Editing Predictability (section)

== In human–computer interaction ==
In the study of [[human–computer interaction]], predictability is the property to forecast the consequences of a user action given the current state of the system.

A contemporary example of human-computer interaction manifests in the development of computer vision algorithms for collision-avoidance software in self-driving cars. Researchers at NVIDIA Corporation,<ref>{{cite web|title=The AI Car Computer for Autonomous Driving|url=http://www.nvidia.com/object/drive-px.html|publisher=NVIDIA|access-date=27 September 2017}}</ref> Princeton University,<ref>{{cite web|last1=Chen|first1=Chenyi|title=Deep Learning for Self -driving Car|url=http://www.princeton.edu/~alaink/Orf467F14/Deep%20Driving.pdf|publisher=Princeton University|access-date=27 September 2017}}</ref> and other institutions are leveraging deep learning to teach computers to anticipate subsequent road scenarios based on visual information about current and previous states.

Another example of human-computer interaction are computer simulations meant to predict human behavior based on algorithms. For example, MIT has recently developed an incredibly accurate algorithm to predict the behavior of humans. When tested against television shows, the algorithm was able to predict with great accuracy the subsequent actions of characters. Algorithms and computer simulations like these show great promise for the future of artificial intelligence.<ref>{{Cite web|url=http://news.mit.edu/2016/teaching-machines-to-predict-the-future-0621|title=Teaching machines to predict the future|date=21 June 2016 }}</ref>