The Idea Machine label as a subjective sense-making data standard

I really like howJonathan Warden in What Deserves Our Attention? dives into the use of ranking algorithms and subjective sense-making data (reactions (e.g., likes)) for curating attention on social networks, and how this can lead to positive or negative outcomes.

So how should content be ranked? What content deserves our collective attention, and how should this be determined?

This is an important question. This is perhaps the most important question for society to answer today. Attention translates to influence. What people pay attention to influences what they believe. What they buy. How they vote. What they fight for. That’s why autocrats try to control the media. It’s why companies pay billions in advertising

This essential question is the heart of the post, and I think also at the heart of online collective sense-making for developing better information ecosystems.

In particular, I like the idea of having an open ecosystem of subject sense-making data standards and ranking algorithms for curating attention.

But our collective attention should not just be a commodity to be exploited. It should be used for the common good. The collective attention of a society turned towards some common object is what allows the formation of common knowledge, a shared basis of facts, a shared reality. Our collective participation in public discourse produces the shared values and narrative that enables collective action toward common goals.

I think an open ecosystem will lead to more localized, community-specific ontologies of annotations and ranking algorithms. Individuals and communities can pick and choose the labels relevant to them, and fine-tune them to fit their context.

For example, if a particular community is interested in directing attention towards content that is backed by evidence (i.e., evidence-based), they can create a label and accompanying ranking algorithm to make that determination.

The labels and associated ranking algorithms can then be adapted by other communities who are interested in an evidence-based annotation, but fine-tuned to meet their community’s definition of evidence-based.

Thus, we can have community-developed and -managed social annotations that are interoperable and composable.

In other words, I am thinking we can have community-developed ontologies for sense-making.

They should be governed by transparent, democratic protocols that direct society’s collective attention towards production of common knowledge, narratives, values, and culture.

I think this vision is more likely to exist if there is an open ecosystem as described above, where communities, ideally using democratic means, govern their annotations and ranking algorithms.

I have been thinking about this regarding the Idea Machine label, a label I use to categorize curated content in the Distroid Database.

An Idea Machine (IM), as defined by Nadia Asprouhova, is described in the quote below.

An Idea Machine is a self-sustaining organism that contains all the parts needed to turn ideas into outcomes:

• It starts with a distinct ideology, which becomes a memetic engine that drives the formation of a community

• The community’s members start generating ideas amongst themselves

• Eventually, they form an agenda, which articulates how the ideology will be brought into the world. (Communities need agendas to become idea machines; otherwise, they’re just a group of likeminded people, without a directed purpose.)

• The agenda is capitalized by one or several major funders, whose presence ensures that the community’s ideas can move from theory to practice – both in terms of financing, as well as lending operational skills to the effort. (Without funding, an idea machine is just that: an inert system that needs fuel to turn the crank and get it moving.)

I find this label useful for categorizing content from the frontier because many projects are influenced by, or are working pursuant towards, the goals of one or more IMs (i.e., movements).

Additionally, the IM label makes it easier to recommend content, and to create collections of related content for audiences in one or more niches.

I personally find it helpful to look for content at the intersections of one or more IMs, because this helps understand the flexibility and re-use of tooling and ideas in one context, and how they can be utilized in another context.

The current IMs I have identified are:

1. Web3

2. Tools for Thought

3. Platform Cooperativism

4. Metascience

5. Open Science

6. Effective Altruism

7. Responsible Technology

8. Climate Change

Inspired by the work of Common Sensemakers, I developed a draft of the Distroid Annotation Standard, a metadata standard for subjective sense-making labels, and a draft label for IM.

You can find the draft of the IM label as a JSON file on Ledgerback’s GitHub, or in the code block below.

I do not expect that my preferred definition for an IM is the only definition that exists. Thus, I would also like to see others adapt the IM label, or even make their own original IM label to meet their own definition.

Draft of IM Label

{
  "name": "Idea Machine",
  "definition": "a self-sustaining organism that contains all the parts needed to turn ideas into outcomes",
  "task": [
    "classification"
  ],
  "sense-making": "categorizing a piece of content as being associated with one or more  idea machine(s)",
  "values": {
    "options": [
      "Web3",
      "Tools for Thought",
      "Platform Cooperativism",
      "Metascience",
      "Open Science",
      "Effective Altruism",
      "Responsible Technology",
      "Climate Change"
    ],
    "selection": [
      "single-select",
      "multi-select"
    ],
    "restrictions": [
      "None"
    ]
  },
  "data-type": "String",
  "creator": [
    "Charles Adjovu"
  ],
  "references": [
    {
      "title": "Idea machines",
      "author": "Nadia Asparouhova",
      "url": "https://nadia.xyz/idea-machines",
      "datePublished": "2022-05-12"
    }
  ],
  "expression": {
    "interactive": {
      "html": {
        "select": "<select name='ideamachine' id='machine'><option value='ideamachine'>Example value</option></select>"
      }
    },
    "non-interactive": {
      "html": {
        "span": "<span> Idea machine </span>"
      },
      "xml": {
        "ideamachine": "<ideamachine> Idea machine </ideamachine>"
      },
      "json-ld": {
        "openAnnotation": {
          "@type": "OpenAnnotationTag",
          "annotations": [
            "ideamachine-1-v1"
          ]
        }
      }
    }
  },
  "identifiers": {
    "common-name": "ideamachine-v1",
    "SHA256": "cyrptohash"
  },
  "semanticTriples": {
    "subject": "content name",
    "verb": "categorized in",
    "object": "idea machine"
  },
  "languages": [
    "en_us"
  ],
  "audiences": {
    "intended": "all ages"
  }
}

Possible Future Work

Possible future work for the idea includes:

1. Creating a label generator and validator/verifier

2. A registry of subjective sense-making labels

3. A registry of issuers of subjective sense-making labels

4. A framework for issuing labels as verifiable credentials, similar to The CommonTrust Network™