century statistician Thomas Bayes, the idea is to treat knowledge as
a belief that we have a certain level of confidence in. For example,
suppose you are strongly considering marrying someone, having
thought carefully about the relationship. In this situation, it would take
a very good reason for you to change your mind. However, if you’re
not totally sure about the relationship, you might be persuaded
against marriage more easily. Something that might seem trivial to the
infatuated may be enough to tip a wavering mind towards a break-up.
The same logic applies to other situations. If you start with a firm
belief, you’ll generally need strong evidence to overcome it; if you are
unsure at first, it might not take much for you to change your opinion.
Your belief after exposure to new information therefore depends on
two things: the strength of your initial belief and the strength of the
new evidence.[54] This concept is at the heart of Bayesian reasoning
- and much of modern statistics.
Yet there are suggestions that people don’t absorb information in
this way, especially if it goes against their existing views. In 2008,
political scientists Brendan Nyhan and Jason Reifler proposed that
persuasion can suffer from a ‘backfire effect’. They’d presented
people with information that conflicted with their political ideology,
such as the lack of weapons of mass destruction in Iraq before the
2003 war, or the decline in revenues following President Bush’s tax
cuts. But it didn’t seem to convince many of them. Worse, some
people appeared to become more confident in their existing beliefs
after seeing the new information.[55] Similar effects had come up in
other psychological studies over the years. Experiments had tried to
persuade people of one thing, only for them to end up believing
something else.[56]
If the backfire effect is common, it doesn’t bode well for canvassers
hoping to convince people to change their minds about issues like
same-sex marriage. The Los Angeles LGBT Center thought they had
a method that worked, but it needed to be evaluated properly. In early
2013, Dave Fleischer had lunch with Donald Green, a political
scientist at Columbia University. Green introduced Fleischer to
Michael LaCour, a graduate student at UCLA, who agreed to run a
scientific study testing the effectiveness of deep canvassing. The aim