SYNOPSIS OF ARGUMENT
Knowledge is a relation between people (the ones who claim to know) and a set of assertions. The knowers commit to those assertions by calling them true. Commitment is an emotional component of truth. People who commit to assertions call them facts. What a group of people call true or knowledge varies. People inquire about the world and seek to understand it. Sciences use methods of inquiry for ascertaining truth that have produced useful results. The usefulness of these methods encourages us to use these methods in ever wider contexts. Even these methods allow for disagreement and revision over time in scientific communities. These revisions and disagreements are in the nature of human inquiry and do not invalidate the inquiry.
‘Knowledge’ is a difficult word to define. Let us first assemble a set of words that often appear in the same contexts as ‘knowledge.’ Can one know something that is in fact false? It wouldn’t seem so. “John knows that the U.S. doesn’t have a constitution” sounds strange, as does “John doesn’t know that the U.S. doesn’t have a constitution.” We can’t say intelligibly that someone knows or doesn’t know something that we presuppose is false. We presuppose many propositions in our conversations. And often our listeners assent to those presuppositions, perhaps not even realizing that they have done so.
So, knowledge is connected to truth. And truth is connected to reality. Some philosophers have defined knowledge as true belief. And belief is connected to emotion. We don’t like to be accused of spouting falsehoods. (At least not most of us.) Philosophers maintain that truth is independent of people’s beliefs. We say, “I know something,” or “I believe something.” So, knowing and believing are relations between people and assertions. Truth is not. But truth does have a connection to knowledge.
Now we have some vocabulary we can use to clarify knowledge.
The phrase “working set” I have chosen to be neutral in relation to words like ‘fact.’ A working set is a set of facts an individual or community works with. Calling them facts adopts the point of view of the individual or the community. From outside the community the working set may appear as mere opinions or even falsehoods, since the outside observer may have a different set of facts, i.e., a different working set. That is, ‘working set’ is free from emotional commitment.
What differentiates working sets of different individuals or communities is an emotional commitment to the working set. The idea of emotional commitment is critical to my account of knowledge and truth. The role of commitment is based on my observations of people. People defend their beliefs with a passion, even trivial beliefs. Merely observe how someone reacts, when you challenge their beliefs. Most people display body language and verbal expressions that reveal a self-protective posture. You can assure them as much as you want that you were not criticizing them only the idea they expressed, but they continue to be self-protective. If you are sensitive to other people’s emotions, you choose your words carefully. Euphemisms abound in language (“has passed to a better place”), as do the opposite, dysphemisms (“death tax”).
Here is a quote from Noam Chomsky using the idea of commitment.
Q: Do you have faith in the scientific method? In the context of having asked Chomsky previously about his religious faith.
Chomsky: “The scientific method is the only method we have to try to get some approximate understanding of the world. I don’t have faith that it will reach the truth. Or even that it is leading us in the true direction. As someone committed to the scientific method, I am also committed to its consequences. And among them are that you and I and the rest of the species are organic creatures who have our specific capacities and limitations and we simply don’t know. And if there isn’t a belief that these capacities are such that we can gain the truth about the world, we do our best. That’s the most we can do.”
THINKING WITH WORKING SETS
We use working sets (beliefs/facts) to connect to other ideas. Following Sloman and Fernbach we may explain some idea by offering causal connections from our working set. Or we may list reasons from our working set without explicitly saying what the connection of those reasons are to the ideas being discussed. Sloman and Fernbach find a distinction between how people react when having to give a causal explanation versus how they react when simply offering lists of reasons. Failure giving causal explanations makes people question how well they understand the topic. In contrast, it is hard to fail at the game of listing reasons, because the list is not explicitly (deductively, causally) connected to a working set.
“The illusion of comprehension arises because people confuse understanding with familiarity or recognition.” P 217
Value-laden topics make emotional commitment to a point of view so intense that there is no chance that we will revise our view when faced with someone challenging it. Sloman and Fernbach cite “Our attitudes are not based on a rational, detached evaluation of the evidence, [Dan] Kahan argues. This is because our beliefs are not isolated pieces of data that we can take and discard at will. Instead, beliefs are deeply intertwined with other beliefs, shared cultural values, and our identities. To discard a belief often means discarding a whole host of other beliefs, forsaking our communities, going against those we trust and love, and in short, challenging our identities.”[P. 160]
If we learn to become less attached to our working set, we can entertain alternative working sets and discover new ways of understanding the world, but this is very hard with value-laden topics.
Sciences demonstrate what progress comes from creating methods of inquiry.
