  A Bell test can rule out local realistic models, and has potential
applications in communications and information tasks. For example, a Bell
inequality violation can certify the presence of intrinsic randomness in
measurement outcomes, which then can be used to generate unconditional
randomness. A Bell test requires, however, measurements that are chosen
independently of other physical variables in the test, as would be the case if
the measurement settings were themselves unconditionally random. This situation
seems to create a "bootstrapping problem" that was recently addressed in The
BIG Bell Test, a collection of Bell tests and related tests using human setting
choices. Here we report in detail our experimental methods and results within
the BIG Bell Test. We perform a experimental test of a special type of Bell
inequality - the measurement dependent local inequality. With this inequality,
even a small amount of measurement independence makes it possible to disprove
local realistic models. The experiment uses human-generated random numbers to
select the measurement settings in real time, and implements the measurement
setting with space-like separation from the distant measurement. The
experimental result shows a Bell inequality violation that cannot be explained
by local hidden variable models with independence parameter (as defined in
[Putz et al. Phys. Rev. Lett. 113, 190402 (2014).] ) l > 0.10 +/- 0.05. This
result quantifies the degree to which a hidden variable model would need to
constrain human choices, if it is to reproduce the experimental results.
