Tag: Knowledge

Shepherds

Shepherds

Posted on by jabittan
“It was no accident that kings and prophets styled themselves as shepherds and likened the way they and the gods cared for their people to a shepherd’s care for his flock,” writes Yuval Noah Harari in his book Sapiens.
 
 
I don’t like bucolic narratives and I don’t like the way that we equate people we don’t like with sheep in modern American political discussions. Bucolic romanticism requires a reductionist way of looking at history, and equating people to sheep is reductionist way of viewing anyone we disagree with and dislike. As Harari’s quote to open this post shows, both styles of rhetoric are much older than their current usage in modern American politics.
 
 
What Harari is saying in the paragraph that the opening quote came from is that some agrarian societies and ancient (and not too ancient) human civilizations treated their domesticated animals very well. Sheep were well cared for, in order to get the most wool possible from them. War horses and workhorses were well cared for, again for the benefit of humans. And even today we pamper our pets as if they were our children. The narrative of the shepherd comes from the care with which humans are capable of treating animals under their protection. A shepherd is a benevolent god who directs his flock to greener pastures and protects them from wild beasts and the evils of nature. Bucolic imagery calls up a simplistic time when humans lived in nature, protected and shielded from the evils of modernity. Combining these two perspectives allows people to feel a child-like protection under the watchful eye of a benevolent leader while we live in a natural peace and harmony with the planet.
 
 
I think the narrative associated with both narratives is deeply troubling, and untrue. David Deutsch was recently on Tyler Cowen’s podcast, Conversations with Tyler, and argued that the belief that we are living in a simulation is no different than believing that Zeus is the supreme god who directs the course of the world. His argument is that if we live in a simulation, there is a barrier at which we can no longer gain more information about the universe. A Simulation, he argues, is the same as a religion where there is a barrier at which people cannot know more about their god, the course of the universe, and why things happen. Invoking the imagery of a shepherd, to me, seems to be exactly the same. A leader comes along, invokes such a message, and says to the people they wish to lead that only they know how to help them, that there is a barrier which normal people cannot cross in terms of knowledge for what is good for them and how to live their lives. The shepherd seems benevolent, kind, and praiseworthy, but really, they are dehumanizing people. They are making statements that there is knowledge and information that only they can know and appropriately utilize, and they are hiding that from the masses. The same process happens in reverse when we call people sheep. We deny their humanity and assume they are non-thinking morons without preferences who are easily misled.
 
 
Bucolic imagery can be just as pernicious as the ideas and narratives surrounding the shepherd or equating people to sheep. Just as the idea that there is some boundary on knowledge which normal people cannot surpass, the idea of a bucolic nature to which we should return or maintain is equally flawed and inaccurate. We romanticize a past and a ‘natural’ way of living that never existed. We don’t fully understand what life with nature has been like for the billions of humans that evolved before our modern times. We fail to see the diseases, the dangers, the struggles, and the deaths of humans living in pre-modern times. We call up this idea to put people in a romantic and child-like state of mind, reassuring them that someone else will take care of them and protect them. It is a narrative that combines well with the narrative of the shepherd to create a false view of reality that we can find comforting, and that we may find the motivated reasoning to believe. Ultimately, however, I think bucolic thinking and the narratives of sheep and the shepherd should be tossed aside and discounted if we want to think more accurately and rationally. 
The Danger of Only Asking Questions We Expect To Be Able To Answer

