With the mostly-unforeseen global financial crisis uppermost in our minds, I am led to consider a question that I have pondered for some time:   How should we assess forecasts and prophecies?   Within the branch of philosophy known as argumentation, a lot of attention has been paid to the conditions under which a rational decision-maker would accept particular types of argument.

For example, although it is logically invalid to accept an argument only on the grounds that the person making it is an authority on the subject, our legal system does this all the time.  Indeed,  the philosopher Charles Willard has argued that modern society could not function without most of us accepting arguments-from-authority most of the time, and it is usually rational to do so.  Accordingly, philosophers of argumentation have investigated the conditions under which a rational person would accept or reject such arguments.   Douglas Walton (1996, pp. 64-67) presents an argumentation scheme for such acceptance/rejection decisions, the Argument Scheme for Arguments from Expert Opinion, as follows:

• Assume E is an expert in domain D.
• E asserts that statement A is known to be true.
• A is within D.

Therefore, a decision-maker may plausibly take A to be true, unless one or more of the following Critical Questions (CQ) is answered in the negative:

• CQ1:  Is E a genuine expert in D?
• CQ2:  Did E really assert A?
• CQ3:  Is A relevant to domain D?
• CQ4:  Is A consistent with what other experts in D say?
• CQ5:  Is A consistent with known evidence in D?

One could add further questions to this list, for example:

• CQ6:  Is E’s opinion offered without regard to any reward or benefit upon statement A being taken to be true by the decision-maker?

Walton himself presents some further critical questions first proposed by Augustus DeMorgan in 1847 to deal with cases under CQ2 where the expert’s opinion is presented second-hand, or in edited form, or along with the opinions of others.
Clearly, some of these questions are also pertinent to assessing forecasts and prophecies.  But the special nature of forecasts and prophecies may enable us to make some of these questions more precise.  Here is my  Argument Scheme for Arguments from Prophecy:

• Assume E is a forecaster for domain D.
• E asserts that statement A will be true of domain D at time T in the future.
• A is within D.

Therefore, a decision-maker may plausibly take A to be true at time T, unless one or more of the following Critical Questions (CQ) is answered in the negative:

• CQ1:  Is E a genuine expert in forecasting domain D?
• CQ2:  Did E really assert that A will be true at T?
• CQ3:  Is A relevant to, and within the scope of, domain D?
• CQ4:  Is A consistent with what is said by other forecasters with expertise in D?
• CQ5:  Is A consistent with known evidence of current conditions and trends in D?
• CQ6:  Is E’s opinion offered without regard to any reward or benefit upon statement A being adopted by the decision-maker as a forecast?
• CQ7:  Do the benefits of adopting A being true at time T in D outweigh the costs of doing so, to the decision-maker?

In attempting to answer these questions, we may explore more detailed questions:

• CQ1-1:  What is E’s experience as forecaster in domain D?
• CQ1-2: What is E’s track record as a forecaster in domain D?
• CQ2-1: Did E articulate conditions or assumptions under which A will become true at T, or under which it will not become true?  If so, what are these?
• CQ2-2:  How sensitive is the forecast of A being true at T to the conditions and assumptions made by E?
• CQ2-3:  When forecasting that A would become true at T, did E assert a more general statement than A?
• CQ2-4:  When forecasting that A would become true at T, did E assert a more general time than T?
• CQ2-5:  Is E able to provide a rational justification (for example, a computer simulation model) for the forecast that A would be true at T?
• CQ2-6:  Did E present the forecast of A being true at time T qualified by modalities, such as possibly, probably, almost surely, certainly, etc.
• CQ4-1:  If this forecast is not consistent with those of other forecasters in domain D, to what extent are they inconsistent?   Can these inconsistencies be rationally justified or explained?
• CQ5-1: What are the implications of A being true at time T in domain D?  Are these plausible?  Do they contradict any known facts or trends?
• CQ6-1:  Will E benefit if the decision-maker adopts A being true at time T as his/her forecast for domain D?
• CQ6-2:  Will E benefit if the decision-maker does not adopt A being true at time T as his/her forecast for domain D?
• CQ6-3:  Will E benefit if many decision-makers adopt A being true at time T as their forecast for domain D?
• CQ6-4:  Will E benefit if few decision-makers adopt A being true at time T as their forecast for domain D?
• CQ6-5:  Has E acted in such a way as to indicate that E had adopted A being true at time T as their forecast for domain D (eg, by making an investment betting that A will be true at T)?
• CQ7-1:  What are the costs and benefits to the decision-maker for adopting statement A being true at time T in domain D as his or her forecast of domain D?
• CQ7-2:  How might these costs and benefits be compared?  Can a net benefit/cost for the decision-maker be determined?

Automating these questions and the process of answering them is on my list of next steps, because automation is needed to design machines able to reason rationally about the future.   And rational reasoning about the future is needed if  we want machines to make decisions about actions.
References:
Augustus DeMorgan [1847]: Formal Logic.  London, UK:  Taylor and Walton.
Douglas N. Walton [1996]:  Argument Schemes for Presumptive Reasoning. Mahwah, NJ, USA: Lawrence Erlbaum.
Charles A. Willard [1990]: Authority.  Informal Logic, 12: 11-22.