When Scientists Go Wrong

Scientific studies on scientists are not always encouraging.

You probably shouldn’t rely on yesterday’s scientific guidelines about diet. The Guardian begins a critique of scientific consensus about nutrition with these words:

In 1972, a British scientist sounded the alarm that sugar – and not fat – was the greatest danger to our health. But his findings were ridiculed and his reputation ruined. How did the world’s top nutrition scientists get it so wrong for so long?

Flawed conclusions taught as fact for 40 years cannot be laid at the foot of corporations, Ian Leslie says. Nor does it show that scientists are open to new ideas as more evidence becomes available. Instead, this incident proves Planck’s maxim that science advances one funeral at a time. So how confident can we be about their advice today?

At The Conversation, Jeremy Gibbons teases with the headline, “Science relies on computer modelling – so what happens when it goes wrong?” We don’t do science the old fashioned way, verifying the properties of nature by hands-on experiment. Gibbons, a professor of computing at Oxford, warns that computer models are simplifications of nature that cannot be precise:

Modelling is used across scientific fields – ranging from astrophysics and climate prediction to bioinformatics and economics. But there is increasing debate about the fact that this science is difficult to validate through reproduction.

It turns out that simply describing experimental methods in words is not enough. That’s partly because natural languages such as English are simply too vague for describing computations precisely. There is, after all, a reason why programmers use programming languages. One of the biggest challenges in software development is in converting vague requirements into precise specifications of behaviour.

He points to clear cases of bugs in inputs and outputs. Often, results are not reproducible because other scientists may not understand what the authors did, what they meant, or even because of the way different programs handle the same numbers.

Oh, but science is truth. Don’t be misled by facts! —Finagle.