Tag: critical thinking

How to Be A Good or Bad Interviewer

The job interview process has been written about extensively, and some people even receive specialized training from their jobs on how to properly conduct an interview. Everyone has ideas about the best way to provide interviews, and large companies tend to have specific motifs or methods of interviewing which can take on an undeservedly mythical reputation. There’s a lot of debate over whether the interview is an effective way of selecting talent, but the median is settled: if you are looking for a job, you will have to have an interview. If you are looking to fill a job, you will have to interview someone. This article is an analysis of common mistakes that I’ve seen interviewers make. I can’t help but propose a few better ways of conducting interviews alongside my analysis.

The best parts of job interviewing are getting to find out interesting things about companies while meeting the potentially cool people who populate those companies. The worst parts of job interviewing are finding out exactly how bad people can be at providing an interview. I am not an expert on interviewing people by any means, nor am I an expert at being interviewed– I’ve made quite a few awful mistakes in both camps, to be sure. I think that I have a few good ideas on what not to do as an interviewer, though. The anecdotes that I’ll provide here are not embellished. I will state that this experience is mostly from interviewing for scientific jobs, and that it may be that the personality of scientists precludes them from being good interviewers, but I don’t believe that this is the case.

Everyone is behooved to be good at acing job interviews because jobs are desirable, but few are so inclined to be perfectionistic about the opposite half. Companies want good talent, but of course they can always provide a job offer to someone they like and at least have a chance of getting them to agree, even if they have performed their interviewing of the candidate poorly and the candidate performed poorly.

Because of this inherent inequality of the process, the process of interviewing candidates is typically far weaker than it should be in a few different dimensions. To clarify this concept: attending the job interview and presenting a good face to potential employers is always a high priority of the job seeker, but preparing to interview a candidate and interviewing a candidate properly is very rarely a high priority for the people providing the interview. This mainstream habit of interviewing carelessness shows like a deep facial scar. The consequence of low-prioritization of interviewer preparation is sloppiness in execution and wasted time for all parties.

First, in all interviews that I have ever been on either side of, there will be at least one person who has not read the resume or given any premeditation about the candidate. Do not be this person, because this person has little to contribute to the investigation into whether the candidate is suitable. Pre-reading the candidate’s resume is a must if the aim of the interview is to determine whether the person is qualified technically and qualified socially.  The purpose of the job interview is not to spend time checking whether the candidate can recapitulate their resume without forgetting their own accomplishments but rather to assess if the candidate will improve a team’s capability to execute work. This fact seems self evident, yet I have been interviewed by several unrelated people who explicitly stated that they would see whether what I was saying was the same as what was reflected on my resume.

Aside from pre-reading the candidate’s resume, interviewers should also pre-think about the candidate. Practically no interviewers I have interacted with have attended to pre-thought about the candidate in any meaningful way. Writing a job description or giving the candidate’s resume a once-over does not count as pre-thinking. If you want to find the perfect person for a position, it is a disservice to your company not to prioritize premeditation about the candidate. Without premeditation, there can be no intelligent questioning of the interviewee. Is the person’s previous experience going to give them unique insights on the job they are hoping to fill? Is this candidate going to be socially successful at this position? Set time aside to write down these questions when there is nothing else competing for your attention.

Frank consideration of whether the person will fit in with the others on the team or not should be broached ruthlessly at this early step. Social conformity is a strong force which applies to people, and an inability to fit in can cause disruption among less flexible teams. To be clear, I think that heterogeneous teams have many advantages, but I also think that most interviewers are largely engaged in an exercise of finding the roughly qualified candidate that conforms most unindependently to the already-established majority. Biases about what kind of person the candidate is are going to the warp judgment of the interviewer no matter what, so it’s better to air them out explicitly such that they may be compensated for or investigated further when the candidate comes in. The objective here is not to find things to dislike about the candidate, but rather identify where the biases of the interviewer may interfere with collecting good data from the candidate when they arrive.

Remember that this critical step is rarely as simple as it seems. What kind of positive job-related things does the interviewer think about themselves? These positive self-thoughts will surely be used as a hidden rubric to asses the candidate, unfortunately. The interviewer identifying with the candidate is one of the strongest guarantors of a job offer.  The other takeaway here is that once the candidate comes in for the interview, be sure to explicitly note points of personal and professional identification between the interviewer and the candidate! Identifying with the candidate is great for the candidate’s prospects of getting the job, but it may not be the correct choice for the team to have to accommodate a new person who isn’t qualified.

Consider doubts about the candidate based on the information available, then write down questions to ask the candidate which will help to address those doubts– being tactful and canny at this step is an absolute must, so if there’s any doubt at being able to execute such questioning gracefully, defer to someone else who is more skilled. Is the candidate too young or old to fit in with the team, or are there concerns about the candidate’s maturity? Is the candidate visibly of any kind of grouping of people which isn’t the majority? Is the candidate going to rock the boat when stability is desired? It’s better to clarify why the candidate may not be socially qualified rather than to hem and haw without explicit criterion.

Winging it simply will not provide the best possible results here, because really the interviewer is interviewing their own thoughts on the candidate who is still unseen. Honesty regarding the team’s tolerance for difference is critical. To be clear, I do not think that the heavily conformity-based social vetting of candidates is good or desirable whatsoever. In fact, I think the subconscious drive toward a similar person rather than a different one is a detrimental habit of humans that results in fragile and boring social monocultures. I am merely trying to describe the process by which candidates are evaluated in reality whether or not the interviewers realize it or not. The social qualification of the candidate is probably the largest single factor in deciding whether the candidate gets the job or not, so it’s important to pay attention rather than let it fall unspoken. Interviewing a candidate is a full but small project that lives within the larger project of finding the right person for the open position.

We’ve reached our conclusion about things to do during to the period before the candidate arrives. But what about once the candidate is sitting in the interview room? In situations where there are multiple interviewers, successive interviewers nearly always duplicate the efforts of previous interviewers. They ask the same questions, get the same answers, and perhaps have a couple of different follow ups– but largely they are wasting everyone’s time by treading and re-treading the same ground.

Have a chat with the team before interviewing the candidate and discuss who is going to ask what questions. The questions should be specific to the candidate and resulting from the individual premeditation that the members of the interviewing team performed before the meeting and before interviewing the candidate. The same concerns may crop up in different candidates, which is fine. Examine popular trends of concern, and figure out how to inquire about them. Assign the most difficult or probing questions to the most socially skilled teammate. If there’s no clear winner in terms of social skill, reconsider whether it’s going to be feasible to ask the candidate gracefully.

Plan to be on time, because the candidate did their best to be on time. In my experience, interviewers are habitually late, sometimes by as much as thirty minutes. This problem results from not prioritizing interviewing as a task, wastes everyone’s time, and is entirely avoidable. Additionally, make sure that your interviewing time is uninterrupted. An interviewer that is distracted by answering phone calls or emails is not an interviewer who is reaping as much information as possible from the candidate. If there is something more pressing than interviewing the candidate during the time which was set aside by everyone to interview them, reschedule. Interviewing is an effort and attention intensive task, and can’t simply be “fit in” or “made to work” if there are other things going on at the same time.  

The interviewers should have the candidate’s resume in hand, along with a list of questions. When possible the questions should be woven into a conversational framework rather than in an interrogation-style format. Conversational questioning keeps the candidate out of interview mode slightly more, though it’s not going to be possible or desirable to jolt the candidate into a more informal mode because of the stress involved in being interviewed. Remember that the goal is to ask the candidate the questions that will help you to determine whether they are socially and technically qualified for the job. The facade of the candidate doesn’t matter, provided that you can assess the aforementioned qualifications.

