I agree that this is an attractive alternative solution.
And allow me to rephrase. Since human scientists stick too much to the first hypothesis that seems to fit the data (confirmation bias) and have a regrettable tendency unfairly to promote hypotheses that they and their friends discovered (motivated cognition—the motivation being the fame that comes from being known as the discoverer of an important successful hypothesis), it would win for the enterprise of science to move where possible to having algorithms generate the hypotheses.
Since the hypotheses “found” (more accurately, “promoted to prominence” or “favored”) by the algorithms will be expressed in formal language, professionals with scientific skills, PhD, tenure and such will still be needed to translate them into English. Professionals will also still be necessary to refine the hypothesis-finding (actually “hypothesis-favoring”) algorithms and to identify good opportunities for collecting more observations.
I agree that this is an attractive alternative solution.
And allow me to rephrase. Since human scientists stick too much to the first hypothesis that seems to fit the data (confirmation bias) and have a regrettable tendency unfairly to promote hypotheses that they and their friends discovered (motivated cognition—the motivation being the fame that comes from being known as the discoverer of an important successful hypothesis), it would win for the enterprise of science to move where possible to having algorithms generate the hypotheses.
Since the hypotheses “found” (more accurately, “promoted to prominence” or “favored”) by the algorithms will be expressed in formal language, professionals with scientific skills, PhD, tenure and such will still be needed to translate them into English. Professionals will also still be necessary to refine the hypothesis-finding (actually “hypothesis-favoring”) algorithms and to identify good opportunities for collecting more observations.