Suggestions
for making knowledge simpler and more powerful
Extending the reach of Occam's razor
Contact: michaelwoodslg@gmail.com 
General
principles 
Maths should not be hard: the case for making academic
knowledge more palatable (7000 word article published in the Higher Education Review in 2002.) 
I'll make it
simple (Short article in the Times
Higher Education, 2002.) 
Simplifying
academic knowledge to make
cognition more efficient: opportunities, benefits and barriers (5000 word article, 2016. Draws on and expands
some of this webpage and linked documents.) 
Ideas which are too
simple  dumbing down (Two pages on the
opposite problem.) 
News
from a couple of alternative futures (short blog post) 

Examples A fairly haphazard
collection of the simple and the complicated, and potential simplifications. 
Six
sigma and the Higgs Boson: a convoluted way of expressing unlikeliness
(Blog post on a strange, and
completely unnecessary, way of complicating a simple concept.) 
Statistics. A
major source of confusion and incomprehension in urgent need of reform. 
Qualitative research  often jargonridden but for no good reason. Peer regard for pot noodles is a blog post reviewing such an article. 
Sustainable Energy – without the hot air by David McKay. Analysis of UK energy options. Uses everyday units and Insists on numbers instead of oversimplified adjectives like "huge". 
Using Excel notation for
mathematical formulae and equations (has advantages over conventional notation). 
Feynman diagrams are simple pictures to visualize the very complex mathematical
expressions describing the behaviour of subatomic particles. They are
said to have "revolutionized
nearly every aspect of theoretical physics". (Unfortunately, I
haven't got the necessary background to understand even this pictorial
version of quantum mechanics.) 
Research methods for social sciences, management, education, etc. Much of the standard fare is misleading, or the obvious translated into jargon. 
Compound (or
exponential) growth and decline. Compound interest and population growth
are usually analyzed using calculus and natural logarithms  but the concepts
can be simplified and presented directly. 
The case for crunchy methods
in practical mathematics. Article published online in 2001 on the virtues
of crude, repetitive methods. 
There are More examples below. 
Implications
for education, growth of knowledge, etc, etc 
Cambridge
University closed to undergraduates. My prediction about the future of
traditional university courses (blog post). 
The
death of a university (Blog post) 
Journals,
repositories, peer review, nonpeer review, and the future of scholarly
communication. Article on
arXiv.org on making the system for publishing research more flexible and effective. 
The
cult of the truth. Truth is a slippery concept which shouldn't be taken
too seriously (blog post). 
Computer packages
as cognitive paradigms. Paper published in 1997 arguing that computer
packages may be a partial substitute for education. Smartphone apps and
simple spreadsheets like this
one and this
one may play a similar role. 
Other
links 

My
university web pages 1 and 2

Everything should be
made as simple as possible, but not simpler (widely attributed to Einstein)
It may be better to simplify a process rather than train people to cope
with complexity (E de Bono)
Many ideas are too complicated and could be simplified without
sacrificing their power and usefulness. The number MMXVII is now written as
2017 which is far more convenient from many points of view, and the metric
system means that children no longer have to learn about stones, pounds and
ounces, and pounds, shillings and pence, and so on. At the other end of the
scale, Newton, Einstein and Darwin came up with beautifully simple theories
which help us make sense of the world.
This principle deserves to be spread far wider. Many complicated ideas
could be replaced by simpler and better alternatives. Otherwise human progress
will slow down or cease as our minds become clogged with unnecessary
technicalities, and inevitable oversimplifications take control of our
thoughts and actions.
I know lots of things. I know how to
make my lunch, how to make my way to Emsworth, the
village where I live, and also a few more complicated things like how Newton's
laws of motion work and a little bit about how the economy works. Knowledge is important to all of us. Life as
we know it could not continue without it.
Some of this knowledge is easy. I
have no difficulty understanding how to make lunch, turn the TV on and so on.
But some of it is not so easy: it is difficult to understand, absorb and make use
of. I think I understand about Newton's laws, but a lot of more recent physics
(like quantum mechanics) leave me largely baffled. And although I can switch
the TV on, I have only the vaguest of ideas of how it works, and how it manages
to home in on the channel I am watching and ignore the myriad other TV
channels, mobile phone signals, and so on that pervade the space around us all.
I don't trust myself to distinguish between the many harmless blemishes on my
skin, and a dangerous melanoma. And so on.
This is a real problem. There is so
much to know, and a lot of it is hard to get to grips with.
Obviously, I'm not very bright,
rather lazy, and my knowledge is certainly very limited, but even the brightest
and best informed person in the world will still come up against their limits.
