When we change the efficiency of knowledge operations, we change the shape of society.

AI-augmented knowledge summarization, refactoring, & integration are about to transform the world. Again.

1. Knowledge operations matter.

Knowledge operations are ‘actions that involve the conveying or processing of knowledge’. For example, publishing and broadcasting are ‘distribution’ knowledge operations where one ‘conveys’ knowledge to a large audience with minimal feedback. Summarization is a ‘processing’ knowledge operation.

2. The past few decades have seen a •dramatic• decrease in the cost of knowledge operations, both by individuals and collectives.

In particular, increases in ‘distribution’ efficiency due to connectivity (e.g. web, messaging, content networks) and selection (e.g. search, recommendations) have had a tremendous impact on the last decade. Arguably, the impact of these efficiency gains has been greater than that of most other societal forces combined, potentially because most forces change more slowly.

3. Changes to the “efficiency of knowledge operations” have led to societal phase changes — dramatic shifts in structures and power dynamics of nations, organizations, and movements.

At one time, organizational, educational, and physical infrastructure was needed to ensure that modern nations could use horses for transportation, communication, and war. The shape of society changed when we transitioned to a more efficient technology for ‘mobility operations’. We saw similar societal phase changes due to changes in the efficiency of knowledge operations resulting from innovations like the printing press, broadcast media, and now social media.

4. It is challenging for most people (or organizations) to fully appreciate the societal impact of changing the “efficiency of knowledge operations.”

This is why so many were caught flat-footed by the societal impact of Facebook and Twitter, which were considered just “useless” technology by many — until they changed the world. It’s also why the telegraph was expected by many to be a harbinger of world peace.

5. The societal impacts of many new technologies depend significantly on the societal context they are introduced to — and even the methods and timing of their introduction.

One visceral example of this is the development of the atomic bomb and decryption techniques during World War II. The timing and context in which those technologies were introduced had significant impacts on the outcome of the war.

6. We have some — albeit limited — ability to influence the context, timing, and method of the introduction of new technologies.

We need to make sure that we use this influence wisely — and time is of the essence. New technologies create bifurcation points where societies can go in very different directions. One notable example was the introduction to the car in the United States vs. much of Europe. In the US, policymakers and car companies worked together to destroy mass transit infrastructure; in sharp contrast to what happened in many other countries that invested in mass transit (e.g. different societal contexts).

7. AI advances are now enabling communications to be automatically summarized, refactored, & integrated — and will reshape our collective cognition.

Recent AI advances portend a new phase in the increase in the “efficiency of knowledge operations” — one of many we will face simultaneously. Just as with ‘horse infrastructure’, we have built elaborate training regimens and societal structures to manage the tremendous cost and complexity of these knowledge operations. Many of those may soon be rendered irrelevant.

Technical Addendum

Terminology

  • Knowledge operations: actions that involve the conveying or processing of knowledge.
  • Conveying: the creation, distribution, and reception of knowledge between entities (inter-entity operations).
  • Processing: transforming knowledge in some way to create a new knowledge output (intra-entity operations).

Domain Frames

This was inspired by work across many fields, from McLuhanesque media theory, to organizational psychology, to information theory (and the corresponding ‘physics of knowledge operations’). I list a few specific examples below, demonstrating how some of these claims can be framed in the terms of that discipline. It is also worth noting that efficiency is just one of several factors crucial to understand about knowledge operations.

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Aviv Ovadya

Founder of the Thoughtful Technology Project & GMF non-res fellow. Prev Tow fellow & Chief Technologist @ Center for Social Media Responsibility. av@aviv.me