| 英文摘要 |
An artificial intelligence (AI) system aimed at automatically producing text, image, audio or video content can be classified as a generative AI. The emerging paradigm today for developing generative AI is based on the so-called foundation model which is trained on broad data and capable of functioning a wide range of tasks after being fine-tuned or adapted. The quantity and quality of data used for training, algorithmic models and required expertise and talent, as well as computational resources are the three major parameters for the competition in the generative AI market. The concentration of market for foundation models has been observed and the big techs such as Microsoft, Google and Meta continue to be the key players on the market. The competition authority should closely watch the structure and competition concerns of the relevant markets. Any abuse of market power by dominant companies on the market for foundation model and cloud computing will be the enforcement priority and“ecosystem lock-in”should be put on the top of the list. Considering the technological logics of generative AI and the associated risks on human society arising from them, entirely relying on the passive ex-post regulation is arguably infeasible. While the formal ex ante enactment for the purpose of controlling generative AI and foundation models has been introduced in the EU, the applicable laws and regulations for the emerging technology are not in a vacuum at all in our country, but thorough review and making the corresponding adjustments based on the AI technological reasonableness is necessary. Due to the homogenization characteristic of foundation models, the failures and flaws in the foundation model will be inherited by the downstream application models. Generative AI algorithms are lack of transparency and the capability of risks control for each participant on the general AI value chain varies and therefore making the accountability of AI and identifying the one who should be responsible for any harm imposed by generative AI become challenging and difficult. Considering the above- mentioned reasons, it is highly suggested that our government should vigorously and carefully calibrate the ex-ante regulation system for generative AI from now on and incorporate, at least, the clauses dealing with data collection and processing, algorithm design and transparency as well as accuracy, the obligations and responsibilities for each actor on the generative AI value chain, and the necessary human oversight on the generative AI. |