Even for the most intelligent, quantum mechanics is difficult and will take
time to master. And this must place constraints on what can be achieved by one
person. My guess is there are very few people, if any, who are experts in
quantum mechanics, and skilled film directors, and expert cooks. Life is just
too short to master all these fields. But it would still be nice to make as
much progress as possible in as many areas as possible.
There are a number of obvious
approaches to help cope with difficult knowledge  go on a course, consult an
expert, get some computer software to help, spend lots of time studying, become
cleverer, and so on. All undoubtedly potentially helpful.
However, the core idea I want to
explore here is that of redesigning difficult knowledge to make it simpler, or
more appropriate for the context. The aim is to make knowledge more user
friendly.
I suspect some readers' hackles will
be rising at this point  phrases like "dumbing
down" perhaps coming into mind to dismiss the idea out of hand. If you are
such a reader, please hold on a minute and consider two examples.
In Roman times, the lack of the
modern notation system for numbers meant that simple arithmetic was not simple.
It is far easier to do arithmetic with numerals like 1949 than with MCMIL, and
the difference is even more pronounced with fractional numbers. We are better
at arithmetic than the Romans simply because we have better concepts to cope
with numbers. Very similar comments apply to the adoption of the metric system
of measures in place of 16 ounces to a pound, 14 pounds to a stone, and so on.
Difficult knowledge has been made easier to the benefit of all.
These days word processors are easy
to use. When they were first invented, however, they were complicated beasts
requiring considerable effort, and training, to master. The education problem
has been solved by making the task easier, and along the way providing help
with spelling, grammar, formatting documents, and so on. Again, things have
been made easier, by changing, in this case, the technology.
Simplification doesn't just make
things easier. The simpler version is usually better, or more powerful, in lots
of ways. It's not just that the modern notation system for numbers makes arithmetic
easier: it's also possible to do things that would be more or less impossible
with Roman numerals. And to take a more technical example, the randomization,
or shuffle test, in
statistics is a computer simulation method, whose rationale is completely
obvious, which does the job of lots different statistical tests each with its
own complicated mathematical theory and recipe for using it. The user of the
shuffle test has far more statistical power at their disposal than the
conventional statistician with chi squared tables, t tables, F tables, etc.
The idea of making things simpler so
that we can manage them more easily is better described as "dumbing up". I hope to convince you that this has real
advantages from many points of view in many walks of life.
But, you may think, these are special
cases and, besides, helping people with spelling is a bad precedent because it
will encourage laziness. OK, the principle that simple is good does not always
apply (but I would say it does apply to spelling), but it is a really useful
possibility in many more scenarios that you may at first imagine  the links on
the right and below give some examples.
Lets imagine that some difficult
knowledge can be simplified by a factor of about a quarter. (I think in many
cases this fraction could be nearer 50% or 75%.) This might mean that people
spend 25% less time learning about some knowledge, or using it, or that the
simplification means that they can master 25% more than they would otherwise
have been able to, or that they make 25% fewer mistakes, or that 25% more
people are able to master it. Over the whole spectrum of difficult knowledge
this has the potential to make an enormous difference. Imagine that students over
the world could spend 25% less time on their studies! The rest of the time
could be spent taking their studies further, or doing something completely
different.
This is all based on the assumption
that such simplification is possible. The only way to make the case is to show
how it would work in particular examples  which I have done in the links in
the boxes above and below. However, in all these examples, the problem is the
same. To see that the simple version really is simpler, and yet will do the
same job as, the more complicated version, the reader needs to appreciate both
the power and complexity of the original version, which is not going to make
for a brief and simple exposition.
Simplifying complex ideas, as a
general epistemological and educational tactic, does not seem to be on
anybody's agenda, and this is probably for reasons similar to those outlined in
the previous paragraph. You need a certain level of expertise to understand the
complex version, and once you have this there is no motive to simplify, and
simplifying may seem almost disrespectful to the "proper" version.
Those without the expertise, who have the motive to simplify, obviously aren't
in a position to simplify something they don't understand, and are likely to assume
that a simplified version is a dumbed down,
relatively useless, version for the masses  and to be fair, this is sometimes
the case. Understandably, but unfortunately, there is as yet no established
tradition of trying to simplify unnecessarily complicated knowledge.
This idea raises
issues that spread a little wider than may be apparent at first sight. For
example:
·
If
difficult knowledge is made simpler, do we need school and university courses to
help us master it? (Rough answer: sometimes we do, often we don't.)
