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Another Voice
The Experimental Imperative We should experiment with ways of overcoming people's cognitive limitations.

You hear about a new drug, and you learn first about its risks, then about its benefits. You weigh them and decide that the drug is in your best interests. Now you learn about another drug, first finding out about its benefits, then its risks. You’re not so keen to take this one. It doesn’t feel like it is in your best interests.

Would you be surprised to find out that these pills are the same drug?

Decisions require information. But providing information in a neutral manner is difficult. In the case above, the problem is a decision bias called the recency effect—the most recent piece of information people received played a disproportionate role in their judgment.

In his provocative essay in this issue of the Report, Peter Schwartz raises important questions about what information should be provided to whom. He criticizes what he calls the quantitative imperative—the belief that patients should be informed, in numerical terms, about the risks and benefits of their treatment alternatives.

You hear about a new drug, and you learn first about its risks, then about its benefits. You weigh them and decide that the drug is in your best interests. Now you learn about another drug, first finding out about its benefits, then its risks. You’re not so keen to take this one. It doesn’t feel like it is in your best interests.

Would you be surprised to find out that these pills are the same drug?

Decisions require information. But providing information in a neutral manner is difficult. In the case above, the problem is a decision bias called the recency effect—the most recent piece of information people received played a disproportionate role in their judgment.

In his provocative essay in this issue of the Report, Peter Schwartz raises important questions about what information should be provided to whom. He criticizes what he calls the quantitative imperative—the belief that patients should be informed, in numerical terms, about the risks and benefits of their treatment alternatives.

Peter A. Ubel, "The Experimental Imperative," Hastings Center Report 41, no. 2 (2011): 3.