Title: Human-in-the-loop Artificial Intelligence,
Abstract: Little by little, newspapers are revealing the bright future that Artificial
Intelligence (AI) is building. Intelligent machines will help everywhere.
However, this bright future has a dark side: a dramatic job market contraction
before its unpredictable transformation. Hence, in a near future, large numbers
of job seekers will need financial support while catching up with these novel
unpredictable jobs. This possible job market crisis has an antidote inside. In
fact, the rise of AI is sustained by the biggest knowledge theft of the recent
years. Learning AI machines are extracting knowledge from unaware skilled or
unskilled workers by analyzing their interactions. By passionately doing their
jobs, these workers are digging their own graves.
In this paper, we propose Human-in-the-loop Artificial Intelligence (HIT-AI)
as a fairer paradigm for Artificial Intelligence systems. HIT-AI will reward
aware and unaware knowledge producers with a different scheme: decisions of AI
systems generating revenues will repay the legitimate owners of the knowledge
used for taking those decisions. As modern Robin Hoods, HIT-AI researchers
should fight for a fairer Artificial Intelligence that gives back what it
steals.