Analogies suggest that compression explains increasing average IQs. Collectively, software engineers improve the efficiency of data compression software. Language encodes (compresses) perceptions, concepts, theories. Coding supplied by language is analogous to coding of algorithms by software. Also, words are reified abstractions: they are things we can manipulate abstractly — juggling them in a brain. All members of society over all generations collectively improve the efficiency of language. Since abstractions encoded by language are more efficient people can more easily juggle more compressed more efficient words representing concepts, and so can solve problems more efficiently. The next analogy is to economics. Societies collectively compress concepts for the anticipated maximum payoff. Hence all processes relating to problem solving, including the lexicon, should over time reflect the same average rate of increase in efficiency. Society channels problem solving resources for the best economic return. Measurements of increases in the size of the English lexicon, increased efficiency in lighting relative to labor cost, increased longevity and other measures seem to reflect the effect compression has on increasing average IQs, in effect the average problem solving rate. Are there are relevant arguments? Are there other ways to measure this effect? I have some articles on arXiv and RG that consider these issues.
Though I could not fully understand your argument, I would like to add some information regarding the term "compress/compression" used in Computer Science. Data compression is done solely for reducing the storage or bandwidth requirements of data. The objective of any compression algorithm is to reduce the redundancies. Typically any digital element has some amount of coding redundancies. There are several other redundancy types available (temporal redundancy, spatial redundancy and psycho-visual/psycho-audible redundancy etc.) based on the type of digital data. Giving the ability to better understand or efficiently analyse is not a generic objective of the "compression" in computer science. You can find many research papers in which the researchers are trying to do different data analysis in compressed domain yet struggling to achieve similar results as it will be in non-compressed or original domain of the data. As a summary, if something is compressed in computer science domain, that thing will take less space in the digital space but most probably less understandable for human and hard to analyse.
However, the term "encoding/encode" is used for refer some process which convert the data to achieve some specific task. encoding is a wider term where compression is narrower.
"Coding supplied by language is analogous to coding of algorithms by software. Also, words are reified abstractions: they are things we can manipulate abstractly — juggling them in a brain."
This is the traditional, mid-twentieth century cognitivist perspective. It has been challenged by the embodied/enactive paradigm that took form and became influential in the last decade of the past century and continues to evolve and transform the way cognition is seen in a wide range of disciplines, including linguistics.
I have put together a thematic bibliography for my students and myself. It can be downloaded here:
https://www.researchgate.net/publication/322234671
(section 8 deals with language).
Dr. Wright-Carr,
This seems to be a great resource. May I ask, of the articles in section 8, in the bibliography you compiled, are there any, say 3 to 5 articles of those listed, that you would recommend as good starting places.
Thank you.
Bob Shour
That's a good question. It depends on what you're interested in. Perhaps for an overview some good sources would be Elk (2016), Gallese & Cuccio (2015), the two papers by Kravchenko (2006, 2007), and Ströbel (2016). For a broader view (not focused on language), a classic work is the book by Varela, Thompson & Rosch (1993). I hope you enjoy these!
You're welcome. From an embodied/enactive perspective, perhaps the ever-widening networks of people communicating with each other is a factor in increasing IQs. The idea of extended cognition sees minds transcending the limits of the epidermis, since cognition (conscious and unconscious) is seen as emerging from the interactions of an organism with its/her/his physical and sociocultural environments. Thus cognition is shared, or distributed, among the population that is interacting. An automated search for the word "extended" in the bibliography I posted here a few hours ago will turn up several sources that explore this idea.
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