Scaling Responsible AI (eBook)

From Enthusiasm to Execution

Noelle Russell (Autor)

eBook Download: EPUB

2025
409 Seiten
Wiley (Verlag)
978-1-394-28965-3 (ISBN)

Infos

Implement AI in your organization with confidence while mitigating risk with responsible, ethical guardrails

Much like a baby tiger in the wild, artificial intelligence is almost irresistibly alluring. But, just as those tiger cubs inevitably grow up into formidable and fierce adults, the dangers and risks of AI make it a force unto itself. Useful and profitable, yes, but also inherently powerful and risky.

In Scaling Responsible AI: From Enthusiasm to Execution, celebrated speaker, AI strategist, and tech visionary Noelle Russell delivers an exciting and fascinating new discussion of how to implement artificial intelligence responsibly, ethically, and profitably at your organization. Responsible AI promises immense opportunity, but unguided enthusiasm can unleash serious risks. Learn how to implement AI ethically and profitably at your company with Scaling Responsible AI.

In this groundbreaking book, Noelle Russell reveals an executable framework to:

• Harness AI's full potential while safeguarding your firm's reputation
• Mitigate bias, accuracy, privacy, and cybersecurity risks from the start
• Make informed choices by seeing through the hype and identifying true AI value
• Develop an ethical AI culture across teams and leadership

Scaling Responsible AI equips executives, managers, and board members with the knowledge and responsibility to make smart AI decisions. Avoid compliance disasters, brand damage, or wasted resources on AI that fails to deliver.

Implement artificial intelligence that drives profits, innovation, and competitive edge-the responsible way.

NOELLE RUSSELL has extensive experience at the forefront of artificial intelligence innovation, having worked with companies including Microsoft, IBM, Red Hat, Accenture, AWS, and Amazon Alexa. She has worked across industries and remains a staunch advocate for inclusive AI engineering and data practices. Russell is a top-rated keynote speaker and is an expert on how to harness the power of mindful leadership to inspire others.

Textauszug

Introduction

People often ask me how I got started in the technology industry. I think back and remember with a smile that I got started in technology during a time when we all thought the world was going to end. Y2K.

I spent the first 12 years of my career at IBM, entrenched in FORTRAN, Smalltalk, and Java. I taught hundreds of thousands of engineers and system administrators how to go from mainframe to client server, from client server to web/mobile, mobile to cloud, cloud to big data, big data to AI. I have always been on the bleeding edge.

Eventually, my career in the tech industry led me to Amazon, where I found myself at the forefront of innovation, leading a team at Amazon Web Services (AWS). Then, in 2014, an email from Jeff Bezos sparked a new chapter in my journey. The vision was to build the Star Trek computer, and I felt an immediate pull to be part of that journey.

As a caregiver to my dad and a mother of six, my oldest child with Down Syndrome, I was searching for a way to use technology to make the world more accessible to the people I love most. When given a chance to help build something that would allow me to use my voice to change the world, I jumped at the opportunity.

On joining the Alexa team, I immersed myself in creating over 100 Alexa skills in the first year, each reflecting my unique perspective as a woman, a Latina, a mother, and a caregiver. I have over 25,000 five-star reviews and have created new categories on what initially was seen as a kitchen device. I saw more.

In a team dominated by men, I stood as the only woman, the only Latina, and the only mom. Throughout my experiences, I strove to build applications that would go beyond the conventional and help caregivers, empower individuals, and foster personal growth.

This journey led me to understand the profound impact that technology, specifically artificial intelligence (AI), can have in enriching lives. It became my mission to harness this technology to create an inclusive and supportive environment, not just for my son but for countless others who would benefit from its potential.

As I immersed myself in the world of AI and innovation, I encountered both triumphs and challenges. One of the most significant hurdles I faced was the lack of representation of women and people of color in the tech industry. I had to navigate spaces where I often felt like an outlier, continually proving my worth and capabilities in a male-dominated environment. However, rather than succumbing to the pressure, I used these experiences to fuel my passion for creating positive change within the industry.

In my pursuit to advocate for inclusive innovation, I became involved in initiatives aimed at empowering women and underrepresented groups in technology. I mentored aspiring technologists, sharing my own journey and encouraging them to pursue their goals with determination and resilience. Through this work, I sought to build a community where everyone, regardless of their background, could thrive and contribute to the innovation that drives our world forward. The AI Leadership Institute was born.

