Chasing RATs: Tracing Reading for and as Creative Activity

This paper proposes "Reading Activity Traces" (RATs) to reframe reading as a creative activity by making the interpretive labor of navigating and connecting sources visible, thereby countering the automation of human interpretation through tools like the speculative WikiRAT system.

The Gist

Here is an explanation of the paper "Chasing RATs," translated into everyday language with some creative analogies.

The Big Idea: Reading is a Creative Act, Not Just a Passive One

Imagine you are an artist. Usually, we think of "creativity" as the moment you pick up a paintbrush and start painting a picture. But the authors of this paper argue that creativity actually starts much earlier, when you are looking for inspiration, reading other people's work, and connecting ideas in your head.

Currently, technology treats reading like a conveyor belt. You sit back, and an algorithm (like on TikTok, YouTube, or news feeds) shoves content at you. You consume it, and the system moves on. The paper calls this "passive consumption."

The authors want to change that. They propose that reading is a form of making. When you click from one link to another, you aren't just moving; you are building a unique path through knowledge. You are "authoring" a journey, even if you never write a single word.

The Problem: The "Black Box" of Modern Reading

Think of your current reading experience like a magic trick.

• The Old Way (Hypertext/Wikipedia): You are the magician. You choose which rabbit to pull out of the hat. You click a link about "Space," which leads to "NASA," which leads to "Astronauts." You built that path. It's messy, personal, and full of your own curiosity.
• The New Way (AI & Algorithms): The magician does the trick for you. The system predicts what you want, summarizes the whole story for you in three bullet points, and hands you the final product.

The problem is that by skipping the journey, we lose the creative labor of getting there. We lose the "aha!" moments, the wrong turns that led to new discoveries, and the personal connections we made between ideas. The paper calls this invisible work "Creative Dark Matter." It's the thinking and connecting that happens inside your head, which no one can see, so technology ignores it.

The Solution: Chasing "RATs" (Reading Activity Traces)

To fix this, the authors invented RATs (Reading Activity Traces).

The Analogy: The Snowball vs. The Snowplow

• The Snowplow (Current Tech): The AI clears the snow (information) and gives you a smooth, flat road. You just drive. You don't see the landscape.
• The Snowball (RATs): Imagine you are rolling a snowball down a hill. As it rolls, it picks up snow, twigs, and rocks. The final snowball is a physical record of the entire journey it took. It shows you exactly where it rolled, what it picked up, and how it grew.

RATs are that snowball. They are a digital record that tracks:

1. Where you went: Every link you clicked.
2. What you thought about: How long you lingered on a page (did you skim or really read?).
3. How you connected things: The invisible bridges you built between two unrelated ideas.

The Prototype: WikiRAT

To test this idea, the authors imagined a tool called WikiRAT for Wikipedia.

Imagine you are exploring Wikipedia. You start at "Intentional Community," click to "Stewart Brand," then to "Hypertext," and finally to the "World Wide Web."

• Without WikiRAT: You just read the articles. When you close the tab, the journey is gone.
• With WikiRAT: The tool creates a map of your trip. It doesn't just show the links you clicked; it draws a "fuzzy map" showing how those ideas are related, even if you didn't click the direct link. It lets you draw your own notes on the map, saying, "Hey, this idea reminded me of that other thing I read yesterday."

This map becomes a creative artifact. It's proof that you did the work of sensemaking.

Why Does This Matter?

The authors see three big benefits to making these "traces" visible:

1. For You (The Reader): It's like a personal memory palace. You can look back at your "snowball" and see how you learned something. It helps you understand your own thinking process.
2. For Communities: If everyone shares their "snowballs," we can see collective wisdom. Instead of an algorithm deciding what's popular, we can see the "desire paths" people actually walk. We can see which ideas are connecting in interesting ways across a whole group of people.
3. For the Future of AI: As AI gets better at summarizing and reading for us, we risk losing our ability to be curious. By using RATs, we can compare Human Reading vs. AI Reading.
   • Question: Does an AI get curious? Does it make weird, creative connections?
   • Answer: Probably not. AI usually takes the shortest path. Humans take the scenic route. RATs help us prove that the "scenic route" is where the real creativity happens, so we don't accidentally design tools that delete it.

The Bottom Line

This paper is a call to action for designers and tech creators. It says: "Stop just measuring what people make (the final painting). Start measuring how people find and connect ideas (the journey)."

By tracking our "Reading Activity Traces," we can build tools that respect our curiosity, preserve our creative thinking, and ensure that even in an age of AI, we remain the authors of our own knowledge journeys.