The Danger of Only Asking Questions We Expect To Be Able To Answer

Posted on by jabittan
It is not fun to face ambiguity and questions that we don’t have any hope of answering. Humans don’t like sitting with the unknown, and we don’t like admitting that there are questions, some very important and definitive, that we simply have no way of answering. Some questions we know we cannot answer at this point, but we expect to be able to answer, and some questions there is almost certainly no hope of answering within our lifetimes, and perhaps not within the entire lifetime of our planet or sun. But that doesn’t mean we shouldn’t still ask such questions.
In his book Sapiens, Yuval Noah Harari writes, “scholars tend to ask only those questions that they can reasonably hope to answer. … Yet it is vital to ask questions for which no answers are available, otherwise we might be tempted to dismiss 60,000 of 70,0000 years of human history with the excuse that the people that lived back then did nothing of importance.”
In this quote, Harari is specifically referring to scholars who don’t ask questions about ancient humans living in times before modern tool use. Such humans didn’t leave an obvious trace through items which can be identified and discovered through archeological explorations. Their tools and items were made of organic materials that decomposed. Their major advances came in languages which were not written down and preserved. Their important contributions to human evolution were psychological and cultural, and didn’t easily leave a trace that could survive 70,000 years of weathering, continental drift, volcanic explosions, floods, and human resettlement. As a scholar, why spend time and put your career on the line investigating questions you can’t answer, knowing that you won’t produce journal articles and research presentations for your non-answers?
It is understandable why scholars don’t ask the questions they have no hope for answering, even beyond questions of early human cultures, but Harar thinks they should. By asking such questions, we remember to think about important factors that can be ignored or easily discounted. We can limit our view of history to only those things that left material imprints and traces on our planet. We can overlook details that we might otherwise find important. As an example, Harari shows how early humans still changed the world around them, primarily through hunting and the use of fire, even if the hunting often involved chasing an animal until it died of exhaustion or burning a part of a forest to force animals out of hiding. We might not find a lot of physical tools and evidence of such behavior, but the changes in the ecology and environment may be detectable. For 60,000 years early Homo Sapiens changed the planet, even though we can’t always detect how. Failing to ask questions about such humans and their cultures, questions we can’t find evidence and information to answer, means that we overlook their contributions to the changes of the planet. Failing to ask unanswerable questions means we also fail to ask questions for which we do have some hope of finding answers. It also means we ignore important areas and topics, leaving them for people who want to abuse history and science with myth and narrative that may not have a hope of actually being accurate or discarded as junk without serious minds thinking about the topic.
The Location of Human Knowledge - Yuval Noah Harari Sapiens - Joe Abittan

The Location of Human Knowledge

Posted on by jabittan
“The average forager had wider, deeper, and more varied knowledge of her immediate surroundings than most of her modern descendants,” writes Yuval Noah Harari in Sapiens. Individual human hunter-gatherers had to know a lot about their environment, and they were not learning from text books and schools. They were learning by trial and error, by being shown what was edible and what was not edible older members of their tribe, and they had to develop a plethora of skills in order to do all the things necessary for survival.
Humans today are not very likely to be able to weave baskets from reeds (as much as we joke about basket weaving courses for college athletes). They also likely can’t sharpen a flint arrowhead, don’t know what animals are around their location and how to hunt them, and don’t know what wild plants are helpful or harmful. Individually, modern humans don’t seem to have the same regionalized knowledge as the ancient humans that came before them. But today we definitely know far more than the humans before us as a whole.
The difference, Harari explains, is that the location of human knowledge has changed. We no longer all hold the same helpful regional information in our heads. Instead, we have a collective knowledge spread across humanity. Each of us is an expert in our own little niche. For example, I studied political science and Spanish. I know a bit about theories of policy processes, such as the Multiple Streams Framework, and I know a bit about medieval literature from the Iberian Peninsula. On the other hand, I don’t really know much about how nuclear submarines work, how my city’s sewage system works, and I don’t really know what migratory birds can be found in the area during the spring versus the fall. Someone else in the collective of human knowledge is an expert in each of those things.
“The human collective,” writes Harari, “knows far more today than did the ancient bands. But at the individual level, ancient foragers were the most knowledgeable and skillful people in history.” This quote may be a broad overgeneralization, but it is nevertheless interesting and thought provoking. Some of us are incredibly skilled with a variety of things and have a great deal of knowledge about much of the world around us. Others don’t seem to have as much skill, and know more about celebrities than we do about what is happening in the world. Overall, the important thing to consider is that the modern world has seen a shift in the distribution of knowledge. We don’t all have to hold information about our immediate surroundings in our heads, and we don’t all have to be able to produce the things necessary for our survival. Only some humans need to know those things and have the skills to produce the basic necessities for life. The rest of us can then go off and explore different areas and learn different things, constantly increasing the collective human knowledge and skill base, even if we individually seem more narrowly skilled and less immediately knowledgeable compared with our ancient forager ancestors.
The Pursuit of Solid Answers

