Syndromes and permutations

By Jennifer Skillen, Gordon Rugg and Sue Gerrard

Some diagnoses are clear and simple, and give you a crisp either/or categorisation; either the case in question has a positive diagnosis, or it doesn’t. Diagnosis involves identification of the cause of a problem; this may occur in medicine, or in mechanical fault finding, or in other fields. This article focuses on medicine, but the concepts involved are relevant to diagnosis in other fields.

The diagram below shows crisp either/or diagnosis visually; cases either go in box A or box B, with no other options.

Not all diagnoses are this simple. Medical syndromes are an example. A syndrome in the medical sense involves a pattern of features that tend to co-occur, but where the cause is unknown. They typically involve multiple signs and symptoms, each of which may or may not be present in a particular case. (Signs are features that can be observed by someone other than the patient; symptoms can only be observed by the patient.) Making sense of syndromes, and of how to diagnose syndromes, is difficult, and often encounters problems with misunderstandings and miscommunications.

This article discusses ways of defining syndromes and related issues. Its main focus is on medical diagnosis, but the same principles apply to problems in other fields that have the same underlying deep structure.

Artificial Intelligence and reality

By Gordon Rugg

There’s a lot of talk about Artificial Intelligence (AI) at the moment, usually framed in either/or terms. For anyone who worked with AI in the 1980s, this is depressingly familiar.

The brief version is that yes, AI will bring massive changes in some areas but not in the ways that most people are claiming, and no, it won’t bring massive changes in others that most people are worried about, and by the way, there are a lot of really useful things that it could be doing, but that have been marginalised or ignored or unknown for over forty years.

So, what’s the reality about AI?

User-centred grammar

By Gordon Rugg

Within linguistics, the scientific study of language, there is a long-established and useful distinction between two approaches to grammar, namely prescriptive grammar and descriptive grammar. This article describes a third approach, namely user-centred grammar. Before describing this third approach, I’ll briefly summarise the other two.

Background

Prescriptive grammar typically takes the view that there is a “correct” form of grammar for a dialect or language that should be followed by everyone, including people for whom that dialect or language is their native tongue. An example from Standard English is the claim that one should say “It is I” as opposed to “It is me”. Similarly, prescriptive grammar often makes normative claims about correctness based on claims that a particular phrasing is in some sense logically correct. An example in English is how to treat two negatives (e.g. “I haven’t got nothing”). Prescriptive grammar typically claims that these should cancel each other out because that is “logical” by analogy with formal logic.

Descriptive grammar describes the grammar used by native speakers of a dialect or language, without any normative claims. For the first example above, the descriptive approach would say that some native speakers of Standard English say “It is I” but that most native speakers of English say “It is me”. For the second example above, descriptive grammar typically states that in various dialects of English, the two negatives are treated as reinforcing each other.

Historically, prescriptive grammar has tended to invoke semi-arbitrary norms based on the grammar of other languages that have high status. In the case of Standard English, for example, prescriptive grammar frequently invoked norms from Latin (“we should use this phrasing in English because that’s what Latin would do”).

The use of descriptive grammar in linguistics has numerous advantages in terms of internal consistency, of avoiding imposition of arbitrary and semi-arbitrary norms on native speakers of a language, and of avoiding the social stigmatisation of dialects and languages other than the most prestigious ones. However, there are situations where phrasings can make a significant difference in how well a person can communicate their intended message to others. This causes problems for anyone attempting to teach ways of avoiding unintended consequences from particular phrasings, because this can look like an attempt to impose subjective norms.

The approach described in this article, namely user-centred grammar, provides a possible way of resolving this apparent paradox.

It’s logic, Jim, but not as we know it: Associative networks and parallel processing

By Gordon Rugg

A recurrent theme in our blog articles is the distinction between explicit knowledge, semi-tacit knowledge and tacit knowledge. Another recurrent theme is human error, in various forms. In this article, we’ll look at how these two themes interact with each other, and at the implications for assessing whether or not someone is actually making an error. We’ll also re-examine traditional logic, and judgement and decision-making, and see how they make a different kind of sense in light of types of knowledge and mental processing. We’ll start with the different types of knowledge.

Explicit knowledge is fairly straightforward; it involves topics such as what today’s date is, or what the capital of France is, or what Batman’s sidekick is called. Semi-tacit knowledge is knowledge that you can access, but that doesn’t always come to mind when needed, for various reasons; for instance, when a name is on the tip of your tongue, and you can’t quite recall it, and then suddenly it pops into your head days later when you’re thinking about something else. Tacit knowledge in the strict sense is knowledge that you have in your head, but that you can’t access regardless of how hard you try; for instance, knowledge about most of the grammatical rules of your own language, where you can clearly use those rules at native-speaker proficiency level, but you can’t explicitly say what those rules are. Within each of these three types, there are several sub-types, which we’ve discussed elsewhere.

