As I have already explained to you in my previous reply, I told you that the hypothesis (meaning the proposed statements and set of predictions) needs to be at least falsifiable and testable to be given the status of being “HYPOTHESIS”.
Intelligent Design isn’t even a “hypothesis” because the entity that you call “Designer” isn’t falsifiable and isn’t testable.
Falsifiability occurred before the actual tests being performed. There is a difference between “testable” and “tested”.
Any statement (eg explanation, prediction or equation presented) that are “falsifiable”, meaning having the potential of being “
testable” and “
refutable”, has the status of being hypothesis.
Those statements that are not falsifiable, don’t even meet the grade of being called “hypothesis”.
If you cannot setup an experiment, where you can actually detect, measure or test the
Designer, then it (ID) is pseudoscience.
The term “tested” means the experiments have already being performed, and any detectable/measurable/quantifiable evidences will either be
- refuted
- verified/validated
ID certainly haven’t been “tested”, because can you “measure”, “observe/detect” or “test” this
Designer?
No.
And no ID adherents have been able to detect/observe the Designer, no one has ever measure or test the
Designer. So in the testing phase of scientific method, testing the validity of hypothesis (explanation/prediction), ID haven’t met the requirements of Scientific Method.
So Intelligent Design isn’t a hypothesis because the Designer isn’t testable.
And Intelligent Design isn’t a scientific theory because there are no recorded observations or measurements to the Designer.
I have never claimed to be scientist.
My backgrounds in science and mathematics are applicable in engineering - more specifically in civil engineering, first, then later in computer science.
Both courses involved in “applied science”, meaning any field in science that I’ve studied, are related to the respective courses.
Examples, in civil engineering, you need basic understanding of mechanics, masses and forces, hence Newtonian mechanics (physics).
Examples in computer science, in the hardware side of computing, you need some basic understanding of electricity, electrical and electronics devices, hence knowing about power, current and voltage (physics), and if I was studying networking, then I need to understand electromagnetism, eg satellite network, WiFi, or if I was into business of laser and fibre optics, I again to know the basic of electromagnetism (physics), as well as optics, such as reflection and refraction (physics).
However, in both course, they both stressed the importance of testing, so evidences and test results and data are important both:
- to civil engineers (eg testing soils, testing the strength and stresses of construction materials (be the materials be concrete or steel or others), ensuring that the design and materials used meet safety standards, etc);
- and to computer programmers (eg creating prototypes, testing and debugging codes), or to computer/systems engineers (eg testing the electronics, circuitry, network, operating systems, etc).
Because of my grounding in engineering and applied science, I hold testable evidences to be of utmost importance, just as experimental science required empirical and verifiable evidences.