- Designed specifically for leaders of AI, data and product teams seeking to develop and deploy trusted, responsible AI for their organizations
- Covers the entire product lifecycle process, from thought exercise to ideation, development, creation, testing and delivery including post-delivery care and end of life management
- Written by an AI pioneer who has been recognized as one of the best data scientists in the world and who has led ground-breaking implementations of fully deployed large-scale AI projects
- Considers key issues such as cybersecurity, data architecture and collection, team structure and processes, deployment and best practices for successful implementation, monitoring and churn, AI governance and compliance and AI sustainability.
- Draws on over 20 years' of cutting-edge, tried and tested industry experience to help tech leaders navigate risk and pitfalls
Responsible AI Product Development
How Tech Leaders Can Develop and Deploy Ethical AI
Grasp how to deliver fully deployed and scalable, trusted and responsible AI and avoid expensive failed solutions and limited proof-of-concepts with this practical guide covering the lifecyle process of AI product development.
Key features at a glance
Temporarily Unavailable
EAN: 9781398617599
Edition: 1
Published:
Format: 234x156
304 pages
About the book
Responsible AI Product Development shows how data, product and tech leaders can drive the development and deployment of trusted, responsible AI and navigate the associated risks and pitfalls.
The book is designed for data, product and tech leaders who are seeking to implement structure and processes to ensure the development of responsible AI products compliant with best practice and key regulatory requirements. It guides readers from inception and team setup of AI through to use case development, full deployment, and monitoring, equipping them with the knowledge and tools they need to ensure an ethical and trusted product. It also helps readers understand the risks and challenges in AI product deployment, giving them guidance on what is important and how to avoid common mistakes.
Responsible AI Product Development offers coverage of the real lifecycle process, from thought exercise to ideation, development, creation, testing and delivery including post-delivery care and end of life management. It combines coverage of ethics and transparency with the technical, procedural and development-focused fundamentals, such as MLOPs, ModelOps, AIOps, TDD and SDLC guidance. It also considers key issues such as cybersecurity and DevSecOps, data architecture, collection and visualisation, team structure and processes, project documentation, business continuity and disaster recovery, AI governance and compliance and AI sustainability.
About the authors
Eva-Marie Muller-Stuler has been recognized as one of the world's best data scientists and as one of the top 10 most influential women in technology. Muller-Stuler is Partner and Leader of the Data & AI practice for EY MENA and has previously held roles such as Chief Technology Officer and Chief Data Scientist at IBM and Chief Data Scientist at KPMG. She advises governments and the UN, UNESCO and ICGAI on the risks of AI and collaborates with them on developing a world-wide AI ethics framework. She is based in Dubai, UAE.
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