bookmark_borderReally Religious Violence

A splinter group of the Pakistani Taliban targeted a crowd of Christian children celebrating Easter:
http://www.cnn.com/2016/03/27/asia/pakistan-lahore-deadly-blast/
In the comments section of my last post on religious violence we had a lively discussion about the causes of religious violence and to what extent they were genuinely religiously motivated. Such attacks as this one (which, alas, are not rare) plainly show the religious motivation of the hatred. The perpetrators promise more such attacks.
Politics, they say, makes strange bedfellows. We have an instance of that in the debate over religious violence. Two groups normally at opposite ends of the spectrum come together to deny that religious violence is really religiously motivated. On the one side you have conservative religious apologists who want to claim that religion, or at least theirs, is innocent of  inciting violence. I saw a title with Regnery Press–the ideological right’s publishing house–that said that Christianity is a religion of peace but not Islam. No doubt there are Muslim apologists who say the opposite.
The other group eager to deny the religious basis of violence is the politically correct left, the Ben Affleck types, for whom avoiding any taint of Islamophobia is the categorical imperative. They fear that any hint that Islamic terrorists are motivated by their interpretation of Islam verges on a blanket condemnation of the religion of 1.6 billion people. Publications of the ideological left insist that the violence has political and socio-economic causes and that Islam has nothing to do with it.
“Islam is a religion of peace” we are told over and over. Well, it seems to depend on whose Islam we are talking about. In Glasgow, Scotland a beloved Muslim shopkeeper, a member of the Ahmadi movement that teaches nonviolence and tolerance for other faiths, was apparently murdered for wishing his Christian neighbors a happy Easter:
http://www.dailymail.co.uk/news/article-3509367/Muslim-shopkeeper-stabbed-death-hours-posted-happy-Easter-message.html
Apparently, some Muslims believe that you should express benevolence to your neighbors of other faiths, and some Muslims believe you should be killed for doing so. Which is the “true” Islam? I would very much like to think that it is the former, and my Muslim friends and colleagues, who are as horrified as I by such events, would strongly assert that it is. But the horrible truth remains that some are willing to massacre a playground full of children to assert that it is the latter.
The fundamental and simple truth that seems to escape ideologues of both the left and the right is this: Good religion can do great good but bad religion can do great harm. Further, every major religious tradition encompasses elements that teach kindness, love and tolerance, and other elements that inculcate violence, vindictiveness, and intolerance. No amount of special pleading by religious apologists or self-righteous hand-wringing by pundits of the left can change this basic fact.

bookmark_borderAquinas’ Argument for the Existence of God – Part 4

NOTE: I began to reconstruct Aquinas’ argument for the existence of God in the post I Don’t Care – Part 4, and continued that effort in  I Don’t Care – Part 5, and I Don’t Care – Part 6.   I am changing the title of this series to better reflect the content, so I consider the previous posts numbered as Parts 4, 5, and 6 to constitute Parts 1, 2, and 3 (respectively) of this new series called “Aquinas’ Argument for the Existence of God”.  That is why I’m calling this post “Part 4”.
The first “half” of Aquinas’ argument for the existence of God can be summarized like this:
(MC2)–>(MC6)–>(MC9)
Here are the key metaphysical claims from that first part of his argument:
(MC2) There exists an FEC being.   (FEC = First Efficient Cause)
(MC6) There exists an IES being.    (IES =  ipsum esse subsistens)
(MC9) There exists an IES being that is in the highest degree of immateriality and that has perfect knowledge. 
There are arguments for each of these claims, and there are intermediate steps between each of these claims, so the actual argument is more complex and involves several other claims, including several other metaphysical claims.  Click on the diagram below for a clearer image of a more detailed summary of this first “half” of Aquinas’ argument for God:
Flow of Reasoning from MC2 to MC9
 
For more details on this first part of Aquinas’ argument, see the previous post in this series.
 
The second “half” of Aquinas’s argument can be summarized like this:
(MC9)–>(MC22)
(MC9)–>(MC23)
(MC9)–>(MC28)
Metaphysical claim (MC22) asserts there is an IES being who is omniscient (i.e. who knows all things by proper knowledge – See Summa Theologica PI, Q14, A6).
Metaphysical claim (MC23) asserts there is an IES being who is perfectly just (i.e. who always acts justly – See Summa Theologica PI, Q21, A1).
Metaphysical claim (MC28) asserts there is an IES being who is perfectly loving (i.e. who loves all things and who always loves the better things more – see Summa Theologica PI, Q20, A4).
There is a final step (or phase?) that goes from the conjunction of (MC22), (MC23), and (MC28) to the conclusion that God exists.
This final step requires that Aquinas either prove that there can be only one IES being, or else that there can be only one IES being that has these three properties.  Also, Aquinas needs to show that other divine attributes belong to this being (i.e. omnipotence, bodilessness, and eternality).  But for now, I have mapped out the flow of Aquinas’ reasoning from (MC9) to the conclusion that God exists, with focus on (MC22), (MC23), and (MC28):
Flow of Reasoning from MC9 to God
 
 
 
Click on this image to get a clearer view of the diagram.
 
