Telling Lies #9: Dissimulation


Pope Innocent by Francis Bacon

Francis Bacon the 16th century English philosopher wrote one of the most famous essays on lying; Of Simumlation and Dissimulation.  Francis Bacon the Irish born 20th Century artist painted a portrait of Innocence:  Pope Innocent X.

This post is about the 16th Century Bacon, and that unused and poorly understood word dissimulation.

In his essay Bacon argues that people use three broad strategies for telling lies:

Closeness or reservation:  This is the Mafia trick of omerta, complete silence,  “I ain’t sayin’ nuthin'”.  If you don’t say anything you can never be caught in a lie.  But it does not make you the best of conversationalists.

Dissimulation is where you say things that allow people to misinterpret your position, and when they misinterpret to your advantage do not correct them.

Simulation is when you say things that are patently untrue.  Flat out lying.

Many years ago I was serving on a University finance committee distributing funds to sports clubs.  At the same time I was chairman of the Rugby club.  At the end of year awards the Rugby Club and the Canoe Club were in competition for most improved club of the year.  The Committee had the final decision by secret ballot.

The Canoe club won by a single vote.

As with all these situations you have a pretty good idea of the support in the room.  There were only very few floating votes.  After the vote was delivered one of the committee members, let’s call him “the dissimlator”, approached me to comiserate with me.  He said he was sorry the rugby club did not win and said as he parted “you know how I voted”, and I thanked him for his support.

Then later in the evening the Chairwoman of the Ladies Hockey club came over to me and told me she had voted for the Rugby club.  I counted up the votes and realised something was wrong.

So I went over to “the dissumlator” and I said “Hi Kxvxx, you know when you said that I know how you voted?  I have to admit I don’t.  Who did you vote for?”

He was caught and impaled like a fish on a gaff.  He opened and closed his mouth, exactly like a fish on a gaff, and shrugged and walked away.  Guilty!  Caught and very embarrassed.

But he never told an actual flat out lie.  It was a classic dissimulation.  He told me that I knew what he did, and I thought I did and he was happy to allow me to believe an untruth if it gave him any political advantage.  He was trying to burden me with an obligation and he was exactly the type of character who would call in that favour in later life.

As you can tell from this post all that is long gone and forgotten, water under the bridge.  If I met Kxvxx today I would trust him 100%.  NOT.




Telling Lies #8: Defamation


Mmmm, gluten free hair!

Defamation is a communication that causes harm.  It may cause harm to a person, a business, a political party, a religion, a race, a group of people, a brand, a product or a category of goods.  Defamation is deliberate and is usually an attempt to profit in some way by the damage it causes to the defamed party.

Smoking causes cancer.  This is proven by science.  Telling people that smoking causes cancer is not defamation.  It is the truth.  It causes harm to the tobacco category of goods, but it is not a lie.  So this is not defamation.

To qualify as defamation it must actually be a lie.

Telling people that vaccinations cause autism is defamation.  Dr. Andrew Wakefield falsified medical studies to cause harm to existing vaccinations.  He did this because he was allegedly working on an alternative vaccination.  He caused widespread confusion around the safety of MMR vaccines, leading to parents rejecting vaccines.  As a result we are seeing explosions in infection rates from measles all across the western world.

Wakefield’s science has been disproved.  His papers have been rejected.  He was struck off the UK Medical register, but he continues to be cited as a reason to avoid MMR vaccination.  Indeed the panic he started has also impacted on takeup of HPV vaccination rates.

Defamation can be very subtle.  It works extremely well in mock denial.  If I make a statement along the lines of  “the prime minister has an STI” I am open to a charge of slander.  My statement will be denied as rubbish and will largely be ignored.

But what if I make a statement like this “I categorically deny any accusation that the prime minister contracted an STI during a visit to a refugee centre in County Louth.”

I denied a rumour.  What rumour?  Does the prime minister have an STI?  Where did he catch it?  What was he doing in that refugee centre?  If he didn’t catch the STI in the Louth refugee centre which one did he catch it in?  By denying the rumor I make the defamation all the more believable and all the more damaging.  Doing it this way unleashes the press horde into the private life of the prime minister.

You can do the same with brands, categories and products.  “Unlike our major competitors we make our shampoo gluten free.”  Is gluten bad for your hair?  If the man in the white coat says it then it must be!

Now I don’t want to defame the fad for gluten free shampoo, so if your partner suffers from Coeliac disease and if they like to clean your head by regularly licking your hair, go for it.


Telling Lies #7: Confirmation Bias

Female scientist doing Oil and gas research

Are you a Blue Pill or Red Pill kind of person?

