Epistemology: The Paradox of the Ravens
Published on Jul 24, 2015
In this video, Marc Lange (UNC-Chapel Hill) introduces the paradox of confirmation, one that arises from instance confirmation, the equivalence condition, and common inference rules of logic.
This was solved by Popper: You don’t look for confirming evidence. You look for DIS-confirming evidence, and hold your hypothesis tentatively.The use of the word “confirmation” is what’s not sound. Sure, you can apply the evidence; your chair without ballet shoes does indeed lend evidence that all ravens wear ballet shoes. See, that one piece of evidence is in support of all ravens being black, but it isn’t enough evidence to completely confirm it. now if you find every non-black thing and there isn’t a single raven among them: you’ll know that every raven is black.
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Science, Technology, Engineering and Mathematics (STEM, previously SMET) is an acronym that refers to the academic disciplines of science[note 1], technology, engineeringand mathematics. The term is typically used when addressing education policy and curriculum choices in schools to improve competitiveness in science and technology development. It has implications for workforce development, national security concerns and immigration policy. Education emphasizing STEM disciplines is considered to be more beneficial to the student than the previous generation of education standards that emphasizes broad “core” disciplines and social skills instead.
The acronym arose in common use shortly after an interagency meeting on science education held at the US National Science Foundation chaired by the then NSF director Rita Colwell. A director from the Office of Science division of Workforce Development for Teachers and Scientists, Dr. Peter Faletra, suggested the change from the older acronym SMET to STEM. Dr. Colwell, expressing some dislike for the older acronym, responded by suggesting NSF to institute the change. One of the first NSF projects to use the acronym was STEMTEC, the Science, Technology, Engineering and Math Teacher Education Collaborative at the University of Massachusetts Amherst, which was funded in 1997.
The hypothetico-deductive model or method is a proposed description of scientific method. According to it, scientific inquiry proceeds by formulating a hypothesis in a form that could conceivably be falsified by a test on observable data. A test that could and does run contrary to predictions of the hypothesis is taken as a falsification of the hypothesis. A test that could but does not run contrary to the hypothesis corroborates the theory. It is then proposed to compare the explanatory value of competing hypotheses by testing how stringently they are corroborated by their predictions.
One example of an algorithmic statement of the hypothetico-deductive method is as follows:
- 1. Use your experience: Consider the problem and try to make sense of it. Gather data and look for previous explanations. If this is a new problem to you, then move to step 2.
- 2. Form a conjecture (hypothesis): When nothing else is yet known, try to state an explanation, to someone else, or to your notebook.
- 3. Deduce predictions from the hypothesis: if you assume 2 is true, what consequences follow?
- 4. Test (or Experiment): Look for evidence (observations) that conflict with these predictions in order to disprove 2. It is a logical error to seek 3 directly as proof of 2. Thisformal fallacy is called affirming the consequent.
One possible sequence in this model would be 1, 2, 3, 4. If the outcome of 4 holds, and 3 is not yet disproven, you may continue with 3, 4, 1, and so forth; but if the outcome of 4shows 3 to be false, you will have to go back to 2 and try to invent a new 2, deduce a new 3, look for 4, and so forth.
Note that this method can never absolutely verify (prove the truth of) 2. It can only falsify 2. (This is what Einstein meant when he said, “No amount of experimentation can ever prove me right; a single experiment can prove me wrong.”)
Despite the philosophical questions raised, the hypothetico-deductive model remains perhaps the best understood theory of scientific method.