As Yilun Wang and Michal Kosinski pointed out, technology such as this is eagerly funded with ease by marketers and big technology, instead of academia. One such for-profit, physiognomic-profiling startup, the Israeli company/application Faception, reveals little about its algorithms or operations but promises it has a “high” accuracy rate of 91 percent for recognizing and categorizing personality types (via facial recognition), given a set of photographs. In a survey, an estimated 68 percent of filmmakers changed their plans and added more significant female presence to their movie projects after hearing of the Geena Davis Institute/Google study findings. As information visualizations have become easier to make and manipulate with digital technology, the operations and histories of image-making processes are all the more informative to historicizing and understanding today’s practices. Photography increasingly contributed its voice to this project as the nineteenth century progressed. The chapter also presents some closing thoughts on the key concepts discussed in the preceding chapters of this book.