The Fraying of Communication and a proposed solution: Bind

In medicine the misinterpretation of a doctors notes could be deadly. I propose that the ambiguity, of even broader discourse, has a serious and undiscovered impact. This problem needs to be researched, and will be expounded further but I would like to explore a solution, which I hope will further open your understanding of the problem.

As with all effective communication, I’m going to name this problem: Fraying. For a mnemonic, consider the ends of a frayed string being one of the many misinterpretations.

His lie was exposed, covered in mud, he had to get away from his unresponsive betraying friend: the quick brown fox jumped over the lazy dog.

That’s my quick attempt of an example where context can be lost. What did the writer mean? What can a reader or machine algorithm misinterpret it to mean? Even with the preceding context, the final sentence can actually still be interpreted many ways. It’s frayed in a moderate way with minor impact.

In this example, it would be possible for the author to simply expound further on that final sentence, but that could ruin the rhythm for the reader (of that story). Another method, is to add such text in parenthesis. Either way, it’s a lot of additional effort by multiple parties. And particularly in business, we strive to distill our messages to be short, sharp and to the point.

My answer of course is a software solution, but one where plain text is still handled and human readable. It’s a simple extensible scheme, and again I name it: Bind (going with a string theme).

The quick [fast speed] brown fox [animal] jumped [causing lift] over [above] the lazy dog [animal]

With this form, any software can present the data. One with understanding of the scheme, can remove the square brackets if there is no facility for an optimized viewing experience. For example:

The quick brown fox jumped over the lazy dog

(Try putting your mouse over the lighter coloured words)

Since the invention of the computer and keyboard, such feats have been possible, but not simply, and certainly not mainstream.

So it would be important to proliferate a Binding text editor which is capable of capturing the intent of the writer.

The benefits of Binding go beyond solving Fray. They add more context for disability accessibility (I would argue Bind is classed as an accessibility feature – for normative people), and depending on how many words are Bound, even assist with language translation.

Imagine Google Translate with a Binding text editor, the translations would be much more accurate. Imagine Google search, where you type “Leave” and hover over the word and select [Paid or unpaid time off work], leaving you less encumbered with irrelevant results.

Such input for search and translation need not wait for people to manually bind historical writing. Natural Language Processing can bear most of the burden and when reviewing results, a human can review the meaning the computer imputed, and edit as needed.

We just need to be able to properly capture our thoughts, and I’m sure we’ll get the hang of it.

Hey, by the way, please add your own narrative ideas for “the quick brown fox jumped over the lazy dog”, what other stories can that sentence tell?

Appendix – Further Draft Specification of Bind:

Trailer MetaData Option:

  • Benefit: the metadata is decoupled visually from the plain text. This makes viewing on systems without support for the Bind metadata still tolerable for users.
  • Format: [PlainText][8x Tabs][JSON Data]
  • Json Schema: { BindVersion: 1, Bindings: […], (IdentifierType: “Snomed”) }
  • Binding Schema: { WordNumber: X, Name: “Z”, Identifier: “Y”, Length: 1}
  • Word Number: Word index, when words are delimited by whitespace and punctuation is trimmed.

Mixed MetaData Option:

  • When multiple preceding words are covered by the Binding, a number of dash indicates how many more words are covered. Bind Text: “John Smith [-Name]” indicates the two words “John Smith” are a Name.
  • The identifiers specified in ontological databases such as Snomed, may be represented with a final dash and then the identifier. Bind Text: “John Smith [-Name-415]” indicates a word definition identifier of 415, which may have a description of “A person’s name”.
  • When a square bracket is intended by the author, output a double square bracket. Bind Text: “John Smith [-Name] [[#123456]]” renders plainly to “John Smith [#123456]”

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