The Pursuit of Solid Answers

Posted on by jabittan
Human’s have egos, and that causes a lot of problems. To be clear, it is often not the ego itself that causes problems, but our feeling that we need to be right, that we need to be powerful, that we need to have important friends and connections that becomes problematic. Humans evolved in small tribes where survival often depended on being high status. Men had to be high status to pass their genes along and being high status meant that people would come to your aid if you needed help. Knowing useful things, being physically imposing, and having useful skills all contributed to make us higher status. Today, the drive for higher status is often understood as ego, and it is still with us, even if survival and evolutionary pressures toward super high status have declined.
One way in which this status and ego pursuit manifests to cause problems in our lives is in our intellectual discussions and debates. We often pursue our own ego rather than accurate knowledge and information when we are in debates. We are both signaling to our tribe and trying to dominate a conversation with our strong convictions rather than trying to have constructive discussions that help us get to correct answers.
Mary Roach writes about this phenomenon in her book Spook when discussing paranormal phenomena. She writes, “hasty assumptions serve no one. To make up one’s mind based on nothing beyond a simple summary of events – as believers and skeptics alike tend to do – does nothing to forward the pursuit of solid answers.” When we get into debates on religious topics, questions of psychic or paranormal phenomena, and complex social science questions, we often fall into reductive arguments that are mostly aimed at people who hold the same assumptions and beliefs that we already hold. We make hasty assumptions because our ego wants us to appear decisive and correct without spending time in ambiguity carefully considering the truth. The goal for us should be to become less wrong, but that is not a mindset that is generally rewarded by the ego, which for much of human evolution was rewarded by conviction and demonstrations of loyalty. Making changes so that more considerate thought is rewarded over ego-centric thought is crucial for us to move forward, but it runs against evolution, our self-interest, and what gets the most attention on social media today. Hasty assumptions may not be helpful, but they do get strong reactions and generate support among like-minded individuals.
Science and Facts

Science and Facts

Posted on by jabittan
Science helps us understand the world and answer questions about how and why things are the way they are. But this doesn’t mean science always gives us the most accurate answers possible. Quite often science seems to suggest an answer, sometimes the answer we get doesn’t really answer the question we wanted to ask, and sometimes there is just too much noise to gain any real understanding. The inability to perfectly answer every question, especially when we present science as providing clear facts when teaching science to young children, is a point of the confusion and dismissal among those who don’t want to believe the answers that science gives us.
In Spook: Science Tackles the Afterlife, Mary Roach writes, “Of course, science doesn’t dependably deliver truths. It is as fallible as the men and women who undertake it. Science has the answer to every question that can be asked. However, science reserves the right to change that answer should additional data become available.” The science of the afterlife (really the science of life, living, death, and dying), Roach explains, has been a science of revision. What we believe, how we conduct experiments, and how we interpret scientific results has shifted as our technology and scientific methods have progressed. The science of life and death has given us many different answers over the years as our own biases have shifted and as our data and computer processing has evolved.
The reality is that all of our scientific fields of study are incomplete. There are questions we still don’t have great answers to, and as we seek those answers, we have to reconsider older answers and beliefs. We have to study contradictions and try to understand what might be wrong with the way we have interpreted the world. What we bring to science impacts what we find, and that means that sometimes we don’t find truths, but conveniently packaged answers that reinforce what we always wanted to be true. Overtime, however, the people doing the science change, the background knowledge brought to science changes, and the way we understand the answers from science changes. It can be frustrating to those of us on the outside who want clear answers and don’t want to be abused by people who wish to deliberately mislead based on incomplete scientific knowledge. But overtime science revises itself to become more accurate and to better describe the world around us.
When to Stop Counting

When to Stop Counting

Posted on by jabittan
Yesterday I wrote about the idea of scientific versus political numbers. Scientific numbers are those that we rely on for decision-making. They are not always better and more accurate numbers than political numbers, but they are generally based on some sort of standardized methodology and have a concrete and agreed upon backing to them. Political numbers are more or less guestimates or are formed from sources that are not confirmed to be reliable. While they can end up being more accurate than scientific figures they are harder to accept and justify in decision-making processes. In the end, the default is scientific numbers, but scientific numbers do have a flaw that keeps them from ever becoming what they proport to be. How do we know when it is time to stop counting and when we are ready to move forward with a scientific number rather than fall back on a political number?
Christopher Jencks explores this idea in his book The Homeless by looking at a survey conducted by Martha Burt at the Urban Institute. Jencks writes, “Burt’s survey provides quite a good picture of the visible homeless. It does not tell us much about those who avoid shelters, soup kitchens, and the company of other homeless individuals. I doubt that such people are numerous, but I can see no way of proving this. It is hard enough finding the proverbial needle in a haystack. It is far harder to prove that a haystack contains no more needles.” The quote shows that Burt’s survey was good at identifying the visibly homeless people, but that at some point in the survey a decision was made to stop attempting to count the less visibly homeless. It is entirely reasonable to stop counting at a certain point, as Jencks mentions it is hard to prove there are no more needles left to count, but that always means there will be a measure of uncertainty with your counting and results. Your numbers will always come with a margin of error because there is almost no way to be certain that you didn’t miss something.
Where we chose to stop counting can influence whether we should consider our numbers to be scientific numbers or political numbers. I would argue that the decision for where to stop our count is both a scientific and a political decision itself. We can make political decisions to stop counting in a way that deliberately excludes hard to count populations. Alternatively, we can continue our search to expand the count and change the end results of our search. Choosing how scientifically accurate to be with our count is still a political decision at some level.
However, choosing to stop counting can also be a rational and economic decision. We may have limited funding and resources for our counting, and be forced to stop at a reasonable point that allows us to make scientifically appropriate estimates about the remaining uncounted population. Diminishing marginal returns to our counting efforts also means at a certain point we are putting in far more effort into counting relative to the benefit of counting one more item for any given survey. This demonstrates how our numbers can be based on  scientific or political motivations, or both. These are all important considerations for us whether we are the counter or studying the results of the counting. Where we chose to stop matters, and because we likely can’t prove we have found every needle in the haystack, and that no more needles exist. No matter what, we will have to face the reality that the numbers we get are not perfect, no matter how scientific we try to make them.
Who Are the Homeless?

