生成式人工智能个人信息处理的叠加风险与合规思考OA

With the iterative evolution of generative artificial intelligence,large-scale models represented by DeepSeek are expected to shake offthe past path dependence of"algorithm stacking".Nevertheless,attendant risks in personal information processing keep emerging and are deeply embedded in the risk chain covering data input,training and output.Driven by the profit-seeking attributes of capital,such risks are superimposed,giv-ing rise to multiple hidden dangers:in the horizontal dimension,the"notice-and-consent"rules become a mere formality;in the vertical dimension,personal information is on the verge of leakage;and in the systemic dimen-sion,the foundation of social trust gradually weakens.These phenomena suggest an urgent need to revisit com-pliance governance strategies.In view of the above,at the horizontal dimension,the substantivization of rules shall be promoted to consolidate the compliance foundation,and mechanisms such as technical empowerment,regulatory constraints,traceability,and accountability shall be relied on to break the vicious cycle of risks.At the vertical dimension,rationalized privacy-protection mechanisms shall be adopted to adapt to the characteristics of information flow,so as to safeguard personal privacy while taking public interests into account.At the systemic dimension,standardized risk-prevention mechanisms shall be established to fulfill the bottom-line requirements of enterprise compliance and respond to the interests of diverse stakeholders.Based on the above-mentioned rule-of-law approaches,feasible governance solutions can be offered to mitigate personal-information-process-ing risks arising from generative artificial intelligence.