TOK Tuesdays

Investigating PT6 – Helpful Biases?

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This is the final of six special TOK posts to directly assist students and teachers in appreciating vital nuances associated with each of the May 2021 Prescribed Titles.  For each title, I will identify some initial key concepts and highlight some specific approaches to address them along with specific Ideas Roadshow’s IBDP Portal resources that can concretely assist in the development of a strong TOK essay for that particular title.   

This piece discusses PT6: “Avoiding bias seems a commendable goal, but this fails to recognize the positive role that bias can play in the pursuit of knowledge.”  Discuss this statement with reference to two areas of knowledge.

Key Concepts:  

This title, together with PT3, are my personal favourites of the six on offer for this session.  Why?  Because along with the usual requirements of carefully parsing phrases and probing subtle aspects of meaning lies an additional opportunity to rethink core aspects of what TOK-thinking really is and how it can be applied to the world around us. 

For PT3, as we’ve already discussed, lurking behind the title’s typically dense wording is the intriguing notion of whether or not it can be justifiably argued that the imposition of any organizational structure to some extent inhibits aspects of our understanding, while in this title we are forced to ponder the notion of “bias” in a much more sophisticated way than is usually the case.  

In particular, this title asks us to consider whether or not biases might sometimes serve a positive role in the knowledge process.  To most students—and perhaps even many teachers—such a notion will initially seem quite startling.  After all, aren’t we all agreed that biases are generally a bad thing, representing a combination of closed-mindedness, pre-set expectations, and a needlessly blinkered world-view?  How can biases possibly be good things to have?

Well, I don’t have “the answer”, of course, and I hardly need to stress here that the entire point of this title is for you to come up with your own view.  But unlike many PTs where the onus is on the student to elaborate subtle shades of grey associated with specific words (e.g. To what extent can we distinguish between “useful” and “most useful”? What do we mean by “element of trust”, exactly, and under what circumstances can we maintain that it is always present?), this title strikes me as one which would appeal to those whose interests are naturally oriented towards the development of broader and refined conceptual frameworks: whatever can be possibly meant by a “positive bias”?  

My own perspective follows from a thought experiment. Imagine a world where knowledge-seekers always start their investigations from a position of total ignorance, wholly uninfluenced by anything that has happened before.   Physicists would sit down to do their experiments ignorant of Newton’s Laws (or any others), historians wouldn’t have read (or at least remembered) any other text before they begin their analysis, anthropologists would judge every human society they encounter as the first one they’ve ever seen. Of course these sorts of scenarios are hardly realistic, but that’s not the point. The idea here is to flesh out two things:

  1. What would it take, exactly, for a knowledge-seeker to be completely without any biases whatever?
  2. Assuming that could somehow be arranged, would it, in fact, be a good thing in terms of their ability to produce knowledge?

Reflecting on the first point makes me appreciate that, for all practical purposes, it is inevitable that—whatever the particular area of knowledge we wish to consider—those involved in the pursuit of knowledge inevitably bring some biases to the table as they begin their inquiries.  Moreover, the more experienced and knowledgeable they are, to a very real extent the larger the number of biases they might have. 

Meanwhile, a few moment’s reflection on the second point brings me to the swift conclusion that a world where knowledge-seekers were all strictly unbiased would be tremendously inefficient from a knowledge-generation perspective. 

OK, so that’s interesting: I’ve just concluded that not only is a certain amount of bias in the knowledge process inevitable, but that seems to be a good thing.  But now what do I do?  After all, and after sitting through hours of TOK classes, I’m also firmly convinced that bias can be significantly detrimental to our development of knowledge.   

There are lots of interesting ways to proceed here. One approach might be to make a distinction between “good” and “bad” bias, or “reasonable” and “unreasonable” biases, possibly based upon some statistical arguments of how likely any initial assumption is likely to be rendered invalid. Another might be to recognize that the problem with bias in this case isn’t so much that we will approach a situation with some pre-set expectations or inclinations but to ensure that we explicitly recognize what they are so that they don’t unduly prejudice our efforts. Again, you have to find the right approach that fits with you, but as usual whatever you decide to do, you’ll likely need to find some pointed and revealing examples of when bias might both help and hinder the knowledge process.  And that’s what the next section is all about.

