Abstract
Agents require a constant flow, and a high level of processing, of relevant semantic information, in order to interact successfully among themselves and with the environment in which they are embedded. Standard theories of information, however, are silent on the nature of epistemic relevance. In this paper, a subjectivist interpretation of epistemic relevance is developed and defended. It is based on a counterfactual and metatheoretical analysis of the degree of relevance of some semantic information i to an informee/agent a, as a function of the accuracy of i understood as an answer to a query q, given the probability that q might be asked by a. This interpretation of epistemic relevance vindicates a strongly semantic theory of information, according to which semantic information encapsulates truth. It accounts satisfactorily for several important applications and interpretations of the concept of relevant information in a variety of philosophical areas. And it interfaces successfully with current philosophical interpretations of causal and logical relevance.
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Notes
In this sense, theoretical information theory is a branch of probability theory, and applied information theory a branch of engineering, see Cover and Thomas (1991).
For an overview see Floridi (2004a).
This is argued in Floridi (2005b), see Sequoiah-Grayson [forthcoming] for a recent defence.
See for example Yus (2006), a bibliography online on relevance theory in pragmatics and related disciplines. For recent review articles on relevance in information science see Greisdorf (2000) and the very useful Borlund (2003). Philosophical accounts of relevance include Gärdenfors (1978); Cohen (1994); Lakemeyer (1997); and Delgrande and Pelletier (1998), all works that have influenced the research for this paper.
“A specific ‘entity’ (such as an action, training sample, attribute, background proposition, or inference step) is irrelevant to a task in some context if the appropriate response to the task does not change by an unacceptable [sic] amount if we change the entity in that context, Otherwise, we view that entity as (somewhat) relevant to the task. This view is explicitly stated in the paper by Galles and Pearl, which deals with causality and where a perturbation corresponds to a material change in the physical world.” Subramanian et al. (1997), p. 2.
The adequacy of Körner criterion of relevance for propositional logic has been proved by Schroder (1992).
The analysis of relevance also depends on the level of abstraction (Floridi and Sanders 2004) at which the process of assessment is conducted. A level of abstraction may be seen as the precise specification of the way in which some information is being accessed and processed, cf. the analysis of “the point of view” according to which something is relevant in Cohen (1994).
Many thanks to Jürg Kohlas for having called my attention to this equivalence.
A question Q is loaded if the respondent is committed to (some part of) the presupposition of Q (Walton 1991, 340) e.g. “how many times did you kiss Mary?” which presupposes that you did kiss Mary at least once.
Two further consequences are that (i) rational agents cannot possess exactly the same information and agree to disagree about the probability of some past or future events. In fact, they must independently come to the same conclusion, and (ii) they cannot surprise each other informationally.
Bowles (1990) follows a similar strategy to explain probabilistically the relation of relevance in propositional inferences.
Accuracy is the degree of conformity of a measure or calculated parameter to its actual (true) value. Precision (also called reproducibility or repeatability) is the degree to which further measurements or calculations show the same or similar results.
Plato, Meno 80d–81a:
“Meno: And how will you investigate, Socrates, that of which you know nothing at all? Where can you find a starting-point in the region of the unknown? Moreover, even if you happen to come full upon what you want, how will you ever know that this is the thing that you did not know?
Socrates: I know, Meno, what you mean; but just see what a tiresome dispute you are introducing. You argue that man cannot enquire either about that which he knows, or about that which he does not know; for if he knows, he has no need to enquire; and if not, he cannot; for he does not know the very subject about which he is to enquire.”
This solution is partly adopted in information theory by Tishby et al. (1999), who “define the relevant information in a signal x ∈ X as being the information that this signal provides about another signal y ∈ Y. Examples include the information that face images provide about the names of the people portrayed, or the information that speech sounds provide about the words spoken.” Note that what they treat as “relevance” is really a quantitative relation of structural conjunction, which can be considered a necessary condition for semantic relevance, but should not be confused with it.
The mere assumption of these values is justified here because this is only an illustrative example. The identification of the right set of Bayesian priors is a hard problem faced by any analysis of real-life phenomena. Of course, the formulation of a prior distribution over the unknown parameters of the model should be based on the available data (including subjective beliefs) about the modelled phenomena, yet this is easier said than done, see for example Dongen (2006).
“Relevance here is a technical term (though clearly related to the natural language homonym), whereby an interpretation is relevant only in cases where the cognitive cost of processing the event which demands the attention of the agent is outweighed by the cognitive benefits of that processing (where benefits include deriving or strengthening new assumptions, and confirming or rejecting previous assumptions). ‘Optimal relevance’ states that the first interpretation which crosses the relevance threshold is the right one; that is, that the first relevant interpretation the addressee arrives at is the one the speaker intended to communicate.” (Emma Borg, Intention-Based Semantics, in Lepore and Smith (2006, p. 255).
“Disinformation” is misinformation purposefully conveyed to mislead the receiver into believing that it is information.
This is consistent with the truth requirement established in Cohen (1994).
I am summarising here a variety of questions and objections raised, with some consistency, at several meetings where I presented the ideas laid out in this article (for a complete list see the acknowledgments). I discussed with Fred Dretske the first objection during the 30th Wittgenstein Symposium. I am very grateful to Jeremy Seligman for having suggested the second objection and for our conversations about it, which greatly helped me to clarify the issue.
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Acknowledgements
The first time I discussed the topic of a theory of epistemic relevance was during a talk I gave at the University of Regensburg (Regensburg, Germany 9 November 2005). I owe to Rainer Hammwoehner and Hans Rott not only the kind invitation but also the conceptual pressure that made me start working on this paper. A first version of the paper was then presented at the Department of Communication Science of the University of Salerno (Fisciano, Italy, 10 May 2006), and I wish to thank Roberto Cordeschi for that opportunity and the feedback I received in that occasion. The paper was further improved and discussed at the “Workshop on Information Theories”, organized by Juerg Kohlas and Giovanni Sommaruga at Fribourg University (Münchenwiler, Switzerland, 17–18 May 2006). They, the attendees, and especially Rolf Haenni and Jeremy Seligman provided some very helpful comments. A new version was the subject of an invited talk at the Department of Philosophy of the University of Siena (Siena, 14 June 2006), where I took advantage of a long discussion with Claudio Pizzi on secondorder probabilities. This led to a paper presented at a seminar organised by the Computer Science Department of Mälardalen University (Västerås, Sweden, September 2006), where I was kindly invited by Gordana Dodig Crnkovic. The discussion with the participants and especially with Gordana, Susan Stuart and Lars-Göran Johansson generated several improvements. The issue of hardwired questions was discussed there. The final version of the article then became the ISI Samuel Lazerow Memorial Lecture I delivered at the University of Arizona (Tucson, 8 February 2007). I am grateful to Don Fallis for the invitation and to the Research Group on the History and Philosophy of Information Access, the School of Information Resources and Library Science and The International Visitors Fund for the kind support. The last opportunity I had to discuss this paper was as an invited lecture at the 30th Wittgenstein Symposium and at the 48th Boston Colloquium for Philosophy of Science. Finally, I would like to acknowledge the help, useful comments and criticisms by Pia Borlund, Ken Herold, Karen Mather, Paul Oldfield and Federica Russo and the journal’s anonymous referees. As usual, all the aforementioned people are responsible only for the improvements and not for any remaining mistakes.
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Floridi, L. Understanding Epistemic Relevance. Erkenn 69, 69–92 (2008). https://doi.org/10.1007/s10670-007-9087-5
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DOI: https://doi.org/10.1007/s10670-007-9087-5