For this week, my goal was to understand information from multiple angles. From the Gleick reading, he focused on the theory of information and how it composes multiple layers. Some questions he asked were: Can machines think and what tasks were mechanical?This got me thinking about what’s actually being produced such as a word, image, or website, but also automatic or pre-determined, such as algorithm improvements. He says, “the justification lies in the fact that the human memory is necessarily limited…Humans solve problems with intuition, imagination, flashes of insight – arguably non mechanical calculation…” (pg. 15). This got me thinking about how absolute certainty plays a required role in machine computing which is able to include all preceding decimals for information. This makes me question, is information in a computer a tool or is it a machine within its own mechanics? Is information just based of gatherings and collections of signals?
Transitioning to the Irvine piece, I really enjoyed learning about the designs of information interfaces and how important the “signal” role is. I am still falling short on the signal transmission theory and the verbiage associated with it. It was difficult to unpack the question at hand, but I’m hoping I achieved a general sense of how to de-black box this.
The main features of signal transmission theory of information would be the digital design of “information” that is structured as “units” of “preserved structures” which use electricity via bits and bytes to extract certain patterns that signal an internal message that gets completed. The signal code transmission model is not a description of meaning because it’s not meant to describe “meanings”. It is designed as single units that are “point-to-point” models that display how “information” passes through a channel. There are data types, signs, tokens, data types, etc. that are involved in this encoding and decoding process. (Irvine, pg. 13-20).
Information theory model is essential for everything electronic and digital because digitized data, information, or tasks do not get performed without being instructed a certain way. This type of model helps ensure certainty with numbers, codes, or data that is transmitted electronically and received electronically, whereas it lacks the verbiage to further explain what each subset performs in terms of semantic meanings, or the specific uses and meanings of other systems. This could also be due to the information theory model is designed to DISPLAY how something is achieved electronically in the simplest way.
It doesn’t necessarily apply to the type of model that would fully explain sign and symbol systems, because it is laid out to explain how something gets done, vs. something of a “symbol” and that typically would not change within the model. Whereas, explaining a sign or a symbol in this type of language wouldn’t fully apply because the information model is based of E-signals that are transmitted and received, and in other cases symbols and signs systems are not.
To expand on this more with more easy to understand vocabulary, I wanted to pull in an outside source through video help me understand this better. When in doubt, YouTube it out! I found a great video that describes how speakers create sound waves, and how signals are transmitted. The user uses physical drawings to reproduce real life signals and explains how “Information” travels wirelessly. I recommend this video to the rest of the class to help us gather more simple terminology of this process.
James Gleick, The Information: A History, a Theory, a Flood. (New York, NY: Pantheon, 2011).
Excerpts from Introduction and Chap. 7.
Martin Irvine, “Introduction to the Technical Theory of Information” 2019.