Below we highlight a number of specific resource examples that are part of Ideas Roadshow’s IBDP Portal  to build a world-class TOK Essay.

Ideas Roadshow’s IBDP Portal offers a strong pedagogical framework where TOK is the backbone of interdisciplinarity throughout all resources.

In what follows, we provide numerous examples of what I referred to above as “good” and “bad” biases from four experts in four different research areas. The TOK Clips are all part of Ideas Roadshow’s IBDP Portal and come with detailed supplementary print materials and citing details to build a great TOK essay. Only subscribers to Ideas Roadshow’s IBDP Portal can use the materials below!

In Predicting the Higgs, world-leading physicist Nima Arkani-Hamed reveals how, by assuming both the inherent correctness of our particle physics models and the common belief that “nature will avail herself of all possibilities that she has open to her”, we were able to successfully predict the existence of the Higgs boson.

In Astonishingly Simple, Prof. Arkani-Hamed again reveals his bias towards the intrinsically mathematical nature of physical laws when he describes how the conspicuously and surprisingly simple final form of a calculation is likely evidence of a deeper underlying structure. But in Distracted by Language Prof. Arkani-Hamed describes how, if we’re not careful, an undue reliance on the vagaries of language can result in a litany of unhelpful biases and assumptions that can lead physicists down the wrong path. 

Meanwhile, political scientist Mark Bevir freely admits to his guiding assumptions (to what extent, you might wish to consider, can “principles” be objectively distinguished from “biases”?) before moving on to demonstrate specific instances where the biases of many of his colleagues lead them astray. In Philosophical Thinking he adamantly expresses how he is convinced that adopting a rigorously philosophical approach is necessary to make progress in the social sciences.

In The Importance of Dialogue Prof. Bevir insists that, regardless of the particular issues at play or the prevailing public attitudes, it is always beneficial for policymakers to solicit the views of the general public before implementing any policy measure, even if it is one that most people object to. But in Descriptions vs Explanations he details how the prevailing bias that is unhesitatingly adopted by many of his colleagues—that the business of the social sciences is to uncover immutable laws just like those in the natural sciences—is both false and dangerously misleading. 

In Optimism, Confirmed, Evolving Moral Understanding and Breaking Down Barriers anthropologist Frans de Waal describes how his optimistic convictions about both human and animal nature played a central role in driving him to develop his extensive research agenda that eventually confirmed many of them, while in A Lack of Empathy, his segment in the TOK Sampler Encountering Assumptions, he relates how a socially conservative and vaguely misogynistic bias long held back biological research into the nature of human and animal empathy.

In Perfect Pitch and Tone Languages and From Song to Speech?, psychologist Diana Deutsch reveals how her personal love of music drove her towards investigating a possible link between perfect pitch and tone languages followed by the development of a broader thesis relating the origin of language to tone languages, while in Losing Control she relates how many psychologists refrain from investigating, or even sometimes recognizing, auditory illusions because it “makes them uncomfortable”.  

Additional resources that students might find helpful for this title include the TOK Samplers Battling Biases, Encountering Assumptions, Extending Experience and Investigating Values

Contact us for information about how you can get access to these award-winning resources!

TOK Tuesdays

Investigating PT4 – All Lies?

If your school does not have an institutional subscription to Ideas Roadshow’s IBDP Portal you can now sign up for an individual teacher or student subscription. Annual individual subscriptions cost only $99 and provide unlimited access to all resources that are part Ideas Roadshow’s IBDP Portal.

This is the fourth of six special TOK posts to directly assist students and teachers in appreciating vital nuances associated with each of the May 2021 Prescribed Titles.  For each title, I will identify some initial key concepts and highlight some specific approaches to address them along with specific Ideas Roadshow’s IBDP Portal resources that can concretely assist in the development of a strong TOK essay for that particular title.

