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What is puzzling about this whole debate about the objectivity of wine critics, however, is why people want objective descriptions of wine. We don't expect scientific objectivity from art critics, literary critics, or film reviewers. The disagreements among experts in these fields are as deep as the disagreements about wine. There is no reason to think a film critic would have the same judgment about a film if viewed in a different context, in comparison with a different set of films, or after conversing about the film with other experts. Our judgments are fluid and they should be if we are to make sense of our experience. When listening to music aren't we differently affected by a song depending upon whether we are at home, in a bar, going to the beach, listening with friends or alone? Why would wine be different? The judgment of any critic is simply a snapshot at a particular time and place of an object whose meaning can vary with context. Wine criticism cannot escape this limitation.

What we want from critics whether of music, art, or wine is a judgment made in light of their vast experience that can show us something about the object that we might have missed without their commentary. That can be accomplished independently of whether the critic is perfectly consistent or objective. We want the critic to have a certain kind of bias, born of her unique experience, because it is that bias that enables her to taste, see, or hear what she does.

From 2001 to 2009, the number of retractions issued in the scientific literature rose tenfold. It remains a matter of debate whether that’s because misconduct is increasing or is just easier to root out.

Science isn’t broken, nor is it untrustworthy. It’s just more difficult than most of us realize. We can apply more scrutiny to study designs and require more careful statistics and analytic methods, but that’s only a partial solution. To make science more reliable, we need to adjust our expectations of it.

Science is not a magic wand that turns everything it touches to truth. Instead, “science operates as a procedure of uncertainty reduction,” said Nosek, of the Center for Open Science. “The goal is to get less wrong over time.”

Some of these biases are helpful, at least to a point. Take, for instance, naive realism — the idea that whatever belief you hold, you believe it because it’s true. This mindset is almost essential for doing science, quantum mechanics researcher Seth Lloyd of MIT told me. “You have to believe that whatever you’re working on right now is the solution to give you the energy and passion you need to work.” But hypotheses are usually incorrect, and when results overturn a beloved idea, a researcher must learn from the experience and keep, as Lloyd described it, “the hopeful notion that, ‘OK, maybe that idea wasn’t right, but this next one will be.’”