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

1. 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.

2. 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

3. 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

4. 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…

5. 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!

6. 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

7. 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.

8. 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!

9. 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

10. 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)

11. 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!

12. Probability: uncertainty • Scientific precision is based on the degree of uncertainty in the original observation. • A conclusion is thus fatally flawed at some level. www.weather.com

13. 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

14. Science and Objectivity • Myth: Method of Science is directional (procedural)! • Doesn’t leave any room for serendipity, creativity, and inspiration.

15. 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

16. Env. Sciences are basically human!

17. 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

18. 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)