies, experts and other stakeholders will be shown the preliminary findings from these studies. The text study was overseen by Giovanni Puccetti, associate professor at the University of Milan; the audio work was led by Xavier Serra and Martin Rocamore, professors at Barcelona’s University Pompeu Fabra; and the image and video study was coordinated by Mario Fritz, a professor at research centre CISPA...

They concern EU government institutions, pursuant to EU Regulation 2018/1725. That Regulation sets the rules for safeguarding personal data within EU government institutions, bodies, offices and agencies, and empowers the supervisor as the institutions’ independent data protection authority. While these guidelines are limited to EU governmental entities, they shed light on how the supervisor may handle generative AI in the future. Given the recently adopted EU Artificial Intelligence Act, due to take effect over the coming years, and the accelerating global shift towards AI regulation, the guidelines hint at what might become the next stage of AI oversight in Europe, the UK, the US and elsewhere. For clarity, generative AI denotes advances in computer deep learning models built to deliver a broad and general spectrum of outputs, able to perform a variety of tasks and uses, such as producing text, images or audio. The most familiar form of generative AI is large language models trained on vast volumes of text data. These systems can create natural language replies to a...

The forthcoming features could offer multi-model functionality, allowing prompts to extend beyond text to encompass images, video and audio queries; alongside enhanced contextual comprehension, enabling it to better recall details from earlier exchanges and draw more of them into handling your latest requests. They might also bring richer personalisation, permitting it to shape replies more precisely to your requirements, informed by its picture of you from prior interactions, your preferences, and your particular needs. Although their promise is exciting, these capabilities carry consequences for legal practice broadly and, in particular, provoke concerns about confidentiality as AI adoption becomes ever more pervasive, with knock-on effects for dispute resolution today, and what such features could signify for our work in the months and years ahead. The rise of AI and confidentiality concerns The legal profession stands on the brink of a profound shift in how its work is carried out, propelled by AI. Among the many ramifications are the challenges of safeguarding client confidentiality and what that entails in an...

Practice Note This Practice Note is aimed at general private-sector commercial organisations in the UK. It highlights typical risks linked to using artificial intelligence (AI) within your business and proposes ways to mitigate them. This Practice Note is not designed for organisations that create or deploy AI solutions as a commercial service for third parties. Separate guidance is available for technology companies—see Practice Note: Artificial Intelligence—UK regulation and the National AI Strategy. What is artificial intelligence? There is no single, settled definition of AI. In essence, it involves machines—usually computer systems—emulating human intelligence. Multiple forms of AI appear in commercial settings, including generative, predictive and extractive AI. Generative AI An AI tool that produces new, lifelike outputs such as text, audio, computer code, data or images, for example using an AI tool to: craft a marketing blog post refine an email you have already drafted produce a product description or a job description prepare a script or slides for...

Background to this thought leadership Precedent This Precedent originated from a Data Protection Intelligence Group thought leadership project in October 2021, with later updates by Lexis+® UK in February 2022 and again in early 2026. It is designed as a launch point to support organisations and stimulate development of thinking about this privacy expectation across the market. The Precedent will continue to adapt as fresh guidance, market practice and engagement emerge. It supplies a basic text template that can be reshaped for a cartoon, video and/or audio, along with other features (eg a message with emojis) to engage children in a way that suits the app provider’s branding and service. It should be: supported by appropriate just-in-time notifications and warnings (eg if a child changes a setting), and enhanced with suitable functionality enabling users to easily gain an overview and navigate between topics For further guidance on adapting the basic text, see Practice Note: Conveying privacy information to children aged 6...