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What do you expect from Science? Science is a process , not a thing.

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Thinking Critically about Science What do you expect from Science? Science is a process , not a thing. Science is a paradigm based on understanding nature (rather than passively observing it, passing judgment on it, or anthropomorphizing it). Understanding nature involves reasoning .

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Thinking Critically about Science

  • What do you expect from Science?
  • Science is a process, not a thing.
  • Science is a paradigm based on understandingnature (rather than passively observing it, passing judgment on it, or anthropomorphizing it).
  • Understanding nature involves reasoning.

What Science Isn’t

  • It doesn’t deal with untestableconcepts (e.g., absolutes such as good and evil)  They can be observed (felt), but not measured (well, that’s debatable…)
  • Subjective ways of looking at the world (morals, religion, aesthetics) are not scientific concepts, they are absolutes (truths?): they are based on faith, beliefs, cultural and personal values

What Science (probably) is…

  • scientific knowledge is tentative (subject to change)
  • empirically-based (based on and/or derived from observations of the natural world)
  • subjective (theory-laden)
  • necessarily involves human inference, imagination, and creativity (involves the invention of explanations)
  • and is socially and culturally embedded
assumptions of science
Assumptions of Science

For Science to work, it has to follow certain rules and guidelines which are notquestioned:

  • Patterns in the natural world can be understood by careful observation and analysis.
  • the patterns should be repeatable in space and time (they should apply: i.e. Physics!).
  • Science uses Reasoning (makes specific observations and arrives at general conceptualizations  hypotheses).
  • These generalizations must be testable for falsehood
    • Yes  you’re good to go
    • No  go back to the drawing table…
state of science
State of Science
  • New observations can disprove theories or fail to do so (dethronement is our lot)  Dynamic feedback and self-correction
  • However, observations and scientific interpretations of these can never provide truth (no absolute proof of the truth of theories: Changing views and concepts!)  Science models do not necessarily represent reality!
  • Science is not more procedural than creative!
science and objectivity
Science and Objectivity
  • Myth:Scientists are NOT influenced by the social environment (REM: Spock??)
  • more realistic approach: recognize that we are all influenced,estimate its effect
  • doesn’t mean fuzzy thinking is acceptable, one must still think critically
what are we really comparing
What are we really comparing?

Deduction vs. Induction

  • Deduction goes from general statements (which may or may not be correct) to account for specific experimental results, (does not require the premises to be true): Swans
  • Induction (inductive generalizations) goes from specific observations to general statements which can be tested and are accepted as correct until proven wrong.
deductive vs inductive proofs an example
Deductive vs. Inductive Proofs:an example
  • problem: Deductive reasoning does not require that the initial premises be correct, the final statement is always true
  • can lead to false conclusions:
  • humans are the only toolmakers
  • Chimps use tools

 Chimps are humans!

error: humans aren’t the only toolmakers!
  • Rephrasing: If humans are the only toolmakers, and If Chimps use tools, therefore Chimps are humans…

 inductive thinking requires that all premises be true (tested by science)

 this leads to the concepts of measurement error, uncertainty, and probability


Scientific Proofs

Measurement Error!

  • Every measurement is only and approximation! (measurement uncertainties are inevitable)
  • Any measurement is meaningless unless it is presented with an estimate of its uncertainty (variability)

Scientific Knowledge is Inherently uncertain: Probability

  • Scientific observations are always uncertain (not algorithmic!)
  • Reality: at some level, the original observation is always uncertain (the fewer the observation, the higher the uncertainty).
  • “Demontrating” something by inductive reasoning only means that it has a high degree of happening again: probability(e.g., sunrise/sunset)
  • Unfortunately, we may interpret these conclusions as truth (!!!) - And we teach science that way!
probability uncertainty
Probability: uncertainty
  • Scientific precision is based on the degree of uncertainty in the original observation.
  • A conclusion is thus fatally flawed at some level.

accuracy vs precision
Accuracy vs. Precision
  • Accuracy: the degree to which a measurement agrees with an accepted value
  • Accepted value??? Depends on consensus of measurement takers (example: water freezes at 0oC)
  • Precision: the degree of exactness to which the measurement is made (e.g., “that’s hot” vs. 100.000oC  how big is the error bar relative to the value)
  • Question: If you measure the temperature of boiling water and find it to be 98.750oC, are you more or less precise than 100oC? More accurate???
  • Answer: you are more precise, but less accurate
science and objectivity14
Science and Objectivity
  • Myth: Method of Science is directional (procedural)!
  • Doesn’t leave any room for serendipity, creativity, and inspiration.
science and objectivity15
Science and Objectivity
  • Myth: Method of Science is directional!
  • Doesn’t leave any room for serendipity, creativity, and inspiration.
  • However, you must maintain critical thinking about observations

Language of Env. Sciences

  • The overall “picture” is more than just the sum of its components
  • Env. Science is intrinsically non-reductionist by nature!
  • The production of a common language (inclusive rather than reductionist) is primordial to the communication of a mutidisciplinary base of knowledge!
  • Env. Sciences thus need horizontality and verticality!
  • Decision makers (in Env. Sciences) need the language and the basic understanding to create a dialogue between horizontal and vertical seekers

Language of Env. Sciences

  • The difficulty of Env. Sciences is to manage a partial knowledge of complex systems!
  • What is complicated vs. complex?
  • We thus only obtain partial images of complex systems (we try to extrapolate from incomplete knowledge).
  • Uncertainty leads to “precautionary principle”  Absence of certainty should not retard the adoption of efficient measures to prevent large-scale consequences
  • Climate Change – Toxic Elements (As, PCB)