1.1 Communicating Ideas
1.2 Perceiving Ideas
1.3 Key to Immortality
1.4 Applications of the Theory
1.4.1 Understanding Innovation
1.4.2 Humans and Machines
References
As humans, we measure extensively. We measure deterministically and probabilistically. We seek measurements for our height and weight and the temperature (be it for indoors or outdoors, or merely as conversation starters) just as often as we desire to learn the odds of winning a gamble. We try to measure intelligence with GPAs, SATs, IQs, and a laundry list of other tests. We measure value with all manner of explicit and implicit prices. And we measure copiously and religiously in all things pertaining to sports.
We also measure hypothetically. So deep does our penchant for measuring things go that we like to create our own units of measurement where none exist or make any sense. We wonder how much our friends like us by how much they desire to engage with us; how ardently our significant others love us by how deeply they look into our eyes or how much thought they put into a gift; how committed we are to some cause by how much fervidness we exhibit, and even how our current behavior entitles us to receive benefits in the afterlife.
The reason we measure some idea is, of course, that we seek information that often helps us assess, compute, or predict some other idea. We rely on mental models that associate ideas in a desire to draw ever clearer links between a range of ideas and the information they can confer; this is a visceral need for humans because it is also an infinite process. The infinitely expansible character of ideas turns all ways of thinking into compromises from exactitude to varying degrees of certainty. Information on ideas can often have critical survival value, and so there appear to be sound evolutionary reasons for being able to improve our measures for the information inherent in ideas. It is no surprise then that a great variety of animals have some ability to measure as well. Some basic facility with counting, for example, is now thought to be a fairly widespread ability among so large a number of animals that a biological basis for it is suspected (Tennesen 2009). It has even been shown that some primates may have the ability to understand the basic principles of barter (Paulos 2011).
Yet, measuring in the pervasive manner that we do is, by and large, a uniquely human attribute.
The reason for this distinction is that humans, regardless of their particular pursuits and interests in life, are not merely satisfied in being able to apprehend ideas, but we are also interested in being able to clarify our ideas by extending them with other ideas, developing them into better ideas and merging them with others in creating new ideas. It is this process that drives us to look beyond the limits of our own minds and to to those of others in our community; as such, it is an essential basis upon which a variety of communities can hold significance to an individual.
In Yuval Noah Harariâs remarkably broad and insightful book, Sapiens, one of the central arguments is the observation that humans have established themselves as the predominant species on the planet by dint of their capacity for fiction and ability for abstractions from reality (Harari 2015). He argues that these characteristics have crucial significance in enabling humans to cooperate in ever larger communities. The human ability to make abstractions in their ideas in useful ways is, indeed, remarkable. Daniel Dennett , in his influential book on the philosophy of the mind, The Intentional Stance, suggested that an understanding of the characteristics of a system and the behavior of people is open to subjective interpretation, but that these interpretations rely on the premise of shared beliefs and rational thinking. He defined three levels of abstraction that humans can take. The âphysical stanceâ would be applicable to phenomena that rely on laws that are useful in making reliable predictions. These largely comprise physical laws that permit consistent and reliable predictions. At one level of abstraction higher than that is the âdesign stanceâ, which takes the physical stance as a given and allows understanding objects that are built or designed on their basis; the physical laws are largely subsumed within the design. At the highest level of abstraction, Dennett proposed the âintentional stanceâ, where assumptions are made on the beliefs, desires, and the objectives of others (Dennett 1989).
We find ourselves in ready agreement with these observations, and with the aid of our theory will seek to articulate an intuitive and fundamental theoretical process for ideas; doing so can suggest why it is that some ideas can exist in isolation where others facilitate the creation of larger groups. What we gain by undertaking this exercise is a broader understanding of how ideas develop, often by blurring the lines across levels of abstraction and between fiction and fact while seeing both as waypoints along an unbroken process. Since this process is variegated and multidimensional, it is, we think, easy to perceive it as being marked by distinct âphasesâ when seen with the help of a chronological framework.
It is perhaps useful at this juncture to also suggest how our view differs from the tradition of research on the Theory of Mind , or ToM, which examines how humans go about understanding the state of their own, as well as someone elseâs mind, including their desires, ambitions, objectives, and beliefs. While there are some obvious similarities in our goal to understand an individualâs ideas, principally our intention is more modest; we wish to examine the process by which there is an innovation of ideas and, as a result, we emphasize the primacy of ideas over the state of an individualâs mind, or how it develops and differs from its peers. With our theory, we are interested in studying the interconnectivity over time and space of all forms of ideas; the interesting topic of the significance of their states, as represented within the mind of any given individual or set of individuals, is of secondary importance for the purpose of our theory. There is, of course, a whole gamut of issues pertaining to interpersonal relationships and perceptions that are then diluted in our approach, but the benefit is that of underscoring the fact that ideas have an independent life and deserve examination in their own right, free from direct attachment to humans.
