个性化如何推动消费者的选择和自主性

DANIEL CASTRO|MAY 2026 As new technologies such as AI expand both user-directed and provider-driven personalizationcapabilities in digital systems, policymakers should ensure that personalization strengthens KEY TAKEAWAYS Personalization in digital systems has evolved from simple user settings into advanced,context-aware AI systems. These technologies consistently help consumers manage Consumers strongly favor digital systems that maintain context and rememberpreferences. Abstract privacy concerns rarely stop users from adopting tools that offer Strict regulatory approaches such as GDPR create heavy compliance burdens that stifletech start-ups. This unintentionally concentrates market power and delays the rollout of Policy frameworks should regulate actual harmful outcomes such as fraud and deception CONTENTS Key Takeaways................................................................................................................... 1Introduction....................................................................................................................... 3The Evolution of Personalization in Digital Technology ........................................................... 4Stateless Computing and Early Persistence (Pre-1990s) ..................................................... 4The Customization Era (1990s–2000s)............................................................................. 7The Algorithmic Era (2000s–2010s)................................................................................. 8The Predictive Era (2010s–Present)................................................................................ 10 INTRODUCTION A new generation of digital systems—driven by growing adoption of artificial intelligence (AI)—ismaking personalization more visible, persistent, and integrated into daily life. Unlike earlierdigital services that operated largely within isolated applications, emerging AI tools increasinglyaccess users’ email, calendars, phones, browsers, productivity tools, commerce platforms, socialmedia, and financial services. These systems can retain context across interactions, remember Major technology firms are rapidly expanding these capabilities. In 2025, OpenAI expandedChatGPT’s memory features to allow the system to reference past conversations and user preferences across sessions.2In 2026, Google introduced “Personal Intelligence” and memorytools in Gemini that connect across Gmail, Photos, Search, YouTube, and other services todeliver more context-aware assistance.3Microsoft has similarly announced memory and These developments have spurred debate about the future of personalization.5Critics often frameincreasingly context-aware AI systems as a form of pervasive surveillance that could enable manipulation, reduce privacy, or concentrate excessive informational power in large technologyfirms.6Concerns surrounding AI memory, persistent context, and cross-platform integration Digital services have long adapted to user preferences, from customized ringtones and homepagelayouts to recommendation systems, search ranking, autocomplete, navigation apps, and streaming At the same time, consumer expectations are moving in the opposite direction. Many usersincreasingly expect digital systems to recognize them, remember prior interactions, and reduce repetitive tasks.8Consumers routinely express frustration when systems fail to retain preferences,lose conversational context, or require the same information to be repeatedly re-entered. Theappeal of AI assistants is not simply automation; it is continuity. Systems that can remember This tension reflects two competing narratives about personalization. One views personalizationprimarily as a surveillance machine that extracts data to influence user behavior. The other viewsit as a digital concierge: a tool that helps users manage information overload, reduce searchcosts, and receive services that better match their individual needs. Both perspectives contain personalization also delivers substantial consumer value by helping users find information,simplify decisions, and interact with increasingly complex digital environments more effectively. Importantly, personalization is not a new phenomenon created by AI. Digital services have longadapted to user preferences, from customized ringtones and homepage layouts torecommendation systems, search ranking, autocomplete, navigation apps, and streaming At its core, personalization is fundamentally about recognition and continuity. History shows thatconsumers generally prefer systems that remember prior interactions, anticipate needs, andreduce unnecessary repetition. The central policy challenge is therefore not whetherpersonalization should exist, but how to ensure that it develops in ways that preserve To achieve this balance and guide the future of context-aware technology, this report proposes aproportional governance framework built around six core policy principle