TOPIC 3
HOW DO WE 'DO' SCIENCE?

Readings - Wolpert, Ch. 4-7

 

INTRODUCTION

Let's start by revisiting topics discussed during our first two lectures. During these lectures, we suggested that it was useful to consider a three-fold division when attempting to understand science: the universe, our model of the universe, and doing science. I might suggest that we now add a fourth, that of the scientists themselves.

UNIVERSE

IMPERFECT MODEL OF UNIVERSE

DOING SCIENCE

IMPERFECT SCIENTISTS

This framework allows us to raise and discuss a series of questions about these four elements and maybe more importantly explore the relationships between them. For example, does the universe really exist? Is it possible for us to truly understand reality? Is our model of the universe science (thus making science an object or product), or is science better viewed as the process by which we obtain this model (an action). If the latter is true, is there a scientific method that one can write down or teach to other prospective scientists? Or are there certain basic requirements that must be met for any activity to be considered science? If the answer is no then what is science? Is scientific knowledge special or valid? Can we really separate our model from the doing of science, or the scientific method from the scientists themselves? Is science so unique that one can clearly define it?

 

IS THERE A KNOWABLE UNIVERSE?

Carl Sagan, in a short essay entitled Can We Know the Universe? explored this question and uses an example of a grain of salt. He concludes that we can't possibly tabulate all information to fully characterize even a single grain. Thus we need to look for the 'big picture', and do so by searching for patterns, rules, or regularities in nature. What we perceive as patterns or restrictions (certain things cannot occur in nature) are simply nature following rules. These patterns or rules generally can't be established from common-sense.

Many philosophers through the ages have argued that we cannot determine reality independent of our own perceptions. For example, the Solipsist view (one philospohical perspective) is that everything is the creation of our imagination. Later in this course we will discuss some "scientific" ideas in quantum mechanics which imply that how we view reality depends on our theories and that our very act of trying to measure reality changes it.

Hawking would argue that the Solipsist view is a waste of time because we do not act on this basis. We all believe in a reality and conduct our lifes according to this belief (the source of our common sense?). Thus why not try to understand our reality as best as possible, whether it is real or not?

This leads us to some, often unstated, assumptions that scientists tacitly accept when "doing science."

Presence of unstated assumptions or 'themata' (George Holton):

- there is an external world separable from our perceptions.

- the world is rational: 'A' is not equal to 'not A'.

- the world can be analysed locally - that is, one can examine a process without having to take into account all of the events occurring elsewhere.

- there are regularities in nature.

- the world can be described by mathematics.

- these presuppositions are universal.

It can be argued that all of these assumptions are testable and consistent with the ability of science to describe and explain a very large number of phenomena.

Two other assumptions are less easy to 'test', even though we accept and use them all of the time while doing science.

- 'the ultimate laws of science, the few simple general principles which determine why all of nature is the way it is...' (Steven Weinberg)

- the best scientific theories will be the most beautiful or elegant.

We accept the first six assumptions and strive for the latter two, simple and beautiful theories that explain to us how the universe functions.

 

 

CAN WE BUILD A CONCEPTUAL MODEL OF THE UNIVERSE?

If we have accepted the existence of our first box (a universe), then our goal is to develop and improve our model of this universe (our second box).

This brings us back to the question of whether the model or method of making the model is science. I will argue that the distinction really has to do with which is particularly unique to science, and will ultimately agree with Hawking and Sagan that the two are inseperable. What do you think? To decide we must first explore further our third box ­ method of doing science.

Carl Sagan: (Broca's Brain, 1979) stated that "Science is a way of thinking much more than it is a body of knowledge." For what we "know" in the scientific sense about the physical world-and, indeed, what we mean by "knowledge" ­ is a function of the means by which we come by knowledge. (Hatton & Plouffe, 1997).

 

WHAT IS THE SCIENTIFIC METHOD?

A general definition might be "an approach of problem solving or method of attainment of knowledge about the natural world."

This begs the question of what is the "approach" or "method." A commonly stated simplistic answer is that one typically needs to go through the following steps: 1. Make observations, 2. Develop a hypothesis from these observations, 3. Use hypthesis to make prediction, 4. Test by conducting experiments or making further observations. 5. Eventually develop a theory. And the scientist following this procedure was expected to be logical, objective, impersonal, and precise. Is this really the scientific method and the way scientists do science?
Lets first go through the steps and explore what each entails. I have slightly reordered these steps into what I believe is a more common approach.

1. Pose a Question (what is universe?):
a. Doing this helps focus data collection;
b. Posing a good scientific question requires a certain background;
c. Posing a good question also takes creativity.

2. Data Collection (fact = things that happen or exist):
a. Datum = representation of fact:
1. Must occur, things that happen or exist;
2. Must be recognizable by others;
3. Have high degree of agreed upon description = reliability;
4. Often collected/observed.
b. A wide variety of ways of "collecting" data.
c. Data, facts have no meaning in themselves.

3. Hypothesis (proposed idea or model explaining data, relationship)
a. Describe with mathematics?
b. Is it specific enough to make predictions?
c. Testable, that is is it possible to prove it wrong?
d. Creativity Important.
e. Personalities strongly affect hypotheses.

4. Testing Hypotheses
a. Experimentation;
b. Make further observations;
c. Compatible or incompatible with current knowledge.
d. Personalities strongly affect hypotheses.

5. Publication of Results
a. Clarity of data acquisition of explanations;
b. Put results under public scrutiny (further testing);
c. Results only of use to others if published, shared knowledge.

6. Theory (generalized hypotheses, laws, or models)
a. Must explain kinds of events/data and not single event;
b. Must be supported by large amounts of data;
c. Must show functional relationships;
d. Relationships must be applicable to different kinds of events.

 

Need for Falsification:

*Science: Conjectures and Refutations (Karl Popper) - How does science differ from pseudo-science?, first person to develop the idea of falsification,

Does Theory Ever Become Fact? (Charles Wynn) - discusses limitations of theories and need to always try to falsify them, not particularly useful,

If a theory cannot be falsified, then it cannot be tested. As Hume noted, ' induction - inferring relationshiops (or theories) from repeated instances (observations) - is logically untenable. By contrast, only negative instances - falsifications - provide evidence that can be trusted.'

However, although scientific theories must be falsifiable, just because ideas are falsifiable does not make them part of science! Absurd ideas are falsifiable, but they are not science.

This leads to a critical idea in science, that there will always be unstated criteria for choosing one theory over another.

- a new theory must be as broad as possible and encompass a wide range of phenomena.

- it should be able to predict new relationships and offer scope for further development.

- it should be as simple as possible, with a minimum number of hypotheses.

- it should be testable by confirmation by independent observers.

- it should be self-consistent

- it should be capable of being linked with other branches of science.

- it should be quantifiable and expressible by mathematics.

 

Critical Observation and Controlled Experiment:

*Learning to See (S. Scudder) - how is one trained to become a scientist, good personal story,

Real observations depend on the experience of the observer.

The 'interpretation' of real observations depends on underlying theories which form the basis for how the brain interprets observations.

 

But is this the way science really proceeds?

The Issue of Sequence/Completeness of Steps:

Ptolemy and Copernicus: started with same data (sun rises and sets) but reached different hypothesis.

Newton: guessed at answer.

Pasteur: made discoveries about things not directly trying to solve. Luck?

Einstein: Started out with intellectual puzzle (about velocities of light measured by different observers) and jumped to theory.

A Method of Inquiry (George Kneller) ­ would argue that there is no clear sequence of steps leading to science, but still gives a set of normal research 'tools', use of the tools generally results in scientific advances. He also discusses the idea of cycles (discovery, validation) of activity.

On Scientific Method (Robert Pirsig) - discussion of logic and elements of scientific method,
The scientific method might be considered to be a mixture of inductive and deductive reasoning. Induction is used to derive general statements from discrete observations, and deduction is used to predict behavior based on the general statements. Obvious limitations are (1) whether the general statements are true 'universal' laws or simply 'local laws which hold until some outside condition changes, (2) whether all necessary premises are considered when predictions of future behavior are made, (3) whether individual observations are correct, (4) whether individual observations are repeatable and similarily interpretable by a variety of individuals,

 

The Issue of Creativity:

Obviously there must be creativity in the process of doing science, but is scientific creativity like artistic creativity?

