Any initial approach of measuring anything (here: book interests) can be attacked on its simplicty.
Neccessarily the first measure will have lots of unwanted special cases and it is just too easy to point these out -
especially if they are obviously biased toward economic value.
[Trying to simplify] is a goal of dumbing down books to get stupid people to understand them. That’s why people cite 1984. Orwell’s newspeech is also about dumbing down intellectual discourse.
It is also easy to laud any approach of measuring based on the gain of information/knowledge it entails and transitively the improvements that gains.
What gets measured gets optimized.
It is always more difficult to see where such a measurement really leads.
Extrapolating can be done on different complexity levels.
The simplest is always to just assume maximization of the measureable (here: maximize fun and by sales monetary gains).
The next level is to consider effects of the maximization and balancing effects (it may fall short or it might tip the system; here: dumbing down authorship tips with Hollywood-sickness result).
Another direction is to consider improvements to the measurement. What else might be measured to give authors feedback? And what results from maximizing that?
The next level is to consider the effect of the public on the process of measurement.
Ultimately one can envision to model this as part of a societal dynamic stabilizing on a fixed point. I wonder whether prediction markets can reach such a level.
My prediction:
The public will voice concerns (as already seen in the comments). This alone will initially have little effect as long as profits can be generated by the measure and not much actual change is visible.
Alternative measures will be introduced by competitors. Some tuned to niches e.g. by measuring not only fun but ‘quality’.
NGOs will monitor companies’ (ab)use of the measure(s).
Policy makers address such issues.
Consolidation sets in.
Development over time is documented.
Actually one can always build such a prediction by assuming the topic develops sufficiently to be come worthy of study.
The direction in time is mostly
math (can it be done) →
technology (how is it done effectively) →
economics (how to generate value from it) →
sociology (how does is affect people) →
politics (aggregate people affects) →
philosophy (reflection and rationalization) →
historics (posthoc documentation)
Any initial approach of measuring anything (here: book interests) can be attacked on its simplicty. Neccessarily the first measure will have lots of unwanted special cases and it is just too easy to point these out - especially if they are obviously biased toward economic value.
It is also easy to laud any approach of measuring based on the gain of information/knowledge it entails and transitively the improvements that gains.
It is always more difficult to see where such a measurement really leads. Extrapolating can be done on different complexity levels.
The simplest is always to just assume maximization of the measureable (here: maximize fun and by sales monetary gains).
The next level is to consider effects of the maximization and balancing effects (it may fall short or it might tip the system; here: dumbing down authorship tips with Hollywood-sickness result).
Another direction is to consider improvements to the measurement. What else might be measured to give authors feedback? And what results from maximizing that?
The next level is to consider the effect of the public on the process of measurement.
Ultimately one can envision to model this as part of a societal dynamic stabilizing on a fixed point. I wonder whether prediction markets can reach such a level.
My prediction:
The public will voice concerns (as already seen in the comments). This alone will initially have little effect as long as profits can be generated by the measure and not much actual change is visible.
Alternative measures will be introduced by competitors. Some tuned to niches e.g. by measuring not only fun but ‘quality’.
NGOs will monitor companies’ (ab)use of the measure(s).
Policy makers address such issues.
Consolidation sets in.
Development over time is documented.
Actually one can always build such a prediction by assuming the topic develops sufficiently to be come worthy of study. The direction in time is mostly math (can it be done) → technology (how is it done effectively) → economics (how to generate value from it) → sociology (how does is affect people) → politics (aggregate people affects) → philosophy (reflection and rationalization) → historics (posthoc documentation)
Damn. I can’t write short comments.