I have now completed a high-level flow of some important parts of Aquinas’ argument for the existence of God.  I have skipped over many details of his specific arguments for each of the many metaphysical claims referenced in the above diagrams, and I have not yet attempted to determine the reasoning for other parts of the argument (concerning the divine attributes of being creator of the universe, a bodiless person, omnipotence, and eternality).  I have also not yet attempted to figure out how Aquinas argues that there is only one being that possesses all of these various divine attributes, so the above diagrams leave out important and essential parts of Aquinas’ argument for the existence of God.
Note that the very first metaphysical claim (MC2) is the ONLY claim (out of the many metaphysical claims referenced in the above diagrams) that Aquinas argues for in the famous “Five Ways” passage.
It should be plainly obvious at this point that the “Five Ways” passage represents only the very beginning of a long and complex argument for the existence of God, and therefore the traditional view that Aquinas presents five arguments for the existence of God in the “Five Ways” passage is utterly and completely wrong, and is utterly and completely STUPID.
Aquinas does NOT give five arguments for the existence of God in just a couple of pages; rather, Aquinas gives ONE argument for the existence of God that takes up over one hundred pages of Summa Theologica (the material included in my diagrams starts near the beginning of Summa Theologica and goes up to Question 21, Article 1, which in my copy is on page 125), and that involves literally dozens of inferences and sub-arguments.
Here are the metaphysical claims referenced in the above diagram of the flow of reasoning from (MC9) to the conclusion that “God exists”:
(MC18) There is an IES being that has a will.   (see Q19, A1)
(MC19) There is an IES being that understands itself.  (see Q14, A2)
(MC20) There is an IES being who perfectly comprehends itself.   (see Q14, A3)
(MC21) There is an IES being who knows all things.   (see Q14, A5)
(MC22) There is an IES being who knows all things by proper knowledge.  (see Q14, A6).
(MC23) There is an IES being who always acts justly.    (see Q21, A1).
(MC24) There is an IES being in which love exists.    (see Q20, A1)
(MC25) There is an IES being with a will that is the cause of things.  (see Q19, A4)
(MC26)  There is an IES being that loves all things.   (see Q20, A2)
(MC27) There is an IES being that loves all things, but loves some things more than others.   (see Q20, A3)
(MC28) There is an IES being who loves all things and who always loves the better things more.  (see Q20, A4).

bookmark_borderHope for a Brighter Future

A recent studv (based on surveys conducted between 1972 and 2014 that produced responses from over 58,000 Americans) shows that belief in God has declined significantly in recent decades.
===============
The findings show that from the early 1980s to 2014:
• Those who identified their religion as “none” increased from 7 percent to 21 percent.
• Those who never attend religious services doubled to 26 percent.
• Those who say they never pray rose from 3 to 15 percent.
• Those who say they don’t believe in God rose from 13 to 22 percent.

bookmark_borderHow to Think about Historical Evidence about Anything, Part 1: The Credibility of Testimony

Note: So far as I know, no one working in New Testament scholarship, apologetics, counter-apologetics, or ancient history is applying the concepts in this blog post. As will soon become obvious, most of the ideas in this blog post are not mine, but if other people find these techniques useful, I would appreciate being given credit for the idea to apply them outside of their source discipline.

1. Schumian Framework for Decomposition of the Credibility of Testimony

Suppose witness W testifies E* that event E occurred. We wish to determine whether E actually happened. Clearly, E* and E are not identical; we could have E* when E did not happen. E* would entail E only if W were perfectly credible; otherwise, E* is evidence of E to the degree that we consider W credible.[1] Following evidence scholar David Schum,[2] I shall analyze the credibility of testimony in terms of three major attributes: veracity, objectivity, and observational sensitivity.  These attributes can be assessed by asking three questions respectively:
(a) Does W believe what he testified? This question focuses on W’s veracity or truthfulness.  If it is doubtful that W even believed what he testified, then W is not truthful and E* does not probabilistically favor E.  On the other hand, even if W believes what he testified, it does not follow that E is true. W could be entirely honest in reporting E, but E might not have happened. This would be the case if W were unobjective or inaccurate.[3]
(b) Did W’s senses give evidence of what he believed? If not, we would say that W is not objective. This would be the case if, for example, W so strongly wished E to occur that he believed E regardless of what his senses told him.[4]
(c) Was the sensory evidence accurate? Even if W believed what he testified and W’s senses gave evidence of what he believes, it could still be the case that what W believes is false. In other words, sensory evidence is not conclusive unless we believe that W is perfectly observationally sensitive. Both W’s physical condition and the general circumstances of observation at the time of observation might have caused the sensory evidence to be inaccurate.[5]
Since there are three credibility attributes and each attribute has two possible values, it follows that there are 23=8 combinations of potential values.
1: W is honest, objective, and observationally accurate.
2: W is honest, objective, and not observationally accurate.
3: W is honest, not objective, and observationally accurate.
4: W is honest, not objective, and not observationally accurate.
5: W is not honest, objective, and observationally accurate.
6: W is not honest, objective, and not observationally accurate.
7: W is not honest, not objective, and observationally accurate.
8: W is not honest, not objective, and not observationally accurate.[6]
The decomposition of the credibility attributes of W’s testimony is illustrated in Figure 1.[7] From W’s testimony (E*) we first draw an inference about his veracity. If we conclude that W did believe what he testified (Eb), we next consider his objectivity. Again, if we conclude that W is objective (Es), we then assess his observational sensitivity. If we then conclude that his sensory evidence was accurate, we then infer that E did occur.  Each inference based upon a credibility attribute is an example of an inferential link or stage of reasoning in a chain of reasoning.
schumian-figure1

Figure 1 Stages of reasoning involving attributes of W’s credibility

As Schum correctly observes, each inferential link in a chain of reasoning must ultimately be justified on the basis of an inductive argument.[8] Typically, such justification appeals to a statistical generalization. For example, the inference from E* to Eb might appeal to the following statistical generalization concerning W’s veracity: “If an ancient author writes that an event occurred, then at the time the document was written the author probably believed that E occurred.” In support of W’s objectivity, one might argue: “If at the time of his alleged observation a person believed that an event occurred, then this person’s senses often give evidence that the event occurred.” In support of W’s observational sensitivity, one could claim: “If a person’s senses give evidence that an event occurred, then usually the event occurred.”[9]
Clearly, not just any statistical generalization can justify an inferential link in a chain of reasoning regarding the credibility a witness’s testimony. Those who have studied the formal structures of inductive arguments know that statistical generalizations are just one premise in the type of inductive argument known as the statistical syllogism.

