Responsible AI Product Development

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.

Auteur
Eva-Marie Muller-Stuler is a senior data science and AI leader and sought-after advisor with over 23 years of industry experience and extensive expertise in leading ground-breaking data science teams and implementations of fully deployed large-scale and global AI projects at leading organizations. She has been recognised as one of The Best Data Scientists in the World by CNVRG and as one of the top 10 Most Influential Women in Technology by Analytics Insights. She advises governments and international bodies, such the United Nations (UN), UNESCO and International Congress for the Governance of AI (ICGAI) and works in collaboration with these bodies on developing a world-wide AI ethics framework. Muller-Stuler is Partner and Leader of the Data & AI practice for EY MENA and has held previous roles as Chief Technology Officer and Chief Data Scientist at IBM and Chief Data Scientist at KPMG. She has led numerous AI deployments and pioneered new concepts and methodologies, such as the Integrated Centre of Excellence strategies, the 7 pillars for successful AI, connected ecosystems with over 10K data signals, new feature engineering techniques and modelling approaches. Muller-Stuler is also a passionate supporter of women in technology and is a mentor, ambassador and co-host of Women in Data Science (WiDS). She is based in Dubai, UAE.

Texte du rabat

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.

Contenu

Chapter - 01: Introduction- What is AI product development; Chapter - 02: Overview of ethical and responsible AI requirements; Chapter - 03: How to assess the problem; Chapter - 04: Risk management and mitigation; Chapter - 05: Data management; Chapter - 06: Team structure and processes; Chapter - 07: Development for deployment; Chapter - 08: Monitoring; Chapter - 09: AI governance and compliance; Chapter - 10: Maintaining for the future