As artificial intelligence (AI) continues to advance, companies face the challenge of selling it to a skeptical public. One of the main issues is the fear of AI replacing human jobs. To address this, companies focus on showcasing AI as a tool that enhances human capabilities rather than a replacement. They emphasize how AI can automate repetitive tasks, allowing employees to focus on more strategic and creative aspects of their work.
Another concern is the need for more transparency and trust in AI systems. An article by
CNBC details, how companies are working on making AI more explainable and understandable to the public. They are developing AI systems that can provide clear explanations for their decisions, ensuring that users better understand how AI works and can trust its outcomes. Preview the chapter,
"Explainable Artificial Intelligence", to delve deeper into how AI can be integrated into all areas of a business.
Moreover, there is a growing need for AI systems to be ethical and unbiased. Companies are implementing strict guidelines and standards for developing and deploying AI to address this. They are also investing in diversity and inclusion efforts to ensure that AI systems are trained on diverse datasets, reducing the risk of bias in their decision-making processes.
The
Encyclopedia of Data Science and Machine Learning (ISBN: 9781799892205) examines current, state-of-the-art research in data science, machine learning, data mining, and more to further enhance the study and understanding of AI. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities.
Preview "Explainable Artificial Intelligence"
Here | Encyclopedia of Data Science and Machine
Learning (5 Vols.) |
Prof. John Wang
© 2023 | 3,143 pgs. | ISBN13: 9781799892205
| - Covers Topics such as Industry 4.0, Maintenance Prediction, and Statistical Model Selection
- Ideal for Data Analysts, Computer Scientists, Technical Managers, and Students
- Featured in the New AI and Machine Learning Brochure
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