That Which Is Accepted Today Is Sometimes Discarded Tomorrow, Essay Example

I would argue that that which is accepted today is often discarded tomorrow. But we have to be careful. What is “knowledge” anyway? Is knowledge only scientific or mathematical because only such knowledge is “certain”? Is a culture’s experience in living and solving problems “knowledge” even though it might not be certain? What if such knowledge is not widely or consciously known in detail, like the body of law? (“Ignorance of the law is no excuse,” we are told, which doesn’t stop old laws from being discarded or ignored and new ones written in their place.) What if some kinds of  knowledge spring from something too deep within us as individuals and as a culture to be scarcely aware of it at all, only coming to the surface of our perception via our own actions — the response to events that we may or may not have brought about ourselves as we face changing real-world conditions? Regardless, my thesis is that discarding knowledge is, for better or worse, the rule, not the exception — but with one proviso: discarded knowledge may be picked up again and brought back into acceptance and at least limited use,[1] the only counterargument I can think of to my first assertion.

The theory of knowledge is known as epistemology, which one source defines as “is the study of knowledge and justified belief” (Stanford Encyclopedia of Philosophy), which sounds a bit circular — the theory of knowledge includes the study of knowledge. The dictionary Merriam-Webster defines knowledge in various more or less intuitively ways, but the one I prefer is: “The sum of what is known :  the body of truth, information, and principles acquired by humankind” (Merriam-Webster). We can probably assume that assumptions — basically axioms, like those in geometry — are “acquired” through our experiences in learning about our world, and so count as knowledge of a sort, and act as a set of principles, those maybe being defined as tested and accepted assumptions. Not that those assumptions are always right. They are not. That is why we frequently need to discard them. Yet principles derived from those changing assumptions don’t themselves necessarily change.

To see what I mean, maybe we should divide knowledge into the hard scientific kind (mathematics, physics, etc.) and the “soft” (if not squishy soft) cultural kind. We can probably take for granted that they have different assumptions but similar principles derived from those assumptions. One current example might be Google’s motto of Don’t Be Evil. That is a good principal with roots in the mathematical world of computer programming and the social world of how information found on the Web via programming is used by people who use Google — including (or maybe especially) those within Google itself — its employees and major stockholders. But can mathematics and programming themselves be “evil”? One wouldn’t think so, at least at first. But math and programming aren’t platonic ideals derived from perfect celestial bodies. They are the products of human beings. They are subject to fashions and fads,[2] showing that even the pure thought of numbers is, in one form another, tossing things aside. As mathematician Henri Lebesgue (1875 – 1941) once wrote of his profession: “Mathematicians have never been in full agreement on their science, though it is said to be the science of self-evident verities — absolute, indisputable and definitive. They . . . have always considered their own age to be a period of crisis” (Felix) — a fact that non-mathematicians must find strange.

The flip side of epistemology seems to be ontology, which one academic website defines with a question: What Constitutes Reality and How Can We Understand Existence? (Raddon). One can see why these two definitions go together, and it is hard to see how that conclusion will ever be discarded. But to keep with the Don’t Be Evil theme, it turns out that ontologies (note the plural) are fundamental to the subject of artificial intelligence (AI) — “knowledge-based, expert systems” (Bench-Capon).  Right away we can see that an ontology in the AI field is not the same thing as our more general, philosophical ontology. Instead, it is a strict (“explicit”) set of definitions that set out exactly what the system is and is not, what it can do and what it cannot. In that sense, it might be thought of as equivalent to Euclidean (or non-Euclidean) geometry. In other words, I think that an AI ontology is deductive: it sets out its conditions, and if logic is followed, some conclusions will be true by definition — which is not the case with inductive logic, where conclusions are drawn and laws passed based on experience alone.

Induction and deduction might be all the top-predator categories of logic and experience we really need. Induction argues from the specific to the general: red sky at morning, sailors take warning, red sky at night, sailors delight. You can see that over the years, sailors observed specific sunrises and sunsets and the weather that accompanied them. From those specific instances, two general conclusions were drawn about them. Deduction argues from the general to the specific. Geometry (and AI) is deductive: all points, lines, etc. and defined in advance — the groundwork is laid first. Then we can say in an infinite variety of situations, that this must be a [point, line] — by definition. Within that logical system, it cannot be false. But look at Euclid’s fifth postulate, the “parallel postulate.”[3]Attempts have been made time and again to discard it as a postulate and prove it as a theorem from the other postulates. The problem is the lack of proof.

