AI-Driven Models for Enhanced Healthcare, Social Analytics, and E-Commerce- Balancing Innovation with Performance and Ethics

Authors

  • Dr. Geoffrey Hinton Author
  • Dr. Sebastian Thrun Author

Keywords:

Artificial Intelligence (AI), Healthcare Innovation, Social Analytics, Consumer Behavior, E-Commerce, Data Privacy, Algorithmic Bias, Machine Learning, Ethical AI, Personalization, Predictive Analytics, Algorithmic Fairness, AI in Healthcare Ethics, Transparency in AI

Abstract

Artificial Intelligence (AI) has rapidly emerged as a transformative technology, reshaping multiple industries by offering solutions that improve efficiency, enhance decision-making, and foster innovation. In healthcare, AI is driving advancements in diagnostic systems, personalized treatment plans, and drug discovery, enabling more accurate and timely interventions. In the field of social analytics, AI models are employed to understand consumer behavior, predict trends, and gauge public sentiment through the analysis of massive datasets derived from social media, surveys, and other platforms. Similarly, e-commerce businesses leverage AI to deliver personalized customer experiences, optimize supply chains, and enhance marketing strategies by analyzing customer data and predicting future purchasing behavior. However, while AI brings remarkable benefits in these sectors, it also raises complex challenges regarding ethics, fairness, privacy, and accountability. The rapid integration of AI systems must be carefully balanced with performance considerations and ethical implications to avoid unintended consequences such as algorithmic biases and breaches of data privacy. This paper delves into the state-of-the-art AI models used across healthcare, social analytics, and e-commerce, discussing the trade-offs between technological innovation and ethical considerations. Through an exploration of these domains, this research emphasizes the need for robust frameworks and regulatory measures to ensure responsible and transparent AI implementation, fostering trust and equity in AI-driven applications.

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Published

2024-11-16

How to Cite

AI-Driven Models for Enhanced Healthcare, Social Analytics, and E-Commerce- Balancing Innovation with Performance and Ethics. (2024). AlgoVista: Journal of AI & Computer Science, 1(3). https://algovista.org/index.php/AVJCS/article/view/34

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