Creativity in the Arts is characteristically intensely personal and reflects the feelings and ideas of the artist. Scientific creativity is always constrained by self-consistency, by trying to understand nature, and by what is already known.

Also, scientific creations become assimilated into public knowledge, while artistic creations are for ever unique and original.

What then is scientific creativity?

1) 'knowing' which problem to work on (most likely to be soluble)

2) 'knowing' when to approximate

3) 'knowing' which experiments to do (which data to collect)

4) recognizing relationships, inconsistencies.

 

Methods of Creativity:

1) Chance-permutation model: Guess a lot of theories and the best will stick around. An analogy is deciphering a coded message.

2) The chance-permutation model may not be reasonable, but one of its results may be - bold conjecture followed by verification or falsification. An example might be Newton's Laws; he first guessed what mathematical laws made sense and then tested them by experiment.

These thoughts on scientific creativity do make clear that science does not progress solely by patient accumulation of facts and tedious observation. Even so, scientific creativity needs the previous facts and observations and lots of work to provide a basis within which to make useful bold conjectures.

 

*How Fermi Would Have Fixed It (Hans Baeyer) - really nice description of approximation and simple mental calculation as an everyday part of science.

Finally, does luck play a significant role in science? No, according to Louis Pasteur: 'Fortune favors the prepared mind.'

 

IMPERFECT SCIENTISTS: ISSUES OF
COMPETITION, COOPERATION, COMMITMENT

 

Scientists do not pursue 'truth' in a vacuum. They do so as a group, and as such their interactions become an integral part of how one does science.

Motivation for Doing Science
Curiosity, Intellectual Stimulation
Impose Order on Natural World
Personal Gratification/Gain

 

In one view, scientists pursue 'truth' in a dispassionate manner, their only reward and goal being better understanding. An alternative view is that scientists are entirely competative and selfish. In all likelihood, both have some elements of truth.

Even though science is ultimately anonymous and it doesn't matter who adds to the body of scientific knowledge, scientists usually need some reward for their efforts. That reward may be personal (and altruistic?!), but more commonly it comes from the regard of their peers.

Individual scientific results have a short time interval in which they may be termed 'important' and new scientific discoveries can only be made once. This leads to a certain amount of competition to get new and exciting results first.

This sense of competitiveness is balanced by the requirement that all science develops on the shoulders of preious work. Therefore there must be some degree of cooperation in order to progress with scientific problems that are beyond the scope of one person to solve. This is becoming an increasingly important notion as scientific problems become more complicated and interdisciplinary. Many important research papers today will have many authors who have all contributed to some new idea or body of observation.

The competitiveness leads to some degree of fraud in science. Luckily it is a very small component of all scientific work. Also, fraud is ultimately not a problem because of the very nature of science - testing, corroborating, falsifying previous data or ideas will always, in the end, throw out fraudulant data or ideas.

Another aspect of the social interaction of scientists is the question of how rival theories are evaluated. It may be that rival theories use concepts that are incomensurate; that is, they cannot be meaningfully compared. The shift from one theory to another by the scientific community as a whole may be termed a paradigm shift. A paradigm is then the dominant conceptual framework for some field of science.

SUMMARY


Hopefully it is now clear that doing science does not proceed in any orderly, set manner. But I will argue that we see many common themes in how scientists are trained and approach doing science. It is also important to remember that science is a communal activity with many scientists attacking problems from many different ways and perspectives. And that scientific knowledge, that is our model of the universe, is also shared by this community of science. We can thus speculate that even though an individual scientist may not follow or complete all the steps in the "scientific method" that the community of scientists will fill in the gaps.
I will also argue that the lines between some (all?) of our boxes are fuzzy and interconnected. It is difficult to separate the scientists with their personalities from the doing of science, and in turn the doing of science from the final product, our ever changing (but hopefully improving) view/model of the universe.

 

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