Why Techno-Babble and Crazy Promises Are Necessary
February 3, 2020
Do you believe the assertions about artificial intelligence, natural language processing, and quantum computing? The question is important because, according to the Nieman Lab, “Humans are hardwire to dismiss facts that don’t fit their worldview.” For those who believe in unicorns and fantasize about unicornification, the wilder and crazier the explanations about technology, the more coherent they sound. But try to provide facts, and the human brain is just not that interested if the research is accurate.
The write up asserts:
In theory, resolving factual disputes should be relatively easy: Just present the evidence of a strong expert consensus. This approach succeeds most of the time when the issue is, say, the atomic weight of hydrogen. But things don’t work that way when the scientific consensus presents a picture that threatens someone’s ideological worldview. In practice, it turns out that one’s political, religious, or ethnic identity quite effectively predicts one’s willingness to accept expertise on any given politicized issue.
What do these references to politicization have to do with technology sales and marketing?
DarkCyber believes that when one points out that an error rate of 85 percent means that there are 15 mistakes per 100 items. People think that error rate is okay, acceptable, maybe great. Apply the error rate to identifying potential bad actors, and someone has to figure out how to explain what happened to the 15 actors put in the bad egg bin.
Present this type of “fact” to a group, and most of the people exposed to the fact will ignore it.
But— and here’s the important point — evoke Star Trek, some magical numerical recipe, or just plain old hocus pocus like Google’s endless yammering about search quality, and people believe this stuff.
Years ago, enterprise search pitch men and pitch women discovered that promising to index “all of an organization’s information” and “eliminating time wasted looking for information” was the key to sales. Explaining that enterprise search was more like crafting a specific search system for a particular and quite specific problem was the more rational approach.
Sales were made, but the users were unhappy. The consequences were dire. Companies failed. Investors lost their money. One search executive was convicted of a criminal offense.
Flash forward to today. Predictive analytics, algorithms, and smart software will improve efficiency, reduce costs, unleash innovation, extract value from dark data, and generate new revenue.
Facts are one thing. Marketing hype another. Guess which takes precedence in search, analytics, artificial intelligence, and quantum computing?
If you said facts, you are in the minority if the Neiman Lab write up is correct.
Stephen E Arnold, February 3, 2020
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