OBSERVATION AND FORMING HYPOTHESES
The first step is to observe and describe what we see. Describing what we see invariably involves classifying the objects and events we observed. My favorite easy example of careful observation and classification is the following passage from The Hound of the Baskervilles.
Sherlock describes Dr. James Mortimer without ever having met him, simply by looking at his walking stick.
“There emerges a young fellow under 30, amiable, unambitious, and the possessor of a favorite dog, which I should describe roughly as larger than a terrier and smaller than a mastiff.
“The dog has been in the habit of carrying this stick behind its master. Being a heavy stick the dog has held it tightly by the middle, and the marks of his teeth are very plainly visible. The dog’s jaw, as shown in the space between these marks, is too broad in my opinion for a terrier and not broad enough for a mastiff. It may have been – yes, by Jove it is a curly-haired spaniel.” The Hound of the Baskervilles
We can continue Sherlock’s speculation. Mortimer is young, because he doesn’t need to rely on the walking stick, since his dog carries it. He is amiable, because owners of dogs pick animals with compatible personalities. As for being unambitious, a curly-haired spaniel is not a pretentious dog.
Sherlock characterizes his method as deduction. But while he does use deduction at times, his main method is observation and connecting the dots: the method of hypothesis. He notices details and assembles those details into a coherent story or hypothesis.
C. S. Peirce (a 19th century American philosopher) distinguishes reasoning by hypothesis as abduction, not deduction, as Conan Doyle terms it. He describes abduction as follows.
You observe a1, a2…aN.
a1, a2…aN would be a matter of course, if A were true, i.e., A implies a1, a2,..aN.
Therefore, assume A is true, until further notice.
Most of our daily judgements are abductive.
MATHEMATICS AND DEDUCTION
Mathematics uses multiple methods. Counting and measurement, including statistical measures, are two central methods. Counting and measurement can be classified as technologies. There are cultures, notably Amazonian, which lack the technology of a counting system. We evaluate technologies in terms of their effectiveness, rather than their truth. Deduction is a third method that mathematics uses. Mathematical logic works to formalize methods of deduction.
Let us move on to a deduction. Mathematics has methods of deduction that check how well our assertions are connected; one following logically from another. I fell in love with mathematics when I took geometry in high school. The idea of proving something true was exhilarating. It contrasted with the jumble of ideas that was in my head, offering an oasis. If I were persistent, I could prove something true! I offer a tiny example of such a geometrical proof, my addition to the hundreds of proofs of the Pythagorean theorem. The following diagram provides the idea of the proof.
The pink squares represent the squares of the sides of the triangle illustrating the Pythagorean Theorem: Hypotenuse2 = Side12 + Side22. The broad outline of my proof of the Pythagorean Theorem is as follows.
- Prove that all the triangles are congruent (same shape and size, differing only in orientation and translation). Hint: Recall ASA and SAS from geometry.
- Then prove the two large overlapping squares equal, i.e., are congruent (differing only in translation).
- Subtract 4 triangles from the right-hand large square to reveal the combined area of the smaller pink squares and then subtract 4 triangles from the left-hand large square to reveal the area of square for the hypotenuse. Subtracting equals from equals produces equals.
Well, almost. Your homework is to prove 1 and 2. 🙂 Admit it, that was exciting! If you are a glutton for punishment, here is a link to 122 proofs of the Pythagorean theorem. https://www.cut-the-knot.org/pythagoras/
Would subjects experience the same effect from trying to construct a deductive proof as trying to describe a causal process? Sloman and Fernbach emphatically say that humans don’t do logical deduction: They are good a causal reasoning, but not deductive reasoning.
I would ask Sloman and Fernbach to define causal reasoning. Causal reasoning may simply come down to remembering past scenarios of events and simply plugging the current situation into those scenarios. The philosopher David Hume comes forward (actually ‘came’ forward 280 years ago) to declare causal reasoning fallacious – the fallacy of “post hoc, ergo propter hoc” (after this, therefore because of this).
Mathematics explicitly acknowledges the working set is a working set and doesn’t attempt to justify it other than through attractive consequences.
TESTING HYPOTHESES BY EXPERIMENTING
Physics uses mathematics to express a working set, such as Newton’s laws of motion, from which we can deduce other connections among natural phenomena in addition to those in the working set. Physicists then add experiments for checking the connections deduced. Physicists associate objects and relations of the experiment with the theoretical objects and relations, in order to check the theory. The physical world makes it relatively easy for a community of scientists to compare observations, in contrast to social sciences. Physics exemplifies causal reasoning. Adding more force to an object causes its acceleration to increase, for example.