Withal, by understanding the nature of ideas we are able to use them as a key unit of analysis to examine both creativity and innovation. It is, therefore, unsurprising that the ability to measure ideas to yield usable information is an attribute that we have been at pains to engineer, codify, and intensify with the help of the machines we create. We tend naturally to think of the age of computers as being pivotal in terms of introducing measurement and computation to machines, but this underemphasizes the fact that self-regulation in machines has been a characteristic that was routinely seen even in the earliest of steam engines at the beginning of the eighteenth century. What is striking now is, of course, the extent to which machines have permeated their influence in our lives and the degree to which their capabilities exceed our own.
Evolution has indubitably provided humans a significant advantage over other species by increasing our relative skills for the processing of information over millennia. Taking the cue from evolutionary logic, humans are now at the verge of building adaptive evolutionary computation systems that can outdo both primitive machines and humans. And this evolution in machine learning is happening at a rate that far outstrips anything in the story of our own evolution.
1.1 Communicating Ideas
There are ostensibly between six and seven thousand languages in existence today. The discrepancy in counting up exactly how many there actually are is understandable for at least two very good reasons. First, many of the languages have no written tradition and are spoken by small populations, often just single-digit cohorts of native speakers who live in remote locations. When such languages will go extinct, they are likely to vanish without leaving much of a trace. Many do, despite the laudable efforts of intrepid linguists who take the time to visit the last remaining speakers of such languages and desperately compile records. Second, the rate at which languages are disappearing is quite staggering (Wilford 2007). It has been estimated that three or four dozen languages are going extinct every year, their traditional speakers opting to learn a more predominantly used language and assimilating into a larger society (Pagel 2012). Naturally, that rate will not continue forever, and some languages will withstand the exodus of its speakers simply by being able to rely on maintaining a large enough community of speakers or on a significant volume of cultural resources that employ their usage. Nevertheless, it has been suggested that in another hundred years or so, the total number of languages remaining will likely decrease by a factor of ten. The languages that do survive will generally be relatively simpler than their predecessors (McWhorter 2015).
Reading about this alarming state of affairs makes us think of what needs languages suffice and why it is that at least some of those needs may have required more languages in the past than might be called for in the future. It appears that one can consider that question from a number of different perspectives, including the economics of how languages facilitate transactions, the sociology of how languages serve as instruments of cultural transmission, the psychology of how languages might serve as modes for cognition and for regulation of behavior, and so forth. One of Noam Chomskyâs key contributions to linguistics was the fascinating proposition that humans are born with a universal grammar that is invariant of the language that they eventually speak. Steven Pinker refined this premise in favor of an evolutionary expedience for humans to be uniquely endowed with an instinct for language (Pinker 2007). While we see this field of enquiry to be a very useful step in the direction of the generality we seek in understanding ideas and innovation, the simpler observation that perhaps has the broadest intuitive appeal belongs to John Locke, who noted that words are nothing but the markers of the ideas that the speaker has in her mind.
When we think about most everyday objects, our ability to refer to them in context is based on their essential features. A hammer devoid of its recognizable featuresâperhaps one that has neither a handle nor a headâmay, of course, still be used as a hammer. However, understanding this other type of âhammerâ would likely require a great deal more effort from a community of people that has already clarified what the essential features of a hammer are over the years, and now relies on this shared definition implicitly. The members of this community would now need to re-evaluate how the featuresâthe âcomponentâ ideasâthat this newfangled hammer represents permits it to also function like the hammer that they are familiar with. They would, in all likelihood, find it convenient to think of the features of this new hammer more abstractly and then see how these abstract features enable it to leverage the same ideasâthe same principles of physics and mechanics, the same ergonomics and feelâthat their own trusty hammer represents. Such abstraction can, of course, vary in difficulty; indeed, if the new hammer looked like a feather suspended by a set of springs, we may even find ourselves at a loss to understand how any of its features might reasonably be translated to those of the trusty hammer in our tool chests.
Note that this example need not have anything to do with languages. It is, of course, true that when we consider the speakers of different languages, we add an interesting layer of complexity in the communication of ideas. However, it is useful to examine the role that ideas play on their own, free from the language that is used to express them.
Generally, the point is simple: Our perceptions of objects around us rely on âlabels â we ascribe to sets of ideas that represent those objects. All objects that are commonly known across some group of people have recognizable features, and while there may be some variance among them in the manner they perceive these features, there is broad consensus on their relevance to the object. This defined group of people understands the objectâs function and shares a language that expresses the ideas of its features with sufficient precision for the objectâs label alone to succinctly convey some acknowledged purpose and intent. Through their use of the object their understanding of the objectâs characteristics, whether good or bad, grows. When the object is then introduced to a second group of individuals who have previously never encountered it the label loses some if not all meaning; commensurate with the degree of ignorance of the object within the second group, the first group would then need to present the ideas that define the object so that it can be ârediscoveredâ by the people in the second group. These individuals wonder what the purpose of the object might be, and perhaps even how it contrasts with objects that might be serving similar functions in their own ...