Z percent of F are G.

x is F.

[Z% probable] Therefore, x is G.

But the Rule of Total Evidence requires that we must take into account the total relevant and available evidence when selecting F (the reference class). This makes it difficult, however, to apply statistical generalizations to unique or singular events. And W has offered a specific account (E*) about a singular event.[10] Any reference class that satisfies the Rule of Total Evidence will be so specific that there will be no frequency data available to justify the generalization.
Drawing upon the work of philosopher L.J. Cohen,[11] Schum describes a method for testing statistical generalizations about singular events that is roughly based upon eliminative induction.[12] In his words:

What we can do is to put this generalization to a variety of different relevant evidential tests, each one designed to invalidate this generalization as far as W and his present testimony are concerned. … The more of these tests that W passes, the more we are entitled to infer that this … generalization holds in the present instance of W and his testimony E*. … A generalization is supported to the extent that this generalization survives our best attempts to show that it is invalid in the particular instance of concern.[13]

The results obtained from this testing constitute ancillary evidence (i.e., “evidence about evidence”) regarding the strength or weakness of the statistical generalization’s relevance to the link in question. If ancillary evidence is not provided in support of a statistical generalization, then the generalization is unsupported and may or may not be applicable to the inferential link.[14] In other words, the generalization that would justify the inferential link was “never put to the test.”[15] Therefore, any probabilistic inference made upon the basis of an unsupported generalization is weak.
Schum deduces, “a chain of reasoning cannot be any stronger than its weakest link.”[16]  It is an immediate consequence of this Schumian framework for witness credibility that the overall degree of credibility for a given piece of testimony (E*) is only as great as the weakest credibility attribute, regardless of how strong the other attributes may be. Accordingly, in order for E* to be credible, there must not be reasonable doubts about W’s veracity, objectivity, or observational sensitivity.

2. Nth Hand Evidence

For any piece of testimony (E*), a witness (W) may have obtained his or her information in one of three ways. First, the witness may have made a direct observation of the event she reports. Second, the witness may have received this information from another source, which I shall call nth hand evidence. I use the term “nth hand” to accommodate situations in which there are multiple sources in the chain. Third, the witness may have inferred the information, based upon information about other events.[17]
Let a source be a person or device who/that allegedly testified to the occurrence or nonoccurrence of some event of interest. A source is a primary source if it allegedly recorded the occurrence or nonoccurrence of that event. An immediate source is the source who/that informed you about this event. If an immediate source is not also a primary source, then the immediate source is either secondhand or nth hand evidence. Evidence is secondhand if there are no intermediate sources between the primary source and the immediate source. If there are intermediate sources, then the immediate source is nth hand evidence.[18]
Figure 2 depicts the chain of reasoning involved in a relatively simple appeal to secondhand evidence. In this example, we have a report (E*2,1) from an immediate source (S2) that a primary source (S1) reported (E*1) the occurrence of event E, which probabilistically favors hypothesis H.[19]
schumian-figure2

Figure 2 Secondhand Evidence

Thus, in order to determine the force of evidence E*2,1 upon hypothesis H in Figure 2, we must assess the credibility of two sources—immediate source S2 and primary source S1. If these two sources are people, we must consider the veracity, objectivity, and observational sensitivity of each witness. Figured 3 illustrates the stages of reasoning, when the credibility of each witness’s testimony is decomposed into those three credibility attributes.

{E, ¬E} S1’s Observational Sensitivity
{Es,1, ¬Es,1} S1’s Objectivity
{Eb,1, ¬Eb,1} S1’s Veracity
{E*1, ¬E*1} S2’s Observational Sensitivity
{Es,2, ¬Es,2} S2’s Objectivity
{Eb,2, ¬Eb,2} S2’s Veracity
E*2,1

Figure 3 Decomposed Credibility Attributes of Secondhand Evidence

It is an immediate consequence of this decomposition and the results of section 1 that the overall degree of credibility for a given piece of secondhand testimony (E*2,1) is only as great as the weakest credibility attribute of either witness (S1 or S2).
Moreover, due to the (alleged) dependence of our immediate source’s (S2’s)  testimony upon the primary source’s (S1’s) testimony, there is an interesting feature of the negations in the partitions for each of the credibility-related attributes. For example, the negation ¬Eb,2 means “Source S2 does not believe that event E happened (as allegedly reported by S1).”[20] Due to S2’s purported dependence upon S1, however, ¬Eb,2 can have two interpretations. First, ¬Eb,2 could mean that S2 believes E did not occur. Second, it could also mean that S2 has no belief about event E, which could be the case if S2 invented a story about S1 telling him that event E occurred.  In order to account for this possibility, then, ¬Es,2 includes the possibility that S2’s senses gave no evidence about what S1 said, ¬E*1 includes the possibility that S1 said nothing to S2; ¬Eb,1 includes the possibility that S1 has no belief about event E; and ¬Es,1 could mean that S1 made no sensory observations of event E. As Schum writes, “If we have to rely entirely upon S2, we have to consider the possibility that S1 said nothing at all about event E to S2 and perhaps never even made a relevant observation.”[21]
We are now in a position to fully appreciate the full significance of the fact that the overall degree of credibility for a given piece of secondhand testimony (E*2,1) is only as great as the weakest credibility attribute of either witness (S1 or S2). The strength of secondhand evidence, unlike that of firsthand evidence, may depend upon a witness whose credibility is unknown. (Indeed, in cases of ancient secondhand evidence, it is not uncommon for hearsay testimony to involve a putative primary witness whose very existence is otherwise unknown!) As Schum writes, “Absent evidence about the veracity, objectivity, and observational sensitivity of all sources in a chain of hearsay, we could hardly form any settled judgment of the inferential force of this species of evidence.”[22]  Any inference based upon such hearsay could not be regarded as a strong inductive argument, viz., such hearsay would not make E more probable than not. In plain English, such hearsay is worthless as evidence for E.
This same observation also applies to information for which we cannot identify a primary or intermediate source, which Schum labels rumor or gossip.[23] If information has come to us through a chain of sources and we cannot identify the primary source, then we do not know where or how they obtained this information.[24] In other words, we have information with an unknown primary source and therefore unknown credibility. Therefore, any inductive or probabilistic inferences based upon rumor or gossip must be regarded as weak.

