Today we finish the rest of chapter 2 (previous post here).
CHAPTER 2: THE HALLMARKS OF SCIENCE
“Science is more than a body of knowledge. It is a way of thinking; a way of skeptically interrogating the universe with a fine understanding of human fallibility.” Carl Sagan
“I am a deeply religious nonbeliever…. This is a somewhat new kind of religion.” Albert Einstein
“We are glorious accidents of an unpredictable process with no drive to complexity, not the expected results of evolutionary principles that yearn to produce a creature capable of understanding the mode of its own necessary construction.” Stephen J. Gould
“The God of the Bible is also the God of the genome. He can be worshiped in the cathedral or in the laboratory. His creation is majestic, awesome, intricate, and beautiful – and it cannot be at war with itself. Only we imperfect humans can start such battles. And only we can end them.” Francis Collins
The very first evolutionist was not Charles Darwin or Lucretius or Thales or Nimrod, but Satan himself. He has not only deceived the whole world with the monstrous lie of evolution but has deceived himself most of all. He still thinks he can defeat God because, like modern “scientific” evolutionists, he refuses to believe that God is really God.” Ken Ham
 This quote is from an interview with Carl Sagan. See: https://www.singularityweblog.com/carl-sagans-last-interview-science-as-a-candle-in-the-dark/.
 Albert Einstein in letter to Hans Muehsam, March 30, 1954, Einstein Archive 38-434, The Expanded Quotable Einstein, p. 218. As quoted in Christopher Hitchens, The Portable Atheist: Essential Readings for the Nonbeliever (De Capo Press, 2007), ebook.
 Stephen J. Gould, Full House: The Spread of Excellence from Plato to Darwin (Harmony, 1996), p. 216. Italics are my emphasis.
 Francis Collins, The Language of God: A Scientist Presents Evidence for Belief (Free Press, 2007), p. 211.
 Henry Morris, The Long War Against God: The History and Impact of the Creation/Evolution Controversy (Master Books, 2000), p. 260. As quoted in Karl Giberson, Saving Darwin: How to Be a Christian and Believe in Evolution (HarperOne, 2008), p. 20.
Philosophy of science comes of age
As science rose to its current seat of intellectual and cultural importance in the 20th century, philosophers and sociologists began to construct models to explain the scientific process and how scientific knowledge is gained or becomes “truth” (collectively called the philosophy of science). An important philosopher of science was Karl Popper, most well known for his work on the so-called demarcation problem that asks: what makes one idea or theory scientific and another not scientific? Popper’s main contribution to the discussion was that if an idea can be formulated into a hypothesis that is potentially falsifiable, it is considered scientific. If the hypothesis cannot be falsified, no dice and you’re in the realm of pseudoscience.
Many interested in the science-religion dialogue, especially those that see science and religion at war, like this criterion because it gives them a missile to fire on their opponents when they feel threatened. Common targets are scientific creationists and intelligent design proponents. Since creationism and intelligent design cannot possibly be falsified, so it goes, they are both pseudoscience and not worthy of anyone’s time. Unfortunately, the falsifiability criterion does not actually solve the demarcation problem because there are some ideas corresponding to the extremes of the natural world – the very small and the very big – that don’t lend themselves well to experimentation, and thus cannot possibly be falsified. But these ideas remain in the realm of science. Interestingly (at least to the author), creationists and intelligent design advocates seem to spend a great deal of effort convincing others that their ideas are falsifiable so they will be considered “scientific.” The arguments are usually quite weak and are an attempt at passing a 60-70 year old science exam that only has one question: are you scientific? I want to say to all parties involved, “The world has moved on.” I guess I just did.
Philosophy of science as a discipline went Hollywood with publication of Thomas Kuhn’s landmark book, The Structure of Scientific Revolutions. Kuhn’s focus on scientists working in communities was spot-on even if he made us out to be lemmings. In addition, Kuhn’s distinction between “normal” and “revolutionary” science is illuminating since historically scientific fields have gone through periods of relative inactivity where old theories are held without question (“normal” science) and new theories develop during bursts of creativity (“revolutionary” science). Nevertheless, I don’t agree with the book likely for the very reason it became popular; it made science seem irrational and over-emphasized the importance of subjectivity in the progression of science. (And this is but one reason why most scientists don’t like the philosophy of science.) Yes, science progresses via the competition between different communities of scientists. No, particular scientific theories don’t win out for sociological or political reasons. What Kuhn did to encourage including the history of science in philosophy of science discussions was a very good thing, so equally bad was the subjective picture he painted in contrast with science’s objectivity.
The philosopher of science that I believe does the best justice to how science actually progresses is Imre Lakatos. Lakatos combined the historicity of Kuhn with Popper’s focus on rationality to produce his theory of “research programmes.” Lakatos appreciated the community aspect of Kuhn’s philosophy but abhorred the apparent irrationality that accompanied it. Lakatos kept the community focus but infused it with Popper’s ideas to provide a model that was both historical and rational. In my mind, his model also is the most accurate at relating the three key aspects of scientific research: theory, hypothesis, and data.
