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If there is such a thing as real expertise in identifying the properties of a wine, then it must be possible to get it wrong.  If tastes, in general, were entirely subjective there would be no right answer to the question of whether, for instance, chocolate ice cream tastes of chocolate.  No one really thinks that. The fact that expert wine tasters get it wrong so often is evidence that wine tasting is harder than identifying the presence of chocolate in ice cream—not that it is utterly capricious. So tastes are not so entirely subjective that our experiences of them have no relationship to an object.

Furthermore, tasters can strive to eliminate environmental factors that have been shown to influence judgments about wine such as conversations, the style of music being played, and changes in the weather, etc. These are all factors that wine tasters can control by adjusting the environment in which they taste. Wine tasters, if they are to maintain credibility, must taste under the appropriate conditions. But that is no different from any other normative judgment we make. Our ability to make ethical judgments, for instance, is similarly influenced by environmental factors. We know (or should know) better than to make ethical judgments when we are excessively angry, fearful, under the influence of powerful desires, etc. Yet, it does not follow from the fact that ethical judgments can be influenced by irrelevant factors that all ethical judgments are subjective.

So the taste of wine (or anything else) is partly dependent on objective features of the world and partly dependent on how our view of those features has been shaped by past experience. The crucial question then is how much of a distorting lens is that past experience.

Is there a connection between language and how we think and behave? In particular, Chen wanted to know: does our language affect our economic decisions? Chen designed a study — which he describes in detail in this blog post — to look at how language might affect individual’s ability to save for the future. According to his results, it does — big time.

Using vast inventories of data and meticulous analysis, Chen found that huge economic differences accompany this linguistic discrepancy. Futureless language speakers are 30 percent more likely to report having saved in any given year than futured language speakers.

But that’s only the beginning. There’s a wide field of research on the link between language and both psychology and behavior. Here, a few fascinating examples:

Computers are very, very fast at making calculations. Moreover, they can be counted on to calculate faithfully—without getting tired or emotional or changing their mode of analysis in midstream. But this does not mean that computers produce perfect forecasts, or even necessarily good ones. The acronym GIGO (“garbage in, garbage out”) sums up this problem. If you give a computer bad data, or devise a foolish set of instructions for it to analyze, it won’t spin straw into gold. Meanwhile, computers are not very good at tasks that require creativity and imagination, like devising strategies or developing theories about the way the world works. Computers are most useful to forecasters, therefore, in fields like weather forecasting and chess where the system abides by relatively simple and well-understood laws, but where the equations that govern the system must be solved many times over in order to produce a good forecast. They seem to have helped very little in fields like economic or earthquake forecasting where our understanding of root causes is blurrier and the data is noisier. In each of those fields, there were high hopes for computer-driven forecasting in the 1970s and 1980s when computers became more accessible to everyday academics and scientists, but little progress has been made since then.

The math behind these formulas may be elegant, but applying them is more complicated.

Predicting the Next Financial CrisisWhy do financial crises occur – and when will the next one come? In the past, economic theory has failed to answer these questions. In this week’s Science Journal Perspectives, economists, physicists, epidemiologists, climate scientists and ecologists call to establish a new early warning system to avoid future global financial crises. They argue that the methods used by scientists to predict weather, traffic or disease epidemics should be used to simulate the financial systems, which could help to avoid the failures we have seen in the past. Professor Doyne tells Jack how the analysis of complex networks could and should be applied to the economy.