Don’t waste everyone’s time with procedural, legal, or “necessary” but informationally unfruitful questions! Leave the routine stuff to HR and instead prioritize getting the answers to questions that are specific to evaluating this candidate in particular. HR isn’t going to have to live with having this person on their team, but they will likely be concerned about logistical stuff, so let them do their job and you can do yours more efficiently. If there’s no HR to speak of, a phone screen before the interview is the time for any banalities. To reiterate: focus on the substantial questions during the interview, and ensure that procedural stuff or paperwork doesn’t eat up valuable time when the candidate is actually in front of you.

If there are doubts about a candidate’s technical abilities or experience, have a quick way of testing in hand and be sure to notify the candidate that they will be tested beforehand. Once again, do not wing it. Remember that the candidate’s resume got them to the interview, so there’s no point in re-hashing the contents of the resume unless there’s a specific question that prompts the candidate to do something other than summarize what they’ve already written down for you. I highly suggest that questions directed toward the candidate are designed to shed light on the things which are not detailed in the resume or cover letter. The thought process and demeanor of the candidate are the two most important of these items.

Assessing the experience or thought process of the candidate can frequently be done by posing a simple “if X, then what is your choice for Y?” style question.  In this vein, consider that personal questions aren’t relevant except to assess the social qualifications of the candidate. Therefore, questions regarding the way that the candidate deals with coworkers are fair game. I highly suggest making questions toward the candidate as realistic as possible rather than abstract; abstract questions tend to have abstract answers that may not provide actionable information whereas real creativity involves manipulation of the particulars of the situation.

Aside from asking fruitful questions, the interviewer should take care with the statements which they direct toward the candidate. I will take this opportunity to explain a common and especially frustrating mistake that I have experienced interviewers making. As is self evident, the interview is not the time to question whether the candidate is suitable to bring in for an interview. To discuss this matter with the candidate during the interview is a misstep and is time that could be better spent trying to understand the candidate’s place in the team more.

To this end, it is counterproductive and unprofessional to tell the candidate that they are not technically or socially qualified for the position they are interviewing during the interview! The same goes for interviewer statements which explicitly or implicitly dismiss the value of the candidate. Interviews are rife with this sort of unstrategic and unfocused foul-play. This has happened to me a number of times, and I have witnessed it as a co-interviewer several times as well.

A red flag for a terrible interviewer is that they tell the candidate or try to make the candidate admit lack of qualifications or experience. Mid-level managers seem to be the most susceptible to making this mistake, and mid-career employees the least. It is entirely possible to find the limit of a candidate’s knowledge in a way that does not involve explicitly putting them down.  Voice these concerns to other interviewers before the candidate is invited in. If your company considers minimization of the candidate’s accomplishments as a standard posturing tactic designed to produce lower salary requests, consider leaving.

Aside from being demeaning, the tactic of putting down the candidate during the interview is frequently used by insecure interviewers who aren’t fit to be performing the task of evaluating candidates. There is no greater purpose served by intentionally posturing to the candidate they they are not valuable and are unwanted! Time spent lording over how ill-fit the candidate is for the position is wasted time that could be better spent elsewhere.

Don’t play mind games with the candidate– it’s immature, misguided, and ineffective. Such efforts are nearly always transparent and constitute an incompetent approach to interviewing based off of the false premise that candidates misrepresent their ability to do work to the interviewers, and so the interviewer must throw the candidate off their guard in order to ascertain the truth about the candidate.This line of thinking dictates that the “true” personality or disposition of the candidate is the target of information gathering during the interview. The habits and realized output of a person while they are in the mode of working are the real target of inquiry in an interview, so don’t get distracted by other phenomena which require digging but don’t offer a concrete return.

Typically, the purpose of these mind games is to get beyond the candidate’s presentable facade in an attempt to evaluate their “true” disposition or personality. This goal is misguided because the goal of an employee is not to have a “true” disposition that is in accordance with what their employer wants, but rather to have an artificial disposition that is in accordance with what their employer wants. We call this artificial disposition “professionalism“, but really it is another term for workplace conformity. I will note that professionalism is a trait that is frequently (but not always) desirable because it implies smooth functioning of an employee within the workplace. The mask of professionalism is a useful one, and all workers understand more or less the idea of how to wear it. A worker’s “true” or hidden personality is unrelated to their ability to cooperate with a team and perform work, if the deeper personality even exists in the individual at all. Conformity keeps the unshown personality obedient and unseen in the workplace, so it isn’t worth trying to investigate it anyway.

After the candidate has left, it’s time for a debrief with the team. Did the candidate seem like they’d be able to fit in with the team socially? If not, could the team grow together with the candidate? Did the candidate pass the relevant technical questions? Is the candidate going to outshine anyone in the team and cause jealousy? Did anyone have any fresh concerns about the candidate, or were any old concerns left unresolved despite efforts to do so? It’s important to get everyone’s perspectives on these questions. Report back on the answers to the questions that were agreed upon beforehand. If everyone did their part, there shouldn’t be much duplicated effort, but there should be a lot of new information to process.

Not all perspectives are equal, and not all interviewers are socially adept enough to pick up subtle cues from the candidate. Conversely, some interviewers will ignore even strong social cues indicated a good fit if their biases interfere. Interviewers have to remember that their compatriots likely had different experiences with the candidate– if they didn’t, effort was wasted and work was duplicated.

Is the candidate worth calling in for another interview, or perhaps worth a job offer right away? What kind of social posturing did the candidate seem to be doing during each interaction? What was their body language like when they were answering the most critical inquiries? Pay particular attention to the differences in the way that the candidate acted around different interviewers. This will inform the interviewers potentially where some of the candidate’s habits lie, and allow analysis of whether those habits will conform with the group’s.

If the interviewing process is really a priority, the interviewers will write down the answers to the above questions and compare them. How you process the results of this comparison is up to you, but if you don’t do the process, you’re not getting the most information out of interviewing that you could. If you take one concept away from this piece, it should be that teams have to make their interviewing efforts a priority in order to avoid duplicating questions, wasting time with posturing, and properly assess social and technical qualifications of the candidate.

If you liked this piece, follow me on Twitter @cryoshon and check out my Patreon page! I’ve been sick the past week (as well as involved in an exciting new opportunity) so I haven’t been writing as much, but I should be over my cold by Monday and back to regular output.

 

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How to be a Good Adviser by Playing Pretend

Upon leaving a job about a year ago, at my going away party one of my friends and coworkers asked me if I had any advice to pass on to the team. At the time, I stated that my advice was not to give generalized advice without a specific issue in mind, because it wouldn’t contain actionable information that would improve the receiver’s experience. With the benefit of time, I can see that there are a few more wrinkles to discuss regarding advising.

Most of my early experience with advising was from my school and university years. Later, I’d go on to advise my friends on their business ventures by asking questions then following up with more questions. I’ll disclose a caveat to my thinking on advising: I’ve never been so keen on asking for advice because of all the bad advice I’ve received over the years. My negative advising experiences have given me a lot of ideas to chew on, though.

There is a distinction between offering a piece of advice, and being an actual adviser, and for this piece I’ll touch on both, with an emphasis on the latter.  I’d like to revisit that sentiment and delve a little bit deeper. Before I do, a brief discussion of what advice is and what advisers are is in order.

Generally speaking, people are familiar with the concept of taking advice from others regarding areas outside their expertise. Additionally, people are usually comfortable with the idea of providing advice to others when prompted– and, frequently to the frustration of others, when they are not prompted. Advice is the transfer of topical information or data by a third party to a person looking for a good outcome. A large volume of our communications are offering, requesting, or clarifying advice.

The concept of advice as information will be familiar to almost everyone. Frequently, the topical information that is elicited by a request for advice is anecdotal. If the adviser is careless or not directed, the anecdotal information offered to the advised may merely be tangentially related or actually unrelated to the issue at hand. Not everyone pays close attention to their outgoing advice if they have no skin in the game. The main problem with anecdotal evidence is that it refers to specific instances of a trend rather than the rules which govern that trend. Yet, most advice is anecdotal, perhaps as an artifact of humanity’s sensitivity to personal stories rather than hard data or universal laws.