Who Are the Homeless

Posted on by jabittan
In the United States we have many housing insecure individuals. We have many people who are chronically homeless, and are unlikely to ever get off the streets. We have many people who experience homelessness only transiently, possibly during an unexpected layoff or economic downturn. And we also have many people who find themselves in and out of homelessness. For each group of housing insecure individuals, their needs and desires of people differ. However, when we think about homelessness in America, we typically only think about one version of homelessness: the visibly homeless man or woman living in the streets.
In his book Tell Them Who I Am Elliot Liebow writes, “an important fact about these dramatically visible homeless persons on the street is that, their visibility notwithstanding, they are at best a small minority, tragic caricatures of homelessness rather than representatives of it.” When we think about the homeless we think about men and women who don’t work, who are smelly and dirty, and who appear to have mental disorders or drug addictions. This means that public policy geared toward homelessness is a reaction to this visible minority, not policy geared to help the many people who may experience homelessness in a less visible way.
People do not like the visibly homeless who live on the street. They feel ashamed to see them begging, feel frustrated by their panhandling, and are often frightened of them. The visibly homeless are not a sympathetic group, and are not likely to be the targets of public policy that supports them.
The less visibly homeless, however, are a population we are less afraid of and less likely to strongly dislike. But because we don’t see them, we don’t think of them when we consider policies and programs designed to assist the homeless. Their needs, their concerns, and the things that could help them find more stable housing are forgotten or simply unknown to the general public and the policymakers they elect. We are often unaware of the individuals who are homeless but still managing to work a job. We don’t think about those who experience temporary homelessness, sleeping in a car for a couple of weeks at a time between gig work. We don’t consider those who live in shelters until a friend or family member can take them in and support them until they can find work. Without acknowledging this less visible side of poverty, we don’t take steps to improve public policy and public support for those working to maintain a place to live. We allow the most visible elements of homelessness to be all we know about homelessness, and as a result our policy and attitudes toward the homeless fail to reflect the reality that the majority of the homeless experience.
Causal Illusions - The Book of Why

Causal Illusions

Posted on by jabittan
In The Book of Why Judea Pearl writes, “our brains are not wired to do probability problems, but they are wired to do causal problems. And this causal wiring produces systematic probabilistic mistakes, like optical illusions.” This can create problems for us when no causal link exists and when data correlate without any causal connections between outcomes.  According to Pearl, our causal thinking, “neglects to account for the process by which observations are selected.”  We don’t always realize that we are taking a sample, that our sample could be biased, and that structural factors independent of the phenomenon we are trying to observe could greatly impact the observations we actually make.
Pearl continues, “We live our lives as if the common cause principle were true. Whenever we see patterns, we look for a causal explanation. In fact, we hunger for an explanation, in terms of stable mechanisms that lie outside the data.” When we see a correlation our brains instantly start looking for a causal mechanism that can explain the correlation and the data we see. We don’t often look at the data itself to ask if there was some type of process in the data collection that lead to the outcomes we observed. Instead, we assume the data is correct and  that the data reflects an outside, real-world phenomenon. This is the cause of many causal illusions that Pearl describes in the book. Our minds are wired for causal thinking, and we will invent causality when we see patterns, even if there truly isn’t a causal structure linking the patterns we see.
It is in this spirit that we attribute negative personality traits to people who cut us off on the freeway. We assume they don’t like us, that they are terrible people, or that they are rushing to the hospital with a sick child so that our being cut off has a satisfying causal explanation. When a particular type of car stands out and we start seeing that car everywhere, we misattribute our increased attention to the type of car and assume that there really are more of those cars on the road now. We assume that people find them more reliable or more appealing and that people purposely bought those cars as a causal mechanism to explain why we now see them everywhere. In both of these cases we are creating causal pathways in our mind that in reality are little more than causal illusions, but we want to find a cause to everything and we don’t always realize that we are doing so. It is important that we be aware of these causal illusions when making important decisions, that we think about how the data came to mind, and whether there is a possibility of a causal illusion or cognitive error at play.
Stories from Bid Data