Scientific knowledge is gained when hypotheses are generated and tested. Scientific use of the term hypothesis mirrors that of its general use. A hypothesis is a conjecture, an educated guess that can be tested in a meaningful way. To test a hypothesis means to subject it to experimentation, with the resulting data refuting the hypothesis or not. (The use of the term data here also mirrors its common parlance.) If the data supports the hypothesis, we don’t say the hypothesis was “proven” as you can never absolutely prove something in science. Nevertheless, when a hypothesis is repeatedly not refuted it becomes “accepted.” It is quite easy to formulate hypotheses, but not as easy to come up with hypotheses that are actually testable. For instance, the hypothesis that I have the same vertical leap as Michael Jordan is both easy to formulate and easy to test: I can jump, fail, and injure my back, and the hypothesis will be refuted (and my friends will laugh at me). The hypothesis that we live in one universe amongst many is not as easy to formulate and immensely more difficult to test.
Importantly, hypotheses aren’t formed out of thin air (at least meaningful ones unlike the comparison of Michael Jordan and me). They are always connected to broader theories and theory is a word with a much different meaning in science than its common use. To most, a theory is similar to a hypothesis and implies lack of evidence or skepticism about the idea’s merit. This is not at all the case when scientists use the term. In science, theories are broad and consist of foundational ideas that have been well established, usually due to multiple independent means of inquiry that have all undergone repeated testing. So, theories (e.g., theory of evolution, theory of general relativity, atomic theory) are in fact the closest thing to truth that science can produce. Let that sink in for a minute.
Back to the connection between hypothesis and theory in Lakatos’ research programs. Let’s look at the theory of evolution, which says that all life forms that exist or have ever existed on this planet have descended from one or a few common ancestors. All evolutionary biologists work under this theory, but different ones will work on different model systems. One may study evolution in bacteria such as E. coli while another studies the evolution of dinosaurs. The bacterial scientist proposes a hypothesis from the perspective of the theory to explain why antibiotics aren’t working anymore (hint, it has to do with something called horizontal gene transfer) whereas the paleontologist proposes a hypothesis for why the last era of dinosaurs came to such an abrupt end (hint, it has to do with an asteroid and lack of dino diversity, at least among the wingless). These hypotheses are not “neutral” and come out of the scientists’ acceptance of evolutionary theory. But the traffic is not only in one direction. Hypotheses don’t just derive from theories but the data they generate can also support theories. A hypothesis that posits the existence of an intermediate life form in a particular geological era most definitely arises out of a commitment to evolutionary theory. But what happens if a scientist testing this hypothesis finds this intermediate species? The theory of evolution is confirmed. Does this sound circular? Yes, it very much does, but the “circle” is in reality feedback between theory and data via hypothesis and depends on logic flowing in both directions (deductive and inductive reasoning). To me, this “organization” of ideas provides the most accurate description so far of science in practice.
An additional utility of Lakatos’ philosophy of science is that different research programs can be compared to determine whether one is “progressing” more than the others (i.e., one is “winning” because it best explains the data). Those programs that are progressing are ones in which the hypotheses not only support the theory but also predict novel data. By contrast, “degenerating” programs are ones in which hypotheses are continually formulated ad hoc to explain away data in light of the theory and don’t predict novel data.
But how long does it take for a research program to officially die off? Interestingly, that’s difficult to predict, but fairly easy to see with the benefit of 20:20 hindsight. A research program will become officially degenerate when a new research program comes along that faithfully explains all of the available data, provides novel hypotheses that welcome further exploration, and convinces proponents of other research programs to jump ship. It certainly helps if the old generation has moved on to, shall we say, greener pastures too.
Perhaps a real-world analogy would best help to illustrate the concept of research programs and interplay between theory, hypothesis, and data. I have been happily married for 12 years. I love my wife and I believe she loves me as well. Let’s say I am driving by a restaurant and see her eating with a man I don’t know. I might be suspicious initially, but I know she loves me from all of the experiences we’ve shared, the three kids we have, the awesome patio set I just bought her (no, seriously, it’s really nice), the fancy dinner I took her to that one time a few years ago, so I choose to ignore it. The next week, I see the same thing. And the next week.
As the data piles up, I’m really starting to wonder what is going on. I thought she loved me? Perhaps my theory is incorrect. I start to re-interpret previous experiences, looking for “clues” as to why this type of behavior could occur. I hypothesize that there were things I said that I shouldn’t have. I hypothesize that I am not spending enough time with her, or she is feeling neglected, or she is worn out and bored from staying home with the kids, or she doesn’t really care about lawn furniture (highly unlikely, I know). Now I start to piece it together and realize that (expletive deleted), my wife is leaving me. Because of this new theory, I think back to things she has said to me that could have suggested she wasn’t happy.