Informally, it’s nearly impossible to escape anecdotal evidence when requesting or giving advice. Frequently, an adviser will forgo telling the actual anecdote, and skip right to the advice that they have distilled from their own experience, leaving the advised with an even more incomplete view. This has predictable consequences when paired with people’s tendency to do as others tell them. Using an incomplete group of anecdotes culled from the experience of others and processed from an uncomfortable position of ignorance, decisions are made based on the emotions of others rather than clear-headed analysis.

I am sure nearly everyone has received completely heartfelt yet completely detrimental advice in their time. If we are lucky, we avoid the consequences of receiving bad advice and catch the mistakes of our advisers in time to reject their thoughts and prevent internalization. If we are unlucky, we follow the path to nowhere and are upset with the results.

Part of maturity is understanding that while others are capable of delivering bad advice, we too are likely to give bad advice if given the chance. We don’t have to commit to delivering advice if we don’t feel qualified, nor do we have to ask for advice or follow advice once given. Advice is just a perspective on an issue, and not all perspectives are equal.

Critically, good advice is specific and actionable rather than vague. If the best that an adviser can do is offer a general direction to follow up on, you’re outside the realm of their experience or outside the amount of effort they’re willing to invest in you. A typical red flag for bad advice is that it’s delivered quickly, sleepily, or nearly automatically.

Good advising is extremely effort intensive! Rid yourself of advisers that don’t respect you enough to apply themselves fully. In my experience, the prototypical awful adviser is coerced into the role rather than choosing it themselves. University advisers are the worst example of being forced into advising. Identify which advisers are around only because they’re required to be, and then avoid them and their bad advice.

So, how are we going to limit our ability to deliver bad advice and maximize our delivery of good advice? Should we simply stonewall all requests for advice and refuse to ask others for help? I don’t think that this is the answer, because advice is one of the principle ways in which we can share the experiences of others and make use of experiences that we have not had ourselves. Sharing experiences is a critical component to being human, and it’s unlikely that we could stop even if we tried.

The way that I propose to avoid delivering bad advice and to actually deliver good advice is to use a mind-trick on ourselves. The mind-trick that I am referring to is playing pretend. First, I’ll need to build a mental image of the thing I want to pretend to be– the best possible adviser– then when it’s time to give advice, I’ll be able to pretend to be the embodiment of the image and put myself in the correct mindset for delivering good advice. After I’ve built the barebones of this mental image, taking it out for a test run with a hypothetical request for advice will help to fill in the details and also provide a template for how to think when it’s time to deliver real advice.

What are the properties of this mental image of the ideal adviser? I think that the perfect adviser is a professorial figure, and so adopting an academic tone and patient, receptive train of thought is necessary. Advising someone else shouldn’t be careless or haphazard, so the perfect adviser should mentally state an intention to provide their undivided and complete attention to the pupil for the duration of the session. The aim is to achieve a meditative focus on the present where the power of the adviser’s knowledge and experience can act without interference. The adviser is never emotional. Value judgments are deferred or unstated; the details and the pupil are at the forefront.

In order to advise properly, this professorial type will know the limits of his knowledge as well as his strong points, and will weight his statements to the pupil in accordance with how much he really knows, making sure to be precise with his language and to qualify his statements. Reaching the limits of the adviser’s knowledge isn’t something to be ashamed of, as it’s an interesting challenge for the ideal adviser to chew on.

The aim of the perfect adviser is to consider the particular details of the situation of his pupil, relate them to the universal trends which the adviser has uncovered with conscious effort, and then use a combination of the universal trends and the particulars of the pupil to offer a prescription for action. The mental image of the adviser will explicitly recite the universal trends to himself as he ponders the direction to indicate to his pupil. The conversation between the pupil and the adviser is marked by long pauses as the adviser takes the time to call critical trends and details into his working memory so that the pupil may make use of them. Advising is a conversation that can’t be rushed, because the adviser might forget to make an important connection of communicate in a precise way. The best advising has no time limit.

With each stanza of conversation, the adviser will find that his idea of the prescription in progress is stalled by a facet of the pupil’s situation which hasn’t been discussed. The adviser asks deeply focused questions which will unblock the progress of making his advice draft. The draft will have to be completely reworked in light of information gathered from the pupil. Once the draft is completed, the adviser will ask validating questions to see whether their draft is workable and realistic. Upon validation, the adviser will deliver the draft in a reassuring yet detached fashion.

I actually use this mental image when I’m called on to give advice, and I think it helps a lot. “Playing pretend” is just a convenient way of stepping into a foreign mindset without getting too self conscious. The important takeaway here is that the mindset of being a good adviser is very different from our normal range of thought because it is both clinical and creative. Clinical in the sense that facts and particulars are recognizable within a general framework, and creative in the sense that the solution to the clinically described problem probably doesn’t have a pre-established treatment.

Advising is a skill that can be learned and perfected, though it’s seldom prioritized. I think that prioritizing becoming a good adviser is absolutely essential if you think that giving advice is a core part of what you do. For the most part, “first do no harm” is a maxim that I wish more advisers practiced. If you liked this article, follow me on Twitter @cryoshon and check out my Patreon page! I’ll probably revisit this article when I have a bit more experience advising.

 

 

How to Ask A Good Scientific Question

One of the first tasks a scientist or curious person must undertake before experimentation is the formulation and positing of a scientific question. A scientific question is an extremely narrow question about reality which can be answered directly and specifically by data. Scientists pose scientific questions about obscure aspects of reality with the intent of discovering the answer via experimentation. After experimentation, the results of the experiment are compared with their most current explanation of reality, which will then be adjusted if necessary. In the laboratory, the original scientific question will likely take many complicated experiments and deep attention paid before it is answered.

For everyone else, the scientific question and experimental response is much more rudimentary: if you have ever wondered what the weather was like and then stepped outside to see for yourself, you have asked a very simple and broad scientific question and followed up with an equally simple experiment. Experiments render data, which is used to adjust the hypothesis, the working model that explains reality:  upon stepping outside, you may realize that it is cold, which supports your conception of the current time being winter.

Of course, a truly scientific hypothesis will seek to explain the ultimate cause as well as the proximate cause, but we’ll get into what that means later. For now, let’s investigate the concept of the hypothesis a little bit more so that we can understand the role of the scientific question a bit better.

Informally, we all carry countless hypotheses around in our head, though we don’t call them that and almost never consider them as models of reality that are informed by experimentation because of how natural the scientific process is to us. The hypotheses we are most familiar with are not even mentioned explicitly, though we rely on them deeply; our internal model of the world states that if we drop something, it will fall.

This simple hypothesis was likely formed early on in childhood, and was found to be correct over the course of many impromptu experiments where items were dropped and then were observed to fall. When our hypotheses are proven wrong by experimentation, our response is surprise, followed by a revision of the hypothesis in a way that accounts for the exception. Science at its most abstract is the continual revision of hypotheses after encountering surprising data points.

If we drop a tennis ball onto a hard floor, it will fall– then bounce back upward, gently violating our hypothesis that things will fall when dropped. Broadly speaking, our model of reality is still correct: the tennis ball does indeed fall when dropped, but we failed to account for the ball bouncing back upward, so we have to revise our hypothesis to explain the bounce. Once we have dropped the tennis ball a few more times to ensure that the first time was not a fluke, we may then adjust our hypothesis to include the possibility that some items, such as tennis balls, will bounce back up before falling again.

Of course, this hypothesis adjustment regarding tennis balls is quite naive, as it assigns the property of bouncing to certain objects rather than to a generalized phenomena of object motion and collision. The ultimate objective of the scientific process is to resolve vague hypotheses into perfect models of the world which can account for every possible state of affairs.

Hypotheses are vague and broad when first formed. Violations of the broad statements allow for clarification of the hypothesis and add detail to the model. As experiments continue to fill in the details of the hypothesis, our knowledge of reality deepens. Once our understanding of reality reaches a high enough level, we can propose matured hypotheses that can actually predict the way that reality will behave under certain conditions– this is one of the holy grails of scientific inquiry. Importantly, a prediction about the state of reality is just another type of scientific question. There is a critical caveat which I have not yet discussed, however.