Technical Summary

Based on the paper "Chasing RATs: Tracing Reading for and as Creative Activity" by Sophia Liu and Shm Garanganao Almeda, here is a detailed technical summary:

1. Problem Statement

The authors identify a critical gap in current Creativity Support Tools (CSTs) and information system design:

• Artifact Bias: Creativity research and tool design overwhelmingly prioritize the production of final artifacts (writing, coding, designing) while neglecting the preceding "interpretive labor" (finding, gathering, and making sense of existing information).
• Invisibility of Reading: The cognitive work of reading, navigating, and curating media is often treated as passive consumption or "idleness," rendering it invisible as a creative act.
• Algorithmic Compression: Modern information ecosystems (algorithmic feeds, AI summarization, infinite scroll) are automating and compressing the reading process. These systems prioritize passive consumption and efficiency, stripping away the "friction," "slowness," and "seamfulness" that are essential for deep associative thinking and serendipitous discovery.
• Loss of Human Agency: As AI agents begin to perform research and summarization on behalf of users, the specific "human-driven rabbit hole" experience—characterized by curiosity, association, and reflection—is at risk of being lost or outsourced.

2. Methodology & Proposed Framework

The paper proposes a conceptual framework and a speculative technical instantiation to address these issues:

• Conceptual Extension (RATs): The authors extend the concept of Creative Activity Traces (CATs) to introduce Reading Activity Traces (RATs).
  • Definition: RATs treat reading (navigating, interpreting, curating) not just as a precursor to creation, but as a creative activity in its own right.
  • Scope: RATs capture trajectories of traversal, association, and reflection across interconnected sources (specifically hypertext).
• Speculative Instantiation (WikiRAT): To demonstrate the feasibility of RATs, the authors propose WikiRAT, a browser extension for Wikipedia.
  • Rationale: Wikipedia's explicit, machine-readable hyperlink topology makes it an ideal testbed for tracing "rabbit hole" sessions.
  • Technical Architecture (Three-Level Tracing): WikiRAT is designed to capture reading activity at three distinct levels of abstraction:
    1. Hyperlinkograph: A directed graph recording the explicit path of hyperlinks clicked by the user, annotated with engagement signals (e.g., dwell time).
    2. Computational Fuzzy Linkograph: An algorithmic layer that adds edges between semantically similar articles (even if not explicitly clicked), surfacing implicit conceptual relationships traversed by the reader.
    3. Reflective Linkograph: A manual interface allowing users to explicitly draw connections between concepts that resonated with them, capturing the user's own retrospection and reinterpretation.

3. Key Contributions

• Theoretical Reframing: The paper argues that reading is a "generative epistemic process." It challenges the "artifact bias" in CST research by positing that the process of sensemaking is a valid and valuable creative output.
• Design Material (RATs): The authors introduce RATs as a new "design material" for the HCI community. This shifts the focus from optimizing for speed and output to preserving the "process aesthetics" of human interpretation.
• Counter-Hegemonic Tool: RATs are proposed as a mechanism to resist the "hegemonic narratives" of algorithmic curation. By making associative paths legible and shareable, RATs empower users to own their interpretive labor rather than having it optimized away by black-box algorithms.
• Comparative Instrumentation: The framework provides a method to empirically compare human reading traces against AI agent traces, allowing researchers to quantify exactly what is lost (e.g., associative logic, moments of surprise, dwell behavior) when automation replaces human exploration.

4. Results & Expected Outcomes

Note: As this is a position and proposal paper, empirical results from a user study are not yet available. The "results" presented are theoretical projections and design implications.

• Individual Level: RATs serve as "reflective epistemic artifacts," allowing users to revisit, reuse, and understand their own sensemaking journeys.
• Community Level: Aggregated RATs can form "collective traces," externalizing the interpretive labor of a community. This creates shared infrastructure that highlights "desire paths" (popular, organic navigation routes) versus uncharted areas, offering a human-driven alternative to algorithmic curation.
• Research Level: The framework enables new forms of reader modeling and comparative analysis. It allows researchers to study the "creative dark matter" of intellectual work that is currently invisible in standard metrics.
• AI/Human Comparison: The paper anticipates that implementing WikiRAT will reveal significant structural differences between human and AI browsing, specifically in how they handle non-linear traversal and associative logic.

5. Significance

• Preservation of Human Creativity: In an era of increasing AI automation, RATs offer a way to preserve and value the specific cognitive labor of human interpretation, which is distinct from mere information retrieval.
• New Paradigm for CSTs: The work calls for a shift in Creativity Support Tools from "composition-centric" to "discovery-centric," supporting the entire lifecycle of creative work, including the often-invisible phases of exploration and sensemaking.
• Ethical Design: By making the "signals" that drive adaptation visible and adjustable (unlike opaque algorithmic feeds), RATs promote transparency and user agency in information systems.
• Future Research Direction: The paper sets the stage for future work in "Browsing Activity Traces" (BATs) and the development of intelligent tools that augment rather than replace human curiosity and associative thinking.