The classic paradigms of Berry Picking and Information Foraging Theory have framed users as gatherers, opportunistically searching across distributed sources to satisfy evolving information needs. However, the rise of GenAI is driving a fundamental transformation in how people produce, structure, and reuse information - one that these paradigms no longer fully capture. This transformation is analogous to the Neolithic Revolution, when societies shifted from hunting and gathering to cultivation. Generative technologies empower users to "farm" information by planting seeds in the form of prompts, cultivating workflows over time, and harvesting richly structured, relevant yields within their own plots, rather than foraging across others people's patches. In this perspectives paper, we introduce the notion of Information Farming as a conceptual framework and argue that it represents a natural evolution in how people engage with information. Drawing on historical analogy and empirical evidence, we examine the benefits and opportunities of information farming, its implications for design and evaluation, and the accompanying risks posed by this transition. We hypothesize that as GenAI technologies proliferate, cultivating information will increasingly supplant transient, patch-based foraging as a dominant mode of engagement, marking a broader shift in human-information interaction and its study.

翻译：经典的“浆果采摘”和信息觅食理论范式将用户视为采集者，通过在分布式信息源中进行机会性搜索来满足不断演化的信息需求。然而，生成式人工智能的兴起正在从根本上改变人们生产、组织和复用信息的方式——这一转变已无法被上述范式完全涵盖。这种转变类似于新石器时代的农业革命，即人类社会从狩猎采集转向农耕生产。生成式技术使用户能够通过“耕作”信息：以提示词形式播撒种子，随时间推移培育工作流程，并在自己的“田地”中收获结构丰富、内容相关的成果，而非在他人的“地块”间进行觅食。在这篇观点论文中，我们提出“信息耕作”作为概念框架，并论证其代表了人类与信息互动方式的自然演进。通过历史类比与实证依据，我们探讨了信息耕作的优势与机遇、其对设计与评估的影响，以及这一转型伴随的风险。我们假设，随着生成式人工智能技术的普及，培育信息将日益取代短暂、碎片化的觅食模式，成为主导的互动方式，标志着人机信息交互及其研究领域更广泛的范式转移。