When discussing knowledge, truth, and information, people often begin speaking of ``misinformation" or ``bad data." Scientists often speak of ``bad data," produced by faulty measurement or poor observations. Misinformation [Fox83] often refers to information that is ``false," that is, the information does not directly reflect the ``true" state of the world. Consider a ``lie" told by an individual or an organization. The person making the lie knows the truth and, instead of repeating it, chooses to produce a lie for some purpose. The lie is then information about the process that produced it. It is misinformation or ``false information" only in the sense that we may not know the nature of the full hierarchy of processes, that is, the characteristics of the function that did eventually produce the lie. The exact nature of misinformation, etc., is subject to a wide range of interpretations (and misinterpretations). Dretske notes that ``no structure can carry the information that s is F unless, in fact, s is F. False information, misinformation, and disinformation are not varieties of information" [Dre83].
Misinformation and related concepts may be defined consistent with the hierarchical model. When what is transmitted is not received as sent, i.e., for some xthat is input to an f(), an information loss has occurred in the process. This can occur when the function fcan be said to be a partially random or noisy process. When this happens, what is transmitted was not reproduced by the function; some of what was transmitted has been ``lost."
When information has been lost in producing a particular output characteristic, the value taken on by the characteristic is determined, in part, by a random or error component. When there exists a non-null error component in determining a characteristic or variable's value, the ``information" contained in the variable may be referred to as ``misinformation." The value of a variable is information about the input; when the information is only partial and is tainted by error, it is better understood as misinformation. Essentially, this is information that is partly or wholly false.
Economists and scholars interested in decision theory [HR92,WY73,YK93] often refer to error free information as perfect information [AW81,BG54,Mar84,HM87,Ner81,Phl88,Sen93]. Perfect information about a source domain Xexists when there is a one-to-one mapping in a noiseless environment for the source X onto the destination set Y [Los90]. Information may be said to be incomplete when the mapping from Xis into Y, not onto Y.
We may define another form of misinformation as information that isn't justified. If one believes something for the wrong reasons, one may be said to be ``misinformed." In these cases, there is a perception that something is wrong with the recipient of the information, and it is this faulty nature of the receiver that makes something ``misinformation."