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(as of Dec 24,2024 04:21:47 UTC – Details)
From the Publisher
Ethical AI: Bridging Theory and Practice
This book is a practical guide, focusing on applying ethical principles in real-world AI development. It provides a middle ground between technical and philosophical AI texts, offering actionable patterns for responsible AI implementation. Ideal for AI practitioners and decision-makers, it’s a reference to navigate the evolving landscape of AI ethics.
ASIN : B0CLKYVLPY
Publisher : Addison-Wesley Professional; 1st edition (December 8, 2023)
Publication date : December 8, 2023
Language : English
File size : 4194 KB
Simultaneous device usage : Up to 5 simultaneous devices, per publisher limits
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Print length : 320 pages
In recent years, the development and implementation of artificial intelligence (AI) systems have grown exponentially. While AI has the potential to revolutionize industries and improve our daily lives, there are also concerns about the ethical implications and potential risks associated with these systems. In order to ensure that AI is used responsibly and ethically, it is essential to follow best practices for creating trustworthy AI systems.
1. Transparency: One of the key principles of responsible AI is transparency. It is important for developers to be transparent about how AI systems are designed, how they make decisions, and what data they use. This transparency helps build trust with users and stakeholders and ensures that AI systems are accountable for their actions.
2. Fairness: AI systems have the potential to perpetuate existing biases and discrimination if not designed and trained carefully. It is crucial to ensure that AI systems are fair and unbiased by regularly monitoring and auditing them for potential biases and taking corrective actions when necessary.
3. Privacy and data protection: Protecting user data and privacy is essential when developing AI systems. It is important to comply with data protection regulations and implement robust security measures to prevent unauthorized access to sensitive information.
4. Human oversight: While AI systems can automate many tasks and processes, they should always be supervised by humans to ensure that they are making ethical and responsible decisions. Human oversight is essential to prevent AI systems from causing harm or making mistakes.
5. Accountability: Developers and organizations that deploy AI systems should be held accountable for the decisions and actions of these systems. This includes establishing clear guidelines for responsible AI development, implementing mechanisms for addressing potential harms, and being transparent about the limitations of AI systems.
By following these best practices for creating trustworthy AI systems, developers and organizations can ensure that AI is used responsibly and ethically. Responsible AI development is essential for building trust with users and stakeholders, and ultimately, for maximizing the benefits of AI technology.
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