3. Nth Hand Evidence and Observed vs. Inferred Sources

Although Wigmorean methods are appropriate for analyzing historical evidence, most discussions of these methods focus on how to apply them in legal contexts.  Thus, for example, when describing secondhand evidence, Schum provides the example of testimony (E*2,1) from an immediate source (S2) that a primary source (S1) reported (E*1) the occurrence of event E, which probabilistically favors hypothesis H.[25] While such an example is surely representative of hearsay testimony in modern courtrooms, it is not representative of nth hand evidence in the writings of ancient historians. As contemporary historian Michael Grant writes:

We nowadays like our historiography to be supported by documents. This did not function in the ancient world, for two reasons. First, the documents and archives, whether public or private, were hopelessly inadequate and without meaning, even if relatively numerous (and in some cases of early date). Second, the Greek and Roman historians did not care very much about these documents and rarely quoted or even paraphrased them.[26]

Nevertheless, there are other sources of evidence for the existence of a primary source besides an explicit reference from the immediate source; there are ways in which we may sometimes confidently detect the existence of a prior source, even if our immediate source fails to mention it. For example, it may be possible to infer the existence of a prior source based upon such factors as the proximity of the immediate source to the event(s) described or textual clues (grammar, vocabulary, etc.).
Since I have been unable to locate any discussion of an inferred prior source in the writings of the new evidence scholars, I shall attempt to advance the discussion by formulating the concept and its implications for the credibility of evidence.
Let us distinguish implicit and explicit forms of nth hand evidence. An immediate source is explicit nth hand evidence if it makes explicit reference to a prior source. For example, suppose we have a report (E*2,1) from an immediate source (S2) that a primary source (S1) reported (E*1) the occurrence of event E. S1 is an observed source because it was explicitly mentioned by an immediate source (S2).
Not all primary sources are explicitly mentioned by the immediate sources that use them, however. As we’ve seen, ancient writers often failed to satisfy modern expectations concerning the identification of the sources of their information. Let us define, therefore, implicit nth hand evidence as an immediate source that is based upon, but does not explicitly mention, a prior source. Thus, we may have a report (E*2,1) from an immediate source (S2) that is based upon, but does not explicitly mention, a primary source (S1) that reported (E*1), the occurrence of event E. S1 is an inferred source because it was not explicitly referenced by an (extant) immediate source.
By the very nature of the case, the credibility of an inferred source may often be unknown. This may be because the information is gossip (and hence the identity of the primary source is unknown) or, even if the identity of the source is inferred, nothing else is known about the identity of the source and hence the credibility of the inferred source is also unknown. If the credibility of the inferred source is unknown, then any inductive inferences based upon the inferred source must be regarded as weak.
Notes
[1] Joseph B. Kadane and David A. Schum, A Probabilistic Analysis of the Sacco and Vanzetti Evidence, (New York: Wiley, 1996), 46, 53.
[2] David A. Schum, The Evidential Foundations of Probabilistic Reasoning (New York: Wiley, 1992), 105.
[3] Schum 1992, 102.
[4] Schum 1992, 102.
[5] Schum 1992, 103-104.
[6] Schum 1992, 229.
[7] Cf. Kadane and Schum 1996, 56.
[8] Schum states that inferential links must always be justified on the basis of a statistical syllogism (in his words, “inductive generalizations”). While Schum is undoubtedly correct that links in a chain of reasoning are in practice usually justified by generalizations, especially in law, I see no reason to believe that inferential links must always be justified in this way. It seems at least possible that an inferential link in a chain of reasoning could also be justified by an explanatory argument.  See Kadane and Schum 1996, pp. 45-46, 51.
[9] Cf. Kadane and Schum 1996, 51.
[10] Schum 1992, 251.
[11] Especially his The Probable and the Provable (Clarendon: Oxford, 1977).
[12] Schum 1992, 243-251.
[13] Schum 1992, 249-251.
[14] Kadane and Schum 1996, 87, 152.
[15] Kadane and Schum 1996, 152.
[16] Schum 1992, 302.
[17] Schum 1992, 94-95.
[18] Schum 1992, 344.
[19] Schum 1992, 346-347.
[20] Schum 1992, 348.
[21] Schum 1992, 349.
[22] Schum 1992, 350.
[23] Schum 1996, 113.
[24] Cf. Kadane and Schum 1996, 113.
[25] Schum 1992, 346-347.
[26] Michael Grant, Greek and Roman Historians: Information and Misinformation (New York: Routledge, 1995), 34.

