scholarly journals Wireless monitoring and artificial intelligence: A bright future in cardiothoracic surgery

2020 ◽  
Vol 160 (3) ◽  
pp. 809-812
Author(s):  
David Kalfa ◽  
Sunil Agrawal ◽  
Nimrod Goldshtrom ◽  
Damien LaPar ◽  
Emile Bacha
2022 ◽  
pp. 139-153
Author(s):  
Renu Yadav

AI-oriented CRM has a bright future in business transformation. We're living in the age of the customer. Due to the proliferation of data, customers are more informed than ever. Armed with empowerment, customers are demanding that customer experience be put on a pedestal. According to research by Walker, customer experience is slated to overtake price and product as the key brand differentiator by the end of 2020. Quality is a buzz word. In this sharp, opportunistic, and calculating world, one can survive only if it is having not only good quality but a unique quality. As it is very well explained by Darwin that the mantra for success is “survival of fittest.” Every organization has its own procedure of achieving its best quality and to sustain in this tough world. This chapter will not only discuss about the zero customer defection but also emphasize on the issues, problems, and trends of artificial intelligence in CRM and in turn zero customer defection.


2020 ◽  
Vol 110 (2) ◽  
pp. 373
Author(s):  
Brendan Jones ◽  
Benjamin Reed ◽  
JW Awori Hayanga

2020 ◽  
Vol 68 (5) ◽  
Author(s):  
Roger D. Dias ◽  
Julie A. Shah ◽  
Marco A. Zenati

2019 ◽  
Vol 64 ◽  
pp. 243-252 ◽  
Author(s):  
Fabio Massimo Zanzotto

Little by little, newspapers are revealing the bright future that Artificial Intelligence (AI) is building. Intelligent machines will help everywhere. However, this bright future may have a possible dark side: a dramatic job market contraction before its unpredictable transformation. Hence, in a near future, large numbers of job seekers may 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. Many learning AI machines are extracting knowledge from unaware skilled or unskilled workers by analyzing their interactions. By passionately doing their jobs, many of these workers are shooting themselves in the feet. In this paper, we propose Human-in-the-loop Artificial Intelligence (HitAI) as a fairer paradigm for AI systems. Recognizing that any AI system has humans in the loop, HitAI will reward these 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 Merry Men, HitAI researchers should fight for a fairer Robin Hood Artificial Intelligence that gives back what it steals. This article is part of the special track on AI and Society.


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