Participants: Clifford Goldstein
Series Code: CFTF
Program Code: CFTF000006
|
00:20 Hi, Clifford Goldstein here your host
00:23 for Contending for the Faith and this is part of a series 00:27 I've been doing on faith and science. 00:31 And you know, speaking of science 00:33 I recently came across some fascinating studies 00:38 using the scientific method of correlation. 00:42 And they came to some fascinating conclusions. 00:46 Now remember I'm talking science here. 00:50 So we have to give this serious consideration. 00:53 I mean, if science could get us to the moon, 00:56 build nanotechnology and GPS systems 01:01 that we can carry in our pockets 01:03 then it's got to be on to something, right. 01:06 Well, of course science is on to something 01:08 I don't think there's any question about that. 01:11 Exactly what it's on to well, that's another matter 01:15 and that's what, what exactly is science on to 01:20 when it tells us things about the world. 01:23 Anyway there is a study showing 01:28 a close statistical correlation between the use of margarine 01:34 and the rates of divorce in a home. 01:37 I mean, there is a chart you can follow 01:40 which shows an amazing correlation between the two. 01:45 The use of margarine tracks the weight of divorce 01:50 with the 99% correlation. 01:54 I mean, incredible. 01:56 I mean, it shows up 01:57 when there was more margarine in home the divorce rates go up 02:02 and when there is less margarine 02:04 the divorce rates go down. 02:07 The correlation is astonishing. 02:11 But there is more. 02:13 Did you know that there is a power correlation 02:16 between the rising per capita consumption of cheese 02:22 to the number of people 02:24 who died by coming entangled in their bed sheets. 02:28 I mean, the correlation is there, 02:31 you can't deny the correlation. 02:34 They track each other 02:37 that is the rate of cheese consumption 02:40 and the rate of those who died by being tangled 02:43 in their bed sheets track each other very closely. 02:49 How could that be? 02:51 Who knows and you can earn it better 02:53 all you want but you can't deny 02:55 the reality of the correlation. 02:59 Or what about the amazing correlation 03:03 between the rising number of Facebook users 03:06 and the growing Greek death crises. 03:10 The Correlation is there. 03:13 Or what about the fact 03:14 that there is an incredibly close statistical correlation 03:18 between the number of people 03:20 who drown in swimming pools every year 03:24 and the number of movies that Nicolas Cage appear in. 03:28 I mean, if you were to chart a graph looking 03:31 at the correlation you would be astonished, 03:35 one follows the other as closely 03:37 as heat follows fire. 03:41 Now, of course come on here, 03:45 oh, this is a bit crazy. 03:46 I can't be serious. Can I? 03:49 Well, in one level of course not. 03:52 I got these powerful correlations 03:55 from a website called "Spurious Correlations." 04:00 And the name says it all. 04:02 It was some criminology student 04:04 in Harvard university created the site 04:08 but he was making a serious point. 04:11 He was making the serious point 04:13 that we have to be very careful 04:16 when we hear scientific pronouncements saying that 04:21 a link has been found between X and Y. 04:25 You can fill in the blanks for X and Y, 04:29 you would have a lot of options. 04:33 I mean, after all haven't we been study showing 04:37 that the rise in alcohol consumption 04:40 at least to a certain degree 04:42 leads to a decrease in heart attacks. 04:45 There's been some scientific studies making that claim 04:49 because there been some powerful correlations 04:52 between the two. 04:54 Of course, there had been other scientific studies 04:57 that have challenged that and I guess the question is, 05:01 which one is correct. 05:03 I mean, haven't we also been told for decades 05:07 that an increase in fat consumption 05:10 can lead to heart attacks. 05:12 I mean, the correlation was there, 05:14 no one's gonna deny it. 05:16 But you know, I recently saw a headline 05:19 in Time Magazine with new scientific studies 05:23 saying that that correlation was false. 05:26 The headline in Time Magazine, 05:30 June 12th, 2014 read, 05:33 "Ending the War on Fat" and the caption said, 05:40 "For decades, it has been the most 05:42 vilified nutrient in the American diet. 05:46 But new science reveals fat isn't 05:50 what's hurting our health." 05:52 Whoa. New science? 05:55 That means for decades all the old science was wrong. 