I finally get up the nerve to ask her about it the next time I see her in the restaurant with him. And lo and behold, the next week I have my chance. So I storm in to yell at her in a fury of excitement. As I’m demanding an explanation…
I realize it’s not her! I was wrong and I have just made a fool out of myself. Instantly, the bungee cord of reality snaps back and I immediately return to my original interpretation of our experiences together. I remember how much she loves me and realize I was being an idiot. My theory of her love is secure. Newton is safe for now.
That’s how science works. Research programs are continually bolstered or “progress” as they adequately take account of the available data and suggest new hypotheses and experiments that can be performed to generate data that support the research program. In time, if the research program is incapable of accommodating the relevant data and ad hoc hypotheses must continually be formed to instead explain away the data, the research program will degenerate and the time is ripe for a competing research program to swoop in and gain acceptance. There are several examples from the history of science in which a research program became stagnant and could not accommodate new data. (See Galileo and the Copernican revolution. See Einstein and the quantum revolution. See Watson, Crick and others and the molecular revolution. Etc.). Science is still dependent on data and hypotheses, but Lakatos enables us to once and for all appreciate its theory-laden nature.
Let’s return to the quotes that opened this chapter. The initial quote by noted astronomer and science popularizer, Carl Sagan, deftly summarizes science, so much so that I would be surprised if there was a practicing scientist who didn’t wholeheartedly agree with it. The other quotes are examples of how three well-respected scientists view the interaction of science and religion. Albert Einstein describes himself as a “deeply religious non-believer,” which likely signifies a sense of awe about the natural world that traditional religions and their doctrines cannot adequately communicate. Next, we have the previously introduced Stephen J. Gould, whose lucid skill as a writer significantly transforms an otherwise sterile quote with the simple addition of one word, “glorious.” Deleting this word reveals an impoverished world because even though Gould was committed to the compatibility of science and religion personally he had no room for religious discourse due to his strong agnosticism. Last, we have Francis Collins, former leader of the Human Genome Project, current director of the National Institutes of Health, and well-known Evangelical who founded the organization BioLogos, which aims to promote dialogue on science and faith. Collins is passionate about reconciling the two worlds of science and faith and attempts a harmony of the two in his book, The Language of God. Collins believes science and religion are independent endeavors, with science addressing questions about the natural world and religion addressing questions of belonging, morality, and ultimate meaning.
All four of these scientists were or are leaders in their respective fields and all would no doubt agree to the descriptions of science provided here. All accept(ed) evolution and the other findings of modern science. What accounts for the different views of science and religion that permeate their writings?
And what about the quote from Ken Ham, well-known young-earth creationism advocate who possesses a bachelor’s degree in applied science and taught in public high school in Australia before becoming president of the organization Answers in Genesis? “ The very first evolutionist was not Charles Darwin or Lucretius or Thales or Nimrod, but Satan himself…”
It is to religion and theology that we now turn.
 For a thorough and very well written introduction to the philosophy of science, see Peter Godfrey Smith’s Theory and Reality: An Introduction to the Philosophy of Science (University of Chicago Press, 2003). For a narrower, but Christian perspective on the philosophy of science see Del Ratzsch’s Science and its Limits (IVP Academic, 2000).
 My understanding of Popper’s work has come primarily by reading introductory volumes on the philosophy of science. For those interested in learning more about his views I can at least suggest the following books, however: Karl Popper, The Logic of Scientific Discovery (Routledge, 2002); Karl Popper, Conjectures and Refutations: The Growth of Scientific Knowledge (Routledge, 2002).
 Thomas Kuhn, The Structure of Scientific Revolutions (University of Chicago Press, 1962).
 Well-educated lemmings, though.
 Imre Lakatos, ed. by John Worrall and Gregory Currie, The Methodology of Scientific Research Programmes: Volume 1: Philosophical Papers (Cambridge University Press, 1980).
 Hereafter referred to as research programs so I can get rid of the quotation marks.
 Send me some retro Jordans if you’re reading this, Michael.
 The tree of life has gotten bushier and more interconnected in the last few decades.
 Novel data refers to data produced by an experiment that tests a new hypothesis or data from another study that was previously unknown to the research program. A strong example of the latter is Mendelian genetics, which was unknown to Darwin and early proponents of his theory of evolution by natural selection even though Mendel’s experiments were already in progress. It’s impossible to know everything in your own narrow field of scientific research, let alone a related field.
 Hat tip to Karl Giberson for the idea of this analogy.
 Please, God, may there never be data to support an Einstein-like revolution. My wife is awesome.
 Interestingly, the new data usually comes from a technical advance that enabled more sophisticated measurements. Who could imagine astronomy without the telescope, cell biology without the microscope, or biochemistry without X-ray crystallography? Today’s high-computing systems and next-generation sequencers are doing the same for genomics and personalized medicine.
 I forgive the reader for not already knowing that Satan got a Ph.D. in biology from Johns Hopkins University immediately after promoting the eviction of garden tenants Adam and Eve, but just before tempting Jesus in the wilderness with beakers and test tubes.
Yes, the quote is ridiculous. That doesn’t mean the quote should be ignored. Quite the opposite, actually.