This piece discusses PT4: “Statistics conceal as much as they reveal.”  Discuss this claim with reference to two areas of knowledge. 

Key Concepts:  

The claim in this title is a pretty strong one, and unlike some of those in other titles, represents a summary judgement that in my view is a lot harder to justify. But regardless of whether your knee-jerk impulse is to agree or disagree with it, clearly a key to successfully grappling with its implications involves coming to terms with the subjective aspects of the acts of “concealment” and “revelation” that lie at the heart of the claim. Statistics in themselves, of course, are merely objective mathematical expressions, but the very act of interpreting and presenting these expressions to others—expressed here by the words “conceal” and “reveal”— clearly has the potential to veer decidedly towards the subjective side of things in a way that could well involve an array of both inadvertent and deliberate errors.   

The idea that fundamentally specious conclusions could be “dressed up” and somehow rendered more authoritative using deliberately skewed statistical arguments is hardly a new thought, and lies at the heart of Mark Twain’s oft-quoted remark that he attributed to Benjamin Disraeli:

There are three kinds of lies: lies, damned lies, and statistics. 

So the first thing to recognize is simply that any statistical argument necessarily involves an interpretation of the mathematics, which will often bring in an array of subjective factors and judgements that we need to make explicit and question, ranging from which conclusions are valid to larger structural issues such as how the statistical study was initially designed.  

That seems clear enough. But a quick glance at the title reveals that that is not, in fact, what it says. The claim is not that “interpreting statistical arguments invariably involve a certain degree of subjectivity” or even “there are times when statistics can be used to support a number of distinct, and even contradictory, conclusions”, but rather “statistics conceal as much as they reveal”.   

To be able to justify such a claim, you not only have to explicitly tackle the thorny issues of what it means to “conceal” and “reveal” concepts related to statistics (which you have to do anyway if you decide to take on this title, and among other things, will likely involve an explicit mention of the concept of beginning an investigation without any initial convictions as to the outcome), but—even more problematically—you are forced to demonstrate that in all instances of statistics, and presumably for any conclusion that is based upon them, there is an equal amount of concealed or hidden information to somehow “counterbalance” what is alleged to be demonstrated by the statistics. 

Once again, that seems a pretty hard position to maintain, and certainly not one I subscribe to. But that’s not the point of a TOK title, of course. I can’t just write: I disagree. I have to demonstrate exactly why I disagree in terms of what, specifically, I find objectionable about the claim. 

In this case, there appear to be two separate issues to tackle no matter what your final position is:

  1. Discuss what exactly could be meant by the words “conceal” and “reveal” in terms of related concepts we’ve discussed above (interpretation, subjectivity, objectivity).
  1. Evaluate to what extent you agree, or disagree, with the claim that the amount of “concealment” and “revelation” is always equivalent in statistical arguments, which I would argue is tantamount to declaring that statistical arguments can never give rise to objectively true statements. 

In my view the best way to go about making your case is to invoke specific examples of statistical reasoning, highlighting associated interpretative (subjective) aspects together with more objective ones. In what follows, I’ll present several helpful resources from Ideas Roadshow’s IBDP Portal that involve explicit mention of statistical arguments and can be used to build an excellent essay.

Below we highlight a number of specific TOK resource examples from Ideas Roadshow’s IBDP Portal to build a world-class TOK Essay. All TOK Clips come with a detailed print component and TOK Essay Practice Videos.

Ideas Roadshow’s IBDP Portal offers a strong pedagogical framework where TOK is the backbone of interdisciplinarity throughout all resources.

In Divining the Date, University of Michigan classicist Richard Janko reveals how he used statistical arguments to date an ancient manuscript by looking at the frequency of certain linguistic expressions, giving additional support to the notion that objectively verifiable conclusions can be deduced from careful, independent-minded statistical studies. 

In Circular Reasoning, University of Oxford physicist Roger Penrose gives an explicit example of how a statistical argument that purports to give an account of “a random sky” wrongly incorporates pre-existing informations, although it’s worth emphasizing that he believes this to be a misinterpretation rather than an active attempt to promote an alternative scientific agenda.