Hypotheses must be testable by experimentation in order to be scientific. We will also say that hypotheses must be falsifiable. If the hypothesis states that the tennis ball bounces because of magic, it is not scientific or scientifically useful because there is no conceivable experiment which will tell us that “magic” is not the cause. We cannot interrogate more detail out of the concept of “magic” because it is immutable and mysterious by default.

Rather than filling in holes in our understanding of why tennis balls bounce, introducing the concept of magic as an explanation merely forces us to re-state the original question, “how does a tennis ball bouncing work?” In other words, introducing the concept of “magic” does not help us to add details which explain the phenomena of tennis balls bouncing, and ends up returning us to a search for more details. In general, hypotheses are better served by only introducing new concepts or terminology when necessary to label the relation of previously established data points to each other. The same could be said for the coining of a new term.

Now that we are on the same page regarding the purpose of scientific questions– adding detail to hypotheses by testing their statements– we can get into the guts of actually posing them. It’s okay if the scientific question is broad at first, so long as increasing levels of understanding allow for more specific inquiry. The best way to practice asking a basic scientific question is to imagine a physical phenomenon that fascinates you, then ask how it works and why. Answering the scientific question “why” is usually performed by catching up with previously performed research. Answering “how” will likely involve the same, although it may encounter the limit of human knowledge and require new experimentation to know definitively. I am fascinated by my dog’s penchant for heavily shedding hair. Why does my dog shed so much hair, and how does she know when to shed?

There are actually a number of scientific questions here, and we must isolate them from each other and identify the most abstract question we have first. We look for the most abstract question first in order to give a sort of conceptual location for our inquiry; once we know what the largest headline of our topic is, we know where on the paper we can try to squint and resolve the fine print. In actual practice, finding the most abstract question directs us to the proper body of already performed research.

Our most abstract question will always start with “why”. Answering “why” will always require a more comprehensive understanding of general instances that govern the phenomena in question, whereas “what” or “how” typically refers to an understanding that is limited to a fewer instances. So, our most abstract question here is, “Why does my dog shed so much?”

A complete scientific explanation of why the dog sheds will include a subsection which describes how the dog knows when to shed. Generally speaking, asking “why” brings you to the larger  and more comprehensively established hypothesis, whereas asking “how” brings you to the more narrow, less detailed, and more mechanistic hypothesis. Answering new questions of “why” in a scientific fashion will require answering many questions of “how” and synthesizing the results. When our previously held understanding of why is completely up-ended by some new explanation of how, we call it a scientific revolution.

At this point in human history, for every question we can have about the physical world, there is already a general hypothesis which our scientific questions will fall under. This is why it is important to orient our more specific scientific questions of “how” properly; we don’t want to be looking for our answer in the wrong place. In this case, we can say that dogs shed in order to regulate their temperature.

Temperature regulation is an already established general hypothesis which falls under the even more general hypothesis of homeostasis. So, when we ask how does the dog know when to shed, we understand that whatever the mechanistic details may be, the result of the sum of these details will be homeostasis of the dog via regulated temperature.

Understanding the integration between scientific whys and hows is a core concept in asking a good scientific question. Now that we have clarified the general “why” by catching up with previously established research, let’s think about our question of “how” for a moment. What level of detail are we looking for? Do we want to know about the hair shedding of dogs at the molecular level, the population level, or something in between? Once we decide, we should clarify our question accordingly to ensure that we conduct the proper experiment or look for the proper information.

When we clarify our scientific question, we need to phrase it in a way such that the information we are asking for is specific. A good way of doing this is simply rephrasing the question to ask for detailed information. Instead of asking, “how does the dog know when to shed”, ask, “what is the mechanism that causes dogs to shed at some times and not others.”

Asking for the mechanism means that you are asking for a detailed factual account. Indicating that you are interested in the aspect of the mechanism that makes dogs shed at some times but not other times clarifies the exact aspect of the mechanism of shedding that you are interested in. Asking “what is” can be the more precise way of asking “how.”

The question of the mechanism of shedding timing would be resolved even further into even more specific questions of sub-mechanisms if we were in the laboratory. Typically, scientific questions beget more scientific questions as details are uncovered by experiments which attempt to answer the original question.

As it turns out, we know from previous research that dog shedding periods are regulated by day length, which influences melatonin levels, which influences the hair growth cycle. Keen observers will note that there are many unstated scientific questions which filled in the details where I simplified using the word “influences”.

Now that you have an example of how to work through a proper scientific question from hypothesis to request for details, try it out for yourself. Asking a chain of scientific questions and researching the answers is one of the best ways to develop a sense of wonder for the complexity of our universe!

I hope you enjoyed this article, I’ve wanted to get these thoughts onto paper for quite a long time, and I assume I’ll revisit various portions of this piece later on because of how critical it is. If you want more content like this, check out my Twitter @cryoshon and my Patreon!

How to Become a Smarty Pants

There’s been a small amount of interest that I’ve seen in a few communities regarding building status as an “intellectual” in the colloquial sense, and I think it’s probably more correct to say that people would rather be perceived as smart than as dumb, which is completely fair.

This article could also be called “How to Look and Sound Like an Intellectual” although frankly that implies a scope that is much larger than anything I could discuss. So, we have a lighthearted article which purports to transform regular schlubs into smarty pants, if not genuinely smart people. If you already fashion yourself as a smarty pants, read on– I know you’re already into the idea of growing your capacities further. Hopefully my prescription won’t be too harsh for any given person to follow if they desire.

While it seems a bit backward to me to desire a socially assigned label rather than the concrete skills which cause people to give that label to others, building a curriculum  for being a smarty pants seems like an interesting challenge to me, so I’ll give it a shot. I hope that this will be a practice guide on how to not only seem smarter, but actually to think smarter and maybe even behave smarter. The general idea I’m going to hammer out here is that becoming an intellectual is merely a constant habit of stashing knowledge and cognitive tools. The contents of the stash are subject to compound interest as bridges between concepts are built and strengthened over time.

In many ways, I think that being a smarty pants is related with being a well rounded person in general. The primary difference between being seen as an intellectual and seen as a well rounded person is one of expertise. The expertise of an intellectual is building “intellect”, which is an amorphously defined faculty which lends itself to making witty rejoinders and authoritative-sounding commentary. There’s more to being a smarty pants than puns and convincing rhetoric, though: smarty pants everywhere have been utilizing obscure namedropping since the dawn of society. Playtime is over now, though. How the heck does a person become a smarty pants instead of merely pretending to be like one?

Being a smarty pants is a habit of prioritizing acquisition of deep knowledge over superficial knowledge. Were you taught the theory of evolution in school? Recall the image that is most commonly associated with evolution. You probably picked the monkey gradually becoming a walking man, which is wrong. The superficial knowledge of the idea that humans and monkeys had a common ancestor is extremely common, but the deeper knowledge is that taxonomically, evolution behaves like a branched tree rather than a series of points along a line.

See how I just scored some smarty pants points by taking a superficial idea and clarifying it with detailed evidence which is more accurate? That’s a core smarty pants technique, and it’s only possible if you have deep knowledge in the first place. Another smarty pants technique is anticipating misconceptions before they occur, and clearing them up preemptively. How should you acquire deep knowledge, though?

Stop watching “the news”, TV, movies, cat videos, and “shows”. Harsh, I know– but this step is completely necessary until a person has rooted themselves in being a smarty pants. This media is intended to prime you for certain behaviors and thoughts, occupy your time outside of work, and provide a sensation of entertainment rather than enriching your mind. The more you consume these media, the less your mind is your own, and the more your mind is merely a collection of tropes placed there by someone else. Choosing to be a smarty pants is the same as choosing isolation from the noise of the irrelevant.