·
Is
the idea relevant to experts at the frontiers of their discipline? (Yes. The
simpler the perspective, the faster the progress. In the long term knowledge can't progress
without simplification. Simplification is an essential aspect of the growth of
knowledge. This has long been
recognised at the frontiers of science, but it also applies to more mundane
levels of expertise.)
·
Surely
the truth is given and can't be simplified? (Not so. Almost all understanding
is partial which should encourage us to consider which parts we need and what
we can ignore. Besides knowledge is not just about truth, and truth itself is a
very slippery concept  see this blog post.)
·
The
difficulty of difficult knowledge may sometimes mean that we don't notice it's
not answering the important questions, so the redesign may need to be more
radical than a simple simplification. The simplified version may provide a new,
very different, perspective, in effect a paradigm shift. (Statistical
significance and p values are good examples of such problematic concepts 
there are dozens of blogs and articles critical of these concepts on the web:
my suggested alternative is explained here. And the modern
notation system for numbers, and modern word processors are both more than a
simplification of their predecessors  they are far more powerful tools.)
·
Simplicity
is not a simple concept. Sometimes it's good, sometimes it's bad, and the
simple assumption that simple is always good would be a disaster. And there are
many different ways in which things can be simplified  e.g. by omitting unnecessary
complications, or redesigning concepts or terminology. (Agreed, which is why we
need to understand simplicity  in the simplest possible way.
Oversimplification is also a big problem  see Ideas
which are too simple  dumbing down.)
But
there are the obvious objections:
·
Isn't
this just giving in to the lazy and the not so bright? (Yes, it will help the
lazy and the not so bright. What's wrong with this?)
·
Isn't
simplifying things likely to lead to dumbing down 
oversimplified answers to complex problems? (If the answer are oversimplified, then yes, by
definition. But a sensible degree of simplification should leave us free to
ponder other things.)
·
Isn't
this just popular science? (No, not really. Pop science generally aims to
provide an overview but without going into the level of detail that would allow
you understand how to use it in a new situation, how it's justified and the
detail of how it works. It is this level of useful, flexible, detailed
understanding that I intend the slogan simple knowledge to refer to.)
Nobody seems to be researching this
issue, or even thinking about it. There are numerous research projects devising
ways of cramming more into students' brains; there seem to be none whose goal
is to reduce the amount that needs to be crammed in. This is very odd. Suppose
that in few years we encounter superintelligent aliens, or even
superintelligent computers we have built ourselves. These superintelligences
are likely to have ways of looking at things that we cannot make sense of, so
the race will be on to translate, or package, or redesign, their wisdom for
less advanced intelligences. But ... we are already at this point. The
conclusions of many scientists and computer packages are already at a point where
we need to consider very carefully how they can be made accessible to a wider
audience. The search for simple ideas, or the reduction of cognitive strain,
deserves serious research now. The links on the right and below are just some
tentative first steps on this endeavour.
The case for simple knowledge depends
on being able to create more appropriate alternatives. The examples in the
panels above and below illustrate a few, just a very few, of the possibilities.
These are mainly topics I happen to know something about because I have been
teaching them in a university. In fact, all the areas I taught in my university
job  statistics, research methods, decision analysis, and aspects of
operational research  are represented here  which suggests that the principle
that useful simplification is possible is a very general one. It is likely that
the opportunities for productive simplification are just as great in other
areas about which I know little.
Some of these examples might strike
you as being rather trivial, but this is really the point  improving trivia
means we will have more time for more important matters. But there are many
nontrivial examples. Statistics is the area I have thought about most: the
opportunities for simplification here are enormous, as are the problems caused
by the conventional version. And
statistics is a good illustration of the possibility that a decent
simplification may answer subtly different, and more appropriate, questions.
These examples are unlikely to fully
live up to the simple knowledge manifesto. They are largely untested. What
people find simple and appropriate for their needs is ultimately an empirical
question; most of what I am doing here is proposing some hypotheses about what
might work. They need testing, and I am sure they can be improved.
Bike power calculator (Excel spreadsheet) using intuitive concepts like an acceleration of 2 miles per hour per second (instead of metres per second per second). 
Why is SPSS so
unhelpful? SPSS is the main
statistical package for social scientists. But it is horribly and unnecessarily
complicated (blog post). 
Userfriendly statistical concepts for
process monitoring and a second article on the theme of quality control, published in the Journal of the Operational Research Society in 1998 and 1999. 
The Pros and Cons of Using Pros and Cons for MultiCriteria Evaluation
and Decision Making. Academic decision theory is complicated and rarely used: this article
tries to make it closer to common sense. 