05:59 Science wrong, all those powerful correlations 06:04 between fat and heart diseases 06:07 were apparently as misleading or maybe not 06:10 but to some degree is misleading 06:12 as the correlation between the number of movies 06:15 Nick Cage plays in and the number of people 06:18 who drown in swimming pools. 06:21 What about the correlation 06:23 between vaccinations and autism 06:25 or cancer and living near high power wires 06:29 or the correlation between women taking hormone therapy 06:33 and lower than average rates of heart diseases. 06:37 Or how about this correlation? 06:41 The faster windmills are observed to rotate, 06:46 the more wind is observed to be present. 06:49 So the correlation is there. 06:52 The faster moving windmills the more wind is there. 06:56 Thus contra-logically argue that 06:58 the windmills create the wind? 07:01 I mean, they are called windmills, right, 07:04 and you can't deny 07:05 the correlation either, can you? 07:08 Now of course, 07:10 everyone knows or should know 07:13 and that was-- which is the whole point 07:15 of spurious correlation the website 07:18 is that correlation is not causation. 07:22 The two events closely correlate 07:25 such as the drowning in swimming pool 07:27 and Nick Cage the movies Nick Cage starred 07:31 doesn't mean that one causes the other 07:33 or that even one has anything to do with the other. 07:37 Okay, it might and scientist and people 07:41 and every day do they look at correlation, 07:44 try to discover causes but that doesn't mean 07:48 the correlation is the cause. 07:51 And the million dollar question 07:54 of science is how do you determine 07:58 if correlation is or isn't a cause. 08:01 Sometimes it is, some times it isn't 08:05 but how do we know the difference? 08:08 Now the correlation is not causation, 08:11 argument can be a very powerful argument. 08:16 After all as we just saw the correlation 08:19 between margarine and divorce 08:21 and clearly one is not the cause of the other. 08:26 But you know, the tobacco industry 08:29 for decades for as long as it could get away 08:31 with argued against the causation. 08:34 It argued used the causation 08:37 is not correlation argument against the correlation 08:41 between smoking and the diseases 08:44 that are believed to be caused by smoking. 08:48 With this the marriage 08:50 the margarine divorce correlation 08:53 and yet we-- and yet scientist working 08:56 for big tobacco tried to disk 08:58 the cancer cigarette correlation as well. 09:02 I mean, after all George Burns smokes cigars 09:07 and George Burns lived to be 100 years old. 09:12 But anyway the point is correlation is not causation 09:17 except when it is causation. 09:20 And so the big question for science is, 09:22 how do we know? 09:24 How do we know that our theories match 09:26 and explain the facts on the ground? 09:28 How do we know that our understanding, 09:30 our explanations of causes are correct? 09:34 How does scientist know that their data 09:37 and that their interpretation of the data is right? 09:41 You know, I recently saw something on Twitter. 09:44 It showed a flood in Saudi Arabia. 09:49 A flood in Saudi Arabia, I mean, come on. 09:53 If that is it more proof of global warming what is? 09:58 I mean, if that doesn't clinch the argument 10:01 for global warming what does? 10:03 Talk about proof, the only problem, 10:06 the only problem the flood occurred 10:09 in Saudi Arabia in 1941 long before 10:14 we were supposedly destroying 10:16 the world with our carbon footprint. 10:18 Now here's the point here. 10:20 I don't want to get into this global warming 10:23 debate one way or the other. 10:25 Only I do find it very spurious, very silly 10:31 that every time there is an exceedingly hot day 10:34 or there is a new storm, 10:35 or there is some extreme in weather 10:38 we are sure by the people who know this more proof, 10:42 this is more evidence of global warming. 10:46 Now if you been-- maybe they are 10:48 maybe they aren't 10:50 but the fact proving things in science 10:53 is despite all of the hype to the contrary 10:56 a very problematic, very, very subjective exercise. 11:02 See, if you've been following this program, 11:05 if you've been following this series at all 11:07 you will see, you will have seen that 11:09 science is not this clear cut objective pursuit of truth 11:15 that it's often been portrayed as. 11:18 On the contrary almost from the time science 11:21 or what was called natural philosophy was practiced. 11:25 Questions has arisen about just what it does? 11:29 How it does, what it does? 11:31 And what does it tell us? 11:32 And how much of it can we really trust? 