Maybe the key point about knowledge is that of deductive-quality proof. I have asserted that it is the rule rather than the exception to discard knowledge tomorrow that we accept today (but that such discarded knowledge may be picked back up again).  Is it only knowledge without proof that is discarded? That could include a lot of scientific (or “scientific”) knowledge — bogus cures, etc.  In many such cases, the “proof” was wrong, or there was only inductive-style proof, not deductive proof, which itself must be the result of controlled experiments or (in the case of AI) ontologies, defined and designed in advance.

That is my on-the-fly nutshell description of “knowledge” — its basic kinds or categories. But now to the argument that more is discarded, if only momentarily, than is kept. It seems like a stretch. Surely we keep more than we discard because we think more of it is (still) right. Actually, I think the question itself is essentially a deliberate ploy to spur discussion than it is a serious assertion. I’m agreeing with whoever said “The past is a foreign country: they do things differently there.”[4] That means people have consistently discarded knowledge as the years passed to the present. We can predict that such discardings will continue. But we have to make an important point. The discardings do not leave vacuums. They are filled with new information.

At least that’s the case with science. People discarded the notion that the earth was the center of the solar system. It was replaced with knowledge that the sun was the center. The mathematicians described by Lebsegue (see above) did the same and no doubt still do. But what about discardings that leave vacuums? I think that happens in the social and political sphere. Consider what happens after political revolutions. Old ways are tossed aside and new leaders come to the fore, ignorant of political realities. Again and again human societies are forced to re-learn the old rules — a case of discardings pick back up, dusted off, and grimly (or happily) put back to work. This is probably why so many revolutions don’t work as well as they are supposed to. As an example of that, think of the book Animal Farm by George Orwell, in which the farm animals overthrow their human owners and, step by step, end up recreating the regime they had suffered under before, only this time with the pigs in charge.[5] Think how many times people fall in love and marry, only to divorce. (In the field of social knowledge, I could rest my case for routine discardings on that example alone.) Think of friends that come and go, and elections, and the people who, year after year, vote in them because they think this time it will make a difference. Think in general how bad modern societies can be in raising their children, as contrasted with how well primitive, indigenous societies do the job. It seems that when societies adapt Western values, they forget the old rules of human behavior, rules that really never change. And yet in this sphere of social values, some things do say the same: Western societies are almost as bad (and maybe are even worse) at dealing with indigenous peoples as Christopher Columbus was. (Think: diabetes, brought about by indigenous people eating fast food.)

Love, courage, fairness, honesty, sacrifice. Even that knowledge can be forgotten in extreme situations caused by war, starvation, and political chaos. Think of all the rules of humanity discarded by Hitler, Stalin, Mao, and drug lords — and their followers. People seem to have a facility in forgetting their human knowledge-base for as long as it is necessary to forget it, and then to put back on the robes of law and justice, and the business suites of commerce as circumstances permit. The old rules are found  — we’ll always remember where we hid them. And we will always remember how to bury them again. Thanks to GPS, we’ll never lose them.

Works Cited

Bench-Capon, Trevor. Ontologies in AI and Law. Liverpool, n.d. PDF.

Felix, Lucienne. The Modern Aspect of Mathematics. New York: Basic Books, 1960. Print.

Merriam-Webster. 2014. Website. 28 August 2014.

Raddon, Arwen. Early Stage Research Training: Epistemology & Ontology in Social Science Research. n.d. Website. 28 August 2014.

Stanford Encyclopedia of Philosophy. 2014. Website. 28 August 2014.

[1] See http://www.npr.org/blogs/krulwich/2011/02/04/133188723/tools-never-die-waddaya-mean-never .

[2] See http://michaelochurch.wordpress.com/2011/08/28/object-disoriented-programming/ and http://educationnext.org/anamazeingapproachtomath/ .  We can see here how, at least in the sciences, discarded (unfashionable) knowledge may eventually be reused after the fads have run their course, and so confirming my proviso or counterargument, stated in the last sentence of the introductory paragraph.

[3] Omitted to save space. The exact wording is available on the Web.

[4] I Googled the phrase. It was by L.P. Hartley, from his novel The Go-Between.

[5] Full text of the book in PDF form can be found at: http://msxnet.org/orwell/print/animal_farm.pdf.