bookmark_borderReligious Violence: The Question that Will not go Away

Every time there is yet another terrorist attack by jihadists, you can count on some immediate responses: The media will devote obsessive attention, national leaders will condemn and decry, bigots will blame the innocent, and presidential candidates (some of whom are bigots) will issue calls to “get tough.” And scores of liberal pundits and academics will ascend soapboxes to reassure us that Islam is not the cause of these horrific events. Any suggestion that those who kill while shouting “Allahu akbar!” might, to some extent, have been motivated by religion will be met with outrage, scorn, and cries of “Islamophobe!” (Actually, some years ago John Leo noted that shouting things like “racist!”, “sexist!”, and “Islamophobe!” is just how some people say “Gee, I have to disagree with you on that.”)
The standard narrative is that “Islamic” terrorism has nothing to do with Islam, but is rather caused by politics and socioeconomic conditions. I heard a commentator on NPR earlier today saying that Muslim youth in cities like Brussels are ghettoized and face high unemployment and feel a strong sense of marginalization and powerlessness. These conditions make them ripe for recruitment by jihadists, who, as one commentator put it, promise them instant transformation from “zero” to “hero.” Also, the West, and the U.S. in particular, are blamed for provoking terrorism. That is, terrorism is seen as a twisted but understandable response to the West’s wars in Islamic countries, its steadfast and apparently unconditional support of Israel, its support for authoritarian regimes (Saudi Arabia and Bahrain), and its cruelty against Muslims (Abu Ghraib, Guantanamo, and the killing of innocent civilians in bombings and drone strikes).
There is no doubt considerable truth in these claims and accusations. It has often struck me, from the Bay of Pigs, to the Tonkin Gulf, to the War of Cheney’s Choice (Gulf War II), how often the U.S. has displayed almost a talent for stupidity in its foreign interventions. Nevertheless, the claim that “religious” violence has nothing to do with religion is simply wrong. The claim that religion is not the cause has been defended at length by scholars of impeccable reputation. For instance, Karen Armstrong, of whose A History of God I am a great admirer, has argued this thesis in her new book Fields of Blood (Anchor, 2015). When so noted a scholar claims something that is so obviously wrong, it is hard to know whether to accuse her of ignorance or disingenuousness since neither would seem to be an appropriate charge.
When explaining human behavior it must be taken as axiomatic that humans are complex and that what they do is complexly caused. If human behavior had simple causes then many persistent social problems could have been eliminated long ago. Another complicating factor is that it is impossible, even conceptually, to define just where religion leaves off and other factors, such as political or economic ones begin. For many Muslims, for instance, the secular West’s idea of a separation of religion from politics would seem wrongheaded if not incoherent (To be fair, many American evangelicals see church/state separation as a dangerous myth.). All we can really say is that the witch’s brew of resentments, obsessions, rationalizations, hatreds, fears, and hopes that motivate the terrorist contain elements or aspects that we can, for practical purposes, designate as “religious,” “political,” “economic,” or “cultural.”
Though causes are complex, simple questions can sometimes promote clarity. The simple question I would ask Armstrong or other defenders of the thesis that “religious” violence is not religious is this: “Can religion do good?” If the answer is “no,” we must conclude that the respondent holds that religion has no influence, for good or ill, upon human life. This seems absurd, and it is hard to see what could motivate such an answer except maybe an old fashioned Marxist insistence on economic causes as the only real ones. If the answer is “yes,” then we have to ask whether religion always does good or only some of the time. The answer that religion always does good and never fails to do good also seems to be absurd and dogmatic. So, we seem to be left with the conclusion that religion sometimes does good and sometimes does not.
When religion fails to do good, does it, in fact, sometimes do positive harm? What kind of harm could religion do? Armstrong and others point to human nature, and it is true that religion did not invent hatred and cruelty; these have mysterious origins in the human heart. However, though religion did not invent hatred and cruelty, it can do a great deal to promote them. Religion, by definition, deals with ultimate things, matters of “ultimate concern” as theologian Paul Tillich put it. Religion therefore uniquely has the power to elevate a concern to the highest level, to make an issue more than mundane and affix a transcendent significance to it. Religion can take an ordinary, everyday hatred and make it a holy cause. Your hatred of “those people” is no longer idiosyncratic or local; God hates them too. With God on your side you can hate with a clear conscience. In fact, hating those whom God hates is a sacred duty, a supreme virtue; indeed, you come to see your acts of hate as acts of love. Christian philosopher Blaise Pascal observed that “Men never do evil so completely and cheerfully as when they do it with religious conviction.”  To this there is nothing to add but “amen.”

bookmark_borderWhy Nobody Should Believe that Jesus Rose from the Dead

First of all, extradordinary claims require extraordinary evidence, but there is only weak evidence that Jesus rose from the dead:

    1. The evidence that Jesus was crucified in Jerusalem and died on the cross on the same day he was crucified is weak.
    2. The evidence that Jesus was alive and walking around in Jerusalem less than 48 hours after he was crucified is weak.
    3. IF the evidence that Jesus was crucified in Jerusalem and died on the cross on the same day he was crucified is weak and the evidence that Jesus was alive and walking around in Jerusalem less than 48 hours after he was crucified is weak, THEN the evidence that Jesus rose from the dead is weak.
    4. IF the evidence that Jesus rose from the dead is weak, THEN it is unreasonable to believe that Jesus rose from the dead.

THEREFORE:

5. It is unreasonable to believe that Jesus rose from the dead.

Nobody should believe that Jesus rose from the dead, because there is insufficient evidence for the claim that Jesus rose from the dead.
The problem with the claim that “Jesus rose from the dead” is not just that the evidence for this claim is weak.  There is also good reason to believe that Jesus did NOT rise from the dead: Jesus was a false prophet.

  1.  Jesus was a false prophet.
  2. IF Jesus was a false prophet and God exists, THEN God exists and God would not have raised Jesus from the dead nor allowed some other being to raise Jesus from the dead.
  3. IF Jesus was a false prophet and God does not exist, THEN God does not exist and we don’t know of any existing person who could have raised Jesus from the dead.
  4. EITHER God exists OR God does not exist.
  5. IF God exists and God would not have raised Jesus from the dead nor allowed some other being to raise Jesus from the dead, THEN Jesus did not rise from the dead.
  6. IF God does not exist and we don’t know of any existing person who could have raised Jesus from the dead, THEN Jesus is not the incarnation of God and it is unlikely that Jesus rose from the dead.

