Information Farming: From Berry Picking to Berry Growing

2026-01-18

AI Summary

This study addresses the limitations of traditional information foraging models in capturing how users actively generate, structure, and reuse information in the era of generative artificial intelligence (GenAI). Drawing an analogy to the Neolithic Revolution, the paper introduces the conceptual framework of “information farming,” which repositions users from passive foragers to active cultivators who plant prompts as seeds and cultivate evolving information workflows within their personal “fields.” Through historical analogy and empirical observation, integrated with the distinctive affordances of GenAI technologies, the work systematically articulates this paradigm shift and reveals a fundamental transformation in human–information interaction—from foraging to farming. This reconceptualization offers a novel theoretical foundation and perspective for the design, evaluation, and governance of future human–AI collaborative information ecosystems.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Game Theory and Economic Paradigms: Imperfect Information

Application Category

• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

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.

Problem

• Information Foraging
• Generative AI
• Human-Information Interaction
• Information Seeking
• Conceptual Framework

Innovation

• Information Farming
• Generative AI
• Prompt-based Cultivation
• Human-Information Interaction
• Information Foraging Theory