For the most part, these media are sources of superficial information and never deep information. You can’t be a smarty pants if you’re only loaded with Big Bang Theory quotes, because being a smarty pants means knowing things that other people don’t know and synthesizing concepts together in ways that other people wouldn’t or couldn’t. There is zero mental effort involved in consuming the vast majority of these media, even the purported “educational” shows and documentaries which are largely vapid. Seeing a documentary is only the barest introduction to a topic. Intellectuals read, then think, then repeat.

I guess I’ve said some pretty radical things here, but try going back and viewing some media in the light I’ve cast it in. There are exceptions to the rule here, of course: The Wire, The Deer Hunter, American Beauty, or an exceptionally crafted documentary. The idea is that these deeper works are mentally participatory rather than passively consumed; the depth and emotionality that the best audiovisual media convey can be considered fine art, and smarty pants love fine art. During your smarty pants training, I would still avoid all of the above, though. Speaking of your smart pants training…

Stop reading “the news”, gossip of any kind, Facebook, Twitter, clickbait articles, and magazines.  These things are all motherlodes of superficial information. As Murakami said truthfully, “If you only read the books that everyone else is reading, you can only think what everyone else is thinking.” This concept is absolutely critical because an intellectual is defined by depth of thought, quality of thought, and originality of thought relative to the normal expectation. Loading up on intellectual junk food is useless for this purpose, so get rid of it and you will instantly get smarter.

Noticed how I namedropped Murakami there? That’s worth smarty pants points because it’s conceptual tie in that is directly relevant to the point I’m trying to make, and expresses the idea more elegantly than I could on my own. Don’t just namedrop obscure people wildly, as you’ll look more like a jackass than a smarty pants, though the line is blurry at times. Being a fresh-faced smarty pants frequently involves making the people around you feel inadequate, but it shouldn’t when practiced properly!

The purpose of self-enrichment is for self-benefit, and should not be used for putting down others. Frequently, knowledge may be controversial or unwelcome, so begin to be sensitive to that when conversing with others. Life isn’t a contest for who can show off the most factual knowledge– but if it were, a good smarty pants would be in the running for the winner, and that’s your new goal.

Pick an area that will be your expertise. Pick something you will find interesting and can learn about without laboring against your attention capacity. This should be distinct from a hobby. Which topic you address is up to you, but I’d highly suggest approaching whatever topic you choose in a multi-disciplinary manner. If you’re interested in psychology, be sure to devour some sociology. If you’re interested in biology, grab some chemistry and physics. If you’re a philosopher, try literature or history. Your expertise in your chosen field will mature over time, and eventually you should branch out to gain expertise in a new field.

The idea here is that the process of picking an area of expertise is useful to the smarty pants. By evaluating different areas, the smarty pants will get a feel for what they’re interested in, what’s current, and what’s boring. The most intellectually fruitful areas of expertise have a lot of cross-applicability to other areas and concepts, an established corpus of literature, and a lot of superficial everyday-life correlates. Suitable examples of areas of expertise are “the history of science” or “modern political thought”. An unsuitable example of an area of expertise would be “dogs” or “engine design”. Unsuitable areas of expertise aren’t applicable to outside concepts and don’t confer new paradigms of thought.

Start reading books, in-depth articles, and scholarly summaries on topics which you want to develop your expertise in. A smarty pants has a hungry mind and needs a constant supply of brain food, which is synonymous with deep knowledge. Reading books and developing deep knowledge is never finished for the aspiring smarty pants. Plow through book after book; ensure that the most referenced scholarly works or industrial texts are well-understood. Understand who the major thinkers and groups are within the area of expertise, and be able to explain their thoughts and relationships. Quality is the priority over quantity of information, however.

Merely stopping the flow of bad information in and starting a flow of good information isn’t enough to be a real smarty pants, though it’s a good start. In order to really change ourselves into smarty pants, we must change our way of engagement with the world. As referenced before regarding media consumption, a smarty pants must interrogate the world with an active mind rather than a passive mind. What do I mean here?

A passive mind watches the world and receives its thoughts as passed from on high. Passive minds do not chew on incoming information before internalizing it– we recognize this the most pungently when a relative makes regrettable political statements culled directly from Fox News. An active mind is constantly questioning validity, making comparisons to previous concepts, and rejecting faulty logic. An active mind references the current topic with its corpus of knowledge, finding inconsistencies.

Creating an active mind is an extremely large task that I’ll probably break into in another full article, but suffice it to say that the smarty pants must get into the habit of chewing on incoming information and assessing its value before swallowing. Learning how to think/write systematically and disagree intelligently are probably both skills that a smarty pants can make use of.

Speaking of relatives, a smarty pants needs to have good company in order to grow. Ditch your dumb old friends and get some folks who are definitely smarter than you– they exist, no matter what you may think of yourself. You don’t really need to ditch your old friends, but you really do need to get the brain juices flowing by social contact with other smarty pants. There are many groups on the internet which purport to be the home of  smart people, but my personal choice is HackerNews.

It’ll hurt to feel dumb all the time, but remember that feeling dumb means that you are being exposed to difficult new concepts or information. Feeling dumb is the ideal situation f0r an aspiring smarty pants because feeling dumb means that you are feeling pressure that will promote growing to meet the demands of your environment. Every time you feel dumb, catch the feeling, resolve the feeling to an explicit insecurity, then gather and process information until that insecurity is squashed by understanding. Like I said before, this step is unpleasant, but nobody said being a smarty pants was easy.

This concludes my primer on how to be a smarty pants. I’ll be writing more on this topic, though a bit more seriously and more specifically. I’d really like to publish a general “how to think critically” article in the near future, and of course critical thinking is a core smarty pants skill. I have a reading list for the most general and abstract “smarty pants education” that I’ll be publishing relatively soon as well. Until then, try practicing the bold points here.

Be sure to follow me on Twitter @cryoshon and check out my Patreon page!

A Response to Paul Graham’s Article on Income Inequality

While perusing HackerNews today, I encountered this article and this comment thread by Paul Graham (PG for short), founder of Ycombinator. I think that a lengthy response is in order. I originally intended this response to be in my HN comment, but it was too long. If you’re not interested in debating income inequality, this response is not for you. I’ll be quoting quite liberally from PG’s essay in this response.

So, let’s get started. I think PG really missed the mark with his assessment of the impact of economic inequality and instead substituted a real world struggle against economic conditions with a rosy economic model which starts from the premise that the rich need the ability to get richer in order to have a successful society.

To quote Graham, mafioso of the startup incubators: “I’m interested in the topic because I am a manufacturer of economic inequality.”

Well, not quite. The throughput of successful startup folks is never going to be enough to make a dent in the economy’s general state of inequality. If anything, YC offers social mobility insurance; the potential for social mobility from the middle classes to the lower-upper class without the potential for a slip from the middle classes to the lower classes in the event of failure.

“I’ve also written essays encouraging people to increase economic inequality and giving them detailed instructions showing how.”

Perhaps PG misunderstand the terms here? Has he been instructing his charges to pay lower wages and fewer benefits as their profits scale upward so as to add more to their own purses? A disconnect between rising productivity and worker income is one of the largest factors for economic inequality in the US.

“The most common mistake people make about economic inequality is to treat it as a single phenomenon. The most naive version of which is the one based on the pie fallacy: that the rich get rich by taking money from the poor.”

Well, “taking” is a bit biased, but broadly speaking, it’s true that the poor must buy or rent what the rich are offering in order to survive. This means that the poor are economically at the whim of the rich unless they choose to grow their own food and live pastorally, which isn’t desirable. People pay rent if they’re poor, and collect rent if they’re rich. The poor sell their labor, whereas the rich buy labor in order to utilize their capital, which the poor have none of. These are traits of capitalism rather than anything to get upset about. People get upset when the rich use their oversized political influence to get laws passed to their benefit; over time, the rich make more money due to their ability to manipulate the political system.

“…those at the top are grabbing an increasing fraction of the nation’s income—so much of a larger share that what’s left over for the rest is diminished….”