11:36 You know, as you know here we are, 11:38 we are in the 21st century 11:40 and we are living with many of the great 11:42 and sometimes not so great technological fruits of science 11:47 and the amazing thing is 11:50 these questions still remain unanswered. 11:55 There is nil, there is still no real consensus 11:58 about what true science is 12:01 or what the scientific method entails 12:03 or what science really does teach us about the world. 12:09 And I want to give you one important example 12:11 of the limitations of what science tells us. 12:15 A limitations that scientist have been 12:17 aware of for centuries that men like Francis Bacon 12:21 and Rene Descartes and Isaac Newton 12:24 these are men from hundreds of years ago 12:27 were aware of and to do 12:30 so I want to talk about something 12:31 that I talked about in an earlier lecture 12:34 but in an earlier program we're going to whip through it. 12:38 You know, I talked how I was raise 12:40 and educated on evolution. 12:43 Taught it my whole life, 12:45 then one day I became a born again believer in Jesus 12:49 and almost from the start I saw that 12:51 there was a contradiction between what I believed. 12:57 Well, somebody gave me some creation as literature 12:59 and as I said I didn't know 13:01 if the stuff was any good or not. 13:05 But what happened was this, 13:08 as I read it the scales came off my eyes 13:11 because as I said for the first time in my life 13:15 I was open to the idea 13:18 that there was an alternative explanation 13:21 to the facts in the ground. 13:23 As I said no one is going to deny 13:25 the dinosaur bones in the ground. 13:28 But for the first time-- I was 24 years old 13:31 and for the first time I was taught that 13:34 there was another option to explain them 13:37 other then the Darwinian one 13:39 that I had been imbued with, 13:41 that I had been propagandized with that. 13:43 I believe that I had been brain washed with 13:46 since I was a child, okay. 13:50 Now remember some argue that 13:51 science does tell us about the real world, 13:54 others argue that either that it can tell us 13:57 only what things do in the real world. 14:00 And if you have seen one of the earlier shows 14:03 some tell us it can all science can do is tell us 14:06 how the world appears to our senses, okay. 14:12 But the one thing 14:13 but with the idea that science-- 14:15 let's just go with the idea for a minute, 14:18 that science can tell us about the real world 14:22 and about why things happen in the real world. 14:25 The scientific project faces a great challenge. 14:30 It's been what has been called 14:32 the under determination of theories by evidence. 14:38 Now, let's think about this for a minute, 14:42 suppose I propose a scientific theory 14:47 and I claim that if my theory is correct 14:52 "Y" is going to turn red for such and such reasons. 14:58 Well, what do you know? 15:00 Y turns red just as my theory predicted 15:06 and even more impressively 15:08 suppose Y turns red 100% of the time. 15:16 Every time I do my predict-- every time I have my theory 15:20 and I do my experiment 15:22 and I say Y is going to turn red 15:24 because of blah, blah, blah, and Y turns red. 15:27 And that say I do my experiment at night, 15:30 I do it in hot weather, I do it in cold weather, 15:33 I do it in a submarine, I do it in an airplane. 15:37 Every time I do my experiment 15:41 Y turns red 100% of the time. 15:47 Well, then what can you conclude 15:50 other than that my theory is correct, 15:53 if predicted Y would turn red 15:56 and Y turned red every time too. 16:00 Thus what can you conclude 16:03 than other than that my theory is right? 16:07 Right? 16:09 Well, no, not necessarily, not necessarily at all. 16:16 In fact, white could turn red 16:18 for reasons that have nothing to do with my theory. 16:23 Other theories, other explanations 16:25 could make the exact predictions that mine did. 16:29 A completely different theory 16:32 with completely different promises, 16:34 completely different understanding of reality 16:38 and yet it comes up with the same thing 16:42 every time I do X, Y turns red. 16:48 In fact, you know, you often taught well, 16:50 your science makes a prediction, 16:51 he comes up with a theory, he makes a prediction, 16:53 the prediction turns out right, the theory is true. 16:56 This is what some people call the scientific method 17:01 but you know, some people argue 17:04 that correct predictions never ever prove a theory right. 17:10 All they show is that has yet to be falsified. 17:13 Remember if you saw on earlier show 17:16 I talked about the Ptolemy view of the universe. 