The Right to be Forgotten (RTBF) was first established as the result of the ruling of Google Spain SL, Google Inc. v AEPD, Mario Costeja Gonz´alez, and was later included as the Right to Erasure under the General Data Protection Regulation (GDPR) of European Union to allow individuals the right to request personal data be deleted by organizations. Specifically for search engines, individuals can send requests to organizations to exclude their information from the query results. It was a significant emergent right as the result of the evolution of technology. With the recent development of Large Language Models (LLMs) and their use in chatbots, LLM-enabled software systems have become popular. But they are not excluded from the RTBF. Compared with the indexing approach used by search engines, LLMs store, and process information in a completely different way. This poses new challenges for compliance with the RTBF. In this paper, we explore these challenges and provide our insights on how to implement technical solutions for the RTBF, including the use of differential privacy, machine unlearning, model editing, and prompt engineering. With the rapid advancement of AI and the increasing need of regulating this powerful technology, learning from the case of RTBF can provide valuable lessons for technical practitioners, legal experts, organizations, and authorities. — Read More
#legalDaily Archives: May 29, 2024
GPT-4 Outperforms Human Analysts in Financial Statement Analysis: A Technological Breakthrough
In a groundbreaking study conducted by the University of Chicago’s Booth School of Business, researchers have revealed that OpenAI’s GPT-4 large language model (LLM) can rival and even outperform human professionals in financial statement analysis. This significant finding could mark a new era in financial analysis, where artificial intelligence (AI) tools become indispensable for making informed financial decisions. — Read More
What does the public in six countries think of generative AI in news?
Based on an online survey focused on understanding if and how people use generative artificial intelligence (AI), and what they think about its application in journalism and other areas of work and life across six countries (Argentina, Denmark, France, Japan, the UK, and the USA), we present the following findings.
ChatGPT is by far the most widely recognised generative AI product – around 50% of the online population in the six countries surveyed have heard of it. It is also by far the most widely used generative AI tool in the six countries surveyed. That being said, frequent use of ChatGPT is rare, with just 1% using it on a daily basis in Japan, rising to 2% in France and the UK, and 7% in the USA. Many of those who say they have used generative AI have used it just once or twice, and it is yet to become part of people’s routine internet use.
In more detail, we find:
— Just 5% across the six countries covered say that they have used generative AI to get the latest news.
— While there is widespread awareness of generative AI overall, a sizable minority of the public – between 20% and 30% of the online population in the six countries surveyed – have not heard of any of the most popular AI tools.
— In terms of use, ChatGPT is by far the most widely used generative AI tool in the six countries surveyed, two or three times more widespread than the next most widely used products, Google Gemini and Microsoft Copilot.
— Younger people are much more likely to use generative AI products on a regular basis. Averaging across all six countries, 56% of 18–24s say they have used ChatGPT at least once, compared to 16% of those aged 55 and over.
— Roughly equal proportions across six countries say that they have used generative AI for getting information (24%) as creating various kinds of media, including text but also audio, code, images, and video (28%).
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THE AI INDEX REPORT 2024
Welcome to the seventh edition of the AI Index report. The 2024 Index is our most comprehensive to date and arrives at an important moment when AI’s influence on society has never been more pronounced. This year, we have broadened our scope to more extensively cover essential trends such as technical advancements in AI, public perceptions of the technology, and the geopolitical dynamics surrounding its development. Featuring more original data than ever before, this edition introduces new estimates on AI training costs, detailed analyses of the responsible AI landscape, and an entirely new chapter dedicated to AI’s impact on science and medicine.
Top Takeaways
— AI beats humans on some tasks, but not on all.
— Industry continues to dominate frontier AI research.
— Frontier models get way more expensive.
— The United States leads China, the EU, and the U.K. as the leading source of top AI models.
— Robust and standardized evaluations for LLM responsibility are seriously lacking.
— Generative AI investment skyrockets.
— The data is in: AI makes workers more productive and leads to higher quality work.
— Scientific progress accelerates even further, thanks to AI.
— The number of AI regulations in the United States sharply increases.
— People across the globe are more cognizant of AI’s potential impact—and more nervous.
— Read More
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