Check out these charts… the data is much-discussed because they are unimpeachable. Ignoring the reality of data is a mistake economists often make, which can explain some of their more incorrect predictions.

“In the real world you can create wealth as well as taking it from others. A woodworker creates wealth. He makes a chair, and you willingly give him money in return for it. A high-frequency trader does not. He makes a dollar only when someone on the other end of a trade loses a dollar.

If the rich people in a society got that way by taking wealth from the poor, then you have the degenerate case of economic inequality where the cause of poverty is the same as the cause of wealth. But instances of inequality don’t have to be instances of the degenerate case. If one woodworker makes 5 chairs and another makes none, the second woodworker will have less money, but not because anyone took anything from him.”

The woodworker works in a wood shop, not alone. The owner of the wood shop has decided that if 5 chairs are sold, it takes 2 chairs worth of money to recoup the costs of making the chair. With three chairs worth of money remaining, he takes two and three fourths chairs for himself and distributes the remaining amount to the worker who created the chair.

The woodworker created the wealth by using the owner’s capital, and so the owner of the capital gets the vast majority of the wealth generated, even though he didn’t actually make the chairs himself. Is the owner “taking” from his employee? No, the employee has merely realized that one fourth of one chair’s income is the standard amount that a woodworker can get from working in a shop owned by someone else, and happened to choose this particular shop to work in. “Taking” is the wrong word; “greed” is the proper word. The proportion of revenue derived from capital that is returned to workers selling their labor is far too low. The woodworkers can’t simultaneously pay off their woodworking school loans, apartment rent, and care for their children on the wages they’re offered.

“Except in the degenerate case, economic inequality can’t be described by a ratio or even a curve. In the general case it consists of multiple ways people become poor, and multiple ways people become rich. Which means to understand economic inequality in a country, you have to go find individual people who are poor or rich and figure out why.”

Actually, economists have been describing it in the terms of ratios and curves for a long time. Piketty’s account is the most current. The “ways” of becoming poor or rich misses the point entirely. Upward social mobility is very low now, and downward social mobility is quite high. Outside “becoming” rich or poor, the standard of living for the rich has risen and the standard of living for everyone else has dropped. Becoming rich is an edge case which isn’t even worth talking about when there are far more people in danger of becoming poor. We have no obligation to stop someone from “becoming rich”– but we have a strong obligation to stop someone from becoming poor.

“If you want to understand change in economic inequality, you should ask what those people would have done when it was different. This is one way I know the rich aren’t all getting richer simply from some sinister new system for transferring wealth to them from everyone else. When you use the would-have method with startup founders, you find what most would have done back in 1960, when economic inequality was lower, was to join big companies or become professors. Before Mark Zuckerberg started Facebook, his default expectation was that he’d end up working at Microsoft. The reason he and most other startup founders are richer than they would have been in the mid 20th century is not because of some right turn the country took during the Reagan administration, but because progress in technology has made it much easier to start a new company that grows fast.”

Not even close. The richest hundred people have gotten wildly richer as a result of crony capitalism in which the richest are able to bend the political system to their will via overt bribery, creating unfair advantages for their ventures and endless loopholes for their personal wealth to avoid taxation. The ventures of the very rich are given unearned integration into political life, again making them a shoe in for special treatment.

Remember how the failing banks in the financial crisis were considered too big to fail, and were accommodated at the public’s expense? This kind of behavior insures the rich’s safety with the money culled from the poor. Information technology is a gold rush, and creates rich people by forging new vehicles of capital– generating wealth. The economics of a gold rush are quite clear, but PG forgets that the vast, vast majority of the workers in the economy are not participating in the gold rush, nor could they.

“And that group presents two problems for the hunter of economic inequality. One is that variation in productivity is accelerating. The rate at which individuals can create wealth depends on the technology available to them, and that grows polynomially. The other problem with creating wealth, as a source of inequality, is that it can expand to accommodate a lot of people.”

Productivity has been increasing for decades, and at one point in time, wages tracked productivity. The relationship between wages and productivity fell apart. This means that the business owners were benefiting from increased worker productivity, but the workers were not benefiting… another cause of economic inequality that can be attributed directly to the owners not allowing enough money to go to their workers. If productivity is accelerating, wages should be too. Rather than understanding workers as slaves that require a dole as they are presently, they must be considered as close partners in economic production.

“Most people who get rich tend to be fairly driven. Whatever their other flaws, laziness is usually not one of them. Suppose new policies make it hard to make a fortune in finance. Does it seem plausible that the people who currently go into finance to make their fortunes will continue to do so but be content to work for ordinary salaries? The reason they go into finance is not because they love finance but because they want to get rich. If the only way left to get rich is to start startups, they’ll start startups. They’ll do well at it too, because determination is the main factor in the success of a startup. [3] And while it would probably be a good thing for the world if people who wanted to get rich switched from playing zero-sum games to creating wealth, that would not only not eliminate economic inequality, but might even make it worse. In a zero-sum game there is at least a limit to the upside. Plus a lot of the new startups would create new technology that further accelerated variation in productivity.”

Once again: the current flap about economic inequality is not about people wanting to become rich, it is about people wanting to get by. Most people are not driven. Everyone wants to at least get by. You will not stop people from being driven to become rich by making it possible for everyone else to get by.

“So let’s be clear about that. Ending economic inequality would mean ending startups. Are you sure, hunters, that you want to shoot this particular animal? It would only mean you eliminated startups in your own country. Ambitious people already move halfway around the world to further their careers, and startups can operate from anywhere nowadays. So if you made it impossible to get rich by creating wealth in your country, the ambitious people in your country would just leave and do it somewhere else. Which would certainly get you a lower Gini coefficient, along with a lesson in being careful what you ask for. ”

No, it wouldn’t. There is lower and higher economic inequality in many places in the world, and many of those places have startups. There is nothing special about startups, and startups persist whether or not the society is extremely unequal. There are startups in Sweden. There are startups in China. There are startups in Nigeria. There are startups in Denmark. There is absolutely no reason to be prideful in the American startup phenomenon if it requires people living in poverty– I do not believe that it does require this, though.

“And while some of the growth in economic inequality we’ve seen since then has been due to bad behavior of various kinds, there has simultaneously been a huge increase in individuals’ ability to create wealth. Startups are almost entirely a product of this period. And even within the startup world, there has been a qualitative change in the last 10 years.”

Do not confuse the tech startup as a method for creating wealth that anyone can step into. Coding is a difficult skill that most people are not about to retrain into, even if it’s lucrative.

“Notice how novel it feels to think about that. The public conversation so far has been exclusively about the need to decrease economic inequality. We’ve barely given a thought to how to live with it.

I’m hopeful we’ll be able to. Brandeis was a product of the Gilded Age, and things have changed since then. It’s harder to hide wrongdoing now. And to get rich now you don’t have to buy politicians the way railroad or oil magnates did. [6] The great concentrations of wealth I see around me in Silicon Valley don’t seem to be destroying democracy.”

Living with economic inequality is uncomfortable for the majority of the population, but it is comfortable for the rich. The way to live with it is to defer having children, not get a graduate education, never own a home, have a shitty car, never eat out, don’t go on vacation, work two jobs, don’t ever get sick, don’t get married, never pay off student loans, never save for retirement or an emergency, and never get arrested.

Seems pretty shitty, right? Seems like something people would want to change for the better, right? I will also state that all of the above items vastly detract from a person’s free-mental and physical energy, which results in less innovation and ultimately less creation of the “startups” that income inequality is supposed to support. PG even acknowledges this, but doesn’t seem to understand the visceral impact of income inequality.

To crystallize everything, let’s hop backward to a time when there was less inequality and compare lifestyles. In yesteryear, families requires only one breadwinner, and debt beyond a mortgage was unknown. People had a car per person, and college education. If you were sick, you could pay for a doctor. People had savings. People married young, and bought starter homes… then moved into larger homes. People had children. People could care for their aging parents without moving back in. People had pensions, retirement funds, and plans to use both. All of this wealth derived directly from workers selling their labor for money. Starting new businesses happened frequently because there was a robust net to fall on in case of failure. Workers banded together to protect their share. Wages tracked productivity.