17:19 This is the idea that the earth sits stationary. 17:24 The center of the universe 17:26 and the planets and the stars and everything circle there. 17:29 People believe that for a thousand years 17:31 and yet as I said on the show 17:33 you couldn't make accurate predictions. 17:36 You could predict what the stars were going to do, 17:39 you could sail your ships where you want to do and it worked. 17:43 But you know, we now know even though it worked, 17:47 even though it made accurate predictions 17:50 we now know the theory was wrong, completely wrong. 17:55 The foundations of it were completely off. 18:01 So this idea then that just because 18:04 you can make a prediction, 18:06 you build a theory and make predictions 18:09 and the predictions work is no guarantee 18:13 that the theory is successful, okay. 18:16 It might be right, you might be right 18:19 and we might have great reasons 18:21 other than the mere accuracy of the predictions 18:24 to believe that the theory is right. 18:27 But to believe that its right 18:29 just because of these predictions 18:31 is to make what's called a varied-- 18:33 to make a logical fallacy. 18:37 Let's do for a moment a tiny little bit of former logic. 18:41 Now just listen carefully, 18:43 listen carefully to what I'm going to say. 18:46 If we say that A is true then B must be true as well. 18:52 It doesn't matter what A and B are, 18:54 that's the point of former logic. 18:56 They are not interested in specifics. 18:58 All former logic wants to do is deal with relationships 19:03 between specifics, that's all. 19:05 So you got A and you B doesn't matter what they are. 19:09 So we say if A is true then B is true okay, 19:14 and what do you know, A is true, 19:17 thus logically B has to be true as well. 19:21 You say, if you got A and you got B 19:23 and if A is true than B is true. 19:26 A is true therefore B has to be true. 19:30 It's simple logic it's called the fancy term 19:34 is modus ponens, modus ponens. 19:38 Now listen to this, 19:40 this is subtle but pick it up because it's important. 19:43 However to say that if A is true then B is true 19:50 and that B is true 19:53 doesn't necessarily mean that A is true. 19:57 B can be true for reasons that have nothing to do with A. 20:01 Let me give you an example. 20:03 If every-- if we have A 20:05 I put on my hat on my head and B it rains. 20:10 It doesn't mean that suddenly B if it's raining 20:13 that I have to put my hat on my head, okay. 20:17 The rain could have absolutely nothing to do with me 20:20 putting my hat on my head. 20:22 It's probably have something to do 20:23 with the low pressure system 20:26 that moves into the area, okay. 20:30 And yet don't miss this crucial point 20:35 and this point is that almost all, 20:37 I would say all or almost all modern science 20:41 and the practice of science 20:43 is built on this kind of experimental prediction. 20:48 You look at something or you do an experiment 20:51 and then you-- based on your understanding 20:54 of what is happening based on your theory 20:57 you make the predictions 20:59 and indeed if those predictions come true 21:02 you claim your theory is right. 21:05 Let me give you a quick example. 21:07 I have a theory, I have a theory 21:11 that they are invisible spiders from Mars 21:16 and these spiders from Mars are pushing everything down. 21:20 Now I want you to test it with me. 21:22 I want you to-- I'm going to raise my hand 21:24 and I let my hand go and boom it drops, okay. 21:28 Do it again. I want to try with this hand. 21:30 You will try it at home, 21:32 you'll lift your hand up and you let it go. 21:34 Does it fall to the ground? 21:37 Well, therefore I just proved my theory. 21:40 Invisible spiders from Mars are pushing everything down. 21:44 Okay, that might be silly but that is reveals 21:49 the fundamental fallacy of every scientific theory. 21:55 It might be right, 21:56 the theory that made the predictions might be right 21:59 but it might not be. 22:01 Your predictions no matter how accurate they are 22:05 might be the result of something entirely different 22:08 from what you propose in your theory, okay. 22:11 That's what this means there. 22:14 What this means that is that 22:15 there is always going to be a limitation on how true 22:20 one can be in regard to what is valid in science. 22:25 Accurate predictions do not make a theory true. 22:30 As we saw you can make some very accurate predictions 22:33 with a theory of the universe 22:35 that had a stationary earth at the beginning of it. 22:38 A stationary earth with the sun and stars moving around it. 22:43 They made accurate predictions totally wrong theory 22:48 and this is not as uncommon as one would think. 