Below I envisage the structure required in a research agency to eliminate confirmation bias 100%

One of the great enemies of market research the confirmation bias is also the enemy of good science.  Good science needs to make use of  carefully designed samples, control groups and double blind testing.

Samples must avoid confirmation bias.  If you send out someone to recruit a “random sample” off a busy shopping street with no rules they will come back with an awful lot of people who are of a similar age, ethnicity and social background as themselves.  Without conducting the first experiment they have affected the results.

A control group is a set of people who are tested without having experienced the subject of the test.  In market research we might expose a group to every product except the one we are testing.  In science we might use a placebo, or no treatment at all as a control.

The purpose of the control is to uncover test treatment errors to research.  These are situations where the setting of the test itself (such as a lab, doctors office, research facility etc) impacts on subject behaviour.  The test subjects don’t know they are changing behaviour because they are being tested, but they do.  The testers themselves may also be amending their behaviour, and consequent test results, unintentionally, but significantly.

The purpose of the double blind is to ensure that the tested person does not know if they are in the test group or the control group, and, more importantly, neither does the tester.

Lets say you have a new type of alcohol to test.  You give it to men and women.  They report the impact and complete some tests.

A classic confirmation bias is where a tester belives in advance (due to personal experience, or test assumptions, or any other reason) that the females in the group will react to the alcohol more strongly.  Without intending to falsify results they allow their own confirmation bias to impact on the results.  They “see” more effects in the females and the “edit out” effects in the men.  Their initial assumptions prove prophetic, they find exactly what they expect to find.

Control groups and double blind testing as well as “fair” samples can be expensive to run in market research.  In many cases the market researcher, or scientist, comes under subtle forms of pressure to relax the rules.

When it comes time to write up the findings the person paying the bill can call the tune.  Researchers and scientists are remarkably able to find conclusions that are exactly what their paymaster wants to see.  Commercial company managers like to work with market research companies that “understand our product and market”, and find the results that they hoped the research would find.

None of the lying is overt, but it is systemic.  Each bias builds upon the last one until the research results may land very far from reality.  Bad science!

Even highly rated scientific papers in peer review journals fail the test for confirmation bias.  Follow the money I say.  If it is a university paper they should be declaring their sources of grant funding.  Look up the funding agency, find out what their goals are and read up on the history of the research they funded in the past.  Always follow the money.

The Business Model:

I have a vision for unbiased research.  On the one hand are funding clients, companies, foundations etc who submit both the question, and the funding.  On the other hand are the front line scientists or market researchers.  In the middle are three layers of administration, with chinese walls between them.

Layer 1 is the business engine and has nothing to do with the research.  Layer 1 accepts the research applications.  Their job is to anonymise the research question and distance it from the source of the funding.

Layer 1 makes a submission to Layer 2.  The client on the job is Layer 1.  The research question is carefully set out to meet the real client needs, but never identifes the client.  Layer 2 receives a budget and a research task.  They make a proposal on how to carry out this task with the available budget.  They specify the sample, the test type, the control etc.  They submit a detailed proposal to Layer 1.  They are the research “pitch team”.

Layer 1 submits the proposal to the client, who approves or rejects the research.  If the research is approved Layer 1 gives approval to Layer 2.

Layer 2 engages a team from Layer 3 to carry out the research.  They are the field research admin team.  They pull from a pool of qualified front line researchers or scientists to perform the work required.  Layer 3 assembles the results and prepares the analysis.  They return the results, finding, limitations, conclusions etc to Layer 2.

Layer 2 run a cross check to ensure all research objectives have been met.  All being well the final report is given back to Layer 1.  Now you have a piece of research with no confirmation bias.  You present the findings, unvarnished to the client.

Then, and only then, if they want the findings “brought to life” will you pull together a team from all layers to make a presentation to the client.

This is all very bureaucratic and very expensive.  It gives absolutely no comfort to clients that they will get the results they are looking for.   But they will get proper research.

The one proviso of this model is that your organisation needs to be large and have so many clients that making “educated guesses” about who your client on any job is would be a waste of time.


Telling Lies #6: Plausible Deniability


Plausible deniability is a tool used widely in commerce and in politics.  It generally involves the identification of areas of knowledge that could, if details are fully known, compromise a senior individual as being complicit in acts that are illegal, immoral or culturally unacceptable.

A CEO of a Western firm, with operations in countries where bribery is endemic, will build a management structure that distances them from knowledge of day to day details of acts of bribery and corruption.

