Generative Artificial Intelligence Impacts and Governance Policy Orientation in the Digital Age

数字时代生成式人工智能影响及治理政策导向

Abstract

In the age of digital transformation, generative AI, exemplified by technologies like ChatGPT, serves as both a catalyst for technological innovation and a potential harbinger of various societal risks. A nuanced and exhaustive understanding of this groundbreaking technology is therefore imperative to harmonize the dual imperatives of technological advancement and effective governance. Employing text analysis techniques to meticulously categorize public comments and formulate theoretical constructs, this research not only offers an incisive look into the inherent complexities and probable societal ramifications of generative AI but also establishes an empirical foundation for crafting governance strategies that are both responsive and responsible. Utilizing a corpus of public commentary on the Reddit platform related to ChatGPT, this study undertakes a multifaceted examination of generative AI. It employs a suite of analytical tools, including Latent Dirichlet Allocation (LDA) models, sentiment analysis, social network analysis, and a bespoke Technology-Technology, Organization, Environment (T-TOE) analytical framework. This comprehensive approach illuminates the various dimensions of generative AI's societal impact. Specifically, the study finds that public discourse largely centers around six core themes, including but not limited to, the technological underpinnings and diverse application domains of generative AI. Among these, issues related to technological transformation and the nuances of human-AI interaction attract heightened attention. Sentiment analysis corroborates a generally optimistic public outlook towards this technology, particularly with regard to its capacity to usher in transformative technological changes. Integrating empirical insights with theoretical extrapolation, the study enables a granular understanding of generative AI. Through the lens of the T-TOE model, the multi-dimensional impact of generative AI is rigorously assessed. In the Technology-Technology dimension, generative AI is posited as a lynchpin for digital and intelligent transformation. Nonetheless, it is accompanied by endogenous technological risks, such as data security vulnerabilities and algorithmic biases, which necessitate vigilant governance. In the Technology-Organization axis, generative AI is expected to substantially enhance organizational efficiency and decision-making prowess. However, the potential for discord between technological adoption and organizational culture—manifesting as managerial missteps or cultural incongruities—raises concerns that warrant careful attention. In the Technology-Environment sphere, generative AI is seen as exerting a pervasive influence on various societal domains through its intelligent capabilities. Yet, lurking beneath are latent risks, including but not limited to, the erosion of privacy norms and the exacerbation of social inequalities, that require preemptive governance measures. In light of these insights, the study concludes by delineating governance strategies across three critical dimensions: technological, organizational, and environmental. In the technological realm, the study advocates for a robust discourse among experts across disciplines to enhance the understanding of inherent risks, coupled with the development of comprehensive technical standards and liability frameworks. Organizationally, it underscores the need for directional guidance from governmental agencies and advocates for a symbiotic collaboration across different sectors, encouraging public-private partnerships for a nuanced approach to governance. Environmentally, the study suggests the construction of a multi-faceted goal system, significant investments in digital infrastructures, and a sustained focus on ensuring both cultural and algorithmic fairness. Taken together, these recommendations offer an integrated governance blueprint, adept at balancing the often competing demands of innovation, societal value, and regulatory order.