In Defining What You’re Looking For and Subjective Distortions, award-winning violinmaker and acoustician Joseph Curtin relates his pioneering “double-blind” experiments to determine whether or not expert musicians can identify the sound of a Stradivari violin, presenting a compelling argument for how a rigorous statistical analysis could filter out many subjective biases commonly held throughout the world of professional musicians.

 In fMRI and Assessing Consciousness, neuroscientists Kalanit Grill-Spector and Martin Monti demonstrate how contemporary brain-scanning experiments that involve explicit statistical algorithms can give rise to an array of well-grounded insights. 

In Autism and Vaccines, UCL psychologist Uta Frith describes the various statistical arguments that went into establishing the conclusion that the development of autism was not causally connected to being vaccinated with the childhood vaccine for measles, mumps and rubella. I suggest that students investigate to what extent potentially “concealed” conclusions could be reduced by increasing the number of such studies and how, in general, the volume of studies impacts the statistics themselves. 

In Scientific Credibility, business professor and environmentalist Andy Hoffman describes how, notwithstanding significant amounts of scepticism from those who are convinced that climate scientists are “concealing contradictory data”, he believes that at the end of the day most people will recognize the objective validity of their many statistical models.

TOK Tuesdays

Investigating PT3 – Systemic Constraints?

If your school does not have an institutional subscription to Ideas Roadshow’s IBDP Portal you can now sign up for an individual teacher or student subscription. Annual individual subscriptions cost only $99 and provide unlimited access to all resources that are part Ideas Roadshow’s IBDP Portal.

This is the third of six special TOK posts to directly assist students and teachers in appreciating vital nuances associated with each of the May 2021 Prescribed Titles.  For each prescribed title I will identify some initial key concepts and highlight some specific approaches to address them along with specific Ideas Roadshow’s IBDP Portal resources that can concretely assist in the development of a strong TOK essay for that particular title.  

This piece discusses PT3: “Labels are a necessity in the organization of knowledge, but they also constrain our understanding.”  Discuss this statement with reference to two areas of knowledge. 

Key Concepts:  

My approach to this title would be somewhat different from the first two discussed in earlier posts. Rather than embarking on a detailed search for a meaningful definition associated with a given concept highlighted in the title, in this case I feel fairly certain that I get the overall gist of what the issue is, and the associated subtlety to be explored is not so much a matter of definition per se, but more of interpretation and personal belief.   

In other words, I don’t believe that it would be terribly fruitful for me to spend my time investigating, What do I mean by a label here? or Under what circumstances can we be said to have our understanding constrained? The claim under consideration here seems to be that if we want to coherently structure our knowledge about the world around us it is necessary to group what we know into specific categories or areas; and that by carrying out this necessary grouping or labelling we will also, unfortunately, inevitably miss the development of some further insight that would have increased our knowledge.  

Personally, I find this the most interesting title of the six because I’m not actually sure what I believe. It might well be true; moreover, it might actually be quite a deep insight. For years educational theorists have trumpeted the importance of “interdisciplinarity”—that we need to move beyond the so-called “fixed silos” of our knowledge framework and instead “make connections across them”.   But the statement in this title is not, it is worth emphasizing, asking us to weigh in on  whether or not we believe in the merits of an interdisciplinary approach to knowledge creation, but rather whether the need for such interdisciplinarity will necessarily always be with us as a direct consequence of the inevitable act of structuring what we know.  

Further Analysis:

So first a bit of formal structure. 

For me to agree with the statement, I need to believe that:

  1. In order to organize knowledge one needs to put labels on things
  2. An inevitable consequence of labelling our knowledge is to constrain one’s understanding

Now, while I freely admit that it’s logically possible to believe that knowledge (or anything else, for that matter) can be “organized” without developing a schema of specific categories (i.e. “labels”) of some sort or another, personally I simply can’t imagine such a thing—indeed, for me, having some sort of categorization structure is precisely what I mean by being “organized”.  

