Professor Angela Zhang of the University of Hong Kong is globally acknowledged for her in-depth understanding of the Chinese tech industry. Her extensive research and numerous published works have shed light on how these firms operate, the impact of regulation on the industry, and the myriad of ethical issues that surround tech development in China.
Prof. Zhang’s contributions to the global conversation about Chinese tech firms and their operations have shaped the understanding of policymakers and corporate leaders worldwide. Her insights have been pivotal in providing a comprehensive picture of the interaction between technological progression and regulatory processes in China.
Expanding beyond traditional topics, Prof. Zhang’s comprehensive portfolio also explores areas such as data privacy laws and Chinese tech firms’ role in global trade. Through her work, she illuminates the unique dynamics at play within China’s rapidly evolving tech industry.
Despite her insightful dialogues on Chinese governmental practices, Prof. Zhang’s relationship with Chinese power players remains tense, triggering her departure from the country.
Exploring Zhang’s insights on Chinese tech
Furthermore, her work remains untranslated in the Chinese language, highlighting the prevailing discord.
Additionally, Prof. Zhang provides a nuanced perspective on the growing popularity of Chinese apps. She cites factors such as China’s vast domestic market, intense corporate competition, and a dedicated labor force, but also expresses concerns about the deliberately addictive designs of apps such as TikTok, Temu, and Shein.
Looking ahead, Prof. Zhang predicts 2023 to be a pivotal year for Chinese tech regulations, specifically due to forthcoming AI laws. These regulations demand greater corporate transparency, which Prof. Zhang views as an enforcement of socialist values and a significant deterrent for foreign tech giants like Google seeking entry into the Chinese market.
While the initial draft of the AI legislation required exactness and truth in AI results, revisions were made considering the inherent uncertainty of AI technology. Instead, companies are now urged to strive for their AI’s accuracy and reliability, which underscores the call for more transparency and accountability in AI operations.
