Title: Sensory Metrics of Neuromechanical Trust,
Abstract: Today digital sources supply an unprecedented component of human sensorimotor
data, the consumption of which is correlated with poorly understood maladies
such as Internet Addiction Disorder and Internet Gaming Disorder. This paper
offers a mathematical understanding of human sensorimotor processing as
multiscale, continuous-time vibratory interaction. We quantify human
informational needs using the signal processing metrics of entropy, noise,
dimensionality, continuity, latency, and bandwidth. Using these metrics, we
define the trust humans experience as a primitive statistical algorithm
processing finely grained sensorimotor data from neuromechanical interaction.
This definition of neuromechanical trust implies that artificial sensorimotor
inputs and interactions that attract low-level attention through frequent
discontinuities and enhanced coherence will decalibrate a brain's
representation of its world over the long term by violating the implicit
statistical contract for which self-calibration evolved. This approach allows
us to model addiction in general as the result of homeostatic regulation gone
awry in novel environments and digital dependency as a sub-case in which the
decalibration caused by digital sensorimotor data spurs yet more consumption of
them. We predict that institutions can use these sensorimotor metrics to
quantify media richness to improve employee well-being; that dyads and
family-size groups will bond and heal best through low-latency, high-resolution
multisensory interaction such as shared meals and reciprocated touch; and that
individuals can improve sensory and sociosensory resolution through deliberate
sensory reintegration practices. We conclude that we humans are the victims of
our own success, our hands so skilled they fill the world with captivating
things, our eyes so innocent they follow eagerly.