Which means that the degree to which I will agree or disagree with the statement in the claim is directly related to #2 above. More specifically, can I imagine a situation where categorizing my knowledge doesn’t constrain my understanding (in which case I have a counterexample to the claim at hand)?   Maybe if I use sufficiently flexible labels, my understanding would be constrained after all, so the question is more about how I label my knowledge than whether or not I do.  Or perhaps those constraints only arise in some instances, like for particular AOKs in particular circumstances. 

After all, who’s to say that “constraining our understanding” is an established universally-agreed-upon concept anyway?  Perhaps one person’s “constraint” is someone else’s “insight”?

Whatever your final position, you’re going to need some specific examples to help illustrate your views.  They might also be highly useful to help you converge on what you actually believe in the first place. In what follows, I’ll offer some concrete examples that can naturally be interpreted in various different ways. 

Below we highlight a number of specific TOK resource examples from Ideas Roadshow’s IBDP Portal to build a world-class TOK Essay. Each TOK Clip comes with a detailed print component and TOK Essay Practice videos.

Ideas Roadshow’s IBDP Portal offers a strong pedagogical framework where TOK is the backbone of interdisciplinarity throughout all resources.

In Beyond the Textbooks, Princeton University physicist Paul Steinhardt relates how, by deliberately ignoring standard textbook views of how atoms of materials could be possibly arranged, he extended our understanding of a new state of matter known as “quasicrystals”  This example could be used to demonstrate the inherently constraining aspects of specific knowledge categories in the physical sciences in the form of “rigid laws”.  Alternatively, it could be used to illustrate the claim that constraints in understanding are much more a function of the training and personal orientation of a researcher than in a label per se. 

In Rethinking the Fifth, Duke University philosopher and law professor Nita Farahany reexamines the Fifth Amendment to the American Constitution in light of our enhanced understanding from modern neuroscience. This example could be used as evidence that any present categorization structure inevitably constrains our understanding and thus needs to be continually reassessed, or as a demonstration of how, by ascribing multiple “labels” to the same knowledge, we can potentially avoid constraints that might otherwise occur. 

In Modelling Politics, Tufts University philosopher Brian Epstein describes how a successful political model must fundamentally incorporate many things that go beyond most standard characterizations of the political realm. As per other examples in this section, this clip simultaneously demonstrates the constraints inherent in a given knowledge categorization framework as well as our potential ability to transcend them.

In Frank Drake’s Agenda, astronomer and former SETI director Jill Tarter illustrates how, by grouping what we know and don’t know into a transparent framework, Frank Drake set the stage for us to better address the likelihood of extraterrestrial intelligence. This example concretely highlights the benefits—and potential liabilities—inherent in a given organizational framework of knowledge.

In Rethinking History and Towards Better Explanations, Princeton University historian David Cannadine details how he believes that deep historical understanding can be extracted by moving beyond the standard categorization scheme of religion, nation, class, gender, race and civilization. This example simultaneously illustrates the power of “labelling constraints to our understanding” and our ability to transcend them. 

A wealth of additional TOK videos directly relevant to this topic can be found in the TOK Samplers Developing Understanding and Personal Perspectives, as well as the TOK Essay Practice Videos which can all be accessed on Ideas Roadshow’s IBDP Portal.

TOK Tuesdays

Investigating PT1 – An Element of Trust

If your school does not have an institutional subscription to Ideas Roadshow’s IBDP Portal you can now sign up for an individual teacher or student subscription. Annual individual subscriptions cost only $99 and provide unlimited access to all resources that are part Ideas Roadshow’s IBDP Portal.

This is the first of six special TOK blog posts to directly assist students and teachers in appreciating vital nuances associated with each of the May 2021 Theory of Knowledge Prescribed Titles.  For each title, I will identify some initial key concepts and highlight some concrete approaches to address them before pointing our subscribers to specific TOK resources that are part of Ideas Roadshow’s IBDP Portal that can concretely assist in the development of a strong TOK essay for that particular title.  

We begin with PT1: “Accepting knowledge claims always involves an element of trust.”  Discuss this claim with reference to two areas of knowledge.

