Semantic Scholar Open Access 2017 314 sitasi

Human-in-the-loop Artificial Intelligence

Fabio Massimo Zanzotto

Abstrak

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.

Topik & Kata Kunci

Penulis (1)

F

Fabio Massimo Zanzotto

Format Sitasi

Zanzotto, F.M. (2017). Human-in-the-loop Artificial Intelligence. https://doi.org/10.1613/jair.1.11345

Akses Cepat

Lihat di Sumber doi.org/10.1613/jair.1.11345
Informasi Jurnal
Tahun Terbit
2017
Bahasa
en
Total Sitasi
314×
Sumber Database
Semantic Scholar
DOI
10.1613/jair.1.11345
Akses
Open Access ✓