So why is it that we don’t know what’s going on in our own heads, and does it relate to the problems that human beings have when they try to make logical, rational decisions? This takes us into the mechanisms that the brain uses to tackle different types of task, and into the implications for how people do or should behave, and the implications for assessing human rationality.

Tacit knowledge: Can’t and won’t

By Gordon Rugg and Sue Gerrard

This is the third post in a short series on semi-tacit and tacit knowledge. The first article gave an overview of the topic, structured round a framework of what people do, don’t, can’t or won’t tell you. The second focused on the various types of do (explicit) and don’t (semi-tacit) knowledge. Here, we look at can’t (strictly tacit) and won’t knowledge.

The issues involved are summed up in the diagram below.

Explicit and semi-tacit knowledge

By Gordon Rugg and Sue Gerrard

This is the second in a series of posts about explicit, semi-tacit and tacit knowledge.

It’s structured around a four way model of whether people do, don’t, can’t or won’t state the knowledge. If they do state it, it is explicit knowledge, and can be accessed via any method. If people don’t, can’t or won’t state the knowledge, then it is some form of semi-tacit or strictly tacit knowledge, which can only be accessed via a limited set of methods such as observation, laddering or think-aloud.

This is summed up in the image below.

The previous article in this series gave an overview. In the present article, we focus on do and don’t knowledge, i.e. explicit and semi-tacit knowledge.

Tacit and semi tacit knowledge: Overview

By Gordon Rugg and Sue Gerrard

Tacit knowledge is knowledge which, for whatever reason, is not explicitly stated. The concept of tacit knowledge is widely used, and has been applied to several very different types of knowledge, leading to potential confusion.

In this article, we describe various forms of knowledge that may be described as tacit in the broadest sense; we then discuss the underlying mechanisms involved, and the implications for handling knowledge. The approach we use derives from Gordon’s work with Neil Maiden on software requirements (Maiden & Rugg, 1996; reference at the end of this article).

In brief, the core issue can be summed up as whether people do, don’t, can’t or won’t state the knowledge. If they do state it, it is explicit knowledge, and can be accessed via any method. If people don’t, can’t or won’t state the knowledge, then it is some form of semi-tacit or strictly tacit knowledge, which can only be accessed via a limited set of methods such as observation, laddering or think-aloud. Because of the neurophysiological issues involved, interviews, questionnaires and focus groups are usually unable to access semi-tacit and tacit knowledge.

The image below shows the key issues in a nutshell; the rest of this article unpacks the issues and their implications. There are links at the end of the article to other articles on the methods mentioned in the table. The image below is copyleft; you’re welcome to use it for any non-commercial purpose, including lectures, as long as you retain the coplyleft statement as part of the image.

The gulf of instantiation

By Gordon Rugg

Two of the most common complaints about managers and about teachers/lecturers are:

• They’re too vague
• They’re too specific

Although these complaints are opposites, the underlying problem for both of them is the same. It involves the gulf of instantiation, which is the topic of this article.

The persistence of old inventions

By Gordon Rugg

Old inventions seldom die; usually, they fade into the background, and then hang around there for a surprisingly long time.

In this article, I’ll look at how this happens with physical inventions; how it happens with innovative ideas; at what is going on underneath the regularities; and at what the implications are. A lot of those implications are important, and counter-intuitive.

I’ll start with pointy sticks.

Image credits are at the end of this article.

Premature closure and authoritarian worldviews

By Gordon Rugg

In a previous article, I looked at the belief structures of the archetypal “crazy uncle” worldview. It’s a worldview with a strong tendency towards whichever option requires the minimum short-term cognitive load; for example, binary yes/no categorisations rather than greyscales or multiple categories.

One theme I didn’t explore in that article, for reasons of space, was premature closure. This article picks up that theme.

Premature closure is closely related to pre-emptive categorisation, which I’ll also discuss in this article. Both these concepts have significant implications, and both involve minimising short-term cognitive load, usually leading to problems further down the road. Both tend to be strongly associated with the authoritarian worldview, for reasons that I’ll unpack later.

So, what is premature closure? In brief, it’s when you make a decision too early, closing down prematurely the process of search and evaluation and decision-making. This takes various forms; knowing these forms improves your chances of stopping at the right point. For clarity, I’ll use examples within the context of common “crazy uncle” arguments.