Key Concepts:  Upon first reading this title, my eye immediately falls upon three key words: “always”, “trust” and “accepting”.  It might seem strange to present them in this order, since “accepting” is the first word I encounter, but this is deliberate, as you’ll shortly see. 

When someone tells me that something always happens in conjunction with something else, I’m immediately suspicious.  Always?  On every possible occasion?  How do we know that that’s necessarily the case?  That would seem to imply a necessary, structural link between the two things in question, but how certain am I that such a link necessarily exists?

Then there’s the expression “an element of trust”, which is one of those everyday figures of speech that we’re all very familiar with, but all too often such routine phrases actually hide a substantial amount of ambiguity lurking behind them: Who is trusting whom, exactly?  Do all people mean the same thing when they talk about trust?  And how big, precisely, is “an element of trust” anyway, and to what extent does it naturally vary from person to person?  

At this point, directly after musing over “an element of trust”, I’m led back to the notion of “accepting”.   After all, what am I talking about here?  What is this thing that allegedly, “always involves an element of trust”?   Well, accepting knowledge claims, of course.   But then, I think to myself, different people naturally have different criteria for acceptance than others.  How might that be addressed?

Some Concrete Approaches:

So now I’m ready to sketch out a few ways of how I might concretely tackle this title.  Can I imagine situations where the acceptance of knowledge claims don’t involve “an element of trust”, or at least strikingly different degrees of trust?

To what extent is trusting the opinions of authority figures the same sort of thing as trusting my sense perception or powers of reason?  Are there some types of knowledge claims that I somehow feel more compelled to accept than others?  In what ways does our knowledge of a subject impact our ability to accept subsequent knowledge claims?   If I’m a molecular biologist, say, how would that influence my acceptance of a newspaper reporting a proposed cure for the current pandemic?

A reasonable way forward would be to explicitly gear such examinations towards the particular two areas of knowledge that I want to invoke. Do “acceptance of knowledge claims” differ between the mathematical sciences and the human sciences?  Under what circumstances can the role of “scientific authorities” be compared to “religious authorities”?  To what extent do intrinsically subjective factors make “knowledge claims” in the arts similar to, and different from, those in history?

Lastly, it’s worth explicitly examining the specific impact that different ways of knowing have on the claim, a notion that was already alluded to when we mentioned sense perception and reason earlier: how can language or faith influence our willingness to accept or reject a given claim?  Under what circumstances can we trust our memory or our intuition?

Below we highlight a number of specific TOK resource examples from Ideas Roadshow’s IBDP Portal to build a world-class TOK Essay.

Ideas Roadshow’s IBDP Portal offers a strong pedagogical framework where TOK is the backbone of interdisciplinarity throughout all resources.

In Proof by Picture, philosopher of science Jim Brown investigates how we come to accept mathematical claims, while in Cultural Mindsets, psychologist Carol Dweck reveals the key role that cultural factors play in interpreting the applicability of certain knowledge claims. In Evolutionary Evidence, neuroscientist Matthew Walker describes how knowledge claims in the natural sciences naturally depend on our faith in the validity of underlying theoretical frameworks, while in Know Thyself, rabbi David Goldberg highlights instances of when subjective knowledge claims about our own identity are not accepted by others. 

In Testing Reality and Measuring Brain Activity, physicist Artur Ekert and cognitive scientist Ellen Bialystok emphasize the role that experiment plays in the acceptance of knowledge claims in the natural sciences.  In Political Games? political theorist John Dunn illustrates how all too often knowledge claims in political science are more of a reflection of internal sociological factors than objective knowledge of the political world, and in History’s Pendulum, historian Maria Mavroudi relates how trusted “traditional narratives” impact our willingness to believe associated historical knowledge claims.

Further insights related to the process of the acceptance of knowledge claims are covered in detail in the comprehensive TOK Essay Practice Video for May 2020 PT 3 (Does it matter that your personal circumstances influence how seriously your knowledge is taken?), while the TOK Samplers Navigating the World and Assessing Spin explicitly highlight how the media and popular opinion influence our inclination to accept knowledge claims across a wide range of different AOKs.