Japan has made its ruling on the situation between Content creators and Businesses. Japanese companies that use AI have the freedom to use content for training purposes without the burden of copyright laws.
This news about the copyright laws in Japan reported over at Technomancers is seen as Businesses: 1 / Content Creators: 0
The Japanese government confirmed that it will not enforce copyrights on data used in AI training. This will open the door for AI systems to make use of any data, regardless of its origin or purpose. As both companies and countries are realising the importance of the AI industry, this decision adds an additional dimension to debates on AI regulation. Japan's move is inline with its motivation to become a leader in AI technology.
Japan clearly plans to avoid any hindrance to AI research and development. And sees this as a way to better leverage this technology and compete directly with the rest of the world.
This follows a similar decision from Israel in January whereby AI based solutions are exempt from legal matters of copyrighting for training. It describes how the “value of AI systems depends first and foremost on the quantity of the materials that the machine is fed at the ML stage, together with the diversity and quality of such materials.”. That “given the immense quantity of works that ML entails, the ML process will almost always require the use of works that are copyrighted by multitudes of third parties.”. Also “lifting the copyright uncertainties that surround this issue can spur innovation and maximize the competitiveness of Israeli-based enterprises in both ML and content creation.”
Like Japan, they have taken a very simplistic, and opportunistic view of the value of copyrighted content. The discussion about copyright laws has already filled up books and articles, but the idea is that they protect works of value. This is understandably thought of as being on a different level to AI, which is predicted to have a revolutionary effect on society. However, taking such a position then means that the resulting AI systems should also be void of both copyright coverage. The resulting AI models should therefore be available for open source solutions to use them for training.
The disclosure of data used for training, and getting to the core of this topic, explaining and divulging which copyrighted materials were used should be regulated. But such regulations should not just strip AI tools and systems of all and any obligation to do so and provide transparency for researchers to better understand them, track sources of bias etc. To also recognise that AI tools are a reflection of the data they use as their footing. Copyrighted or not.
I question the reliability and accuracy of Generative AI (GenAI) in enterprise scenarios, particularly when faced with adversarial questions, highlighting that current Large Language Models (LLMs) may be data-rich but lack in reasoning and causality. I would call for a more balanced approach to AI adoption in cases of assisting users, requiring supervision, and the need for better LLM models that can be trusted, learn, and reason.
I discuss my experience with chatbots, contrasting older rules-based systems with newer GenAI (General Artificial Intelligence) chatbots. We cannot dismiss the creative capabilities of GenAI-based chatbots, but these systems lack reliability, especially in customer-facing applications, and improvements in the way AI is structured could lead to a "software renaissance," potentially reducing society's technical debt.
The article discusses the contrasting debate on how AI safety is and should be managed, its impact on technical debt, and its societal implications.
It notes the Center for AI Safety's call for a worldwide focus on the risks of AI, and Meredith Whittaker's criticism that such warnings preserve the status quo, strengthening tech giants' dominance. The piece also highlights AI's potential to decrease societal and technical debt by making software production cheaper, simpler, and resulting in far more innovation. It provides examples of cost-effective open-source models that perform well and emphasizes the rapid pace of AI innovation. Last, the article emphasises the need for adaptive legislation to match the pace of AI innovation, empowering suitable government entities for oversight, defining appropriate scopes for legislation and regulation, addressing ethical issues and biases in AI, and promoting public engagement in AI regulatory decisions.
Japan has made its ruling on the situation between Content creators and Businesses. Japanese companies that use AI have the freedom to use content for training purposes without the burden of copyright laws. This news about the copyright laws in Japan reported over at Technomancers is seen as Businesses: 1 / Content Creators: 0 The […]