As I have noted before, something I call the Traditional Template shapes the way most minds approach the issue of design in biology. Basically, the Traditional Template builds on the false dichotomy of “evolution vs. design,” where both sides seem to agree that in order to find evidence of design, we need to disprove the evolution of some feature.
I have suggested an alternative approach.
1. Instead of approaching the issue like a philosopher trying to establish design in one step, approach the issue as a detective looking for clues – inductive gradualism.
2. Instead of taking a negative approach that revolves around skepticism about evolution, take a positive approach that seeks out signals we might expect to see if design occurred.
3. Recognize that we cannot objectively measure design, as “detecting design” is akin to detecting another mind.
Throughout all of this, we need to strive to remain open-minded and intellectually honest, trying to strike the balance between confirmation bias and disconfirmation bias.
To this end, I have offered the Design Matrix. I propose four criteria that, on balance, represent a positive approach – Analogy, Discontinuity, Rationality, and Foresight. We can know the criteria are solid for several reasons:
· As I already have shown, the criteria of Analogy and Discontinuity are effectively used by proponents of SETI.
· Natural selection, working with random mutations, is the only plausible non-teleological candidate for a designer-mimic. But since these processes have no “mind’s eye,” and are thus more likely to generate kluges and frozen accidents, the criteria of Rationality and Foresight are very helpful in distinguishing between genuine design and designoid phenomena.
· If “detecting design” is akin to detecting another mind, pause and consider these are the criteria we use to detect others minds. This is how we know there is another person communicating to us on the other end of the computer and not a blind program.
· I did not invent these criteria. Throughout the years, they have all been used to argue against design by various scientists and philosophers. If these criteria can be used to argue against a design inference, it stands to reason the street can run both ways.
However, it is important to remember that these criteria are not intended as tools to serve the Traditional Template. For example, no argument about analogy or rationality is intended as a means to disprove evolution. These criteria are not “other ways” to stab at evolutionary theory. On the contrary, the criteria work best if used as follows:
First, the criteria should be used as independently as possible. Just as analogy is not evidence against evolution, evidence for evolution is not evidence against analogy. By keeping the scores independent, we steer clear of the Traditional Template and keep our focus on a positive approach to detect signals of another mind. Furthermore, by keeping the criteria independent, it is easier to focus on areas where the case can be strengthened or weakened.
Second, the criteria can be used to the score features along a sliding scale. I set the scale to range from – 5 to +5, where 0 represents an agnostic position (+ means the criteria applies; – means it does not apply; the numerical value represents the level of conviction). The scale is a crucial ingredient because it steers us away from posturing, allows us flexibility in our convictions, and brings yet more focus on where the case can be strengthened or weakened.
After a feature is scored along the four prisms of Analogy, Discontinuity, Rationality, and Foresight, the scores are fused to provide an average score. This fusion gives us a more holistic positive perspective that short-circuits attempts posture evolution against design by removing the God-of-the-Gaps approach, along with the attempts to rule out design by invoking evolution.
The score is, of course, subjective. But that is an irrelevant point if detecting design is akin to detecting another mind. What matters is that it is an informed, subjective assessment that is open to further modification in light of new data or a new appreciation for old data.