Do you think you are a better-than-average driver? Chances are you do. And you know what? So do 80-90% of other drivers.
The labels on cigarettes are clear and yet, about 500,000 people die from using tobacco products every year.
The warnings about driving while under the influence of alcohol are well known. Yet about 10,000 people die every year in alcohol-related traffic accidents.
We know wearing masks significantly reduces the chances of catching COVID, yet many of us still go without.
The examples can go on. Some call this the optimism bias. Optimism bias is the belief that each of us is more likely to experience good outcomes and less likely to experience bad outcomes. The key to optimism bias is that we disregard the reality of an overall situation because we think we are excluded from the potential negative effects.
The optimism bias is the only way I can make sense of decisions being made by technology companies discussed in this brilliant article by Sun-ha Hong. In the article Hong provides examples of how data collected for one purpose gets used by the same company for something completely different. Call it a pivot, call it business, call it whatever – almost always it results in harm for the person about whom the data is. And the founders know this, but it continues. Perhaps its greed, ego, or the desire to innovate. But there also seems to be a perception that they (and their families) will be immune to the harm. It won’t happen to us. Optimism bias.
And we do this too. In our projects, when potential for harm is pointed out, we tend to ignore it, explain it away, or say ‘it won’t happen to us’. Control creep, scope creep, or whatever creep happens, especially with data and digital.
One way to help overcome the optimism bias is to focus on the positive. So not highlighting the harm, but rather saying by not smoking you have a better chance of making the football team. So what does that look like for you? for us?