Erik J Olsson

What is the Problem of Coherence and Truth

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Providing Foundations for Coherentism

We prove that four theses commonly associated with coherentism are incompatible with the representation of a belief state as a logically closed set of sentences. The result is applied to the conventional coherence interpretation of the AGM theory of belief revision, which appears not to be tenable. Our argument also counts against the coherentistic acceptability of a certain form of propositional holism. We argue that the problems arise as an effect of ignoring the distinction between derived and non-derived beliefs, and we suggest that the kind of coherence relevant to epistemic justification is the coherence of non-derived beliefs.

Norms of Assertion and Communication in Social Networks

Epistemologists can be divided into two camps: those who think that nothing short of certainty or (subjective) probability 1 can warrant assertion and those who disagree with this claim. This paper addressed this issue by inquiring into the problem of setting the probability threshold required for assertion in such a way that that the social epistemic good is maximized, where the latter is taken to be the veritistic value in the sense of Goldman (Knowledge in a social world, 1999). We provide a Bayesian model of a test case involving a community of inquirers in a social network engaged in group deliberation regarding the truth or falsity of a proposition

Corroborating Testimony, Probability and Surprise

p.

Trust and the value of overconfidence: a Bayesian perspective on social network communication

p. Results obtained by means of computer simulation indicate that the certainty rule is optimal in the limit of inquiry and communication but that a lower threshold is preferable in less idealized cases.

In Defense of the Conditional Probability Solution to the Swamping Problem

This chapter describes a simulation environment for epistemic interaction based on a Bayesian model called Laputa. An interpretation of the model is proposed under which the exchanges taking place between inquirers are argumentative. The model, under this interpretation, is seen to survive the polarization test: If initially disposed to judge along the same lines, inquirers in Laputa will adopt a more extreme position in the same direction as the effect of group deliberation, just like members of real argumentative bodies. Our model allows us to study what happens to mutual trust in the polarization process. We observe that inquirers become increasingly trusting which creates a snowball effect. We also study conditions under which inquirers will diverge and adopt contrary positions. To the extent that Bayesian reasoning is normatively correct, the bottom line is that polarization and divergence are not necessarily the result of mere irrational “group think” but that even ideally rational inquirers will predictably polarize or diverge under realistic conditions. The concluding section comments on the relation between the present model and the influential and empirically robust Persuasive Argument Theory (PAT), and it is argued that the former is essentially subsumable under the latter.

Do computer simulations support the Argument from Disagreement

L. Jonathan Cohen has claimed that in cases of witness agreement there is an inverse relationship between the prior probability and the posterior probability of what is being agreed: the posterior rises as the prior falls. As is demonstrated in this paper, this contention is not generally valid. In fact, in the most straightforward case exactly the opposite is true: a lower prior also means a lower posterior. This notwithstanding, there is a grain of truth to what Cohen is saying, as there are special circumstances under which a thesis similar to his holds good. What characterises these circumstances is that they allow for the fact of agreement to be surprising. In making this precise, I draw on Paul Horwichs probabilistic analysis of surprise. I also consider a related claim made by Cohen concerning the effect of lowering the prior on the strength of corroboration. 1 Introduction 2 Cohens claim 3 A counterexample 4 A weaker claim 5 A counterexample to the weaker claim 6 The grain of truth in Cohens claim 7 Prior probability and strength of corroboration 8 Conclusion

A DDL Approach to Pluralistic Ignorance and Collective Belief

Fido sees that there is a bone on the plate, but does Fido know that there is a bone on the plate? David, a two-year-old, sees that the door to the refrigerator is open, but does he know that it is open? Examples such as these prompt very different reactions from philosophers. Some think it is obvious that Fido and David know, and that they know in the same sense as adult humans do. Others respond, equally emphatically, that they do not know, at least not in the same way as adult humans. Philosophers ofthe latter inclination may grant that someone who believes that Fido knows is allowed to use the term ‘know’ in any way he or she wishes and, further, that there might be some point in defining a concept of knowledge applicable also to Fido; but, they will urge, that concept will not be of great interest if what we really care about is human knowledge in its characteristic form.