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.

Technology creators, funders, and policymakers must understand how changes in knowledge operations can impact society.
This is intended to be a short primer making a series of claims about these impacts. Each claim could be a book (many are).

1. Knowledge operations matter.

Many core ‘societal activities’—from conflict mediation to identity formation—both (1) require knowledge operations and (2) operate in a world awash with ongoing knowledge operations that influence the outcomes of those activities. Consequently, knowledge operations are fundamental to how we think, how we act, and who we are — individually and collectively. They impact emotion, culture, politics, and power.

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

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.

These efficiency changes impact everything from how we make war, to how we love, to how our brains work, to how we find meaning. This is not new.

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

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.

Similarly, new communications technologies in some societies have likely increased polarization, while in others they may have reduced it — potentially as a result of their political structure or culture.

There are many socio-technical and political economy considerations that determine the impact of more efficient knowledge operations in a given context, e.g. (1) the types of costs being reduced, (2) the actors paying (or not paying) the costs of those operations previously and (3) the externalities of these operations and the degree to which they can they be managed.

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

As we have seen with the rise of radio, TV, and now social media, if we want more efficient knowledge operations to lead to good societal outcomes, we must act to make it so. It is unlikely to happen automatically.

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

We have also failed to resolve many crucial education, conflict mediation, and governance problems as a result of that computational complexity. New ‘knowledge technologies’ may allow us to to succeed.

Technical Addendum

Terminology

  • 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

A. Traditional Economic Frame: The functional marginal cost of many operations is being dramatically reduced—often to ~zero.
This is partly because the types of resources needed for those operations have changed from atoms to bits, or from human time to compute time, such that the current limiting resource is no longer necessary.

B. Computer Science Frame: We are significantly decreasing the *computational complexity of knowledge operations.*
In asymptotic computational complexity terms, selection and connectivity have made knowledge operations that were logarithmic with human time (or much worse) into operations that are functionally constant time: O(≥log(n)) → O(1). Machine learning advances will bring these kinds of speedups to many new domains.

Decreasing computational complexity is an even more profound shift than making something 2x more efficient or even 1000x more efficient — it’s changing how the ‘amount of stuff in the system’ impacts efficiency.

C. Behavioral Economics Frame: More efficient knowledge operations impact our ‘bounded rationality’.
Both individuals and groups of people have bounded rationality. Arguably, many (though clearly not all) of the societal problems we face are an indirect result of that bounded rationality making effective decision-making and conflict resolution challenging. Thus, more efficient knowledge operations may significantly enhance our ability to resolve these conflicts. Whether or not this is true depends the relative advantage that increased efficiency provides to those seeking to resolve a conflict vs. those seeking to prevent resolution (among other factors).

Written by Aviv Ovadya at The Thoughtful Technology Project.
You can find Aviv on Twitter
@metaviv, this mailing list, or via email.
This is excerpted from a more formal piece in-progress; future excerpts will go into detail around the emergent threats and opportunities relating to specific knowledge operations.

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

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