Online research in philosophy

Nearly all current attempts at environmental impact analysis and technology assessment fall victim to an ethical and methodological assumption that Keniston termed “the fallacy of unfinished business.” Related to one version of the naturalistic fallacy, this assumption is that technological and environmental problems have only technical, but not social, ethical, or political solutions. After using several impactanalyses to illustrate the policy consequences of the fallacy of unfinished business, I suggest how it might be overcome. Next I present three standard arguments, repeatedly used in technology and environmental impact assessments, by those who subscribe to this “fallacy.” I briefty examine the logical, consequentialist, and historical reasons for rejecting all three arguments in favor of this assumption. Ifmy suggestions are correct, then environmental impact analysis is not only a matter of discovering how to finish our technological business, but also a question of learning how to recognize the ethical and epistemological dimensions of our assessment tasks.

In this paper, I propose an accurate description of the cognitive process involved in the one-sidedness fallacy, a widespread type of fallacy. I describe first several characterizations of the one-sidedness fallacy, that are either inductive or deductive, or occurring at a meta-philosophical level. I recall, second, the framework of the cognitive distortions described in Franceschi (2007). I give then a definition of the one-sidedness fallacy, by describing it as a general cognitive distortion: the disqualification of one pole. I show finally how the one-sidedness fallacy distinguishes itself from the confirmation bias.

The naturalistic fallacy is a source of much confusion. In what follows I will explain what G. E. Moore meant by the naturalistic fallacy, give modern day examples of it then mention some of the different types of views it has spawned. Finally, I will consider a few criticisms of it.

Indirect negative evidence is clearly an important way for learners to constrain overgeneralisation, and yet a good learning theoretic analysis has yet to be provided for this, whether in a PAC or a probabilistic identification in the limit framework. In this paper we suggest a theoretical analysis of indirect negative evidence that allows the presence of ungrammatical strings in the input and also accounts for the relationship between grammaticality/acceptability and probability. Given independently justified assumptions about lower bounds on the probabilities of grammatical strings, we establish that a limited number of membership queries of some strings can be probabilistically simulated.

Introduction -- Fallacy # 1, you can never be sure -- Fallacy # 2, "there is no truth" -- Fallacy # 3, there are no absolutes -- Fallacy # 4, there is only physical-experiential reality -- Fallacy # 5, philosophy is boring : I should know, I tried it once -- Fallacy # 6, God does not exist -- Fallacy # 7, isn't it a contradiction to say "God is good" when we see so much evil in the world, I mean with so many wars, famines, plagues, and whale hunting and everything? -- Fallacy # 8, if God knows all things, even the future, then we are not free -- Fallacy # 9, if God is all-powerful can He make a "PB&J" so big he couldn't eat it in one bite? -- Fallacy # 10, man has no human nature -- Fallacy # 11, my body belongs to me! -- Fallacy # 12, the human person is a spiritual person and since spirits are neither female and male, our sexual distinctions are merely social constructs -- Fallacy # 13, I'm free to do whatever I want -- Fallacy # 14, don't force your ethics down my throat! -- Fallacy # 15, you just admitted that there is a lot of divergence of opinon as to how we should act : therefore, there can be no universally binding law to govern us -- Fallacy # 16, I know he shouldn't do that, but he's a good guy -- Fallacy # 17, if it feels good, do it -- Fallacy # 18, ...yeah, but it's my right! -- Fallacy # 19, I vas just followink orders -- Fallacy # 20, ethics are a personal matter, so what I do is my own business! -- Fallacy # 21, it doesn't matter if two consenting adults are married or not, what counts is their sincerity -- Fallacy # 22, the traditional family structure is arbitrary : actually there are many other valid expressions of this same reality -- Fallacy # 23, I learned at my university that monogamy is an out-dated social structure imposed on us by a Judeo-Christian culture! -- Fallacy # 24, no one's going to tell me how many children I going to have! -- Fallacy # 25, I can do whatever makes me happy!

In many base rate studies, a judgment is required for which the base rates are relevant, and subjects do not use them. It is inferred that the base rates are ignored; I question this inference. Second, I argue that the base rate fallacy is not less significant for what it reveals about human reasoning, if it occurs less frequently than has been alleged.

The conjunction fallacy occurs whenever probability compounds are thought of as more likely than its component probabilities alone. In the experiment we present, subjects chose between simple and compound lotteries after some practice. Depending on the condition, they were given more or less information about the nature of probability compounds. The conjunction fallacy was surprisingly robust. There was, however, a puzzling dissociation between verbal and behavioral learning: verbal responses were sensitive, but actual choices entirely insensitive, to the amount of verbal instructions being provided. This might reflect a dichotomy between implicit and explicit learning. Caution must be exercised in generalizing results from what people say to what people do.

This book also spotlights a program at Yale University that, in response to the dearth of play in preschool curricula, emphasized learning through play for ...

discussions of risk contain logical and argumentative fallacies that are specific to the subject-matter. Ten such fallacies are identified, that can commonly be found in public debates on risk. They are named as follows: the sheer size fallacy, the converse sheer size fallacy, the fallacy of naturalness, the ostrich's fallacy, the proof-seeking fallacy, the delay fallacy, the technocratic fallacy, the consensus fallacy, the fallacy of pricing, and the infallability fallacy.