22:51 Some times that might even be more of the exception 22:53 rather than the rule. 22:55 I talked to you in an earlier program 22:57 about general relativity and quantum theory. 23:01 Two theories that have been proven beyond 23:04 and they make incredibly accurate predictions, 23:07 it's amazingly accurate predictions 23:09 and yet we saw that 23:11 they basically contradict each other. 23:13 Scientist know that quantum theory 23:15 as we understand it and general relativity 23:18 as we understand it in certain ways 23:20 and complete contradiction to each other. 23:24 But how could that be? 23:25 They make accurate predictions. 23:28 Well, the answer is easy, 23:29 accurate predictions doesn't necessarily mean 23:33 that a theory is true. 23:36 I talked to you also about how? 23:39 In the past you could have theories that 23:40 they built technology on. 23:43 Technology was built on theories 23:45 that have been proven wrong. 23:48 I got this quote from a professor 23:50 of philosophy named Dr. Goldman. 23:53 "The theories we currently hold to be true 23:56 are as likely to be falsified in the next 100 years 24:00 as the theories that we look back on 24:02 as having been falsified in the last hundred years. 24:07 Wow, that's pretty heavy. 24:09 So the theories we hold today, 24:11 theories that many ways work 24:14 could later be shown to be false 24:16 as were many theories in the past 24:18 that were believed that worked, 24:21 that made predictions were shown to be false. 24:26 You know, I'm not going to do it now 24:30 but I think it would be fun. 24:31 It would be fun to do a whole program, 24:34 do a whole program on scientific theories 24:38 that were believed have been true 24:40 and that they built technology on fruitful technology 24:45 that later were shown to be false. 24:48 But I can think for a few ideas 24:50 that were once so believed in science 24:54 and that now had been rejected. 24:56 The existence of the universe of an eternal universe 25:00 once a foundation theory of science is gone, 25:06 known to be, believed to be wrong now. 25:08 The static nature of the universe, 25:11 the universe was once believed to be static, gone. 25:15 The idea of absolute space, 25:17 absolute time the two assumptions that 25:20 Newton used to create his theory of gravity, gone. 25:25 And a big one, 25:26 the idea that energy was continuous 25:29 that it could be divided-- infinitely divided in smaller, 25:33 smaller sections on and on and on. 25:36 This is the foundation of quantum theory 25:39 and it's completely gone. 25:41 If you are seeking truth as in the truth 25:45 then science is probably going to directly disappoint you. 25:50 On the other hand if you want as we said, 25:53 if you are just looking to build a better mousetrap, 25:56 if you are just looking to build some technology 25:59 then you don't care about these questions. 26:03 In fact, one of the most famous philosophers 26:05 of science Karl Popper has argued this very point. 26:10 He said we can never prove a scientific theory true. 26:15 All we can do is show that it is false. 26:20 We can never prove a theory true 26:22 only that it hasn't been proven false. 26:25 What does that mean? 26:27 Well, Popper still very influential 26:30 but he basically to this conclusion 26:32 from the same reason about what we are saying. 26:34 You could have all the predictions you want, 26:38 you can make all the proper predictions 26:41 based on your theory, you could build weapons, 26:44 you could make money, you can do all these things 26:48 but it doesn't make it true, accurate predictions are cheap. 26:52 Things that-- astrology can make accurate predictions. 26:56 And said for Popper it doesn't matter 27:00 any real scientific theory in principle is falsifiable. 27:06 You can never be sure something new isn't going to come along 27:11 and totally uproot your theory 27:15 regardless of how well of all predictions it makes. 27:21 Now the reason I bring this up again 27:25 though this element comes in as we've looked at is again-- 27:28 it just a deal with this idea 27:32 of the certainty of scientific knowledge. 27:36 We-- scientific knowledge is not certain. 27:40 I mean, no knowledge in that sense is certain. 27:43 There are questions, there are loopholes, 27:46 there are things that you have to take on faith on science 27:50 as you do with every thing else. 27:53 Thus science is great, teaches us a lot 27:56 but it's not the final orbiter of truth. |
Revised 2015-02-19