Dedomenocracy in action: forecast and response to DC snow event of February 17, 2015

My recent posts have promoted the concept of dedomenocracy as a legitimate form of government. In much of those discussions, I assumed that it was futuristic form of government because data technologies are not yet sufficient to automated normal government decisions. I’ve already noted that we are already seeing the authoritarianism of data in health care. A similar case can be made concerning metropolitan area decisions based on weather forecasts. In these areas, we are experiencing automated decision making where humans given no choice but to follow the recommendations from data (and in particular simulation models).

Model-generated dark data contaminates our data stores with outdated information

There are multiple reports that the epidemic is not spreading as quickly as predicted earlier. These observation deserve more credibility than the simulation results. However, other reports dismiss these observations as being a fault of data collection problems. This dismissal implies a preference for the simulation results instead of direct observations. This use of simulation results as competitive to actual observations is what I call dark data. I value the observations more than I trust simulated data for the same facts.

Discrete Set Simulation

In my discussions on data science, I’ve explored the intersection of my experience with the big data trends.   In particular, I focused on my particular experience in assigning trust to data types, or more accurately my assigning of various levels of suspicions about data.   I don’t think I encountered a data source that…