1. The Drake Equation Assumptions & Science
A demonstration internal assessment oral for IB Theory of Knowledge
[ S.Kern, 2015 ]
Assumptions & Science

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3. SETI and the Drake Equation
1 minute
The first SETI (Search for ExtraTerrestrial Intelligence) conference in 1961 at the National Radio Astronomy Observatory in West Virginia with Dr. Frank Drake, presiding:
“As I planned the meeting, I realized we needed an agenda. So I wrote down all the things you needed to know to predict how hard it’s going to be to detect extraterrestrial life. And looking at them, it became pretty evident that if you multiplied them all together you got a number, N, which is the number of detectable civilizations in our galaxy.”
Here is the “Drake Equation:”
N = R* fp ne fl fi fc L
Describing the RLS

4. N = R* fp ne fl fi fc L
Where N = The number of intelligent, communicative civilizations in the galaxy
R* = The rate of formation of suitable stars [5 per year]
fp = The fraction of those with planets [50%]
ne = The number of Earth-like worlds per system [2]
fl = The fraction of those where life develops [100%]
fi = The fraction of those where intelligence develops [20%]
fc = The fraction of the those that develop communicative technology [100%]
L = The "lifetime" in years of those civilizations [10,000]
Drake’s original estimate:
N = 10,000 intelligent, communicative civilizations in the galaxy
1 minute
Describing the RLS

5. Knowledge Question
30 seconds
How do scientists justify the assumptions they use to make estimates?
In this context, an assumption is an unproven but plausible speculation.
Stating the KQ

6. Exploring / developing KQ generally – do not refer to RLS here!
Assumptions
2 minutes
Purpose: Critical to research and unavoidable
Start somewhere: like “givens” in math
Determine what/how we investigate
Fine-tuning & improvement
Main ways of justification
Extrapolating
Constructing models
Making arbitrary guesses
Limitations
Reliability: Data
Validity: Models
“The problem of induction”
Exploring / developing KQ generally – do not refer to RLS here!

7. How were Drake’s assumptions justified?
Extrapolating from known facts (data)
R* = rate of suitable star formation [5 per year]: well-justified - based on extensive data through direct observation
fp = fraction with planets [50%]: less well-justified - based on some empirical data and indirect observation
Use of models (our earth and solar system)
ne = Earth-like worlds per system [2]:
fl = The fraction of those where life develops [100%]
Validity: Are these models representative of other systems?
Arbitrary guesses
fi = The fraction of those where intelligence develops [20%]
fc = The fraction of those that become communicative [100%]
L = The "lifetime" of these civilizations [10,000]
Little justification: little or no data (deductive not inductive)
If N is 10,000, where are all the ET’s?
Could some of Drake’s assumptions been faulty?
Over the years, other perspectives have offered very different assumptions (and N’s)!
2 minutes
Applying KQ to RLS

8. Other real life situations
Other RLS’s in which assumptions play major roles
Global warming / climate change
Battling epidemics/pandemics of “spillover” diseases
Common denominators
Extrapolation
Projecting trends
Building representative models
Using computers to simulate complex situations
1 minute
Demonstrating significance: other RLS’s

9. Demonstrating significance: overall
Significance: So what?
No exaggeration: Improving our assumptions can be a matter of life and death.
Well-justified assumptions…
Clarify expectations & potential outcomes
Inform action
Next steps for research
Policy decisions
i.e., If our assumptions make a dangerous outcome seem unlikely, we are less likely to act.
The problem of arbitrary guesses:
“Garbage in, garbage out” vs. “but we have to start somewhere.”
Therefore, even the most well-justified assumptions need to be explicit, debated, and revised with further research.
1 minute
Demonstrating significance: overall

10. Want to add your own perspective?
Check out an interactive version of the Drake Equation with you can adjust the assumptions: