数字经济时代,人工智能驱动的个性化推荐系统在电子商务,新闻,社交等领域应用广泛,同时也带来了数据隐私保护、数据泄露、算法透明性与公平性、以及新兴技术与现行法律框架的冲突等问题,为实现法律之治,可从数据最小化与匿名化、加强监...数字经济时代,人工智能驱动的个性化推荐系统在电子商务,新闻,社交等领域应用广泛,同时也带来了数据隐私保护、数据泄露、算法透明性与公平性、以及新兴技术与现行法律框架的冲突等问题,为实现法律之治,可从数据最小化与匿名化、加强监督与处罚、用户知情权的加强、算法可解释性提升、保持对新兴技术的敏感度与规制几方面对人工智能驱动的个性化系统进行法律约束,切实保障用户权益。In the digital economy era, AI-driven personalized recommendation systems are widely used in e-commerce, news, social networking and other fields. At the same time, they also bring about problems such as data privacy protection, data leakage, algorithm transparency and fairness, and conflicts between emerging technologies and the current legal framework. In order to achieve the rule of law, AI-driven personalized systems can be legally constrained from the aspects of data minimization and anonymization, strengthening supervision and punishment, strengthening user right to know, improving algorithm interpretability, maintaining sensitivity and regulation to emerging technologies, and effectively protecting user rights.展开更多
In order to provide individual information service in digital library,it′s necessary to develop a personalized recommender system Based on information retrieval,information filtering and collaborative filtering techn...In order to provide individual information service in digital library,it′s necessary to develop a personalized recommender system Based on information retrieval,information filtering and collaborative filtering technologies,this article gives some examples of the recommender system and analyzes their key展开更多
文摘数字经济时代,人工智能驱动的个性化推荐系统在电子商务,新闻,社交等领域应用广泛,同时也带来了数据隐私保护、数据泄露、算法透明性与公平性、以及新兴技术与现行法律框架的冲突等问题,为实现法律之治,可从数据最小化与匿名化、加强监督与处罚、用户知情权的加强、算法可解释性提升、保持对新兴技术的敏感度与规制几方面对人工智能驱动的个性化系统进行法律约束,切实保障用户权益。In the digital economy era, AI-driven personalized recommendation systems are widely used in e-commerce, news, social networking and other fields. At the same time, they also bring about problems such as data privacy protection, data leakage, algorithm transparency and fairness, and conflicts between emerging technologies and the current legal framework. In order to achieve the rule of law, AI-driven personalized systems can be legally constrained from the aspects of data minimization and anonymization, strengthening supervision and punishment, strengthening user right to know, improving algorithm interpretability, maintaining sensitivity and regulation to emerging technologies, and effectively protecting user rights.
文摘In order to provide individual information service in digital library,it′s necessary to develop a personalized recommender system Based on information retrieval,information filtering and collaborative filtering technologies,this article gives some examples of the recommender system and analyzes their key
