Johannesburg - Good journalism comes down to three simple things: accuracy, objectivity, fairness.
The first two are easy. Accuracy? Get the facts right. Objectivity? Don’t take sides. Almost everyone understands these.
Fairness is a more difficult concept for most people to grasp. Example: Sit down to watch a soccer match where the ref makes a call against the team you are supporting; chances are your standard for fairness goes right out of the window.
Here’s my simple take on fairness in journalism: Don’t bring in information unrelated to the facts at hand.
In my journalism classes over the past decade, I’ve used South Africa’s former president as an example of this principle: “When reporting on Jacob Zuma’s purported involvement in corruption, it would be unfair to report that he once stood trial for rape.”
Why? Well, the charge of rape is completely unrelated to the matter of corruption. The only reason why one would want to mention that fact is to sway the mind of the reader that Jacob Zuma is fundamentally a bad person.
Now for you reading these words at this moment, assuming you had not been aware that Jacob Zuma had been charged with rape, you would immediately have begun to form certain associations in your mind. If I told you that he had faced “criminal” charges, that would further affect those associations. If I told you that his accuser was 30 and he was 63 at the time, more grist for the mill.
Let’s now assume that five years from when you first heard of the rape accusation, you and I are having a discussion in a social setting where the former president’s name comes up and you say, “Wasn’t he charged with rape?”
At that point, I reach into my pocket for my phone and quote from page 173 of the 174-page judgement in Jacob Zuma’s rape trial:
“… it is clear that the probabilities show that the complainant's evidence cannot be accepted. She is a strong person well in control of herself knowing what she wants. She is definitely not that meek, mild and submissive person she was made out to be.
“On the evidence as a whole, it is clear that the accused's version should be believed and accepted. The accused's evidence was also clear and convincing in spite of media efforts to discredit him. At least one cannot say that the accused's evidence is not reasonably possibly true.”
Now a rational response at this point would be for you to say, “Oh, so he was not guilty? That’s alright then.” But that’s not going to happen. If anything, you would be more likely than ever to believe Jacob Zuma is a rapist because you’ve carried that belief around with you for five years.
This does not make you a bad person; it just means that you, like most human beings, are susceptible to cognitive bias. This particular example is what psychologists call “The Backfire Effect”.
Here’s how this works: If I asked you what you would do if your beliefs are challenged by new facts, you would probably tell me that you would incorporate those facts into your thinking and change your beliefs.
In fact, the opposite is more likely to happen; when your deepest convictions are challenged by contradictory evidence, your beliefs get stronger.
Here’s a clear example: opponents of Barack Obama have long propagated the idea that he should never have been elected president as he was not born in the United States. When the Obama administration produced the then president’s unabridged birth certificate in April 2011, his opponents doubled down, casting doubt upon its authenticity and spreading new conspiracy theories.
Now consider that judges are as human and are as susceptible to cognitive bias as the rest of us. I expect many judges are aware of this and will try their best to shelve their own prejudices.
But here’s the question I’m opening up for debate: is it possible for us to mathematically calculate the impact of such prejudices that all of us carry?
It turns out that there is exactly such a thing. It’s called “Bayes Theorem” or “Bayes Law”, named after Reverend Thomas Bayes (1701–1761) and describes the probability of an event, based on prior knowledge of conditions that might be related to the event.
You might not know about the Bayes Rule but this one equation powers most of modern business and life today.
Let’s say you want to buy life insurance. If you are in your twenties and are healthy, you will probably pay a very small premium. As you get older and acquire more risk factors, those premiums rise. Are you a smoker? Got HIV? Drink more than a glass of wine a day? Pick up many speeding fines? Got a history of heart disease in your family? Got a history of diabetes in your family? Every one of these factors gets multiplied out by the Bayes rule to calculate the probability of your dying, and that probability sets the premium that the insurance company charges you.
I use Facebook. That means they already know my age, geographic location, gender. So, if you are a 50-something male in Johannesburg (as I am), they already know that I am the target market for 80s music, for retirement planning, and prostate screening. But when they see that I have “liked” pictures by my friends describing their new car or workout routine, that allows them to send adverts for new cars or new gym gear to me because my behaviour makes me more susceptible to such purchases.
But let’s go back to our judiciary. In criminal cases in most parts of the world, for the court to hand down a verdict of guilty, the findings have to be “beyond Reasonable Doubt”. This means that for a defendant to be found guilty the case presented by the prosecution must be enough to remove any reasonable doubt in the mind of the court that the defendant is guilty of the crime with which he or she is charged.
This is very different from civil matters or labour matters - in those cases, what is required is “balance of probabilities”. Criminal cases, where the freedom or the very life of the individual is at stake, set a higher standard.
This principle can be traced to the English jurist William Blackstone in the 1760s who said: “it is better that ten guilty persons escape than that one innocent suffer". In other words, if there is any doubt that a person is guilty, they should be acquitted than to risk an innocent person being convicted.
So, when a person goes on trial, to convict, the court has to find the probability of guilt is beyond “Reasonable Doubt”. If we asked most people to put a number to this, we would get answers like 95% or even 99%. For our purposes though, let’s say that the judge has to find a better than 90% probability that a person is guilty.
The Bayes rule says the probability of guilt after the trial is equal to the sum of the probability of guilt before the trial and the level of bias, multiplied by the weight of the evidence required to convict.
Before the trial, if the judge is not biased, the probability of guilt in the judges’ mind has to be equal to the probability of guilt of the average citizen. That probability is going to be no more than one or two percentage points. However, to err on the side of caution again, let’s call it less than or up to 10% at most. This still leaves us with the judge needing to be 90% sure that the accused is guilty - let’s call that a guilty score of 9 out of 10.
But what if the judge comes into the case with unconscious bias primed by information not related to the case (like the example I’ve given of the Jacob Zuma rape charge)?
Let’s look at the math of the Bayes rule and say the same thing differently: The weight of the evidence required to convict is equal to the probability of guilt after the trial divided by the sum of the probability of guilt before the trial plus the bias expressed as a probability.
If the judge comes into the case with a 10% level of bias, the math shifts from 9/10 to 4.5/10.
What if the level of the judge’s bias is 30%? To convict only requires a weight of evidence greater than or equal to 3/10 ( a third of what is required absent bias). This is fine for a 30% matric pass rate, but should a person’s freedom be at stake for a 30% probability he or she is guilty?
Now if you were to ask me, personally, whether Zuma should be held criminally liable for money purloined from the state coffers during his tenure as president of the country, I would say “yes” immediately. After all, I have read the Gupta Leaks reports, I know about the wedding party landing at Waterkloof, I know about palaces in Dubai.
But if I am sitting as a judge in the forthcoming trial of Jacob Gedleyihlekisa Zuma, I need to wipe those factors from my head. To convict, the court has to find a better than 90% probability that an accused is guilty, purely based on evidence supplied before the court, and ignoring the overwhelming wave of sentiment from the rest of the nation who want to see people held accountable.
What do you think is the probability of that happening?
Now imagine it’s you in the dock.
* The views expressed here are not necessarily those of IOL.