THE FUTURE OF ARTIFICIAL INTELLIGENCE AT WORK: A REVIEW ON EFFECTS OF DECISION AUTOMATION AND AUGMENTATION ON WORKERS TARGETED BY ALGORITHMS AND THIRD-PARTY OBSERVERS

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Dhaya Sindhu Battina

Abstract

The main purpose of this paper is to review the future of artificial intelligence at work especially how it will affect decision automation and augmentation on workers. Automation and augmentation of decision-making processes in the workplace are becoming more common because of advancements in artificial intelligence. In addition to transforming our homes, smart technologies are also making inroads into a wide range of businesses and causing havoc in the workplace [1]. Although AI can boost productivity, efficiency, and accuracy throughout a company, is this always a good thing for the organization? There is a widespread belief that the advent of AI will result in the replacement of human employees by computers and robots and that this advancement in technology represents a danger rather than an opportunity to improve ourselves. Leaders must understand how AI will affect their workforces and then prepare them by upskilling certain individuals to perform current occupations, but with AI, and retraining and hiring others for the new positions that AI will require. Schools and parents will have to instill in their children a love of STEM as well as a sense of wonder and curiosity for learning throughout their lives [1].

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Dhaya Sindhu Battina. (2018). THE FUTURE OF ARTIFICIAL INTELLIGENCE AT WORK: A REVIEW ON EFFECTS OF DECISION AUTOMATION AND AUGMENTATION ON WORKERS TARGETED BY ALGORITHMS AND THIRD-PARTY OBSERVERS. International Journal of Innovations in Engineering Research and Technology, 5(7), 40-47. https://repo.ijiert.org/index.php/ijiert/article/view/2959
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How to Cite

Dhaya Sindhu Battina. (2018). THE FUTURE OF ARTIFICIAL INTELLIGENCE AT WORK: A REVIEW ON EFFECTS OF DECISION AUTOMATION AND AUGMENTATION ON WORKERS TARGETED BY ALGORITHMS AND THIRD-PARTY OBSERVERS. International Journal of Innovations in Engineering Research and Technology, 5(7), 40-47. https://repo.ijiert.org/index.php/ijiert/article/view/2959

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