Other sciences use experimental techniques with minimal theories of causal connections. An example is dietary research, where scientists try to determine a correlation between consumption of saturated fat and heart disease, for example, without a causal theory. History does not typically use experiments explicitly but does look for familiar patterns in the historical record into which to fit recorded events, i.e., abduction. All sciences use deduction to some extent, even when not featuring it.
Now to the definition of truth and knowledge. We already established that one cannot know something that is false. So, let us try to define truth. Even if we restrict ourselves to truths developed by methods that have been successful in sciences, we run into a problem. Scientists end up changing their theories over time and scientists can disagree. We learn from the history of sciences that there is no certainty for all time using their methods. So, what do we have? We have methods that lead us from working set to working set, but along the way the experiments performed lead us to technologies that allow us to interact with the world more effectively and produce benefit to our species.
Truth then is reduced to a working set that is produced and revised by inquiry using tested methods of inquiry by a community that uses those methods. What we know is a set of facts according to a working set. This does not mean that truth is arbitrary. Reality eventually intervenes. Very few working sets can claim the impact on our lives we have witnessed in physics and medicine, for examples.
A paradox of physics is that we have different theories of the physical world: Newtonian physics, Relativity, and Quantum physics. Certainly, many engineers use Newtonian mechanics, for example, to calculate trajectories for a rocket. But physicists have decided that Newtonian mechanics isn’t a complete theory of the physical world. We have three different working sets. Is this a problem? Can we actually get along with multiple theories? Which one is true? Which one is the one that we can be said to know? Maybe we can pick or commit to the working set that is most efficient for the problem at hand. I repeat the caution that having multiple theories (working sets) throughout history or even at the same time doesn’t mean that truth is arbitrary.
THE KNOWLEDGE ILLUSION
Let us now look at the methods the authors Sloman and Fernbach use.
They describe many experiments attempting to assess people’s confidence (a type of emotion) in their knowledge. They conclude that people’s confidence drops, when they are asked to explain how something works. The effect seems to disappear for values topics. They go on to investigate the source of people’s confidence in their knowledge, concluding that people depend on knowledge outside their own for feeling confident, to the extent of even feeling more confident in their knowledge because of being able to access the internet.
Consider that knowing how involves causal reasoning or at least remembering scenarios. Knowing how typically consults the environment to remind one of what steps are next. So, the sense of knowing something based on access to information is natural. Sloman and Fernbach are right about that. Imagine if a friend asks you for detailed directions from their home to yours (no GPS). You do your best to visualize each corner where they will have to make a turn. You quickly realize that, try as you will, the result is a proverbial patchwork quilt, not even close to a complete picture. Your difficulty visualizing the trip comes in spite of your being able to confidently drive the route, which you have done many times coming back from meetings at the friend’s house. You claim to know the way, because you rely on landmarks you see along the way to decide where to turn. Is it fair of Sloman and Fernbach to cast aspersions on people’s knowledge of how a flush toilet works without them being able to inspect the workings of a toilet? They have designed laboratory experiments, where maybe they should have observed people’s behavior “in the wild.”
One area I believe they need to investigate more thoroughly is the role of emotions and how they relate knowledge. My alternative to The Knowledge Illusion for last month was Elizabeth Barrett’s How Emotions Are Made. We are emotional about our beliefs, passionately defending them against criticism. Calling something true is a way of defending our working set. My favorite philosopher C. S. Peirce characterizes a true statement as one that is defensible by scientific methods against all criticism by scientific methods. We commit to a theory for various reasons. A rocket scientist commits to Newtonian mechanics. A quantum computing research group commits to quantum mechanics. Again, I repeat the previous caveat. One can’t choose just any working set to commit to. It should come from the inquiry of a community that uses successful methods.
There are many words we use daily, like ‘liberal’ and ‘conservative’ or ‘Republican’ and ‘Democrat,’ that we don’t take time to clarify and perhaps can’t, because they change their meanings too rapidly over time and geography. Meanings of words are dependent of their context of use and as the contexts change, so do the meanings. Sloman and Fernbach could have done a study of how well their subjects know the meanings of words, which they are aware of.
“It’s one thing to be familiar with some text or even to know it by heart, and another to really get its meaning.” P 217
Their experiments used words in the prompts. I am sure they tried to choose the words carefully, so as not to bias the prompts. But that is hard to do. We all have seen poll questions that show a bias, sometimes intentional. I tend to discount polling data, e.g., about the Democratic candidates, as having little to do with what the voters’ decision-making process will be when voters cast their votes.