Stories from Big Data

Posted on by jabittan
Dictionary.com describes datum (the singular of data) as “a single piece of information; any fact assumed to be a matter of direct observation.” So when we think about big data, we are thinking about massive amounts of individual pieces of information or individual facts from direct observation. Data simply are what they are, facts and individual observations in isolation.
On the other hand Dictionary.com defines information as “knowledge communicated or received concerning a particular fact or circumstance.” Information is the knowledge, story, and ideas we have about the data. These two definitions are important for thinking about big data. We never talk about big information, but the reality is that big data is less important than the knowledge we generate from the data, and that isn’t as objective as the individual datum.
In The Book of Why Judea Pearl writes, “a generation ago, a marine biologist might have spent months doing a census of his or her favorite species. Now the same biologist has immediate access online to millions of data points on fish, eggs, stomach contents, or anything else he or she wants. Instead of just doing a census, the biologist can tell a story.” Science has become contentious and polarizing recently, and part of the reason has to do with the stories that we are generating based on the big data we are collecting. We can see new patterns, new associations, new correlations, and new trends in data from across the globe. As we have collected this information, our impact on the planet, our understanding of reality, and how we think about ourselves in the universe has changed. Science is not simply facts, that is to say it is not just data. Science is information, it is knowledge and stories that have continued to challenge the narratives we have held onto as a species for thousands of years.
Judea Pearl thinks it is important to recognize the story aspect of big data. He thinks it is crucial that we understand the difference between data and information, because without doing so we turn to the data blindly and can generate an inaccurate story based on what we see. He writes,
“In certain circles there is an almost religious faith that we can find the answers to … questions in the data itself, if only we are sufficiently clever at data mining. However, readers of this book will know that this hype is likely to be misguided. The questions I have just asked are all causal, and causal questions can never be answered from data alone.”
Big data presents us with huge numbers of observations and facts, but those facts alone don’t represent causal structures or deeper interactions within reality. We have to generate information from the data and combine that new knowledge with existing knowledge and causal hypothesis to truly learn something new from big data. If we don’t then we will simply be identifying meaningless correlations without truly understanding what they mean or imply.
Complex Causation Continued

Complex Causation Continued

Posted on by jabittan
Our brains are good at interpreting and detecting causal structures, but often, the real causal structures at play are more complicated than what we can easily see. A causal chain may include a mediator, such as citrus fruit providing vitamin C to prevent scurvy. A causal chain may have a complex mediator interaction, as in the example of my last post where a drug leads to the body creating an enzyme that then works with the drug to be effective. Additionally, causal chains can be long-term affairs.
In The Book of Why Judea Pearl discusses long-term causal chains writing, “how can you sort out the causal effect of treatment when it may occur in many stages and the intermediate variables (which you might want to use as controls) depend on earlier stages of treatment?”
This is an important question within medicine and occupational safety. Pearl writes about the fact that factory workers are often exposed to chemicals over a long period, not just in a single instance. If it was repeated exposure to chemicals that caused cancer or another disease, how do you pin that on the individual exposures themselves? Was the individual safe with 50 exposures but as soon as a 51st exposure occurred the individual developed a cancer? Long-term exposure to chemicals and an increased cancer risk seems pretty obvious to us, but the actual causal mechanism in this situation is a bit hazy.
The same can apply in the other direction within the field of medicine. Some cancer drugs or immune therapy treatments work for a long time, stop working, or require changes in combinations based on how disease has progressed or how other side effects have manifested. Additionally, as we have all learned over the past year with vaccines, some medical combinations work better with boosters or time delayed components. Thinking about causality in these kinds of situations is difficult because the differing time scopes and combinations make it hard to understand exactly what is affecting what and when. I don’t have any deep answers or insights into these questions, but simply highlight them to again demonstrate complex causation and how much work our minds must do to fully understand a causal chain.