THEREFORE:

7. EITHER Jesus did not rise from the dead OR Jesus is not the incarnation of God and it is unlikely that Jesus rose from the dead.

If somebody claimed that “God raised Hitler from the dead” we would have good reason to disbelieve this claim, because God, if God exists, would not raise such an evil person from the dead.   The fact that Hitler was evil and insane did not stop people from following Hitler as if he was a prophet from God.  So, raising Hitler from the dead would have  just confirmed the already widespread delusion that Hitler was a leader who ought to be followed and obeyed.  God would not raise Hitler from the dead, because Hitler was evil and because doing so would have involved God in a great deception.
Jesus was not evil or insane like Hitler, but Jesus promoted worship of, and obedience to, a person who was very much like Hitler, and thus Jesus was a false prophet.  Jesus promoted worship and obedience to the deity known as Jehovah (or Yahweh), and Jehovah was as evil and as insane as Hitler.  Thus, God (if God exists) would never have raised Jesus from the dead nor allowed some other being to raise Jesus from the dead, because that would involve God in a great deception. God being perfectly good and perfectly just would not be involved in encouraging people to accept the view of a false prophet that they ought to worship and obey the evil deity named Jehovah (or Yahweh).
It is clear that Jesus was a false prophet, because Jesus encouraged his followers to worship and to obey Jehovah, and Jehovah was an evil person.  It is clear that God, if God exists, would never raise such a false prophet from the dead, nor would God allow some other person to raise such a false prophet from the dead.  Therefore, we can be confident that EITHER Jesus did not rise from the dead, OR Jesus was not the incarnation of God and it is unlikely that Jesus rose from the dead.

bookmark_borderTexas AG Hires Anti-Gay and anti-Church/State Separation Activist

Texas Attorney General (and indicted securities fraud suspect) Ken Paxton has hired fundamentalist activist Jeff Mateer as his top assistant:
http://www.houstonchronicle.com/150years/article/Paxton-hire-draws-ire-for-fighting-gay-marriage-6925133.php
In Texas it is just business as usual to hire zealots and ideologues and put them in positions where they are supposed to be working for the people, all the people (an not just the ones, like Betty Bowers, who are so close to Jesus that they share a bank account). Nothing surprising here in a state where the State Board of Education has promoted “intelligent design” over science and David Barton’s preposterous fantasies over historical scholarship.
The most interesting bit of the article is where Mateer challenged students to cite verbatim the part of the U.S. Constitution that establishes separation of church and state. He offered a $100 prize to the one who could. Let me try: “Congress shall make no law respecting an establishment of religion, or prohibiting the free exercise thereof…” I just checked to see if I got it right, and I did. Do I get my $100 now?
“Respecting” is the interesting word in this passage. In this context it means “concerning” or “relating to” or “in reference to.” In this context, therefore, the word is quite vague. I assume that the Founders chose their words carefully. If they had only meant to say that the U.S. would have no official, established religion or denomination, then that is what they would have said. Instead they intentionally left if vague. Why? Probably because they could see that the U.S. unfortunately contains individuals like Mr. Mateer–those of theocratic propensities who have no problem with using the prestige, power, or authority of government to promote sectarian ends. With people like Mateer, outlawing de jure establishment of religion will not stop them from establishing a de facto theocracy. Perhaps if Mr. Mateer and his ilk had their way we would not officially be called the Baptist States of America, but every government office would have the Ten Commandments and the Beatitudes; Bible readings and Christian indoctrination would occur in all public schools; all public property would have crosses all year and Christmas and Easter displays in season; creationism would be taught in science classes; LGBT people and Muslims would be second-class citizens; and Medicare, Medicaid, and Social Security would be replaced by “faith based” charities. The authors of the Constitution, in their wisdom, sought to prevent anything even respecting (i.e. concerning or relating to) an establishment of religion, whether de jure or de facto.