Now: none of the above, and families often consist of two breadwinners (& no children) with a hearty amount of debt, nothing owned, and few savings. The family unit itself may even be weaker because of less shared ownership. Wages haven’t tracked productivity for decades, so wages haven’t risen since the previous story was normal. We’ve lost all of that ground: not just some of it, all of it, and more. We’re back to the 1920s– wage slaves with few rights and no political ability to change things.

Is this what PG thinks is okay?

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How to Disagree Intelligently At Work

One of the large differences I see between technical/scientific people and laymen is in the communication style that critiques or disagreements are offered. Disagreeing with other people in an effective and respectful way is an extremely difficult skill that takes considerable guts to practice.

For the most part, people find disagreeing with each other as difficult and uncomfortable, and use watered-down and less effective language as a result. Some people have the opposite problem, where they are too willing to disagree with others tactlessly without really considering why they disagree in the first place. The prior style of disagreement leads to miscommunication and unfixed problems, whereas the latter leads to bruised egos and frayed team morale.

There’s clearly a big incentive to disagree effectively. Needless to say, there are many possible ways of delivering the sentiment of disagreement correctly and incorrectly. Certain personalities and dispositions are biased toward certain disagreement styles. The scale of disagreement matters too, as a technical dispute may be easier to resolve than a philosophical spat. This article pertains to both of those disagreements, though I think the technical spats are generally easier to resolve quickly as it’s possible to conduct experiments and determine which technical option is better. I’ll characterize ineffective ways of disagreeing and offer a few smarter methods in this article. First, it makes sense to elaborate on exactly what disagreement is in a professional context.

What is disagreement? I will define disagreement as an inconsistent opinion between parties. If an opinion is consistent among all parties, there is consensus. In a professional context, disagreement is a communication modality that is  found within teams or pairs of individuals. Communication modalities are fluid, and are emergent from the interactions between individuals that make up a group. A group made of particularly cantankerous individuals will likely be in the modality of disagreement far more than a group of shy people. Do not take this as a suggestion to form teams of compliant people: disagreement is how bad ideas are destroyed before they cause real damage, and a team is empowered by strong ideas. Disagreement can be essential pruning when used properly.

So, our understanding of disagreement is that  it’s a pattern of communication resulting from inconsistent opinions on a given issue. Much of our time spent in meetings is actually spent trying to jostle the group’s current communication modality from  disagreement to consensus. We may even decide to form groups based off of how much or little the members of the group are likely to have internal agreement or disagreement, though an excess of either is likely to be harmful for the actual output of the group.

One of the functions of leaders in the workplace is to try to circumvent a state of disagreement via executive action– though a definitive ruling will typically allow for work to continue despite the disagreement, it rarely actually resolves the dispute at hand and is frequently akin to the ego-bruising too-direct style of disagreement in terms of damage caused to the team.

Instead of promoting coping strategies for leaders to use in an attempt to ease the pain of being overruled, I think it’s much more effective for leaders to ease disputes via consensus building rather than default to authority’s power. Part of moving the team from disagreement to consensus is  accepting that opinions are malleable and subject to extreme change under the right conditions.  In order for the leader and group members to move toward consensus, effective disagreement is critical.

Ineffective disagreement:

  • Uses personal attacks against others, even if they aren’t present
  • Prompts negative defensive reactions from others via indirect criticism or passive aggression
  • Appeals to office politics or the sanctity of individual fiefdoms
  • Denies or neglects unchangeable frameworks or obstacles
  • Asserts incompetence of other people or groups that will be relied on, even if it’s true
  • Denies attempts to refine points of disagreement
  • Dismisses disagreement as irrelevant without explaining why
  • Breaks group up via factional lines instead of individual opinion
  • Is delivered shortly, bluntly, and without true consideration of the facts
  • Does not rally facts and data to support statements
  • Is delivered agitatedly or emotionally
  • Assumes negative reaction to disagreement from others before it’s actually given
  • Fills in details of opposing arguments without having explicitly heard them
  • Is overly general or lacking specific articulate criticisms
  • Can be reduced to “my gut feeling doesn’t like this”
  • Paves over or ignores opposing viewpoint when convenient
  • Detracts from importance of the issue in disagreement rather than address the disagreement itself
  • Expects authority to effect a particular action regardless of discussion
  • Is delivered only because it is expected by superiors
  • Surrenders quickly due to discomfort associated with disagreeing
  • Plays devil’s advocate wantonly or without purpose

Effective disagreement:

  • Maintains an open mind and pliable opinion
  • Accepts that disagreements can be resolved via changing of opinion
  • Does not assume personal correctness of opinion
  • Does not shut down discussion before the group has agreed to stop
  • Is delivered after considering the merit of the opposing viewpoint relative to the facts and data at hand
  • Is delivered coolly with constant reference to established facts and data for each statement
  • Attempts to refine points of disagreement between parties first, then resolve disagreements second
  • Seeks to actually change opinion of disagreeing parties to reach a consensus that all parties will agree is the most effective path forward
  • Does not respond to emotionality or passionate arguments, preferring impartial consideration
  • Accepts disagreement as an essential and positive part of team functionality
  • Assumes good will and common goals of people with different opinion
  • Understands the personalities and thought processes of the people supporting the opposing opinion
  • Tenaciously argues for opinion, but accepts defeat when clearly outmaneuvered
  • Accepts that there is usually no moral content of disagreement in the professional context
  • Does not build grudges or allow tainting of discussion by grudges based off of disagreements
  • Is scientifically detached from both the issue and the individuals at hand
  • Is blind to status and applied equally
  • Is delivered respectfully, directly, without personal attacks or passive aggression
  • Is delivered in neutral language, in a neutral tone

There’s quite a bit to keep track of here, so I’ll summarize the biggest points of each quickly. Ineffective disagreement is emotional, argumentative, judgmental, fact-free, loud, and political. Effective/intelligent disagreement is data-driven, neutral toned, open minded, inquisitive, and status-blind. Of course, getting yourself and your team to disagree in an effective way is easier said than done, as many people have been disagreeing ineffectively for a lifetime. The colloquial pattern of disagreement is easy to fall into, but has no place in a work environment because it’s an expression of emotion rather than an attempt to navigate a path forward.

Delving into resolving disagreements, I highly suggest that you understand your own opinion on the disagreed-on issue completely. Write your opinion down, and think systematically! Most of the time, our opinions are not nearly as clarified or explicit as we would suspect. Very frequently, clashing opinions are a result of unclarified thoughts that lie in between premise and conclusion. The human brain has a fantastic ability to sketch an idea’s outskirts, then trick itself into believing that the interior is filled with detail without actually investigating each wrinkle. Upon examination of the area in between the edges, we find that our idea isn’t really as developed as we had initially hoped.

Referencing data and forcing a step by step compilation of an opinion’s logic is one of the strongest tools for evaluating ideas, and is an essential tool for smart disagreement. If an opinion is fully developed and linked to supporting data, it is easier to positively assert that the opinion is correct and also easier to refute clashes with other opinions. If an opinion is fully thought out and linked to data, it will usually be more persuasive than an emotional opinion and allow for a faster resolution of disagreement.

In the laboratory, the way to resolve certain disagreements of fact was to conduct experiments. The results of the experiment would clarify which opinion was correct, and instantly catalyze a consensus. Of course, there was always the chance that the data from an experiment would raise new disagreements and questions, but this too was a welcome consequence, and moved the discussion forward.

Conducting experiments to resolve disagreements may not always be possible in a work setting, but sometimes a thought experiment or hypothetical experiment can be helpful in clarifying opinions. If the path through a jammed disagreement isn’t being loosened by talking through the logical steps and evidence for each opinion, try an experiment. I’ve discussed how to conduct an experiment in a work setting in my previous post.

