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Boosting Taiwan’s Competitiveness Through AI

Similar to other nations across the world, Taiwan is also grappling with issues posed by the rising trend of AI-powered, generated, or supported content and tools. These advancements have brought about various debates and discussions regarding their impact on society, particularly with regard to issues such as copyright laws, legal norms, and the role of creators in this rapidly evolving landscape.

Hosted by President Cai Zhihong of Taiwan’s Shilin District Court, Taiwan Internet Lecture Hall discussed the topic where a panel of experts delved into a range of pertinent issues related to the emergence of AI-generated works and their impact on creators.

Discussions, perspectives and forecasts for the future revolved around the prospects and challenges posed by AI-generated works and explored ways to foster a mutually beneficial relationship between creators and AI-generation technologies.

Cai clarified that the domestic copyright law protects expressions, not the ideas expressed. He stated that without copyright protection, the ideological investment could become meaningless, and giving incentives is a matter worth debating.

On the topic of legal ownership of AI-generated works, Professor Feng Zhenyu advocated a nuanced approach which involves analysing not just who owns the copyright to AI-generated works, but also whether they are legally liable.

According to Chen Jiajun, Chairman of the Taiwan Information Intellectual Property Association, there is no standard answer now, but the consensus is that the copyright of AI-generated works is not protected. However, these are primarily administrative agency opinions, and no court decision has yet been rendered.

A general manager of a prominent domestic company specialising in immune function testing stated that AI is the most effective tool for analysing and deriving simple conclusions from complex data, but there are still obstacles to overcome. Obtaining valuable data and persuading the public of the benefits of the distinctions between conventional cancer tests and AI-based cancer tests are the two greatest obstacles to AI big data analysis for immune function.

The key to the success of AI lies in the acquisition of valuable data, and the catchphrase “garbage in, garbage out” in computer science and communications emphasises that the data entered the system must be valuable to produce valuable conclusions. The way forward is to leverage large volumes of data along with AI analysis, incorporate existing screening tests, and subsequently apply them to key areas of clinical practice.

According to AI Taiwan, the country’s strong ICT and semiconductor industries have laid a solid groundwork for the advancement of intelligent technologies. The country is actively pursuing the development of a cutting-edge AI-on-device solution and a robust ecosystem that can carve out a niche market and establish Taiwan as a significant player in the global value chain of intelligent systems. This involves hardware-software integration and collaboration, as well as the creation of test fields, regulations, and a data-sharing environment to foster AI adoption in various industries.

Last month Taiwan’s government officially opened its AI Center of Excellence. The Taiwan AI Center of Excellence (Taiwan AICoE) is tasked with developing Taiwan’s artificial intelligence (AI) capability.

The future of higher education is being shaped by generative AI technology – which in turn will shape a country, its economy and its overall development. Artificial intelligence systems are developing quickly in the current digital landscape and getting in-depth training in the technology not only can assist students with their academic work but prepare them for the workforce.

Other AI initiatives are expected to bolster the nation’s digital ambitions. The Asia New Bay Area 5G AIoT Innovation Park will focus on industrial development, talent cultivation, R&D subsidies and field application and has attracted domestic and foreign investment, generating over a billion in production value.


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