bookmark_borderWilliam Lane Craig’s Logic Lesson – Part 4

In the March Reasonable Faith Newsletter William Craig asserted this FALSE principle about valid deductive arguments that have premises that are probable:
… in a deductive argument the probability of the premises establishes only a minimum probability of the conclusion: even if the premises are only 51% probable, that doesn’t imply that the conclusion is only 51% probable. It implies that the conclusion is at least 51% probable.
There are a variety of natural tendencies that people have to reason poorly and illogically when it comes to reasoning about evidence and probability.  So, it is worth taking a little time to carefully review Craig’s mistake in order to LEARN from his mistake, and to understand how the logic really works in this case, so that we can avoid making the same mistake ourselves, and so that we can more readily notice and identify when others make similar mistakes in their reasoning.
One way that Craig’s principle can fail is because of the fact that a valid deductive argument can have multiple premises and because standard valid forms of deductive inferences/arguments require that ALL premises be true in order to work, in order to logically imply the conclusion.  In the case of a valid deductive argument with multiple premises that are probable rather than certain, it is usually the case that ALL of the premises must be true in order for the argument to logically imply the conclusion.
If the probable premises of such an argument are independent from each other (so that the truth or falsehood of one premise has no impact on the probability of the truth or falsehood of other premises in the argument), then the simple multiplication rule of probability applies, because what matters in this case is that the CONJUNCTION of all of the probable premises is true, and the probability of the conjunction of the premises of such an argument is equal to the product of the individual probabilities of each of the probable premises.  This means that the premises of a valid deductive argument can each have probabilities of .51 or greater while the conclusion has a probability of LESS THAN .51.  Examples of such arguments were given in Part 2 of this series of posts.
Another way that Craig’s principle can FAIL is based on situations where one or more premises of a valid deductive argument have dependencies with other premises in the argument.
Here is an example of a valid deductive argument with a premise that has a dependency on another premise :
1. I will get heads on the first random toss of this fair coin.
2. I will get tails on the first random toss of this fair coin. 
THEREFORE:
3. I will get heads on the first random toss of this fair coin, and I will get tails on the first random toss of this fair coin.
The probability of (1) is .5, and the probability of (2) is also .5 (considered on its own).  However, these two premises are mutually exclusive.  If (1) is true, then (2) must be false, and if (2) is true, then (1) must be false.  Thus, the conclusion (3) asserts a logical contradiction, and thus the probability that (3) is true is 0.   In the case of this argument, we cannot simply multiply the probability of (1) , considered by itself, times the probability of (2), considered by itself, in order to determine the probability of the CONJUNCTION of (1) and (2).
We have to multiply the probability of (1) times the probability of (2) GIVEN THAT (1) is the case.   Because the truth or falsehood of (1) impacts the probability of the truth or falsehood of (2), we cannot use the simple multiplication rule with this argument.  We must use the general multiplication rule:
The probability of the conjunction of A and B is equal to the product of the probability of A and the probability of B given that A is the case.
Here is the mathematical formula for the general multiplication rule of probability:
P(A & B) =  P(A) x P(B|A)
NOTE: The general multiplication rule can be used whether or not there is a dependency relationship between the premises of an argument.  If there is no dependency relationship between A and B, then the probability of B given that A is the case will be the SAME as the probability of B considered by itself.
Since the truth of (1) clearly excludes the possibility of the truth of (2), the probability of (2) GIVEN THAT (1) is the case is 0.  The probability of the conjunction of (1) and (2) is thus equal to:  .5   x  0  =  0.  So, the probability of the conclusion (3) is 0, even though the probability of (1) is .5.
This demonstrates how the probability of the conclusion of a valid deductive argument can be LESS THAN the probability of a premise in the argument (considered by itself).  The main reason why the probability of (3) is 0 is that there is a logical incompatability between premise (1) and premise (2) which rules out the possibility of it being the case that BOTH premises are true.  The truth or falsehood of (1) has an impact on the probability of the truth or falsehood of (2), so there is a dependency between the truth or falsehood of these premises.
Considered by itself, premise (2) has a probability of .5, but for the argument to work, both premises have to be true, and the probability of (2) can be impacted by whether (1) is true or false, so we need to assess the probablity of (2) on the assumption that (1) is true, and when we do so, the probability of (2) in that scenario is reduced from .5 down to 0.  Therefore, it is this dependency relationship between (2) and (1) that results in the conclusion having a probability that is extremely low, as low as probabilities can get: 0.
The same mathematical relationship holds when the probability of an individual probable premises is greater than .5:
4. I will not roll a six on the first random roll of this fair die.
5. I will roll a six on the first random roll of this fair die.
THEREFORE:
6. I will not roll a six on the first random roll of this fair die, and I will roll a six on the first random roll of this fair die.
The probability of (4) considered by itself is 5/6 or about .83, and the probability of (5) considered by itself is 1/6 or about .17.  However, these two premises are mutually exclusive. If (4) is true, then (5) must be false, and if (5) is true, then (4) must be false. Thus, the conclusion (6) asserts a logical contradiction, and thus the probability that (6) is true is 0. In the case of this argument, we cannot simply multiply the probability of (4) considered by itself, times the probability of (5) considered by itself, in order to determine the probability of the CONJUNCTION of (4) and (5).
Because there is a dependency relationship between (4) and (5), we must use the general multiplication rule to determine the probability of the conclusion.  The probability of the conjunction of (4) and (5) is equal to the product of the probability of (4) and the probability of (5) given that (4) is the case:
P[(4) & (5)] =  P[(4)]  x  P[(5)|(4)]
=  5/6  x   0 =  0
Thus, because of the dependency relationship between (4) and (5), the probability of the conclusion is reduced to 0, even though the probability of premise (4) considered by itself is 5/6 or about .83, which is GREATER THAN .51.  This argument is therefore another counterexample to Craig’s principle.  It is a valid deductive argument which has a probable premise with a probability GREATER THAN .51 but where the probability of the conclusion is LESS THAN .51.
The dependency relationship between premises need not be as strong as in the above examples. So long as the truth or falsehood of one premise impacts the probability of some other premise in the argument, Craig’s principle about valid deductive arguments can  FAIL.
Here is a counterexample against Craig’s principle that involves a dependency relationship that is weaker than in the above examples (something less than being mutually exclusive):
10. I will not select a heart card on the first randomly selected card from this standard deck.
11. I will not select a diamond card on the first randomly selected card from this standard deck.
THEREFORE:
12. I will not select a heart card on the first randomly selected card from this standard deck, and I will not select a diamond card on the first randomly selected card from this standard deck.
The probability of (10) considered by itself is .75, and the probability of (11) considered by itself is .75.  However, there are dependency relationships between these premises which make the conjunction of the premises less probable than if we simply multiplied these probabilities of each premise considered by itself.
If we ignored the dependency then the probability of the conjunction of the three premises would be calculated this way: .75  x  .75  = .5625 or about .56.  But to properly determine the probability of the conjunction of the three premises, we need to use the following equation (based on the general multiplication rule):
P[(10) & (11)] =  P[(10)]  x  P[(11)|(10)]  
=  3/4   x   2/3    =   6/12  =  1/2  =  .50
Thus, the probability of the conclusion of this argument is .50, which is LESS THAN .51.
The probability of premise (10) considered by itself is 3/4 or .75, and the probability of (11) is 3/4 considered by itself, which is GREATER THAN .51, and the probability of (11) given that (10) is the case is 2/3 or about .67, which is still GREATER THAN .51, but the probability of the conclusion of this argument is LESS THAN .51, so this argument is a counterexample to Craig’s principle, and part of the reason why the probability of the conclusion is so low is that there is a depenedency relationship between the premises.
Here is a final counterexample based (in part) on there being a dependency between premises:
14. I will not roll a six on the first random roll of this fair die.
15. I will not roll a five on the first random roll of this fair die. 
16. I will not roll a four on the first random roll of this fair die.
THEREFORE:
17. I will not roll a six on the first random roll of this fair die, and I will not roll a five on the first random roll of this fair die, and I will not roll a four on the first random roll of this fair die.
Each of the premises in this argument has a probability of 5/6 or about .83 when considered by itself.  If we ignored the dependency relationship between these premises, then we would calculate the probability of the conjunction of premises (14), (15), and (16) simply by multiplying these probabilities:  5/6  x  5/6  x  5/6   =  125/216   which approximately equals .5787 or about .58.  However, because there are dependencies between these premises, we must use the general multiplication rule.  Here is a formula for this argument that is based on the general multiplication rule:
P[(14) & (15) & (16)] =  
P[(14)]  x  P[(15)|(14)]  x  P[(16)|[(14) & (15)]]  
= 5/6  x  4/5  x  3/4  =   60/120  =  1/2  =  .50
Thus, the probability of the conclusion (17) is 1/2 or .50 which is LESS THAN .51.
So, the probability of each premise (considered by itself) is greater than .51, and the probability of premise (16) given that all the other premises are true is 3/4 or  .75, which is still greater than .51, but the probability of the conclusion (17) is LESS THAN .51, so Craig’s principle FAILS in this case, and thus Craig’s principle is shown to be FALSE.