I find that being more in tune with emotions and personal state of mind helps to disagree more intelligently. As out there as it may sound, a lot of team disagreements over otherwise trivial issues are born from outside stressors. If a person is stressed out or otherwise emotionally run down, their disagreement style will trend toward the “ineffective disagreement” list. Defensiveness, emotionality, and reactivity are far more likely to crop up. In this sense, ineffective disagreement can be a symptom of other problems in the work environment.

The companion post to this will probably be discussing how to agree effectively in the workplace– easier said than done, I think! I may also revisit this post at a later time with special attention to office politics and personal fiefdoms, which I have found to be particularly poisonous for team cohesiveness and effective disagreement.

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How To Write Systematically in 11.5 bites

After a few years of working in biomedical research and a philosophy degree from college, I know a few things about writing and thinking systematically. Unfortunately, I see a lot of people stumbling in their writing when they try to create complex abstract or technical materials– writing is tough, and accurate, succinct, detailed, and logical writing is even harder.

To me, systematic writing is a method of writing which seeks to transmute the complex relationships between raw or parsed data into a coherent, readable narrative that can be effectively understood and analyzed by someone who is generally knowledgeable on the topic, but who didn’t gather or prepare the data. Systematic writing is part of a greater family of writing that includes scientific writing, technical writing, and financial writing, along with other types I probably haven’t even thought of.

While this definition may seem overly abstract, I’d like to point out that most of our received and sent communications are not systematic; a news anchor is not relaying systematically prepared information to the public, even though the reporters have gone through the trouble of parsing raw data (events that happened) into a narrative (what the anchor says). The quantity of technical detail and data referencing in a news report is slim, as news reports are designed for a very wide audience who have little previous context for the event that happened (the data). An email we send to a colleague referencing data or analysis is not necessarily systematic writing, as it’s entirely possible for a certain context to be inferred between two people; systematic writing provides its own context and content explicitly to the audience.

Systematic writing is typically intended for a small, already-savvy audience, and should only offer the minimal viable context. A reader with general knowledge on the topic of the piece should be able to acquaint himself with a systematically written piece in short order, but a layman should not, because establishing the amount of context required for a layman would involve a lot of background information which falls outside of the scope of a particular instance of systematic writing. We don’t want our systematic writing to sprawl, because systematic writing is intensely purposeful and detail-heavy writing, and lots of background information and tangents dilute the factual details we’re trying to communicate.

So, the title promises 11.5 bites describing the process of writing systematically, and without further ado here’s a primer on how to write and think systematically:

  1. Define your goal. What kind of narrative do you want to make, and what data are you planning on using? Who is going to read the report, and how much context will be required?
  2. Put on your white thinking hat.  To use the terminology of the fantastic thought guide Six Thinking Hats, the white thinking hat is purely unbiased and factual thinking used for establishing a common ground among readers. If you’re going to be writing a systematic document which refers to data, you need to make sure that you don’t take any liberties with the data without explicitly qualifying them as speculation or partially supported. No spin!
  3. Assemble your data. You can’t write systematically without having data. Ensure that your data is collated/parsed/charted in a non-deceptive and easy to understand way– the only person you’re trying to inform at this step is yourself, so it behooves you to be honest about the quality of your data and what knowledge we can actually extract in analysis. If there are computations or manipulations required of your data, now is the time to do them.
  4. Determine the limits of what your data can tell you. Soon, we’ll analyze our data, but first, we need to vaccinate ourselves against narrative mistakes. Though it seems simple, it’s easy to slip up and attribute facts to your data that aren’t actually there. Explicitly state the variables which your data depicts (sales, months). Remember that going forward, all of your statements should be in terms of the variables which you outline here. If you’re not talking about information within the purview the data that your variables describe, you’re not being systematic.
  5. Extract verbal information from your data.   Write down simple statements to these effects,  such as, “the data for November showed 42 sales.” If you computed averages or other values in your data assembly step, now is the time to introduce it as a simple phrase. If you expect that handling the data in this way will be confusing, document your process simply and clearly so that your audience will understand. Do not introduce any explanation at this point, merely state what the data say, and, if necessary, state how the data were processed. Remember not to speculate, the point of this step is to establish purely factual statements.
  6. Analyze your data at a basic level. Now that you have a series of simple statements depicting your data in an unbiased way, comparisons between data statements can begin. Are the sales from November higher than the sales from October? Write that comparison down if it’s relevant to your originally stated goal, and make sure to directly reference the values in your new synthesis statements. The point of this step is to explicitly state simple relationships of the data, independent of any narrative.
  7. Analyze your data deeply. Stay focused on your original goal during this step. What questions can your impartial data statements answer explicitly? Implicitly? What trends in your data are noteworthy? What points of data are outliers? Can you explain the outliers? In this step, writing more complex statements is necessary. “The sales data from November (42 sales) are higher than October (30 sales), following the upward trend of the fall season. These data tell us that the fall season is our strongest selling period, despite the high sales in December.” Don’t try to speculate or hypothesize about “why” yet, just tease out the more complex relationships in your data, and write them down in a clear way. As always, reference your data directly in order to build context for your audience and keep them on the same page. Don’t worry about over-analyzing at this point, we’ll prune our findings later.
  8.  Ask Why. Why did we see the data that we saw in our analysis? What are the general principles governing our data? Address each piece of relevant data with this question, and ensure to answer it briefly. The outliers that were previously identified need special attention at this point. Keep explanations of your data concise and factual, though remember that your explanations are not actually within your data set, so you should draw in outside proof to support your explanations if necessary. It’s okay to hypothesize if you don’t know exactly why certain data turned out the way that they did, but be sure to explicitly label speculation.
  9. Build a narrative using your data, analyses, and explanation. Consider your starting goal, and how to marshal the data, analyses, and explanations in order to accomplish that goal. Your narrative should proceed first with the data, then with a simple factual explanation of the data, then with a more complex analysis of the data, and finish off with an explanation of the data if it’s required. The narrative step of systematic writing is where you put all of the pieces together and put it into one attractive package for your audience. Don’t neglect graceful segways between different portions of the data set. The final product of this step can be considered a first draft of your systematic writing effort, and may take the form of a PowerPoint presentation, meeting agenda, technical report, or formal paper.
  10. Anticipate questions and comments from your audience. Look for areas in which your explanation, analysis, or data prompt a response, and plan accordingly. Questions regarding your narrative are typically the easiest to address by clarifying what you’ve already written explaining why your data appears the way it does. Questions regarding your analysis can get a bit technical depending on the audience, and so you should be prepared to refer back to the source data in your responses. Questions regarding the data itself  or the parsing of the data are the most difficult; typically, the outliers will be under the most scrutiny, and their data quality may be called into question. I find that it helps to get out in front of questions regarding outliers, addressing them to your audience before taking questions.
  11. Prune non-critical information. This is the step where most of the data-statements and analysis statements meet their demise. Which analyses, explanations, and narrative elements aren’t strictly serving your original goal? Remove extraneous information to create a hardened product. Ensure that the relevant context and core data analysis remains, and don’t build a misleading narrative by omitting contradictory relevant data.

The final half-step is, of course, crossing the t’s and dotting the i’s for your final draft– and make sure it’s perfect! A missed detail on something not mission-critical will still distract your audience from your data and analysis.

I hope that my readers have a better idea of how to write and perhaps think systematically after reading this piece. I think that many non-technical people struggle with systematic writing because of how data-centric it is; communicating in the style of referencing data and withholding speculation can be quite difficult for people accustomed to relating written concepts intuitively and emotionally.

If you have any questions, leave em’ in the comments and I’ll respond. I know that the 21st century will have the highest demand yet for systematic thinkers and writers, so I’m also considering forming a consultancy in order to help organizations with training their employees and executives to think and communicate in systematic ways, so expect more on topics like this in the future.

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