Consequences for writing teachers
The book’s title also promises consequences. Regardless of their vision of the role of these machines, the contributors are on task and again blunt about their effects. Ericsson hedges not at all: “If composition is about making meaning… then scoring machines are deadly,” and “we need to take responsibility for getting [students] what they deserve” (37). Anson says AI graders “strip writing of its relationship with readers—that is, to turn it from writing into mindless bits of linguistic code” (48). Bob Broad draws on tech criticism to note that many tech advances exact revenge later (a la Edward Tenner’s Why Things Bite Back, perhaps). ETS’s Criterion software claims to save time and reduce labor (appealing to our natural aversion to drudgery?), but Broad says the real motto should be, “Teach your students to write like machines for a reader who is a machine” (224). Once again, people are particularly sharp about the consequences of professional inertness toward technology. Ken McAllister and Edward White say we should not only think harder about computer-assisted writing assessment but about writing assessment, period. We better figure out ways of showing that what we are doing works, they say, otherwise “humanists… will be sent out of the room when serious discussion gets under way between the entrepreneurs and the adopters” (27). This is unforgiving language: We’re being patronized, ignored, and maybe ridiculed; folks, it is time to get angry, because if “we fail to imagine the application” of these technologies to improve education, “we may simply forfeit computer-assisted writing assessment to those who prioritize lucre above literacy” (27).
The book's contributors rarely hold back. But, of course, in a book about a topic as potentially controversial as machine-based scoring of student writing, some problems arise.