Price: $43.13
(as of Dec 24,2024 02:44:22 UTC – Details)
Publisher : Packt Publishing (July 31, 2023)
Language : English
Paperback : 318 pages
ISBN-10 : 1803230525
ISBN-13 : 978-1803230528
Item Weight : 1.23 pounds
Dimensions : 9.25 x 7.52 x 0.67 inches
In today’s rapidly evolving digital landscape, the use of artificial intelligence (AI) in enterprise settings is becoming increasingly prevalent. However, with great power comes great responsibility, and it is crucial for organizations to prioritize responsible AI practices in order to mitigate potential risks and ensure the development of transparent, auditable, and safe AI models.
One key aspect of responsible AI in the enterprise is the need for explainable AI models. This means that AI systems should be designed in a way that allows their decisions and actions to be easily understood and interpreted by humans. By prioritizing explainability, organizations can ensure that their AI models are transparent and accountable, which is essential for building trust with stakeholders and regulatory bodies.
Another important consideration for responsible AI in the enterprise is the implementation of robust auditability mechanisms. This involves keeping detailed records of the data used to train AI models, as well as the decisions made by these models in real-world applications. By maintaining thorough audit trails, organizations can identify and address potential biases, errors, or unintended consequences in their AI systems, ultimately improving their overall performance and reliability.
When it comes to building safe AI models, organizations can benefit from partnering with hyperscalers like Microsoft Azure and OpenAI. These industry leaders offer a range of tools and services that can help enterprises develop and deploy AI solutions in a secure and compliant manner. By leveraging the expertise and resources of hyperscalers, organizations can enhance the robustness and resilience of their AI models, while also staying ahead of emerging threats and regulatory requirements.
In conclusion, responsible AI in the enterprise is essential for building trust, ensuring compliance, and maximizing the value of AI technologies. By prioritizing explainability, auditability, and safety in their AI initiatives, organizations can mitigate risks, drive innovation, and create lasting positive impact for both their businesses and society as a whole.
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