Holloway points out that companies today are awash in information. But which patterns are real? Which are cloud bunnies?
One way business intelligence can address this problem (false positives) is hypothesis testing. The data analyst can generate a figure for the probability that a pattern is real, not imagined. The difficulty is that, for strong guarantees, the patterns must be proposed before they are seen in the data. But the more the analyst looks at the data to derive a pattern, the more that analyst falls prey to seeing patterns that are not really there. Thus, the need to state all patterns up front is a huge restriction and deadlocks our ability to gain insight from the data.
Welcome to Data Deadlock. Should we just go home now?
Intelligent design theory might help us make new headway in the fields of information theory and statistics. The problem is familiar: how can we be sure that a pattern we see, for example, apparent design in the biological record, is not merely a chance outcome? Intelligent design theory makes the novel proposal that we can derive patterns from the data after the fact while retaining the strong guarantees of hypothesis testing.Eric Holloway , “How Business Intelligence Can Break the Data Deadlock” at Mind Matters News
ID theory, he says, offers a way around false positives.
See also: Does information theory support design in nature William Dembski makes a convincing case, using accepted information theory principles relevant to computer science
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