Name: Fears and Worries With Biases in Artificial Intelligence: An Academic Perspective for Ethical Analysis of Biasespossible With ai (en Inglés)
Price: 216.34 PEN
Availability: InStock
Author: Mohammad Kaleem Galamali
ISBN: 9786206157830

portada Fears and Worries With Biases in Artificial Intelligence: An Academic Perspective for Ethical Analysis of Biasespossible With ai (en Inglés)

Formato

Libro Físico

Editorial

Lap Lambert Academic Publishing

Autor

Mohammad Kaleem Galamali

Idioma

Inglés

N° páginas

Encuadernación

Tapa Blanda

ISBN13

9786206157830

Fears and Worries With Biases in Artificial Intelligence: An Academic Perspective for Ethical Analysis of Biasespossible With ai (en Inglés)

Mohammad Kaleem Galamali (Autor) · Lap Lambert Academic Publishing · Tapa Blanda

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Reseña del libro "Fears and Worries With Biases in Artificial Intelligence: An Academic Perspective for Ethical Analysis of Biasespossible With ai (en Inglés)"

With Development AI, many people are just being overwhelmed and go by the trust that everything is fine with the trend of 'sophistication'. Experts know that this is not already the case unless specific implementations is oriented accordingly. The field which studies the matter is "Ethics", whereby several factors for societal benefits are considered. Each technology can be a contributing piece of power. Correspondingly, the need for preventing such powers from corruptions must be devised and implemented, along with technical progresses. Despite all these features, fears and worries due to AI biases prevail. There is need for distinct studies about ethics in AI to well understand the roots of such fears and worries. The subsequent objective is to formulate appropriate ethics guidelines and implementation pathways to be imbibed in development procedures. One means is to dig down the criticisms of AI to serious levels or previously unidentified levels, even if some may consider it disturbing or pessimistic, and formulate appropriate studies around them. Ethical objective of producing clean/workable/acceptable enhancements in AI, especially as concerns human factors can be worked out.