bookmark_borderWilliam Lane Craig’s Logic Lesson – Part 3

I had planned to discuss counterexamples (to Craig’s principle) that were based on dependencies existing between the premises in some valid deductive arguments.  But I am putting that off for a later post, in order to present a brief analysis of some key concepts.
It seems to me that an important part of understanding the relationship between valid deductive arguments and probability is keeping in mind the distincition between necessary conditions and sufficient conditions. So, I’m going to do a brief analysis of this relationship.
SUFFICIENT CONDITIONS ESTABLISH A MINIMUM PROBABILITY
1. IF P, THEN Q.
Claim (1) asserts that P is a SUFFICIENT CONDITION for Q.
Assuming that (1) is true, the probability of P establishes a MINIMUM probability for Q.
If the probability of P was .60, then assuming that (1) is true, the minimum probability for Q would also be .60, because whenever P is true, so is Q.
However, (1) is compatible with Q being true even if P is false. There could be some OTHER reason for Q being true:
2. IF R, THEN Q.
If (2) is also true, and if R has some chance of being true even when P is false, then the probability of Q would be GREATER THAN the probability of P.  In this scenario the probability of Q would be GREATER THAN .60.
Suppose that the truth of R is independent of the truth of P. Suppose that the probability of R is .80. We can divide this scenario into two cases:
Case I. P is true.
Case II. It is not the case that P is true.
There is a probability of .60 that case I applies, and if it does apply, then Q is true. This gives us a minimum baseline probability of .60 for Q.
But we must add to this probability any additional probability for Q being true from case II.
There is a probability of .40 that case two applies, and if it does apply then there is a .80 probability that R is true (since the probability of R is not impacted by the truth or falsehood of P).  Since R implies Q, there is (in this second case) a probability of at least .80 that Q is true. So, we multiply the probability that case II applies times the probability of Q given that case II applies to get the (minimal) additional probability: .40 x .80 = .32.
To get the overall minimal probability of Q, we add the probability of Q from case I to the (minimal) probability of Q from case II: .60 + .32 = .92 or about .9.
NOTE: The actual probability of Q might be higher than .92, if there is some chance that Q was true even if both P and R were false.
NECESSARY CONDITIONS ESTABLISH A MAXIMUM PROBABILITY
3. IF Q, THEN P.
Claim (3) asserts that P is a NECESSARY CONDITION for Q.
Assuming that (3) is true, the probability of P establishes a MAXIMUM probability for Q.
If the probability of P is .60, then assuming that (3) is true, the maximum probability of Q would be .60, because whenever P is false, Q must also be false.
However, (3) is compatible with Q being false even when P is true. There could be some OTHER reason why Q is false:
4. IF Q, THEN S.
If (4) is also true, and if S has some chance of being false even when P is true, then the probability of Q would be LESS THAN the probability of P. In this scenario, the probability of Q would be LESS THAN .60.
Suppose that the truth of S is independent of the truth of P. Suppose that the probability of S is .20.  We can immediatly infer that the maximum probability of Q is .20, because the truth of S is a necessary condition for Q.  However, the combination of (3) and (4) reduces the maximum probability of Q even further.
We can divide this scenario into two cases:
Case I. P is true.
Case II. It is not the case that P is true.
Let’s consider case II first.  There is a probability of .40 that case II applies (because there is a probability of .60 that case I applies and the combined probabilities of both cases = 1.0), and if it does apply, then Q would be false (because P is a necessary condition of Q).  This establishes a baseline minimum probability of .40 for the falsehood of Q.
But we must add to this probability any additional probability for Q being false from case I.
There is a probability of .60 that case I applies, and if it does apply, then there is a .20 probability that S is true (because the probability of S is not impacted by the truth or falsehood of P), thus if case I applies, then there is a probability of .80 that S is false, and thus a minimum probability of .80 that Q is false (because S is a necessary condition of Q).  We meed to multiply the probability that case I applies times the (minimal) probability that Q is false given that case I applies:   .60 x .80 = .48.
Now we must add the probability of the falsehood of Q from case II with the (minimum) probability of the falsehood of Q from case I to get the overall minimum probablilty of the falsehood of Q:  .40 + .48 = .88.  The overall minimum probability of the falsehood of Q is .88, and this implies that the overall MAXIMUM probability of Q is .12.
NOTE: The actual probability of Q could be lower than the maximum probability, if there is some chance that Q was false even if both P and S were true.