The Chairman of the board of an auto manufacturer may never ask directly if accident rates in their cars are an endemic manufacturing problem.  To do so may result in a widespread recall and catastrophic fall in share prices.  Better to retain plausible deniability.

The premier of a nation will structure allocations to “security agents” (AKA Black ops or Spies) as “Black Box” payments.  There is no direct link between the money allocation and the acts carried out by the security teams.  The President can’t be held directly responsible for an assassination because she never directly ordered it.

It is a plot line in the movie “Independence Day” when the CIA keep knowledge of the existence of aliens from the President even after an alien presence makes itself known.

No good Barrister will ever ask a question in court without first knowing the answer, and in may cases, knowing the answer, will never ask the question in order to maintain plausible deniability.

As Sir Humphrey Appleby says in “Yes Minister” one should never ask a direct question because it might result in a direct answer.

He also pointed out that the Official Secrets act was not designed to protect secrets, it was designed to protect public servants.

The script of Yes Minister is a fertile garden of plausible deniability.

plausible deniability


Telling lies #5: Bluff

medicine bluff

A bluff as a geographical feature is a broad cliff or bank, overlooking a body of water (or a dried up water course) which was created by erosion.  A bluff is blunt, solid and strong.  It is perhaps this show of strength that gives us the lie.  A bluff person is somone of solid build, quiet strength, simple honesty.

A bluff as a lie is commonly used in gambling.  It involves presenting a strong position to deter an opponent from meeting your bet.

In business bluffing is a frequently used technique.  A seller will bluff a buyer by inferring that they have many buyers interested in the goods.  A buyer will bluff the seller by inferring that this is only one of many competing offers.

Every job interview in history has involved bluffing.  Interviewees bluff the employer as to the depth, success or seniority of their previous roles.  Interviewers bluff the candidate with regard to the attractiveness of the role, the seniority of the role, the budgets available, the autonomy possible and so on.  A certain element of bluffing is expected on both sides, but there are limits to acceptability before a bluff becomes an outright deception.  A candidate can get away with inflating their previous salary by 10 or 15% to negotiate a raise from their prior role.  But when they begin the job, and their taxation documentation comes across the employer will have a strong sense of the prior salary.  A candidate who inflated their salary by 50% could be accused of a lie instead of a bluff, because that could represent a significant difference in seniority sufficient to exclude them from the role.

A good bluffer, a really good bluffer, is never caught in the bluff.




Telling Lies #4: Confabulation


Heracles slays the Hydra one head at a time

Sometimes called “An Honest Lie” the confabulation is an unintended lie.  It is an inaccurate statement believed by the protagonist with no intent to deceive.  For this reason some people do not consider a confabulation as a lie.

It is neatly summed up by Mark Twain in the statement “It ain’t what you don’t know will kill you, it’s what you know for sure that just ain’t so”.

A confabulation is something I call a “script” and a script is a narrative that has been passed to you, usually from parents, older siblings, grandparents or teachers.  It is a script you accept because it comes from a source you respect.  But it is just plain wrong when it is tested against the cold hard facts.

Even after the confabulation has been demonstrated to be wrong there are many people who find it difficult to drop the script.  It forms a deep foundation of their weltanschauung.  So many other scripts hang off the proven confabulation that it has become a Hydra in their belief system.  Cutting off one or two heads has little or no impact.


Enough confabulation, let’s talk facts:  Howard Moss was born this day in 1922 if you can believe that.

The Lie; by Howard Moss

Some bloodied sea-bird’s hovering decay
assails us where we lie, and lie
to make that symbol go away,
to mock the true north of the eye.
But lie to me, lie next to me;
the world is an infirmity.

Too much of sun’s been said, too much
of sea, and of the lover’s touch,
whole volumes that old men debauch.
But we, at the sea’s edge curled,
hurl back their bloody world.
Lie to me, like next to me,

for there is nothing here to see
but the mirrors of ourselves, the day,
clear with the odors of the sea.
Lie to me. And lie to me.

Telling Lies #3: Truncated Scale


Which brand has the higher approval rating?  Brand X or Brand Y?

There is no difference is there?  Is there not?

When it comes to brand marketing a true believer will always find a difference.  It’s just a simple matter of manipulating the statistics.  Take the same data, and present it in a more compelling way.  Just truncate the axis and show the difference instead of the absolute scores.  Then you get this graph:

bap 1

Woah, Brand X has a way higher approval rating than Brand Y.  It must be 3 times higher!  Now that’s a good result.

Note to art department:  Just don’t bother with those pesky numbers down the left hand side.  Get rid of them entirely.  A picture paints a thousand words.