Abstract: Scott Aikin and Robert Talisse have recently argued strenuously against James’ permissivism about belief. They are wrong, both about cases and about the general issue. In addition to the usual examples, the paper considers the importance of permissiveness in scientific discovery. The discussion highlights two different strands of James’ argument: one driven by doxastic efficacy and another driven by inductive risk. Although either strand is sufficient to show that it is sometimes permissible to believe in the absence of sufficient evidence, the two considerations have different scope and force.
The LA Times has an interesting interview with self-described “data skeptic” Cathy O’Neil, the author of Weapons of Math Destruction. Although the Times puts her skepticism in terms of big data, her concerns are really about values in science. Algorithms, she suggests, have a veneer of objectivity but always reflect choices and valuations. When the algorithms are secret, then the values incorporated in them aren’t open to scrutiny. She says:
I want to separate the moral conversations from the implementation of the data model that formalizes those decisions. I want to see algorithms as formal versions of conversations that have already taken place.
She also makes a point about how polling isn’t just objectively reporting on the state of the electorate, something I would probably have mused about if I’d written the post about the election that I never quite wrote:
[P]olitical polls are actually weapons of math destruction. They’re very influential; people spend enormous amounts of time on them. They’re relatively opaque. But most importantly, they’re destructive in various ways. In particular, they actually affect people’s voting patterns. … Polls can change people’s actual behavior, which disrupts democracy in a direct way.
I’ve ordered a copy of her book, and when it arrives I will put it on top of the stack of books I regret not having read.
There are a number of different connections between values to science. These sometimes get lumped together in the values and science literature. Even when they are distinguished, it isn’t always noted that each connection (1) applies to somewhat different values and (2) applies to somewhat different aspects or parts of science.
I distinguish five different ways in which values and science are connected in a preliminary attempt to sort some of this out.
By coincidence, my seminar on science and values covered Rudner’s Argument from Inductive Risk on the same day that Matt Brown posted an exchange about the Argument with Joyce Havstad. It’s taken me a couple of days to collect my thoughts.