Saturday, 28 December 2013

On Science

For the last 8 to 9 years, the word Technology was part of my designation. Though I understand the word from my professional journey perspective, I wish to understand it in more depth.

But I guess Technology comes after science. I mean both procedurally and epistemologically. I am not really sure what the heck the previous sentence means exactly, but basically since technology is the application of science, it is correct to get to know the word science first. Hence this post is on science; however it is not to give any new insight about it, but just compile material that people have already said. It's more like high-school notes, for me to read over and over, and stick it in my mind. Also, this is one of those placeholder kind of posts that I would be periodically updating.

My summary about science consists of its definition, what Popper said, the scientific method and Kuhn's insights. Here goes --

A) Definition
i) from
1. a branch of knowledge or study dealing with a body of facts or truths systematically arranged and showing the operation of general laws: the mathematical sciences.
2. systematic knowledge of the physical or material world gained through observation and experimentation.
3. any of the branches of natural or physical science.
4. systematized knowledge in general.
5. knowledge, as of facts or principles; knowledge gained by systematic study.
ii) from wikipedia
Science (from Latin scientia, meaning "knowledge") is a systematic enterprise that builds and organizes knowledge in the form of testable explanations and predictions about the universe. In an older and closely related meaning, "science" also refers to a body of knowledge itself, of the type that can be rationally explained and reliably applied.

B) What Popper said
(source: The Logic of Scientific Discovery by Karl R. Popper)
But I shall certainly admit a system as empirical or scientific only if it is capable of being tested by experience. These considerations suggest that not the verifiability but the falsifiability of a system is to be taken as a criterion of demarcation. In other words: I shall not require of a scientific system that it shall be capable of being singled out, once and for all, in a positive sense; but I shall require that its logical form shall be such that it can be singled out, by means of empirical tests, in a negative sense: it must be possible for an empirical scientific system to be refuted by experience.

C) The scientific method
(source: Algorithms Fourth Edition by Robert Sedgewick and Kevin Wayne)
Observe some feature of the natural world, generally with precise measurements.
Hypothesize a model that is consistent with the observations.
Predict events using the hypothesis.
Verify the predictions by making further observations.
Validate by repeating until the hypothesis and observations agree.
One of the key tenets of the scientific method is that the experiments we design must be reproducible, so that others can convince themselves of the validity of the hypothesis. Hypotheses must also be falsifiable, so that we can know for sure when a given hypothesis is wrong (and thus needs revision)

D) Kuhn's insights
(source: The Structure of Scientific Revolutions by Thomas Kuhn)
Science progresses through revolutions. "... the reception of a new paradigm often necessitates a redefinition of the corresponding science. Some old problems may be relegated to another science or declared entirely "unscientific." [e.g. alchemy] Others that were previously non-existent or trivial may, with a new paradigm, become the very archetypes of significant scientific achievement. [e.g., tidology, the study of the tides] The normal-scientific tradition that emerges from a scientific revolution is not only incompatible but often actually incommensurable with that which has gone before."

Update on 24-Jul-2015
E) When is a Field a Science?
(source: The Science in Computer Science by Peter J. Denning. Communications of the ACM, May 2013, Vol. 56, No. 5.)
The brief history suggests that computing began as a science, morphed into engineering for 30 years while it developed technology, and then entered a science renaissance about 20 years ago. Although computing had subfields that demonstrated the ideals of science, computing as a whole has only recently begun to embrace those ideals. Some new subfields such as network science, network social science, design science, and Web science, are still struggling to establish their credibility as sciences.

What are the criteria for credibility as science. A few years ago I compiled a list that included all the traditional ideals of science.
--> Organized to understand, exploit, and cope with a pervasive phenomenon.
--> Encompasses natural and artificial processes of the phenomenon.
--> Commitment to experimental methods for discovery and validation.
--> Reproducibility of results.
--> Falsifiability of hypotheses and models.
--> Ability to make reliable predictions, some of which are surprising.

F) A Scientific Way of Thinking
(source: pg 154, Implementing Lean Software Development, From Concept to Cash by Mary and Tom Poppendieck. 2007, Addison-Wesley / Pearson Education.)
As any scientist knows, the scientific method works like this:
1. Observe and describe a phenomenon or group of phenomena.
2. Formulate a hypothesis to explain the phenomena.
3. Use the hypothesis to predict something -- the existence of other phenomena or the results of new observations.
4. Perform experiments to see if the predictions hold up.
5. If the experiments bear out the hypothesis it may be regarded as as a theory or rule.
6. If the experiments do not bear out the hypothesis, it must be rejected or modified.

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