This intricate intersection of technology, my core values, and advocacy shaped my identity and purpose in profound ways. It fueled my creativity and commitment to effecting positive change, not only for my own family but for communities worldwide. My journey with technology and innovation became a testament to the transformative potential of embracing diverse perspectives and harnessing technology to elevate humanity.

After Amazon, I was recruited to join the team at Microsoft to help launch a new world of democratized AI through Azure AI services. During my tenure there, I influenced over $1 billion in Azure AI sales to the top worldwide brands looking to implement AI solutions, and this was all before 2018.

One thing I learned at Microsoft, Amazon, and IBM is that although it is important to have good technology, you must have responsible leadership to match. Many organizations that invested in AI from 2014 to 2020 struggled to deploy those ideas to production.

This book explores what I saw working and not working in the world of AI at the companies I helped along the way. From playground to production, there are steps the successful have taken, and I want to share those ideas with you. This book will outline the frameworks, checklists, and resources I have used to help advise organizations just like yours.

Artificial intelligence, in the early stages, is a lot like a baby tiger. Through the course of this book, we will tame that tiger into a solution that is safe and responsible and that serves everyone.

What Does This Book Cover?

Artificial intelligence has moved beyond the realm of hype and headlines, becoming an integral force shaping industries, economies, and societies. Yet, with great power comes the need for great responsibility. Scaling Responsible AI: From Enthusiasm to Execution is a definitive guide for leaders, innovators, and practitioners navigating the complexities of building and deploying AI at scale.

This book bridges the gap between the excitement of AI's potential and the disciplined execution required to harness it responsibly. With frameworks like LEAD AI and SECURE AI, practical strategies for scaling, and thoughtful discussions on ethics, governance, and fairness, this book equips readers with the tools to build AI systems that are innovative, impactful, and inclusive. Whether you're grappling with the challenges of ideation, implementation, or long-term resilience, this book provides the insights and lessons needed to lead the AI transformation with confidence and clarity.

• Chapter 1: Lead AI: A Framework for Building Responsible AI In this first chapter, explore the pillars of the LEAD AI framework—a roadmap encompassing Leadership, Ethical foundations, AI governance, Designing for inclusivity, AI strategy, and Implementation—to lay the groundwork for developing artificial intelligence that is helpful, honest, and harmless.
• Chapter 2: The Hype of AI: Capturing the Excitement Explore both the thrilling possibilities and the sobering realities of AI's rapid emergence through analogies like the darling yet dangerous baby tiger, highlighting the importance of responsible and ethical development amid the hype.
• Chapter 3: Building the AI Sandbox: Safe, Responsible Spaces for Innovation Discover how to construct a controlled playground for AI experimentation, from establishing ethical policies and identifying low-risk use cases to aligning innovations with core values and scaling solutions responsibly.
• Chapter 4: From Ideation to Action: Setting Up for Successful Business Outcomes Journey from vision to implementation as we explore strategies for aligning AI with business values, pushing boundaries responsibly, evaluating risks, finding the right complexity level, and ultimately delighting users with remarkable solutions.
• Chapter 5: From Playground to Production: Embracing the Challenges Traverse the details of transitioning from concept to implementation as we tackle infrastructure needs, team dynamics, data challenges, balancing iteration speed with steady progress, and ultimately planning for the long-term sustainability of AI solutions.
• Chapter 6: Beyond the Prototype: What Happens After POC? Transition from prototype to production pilot as we tackle shifting mindsets, visualization, scalability, continuous improvement, and balancing short-term wins with a long-term vision to successfully scale AI solutions and prepare for future challenges.
• Chapter 7: SECURE AI: A Framework for Deploying Responsible AI Explore the SECURE AI framework spanning security, ethics, compliance, bias mitigation, Red Teaming, explainability, accountability, and iteration to responsibly evaluate, develop, and deploy artificial intelligence.
• Chapter 8: Architecting AI: Designing for Scale and Security Master the intricacies of architecting enterprise-grade AI through strategies for security, scalability, evaluating options, and responsible implementation across the full development lifecycle.
• Chapter 9: Why Change Is the Only Constant in AI Navigate the ever-shifting landscape of AI by embracing uncertainty, fostering resilience, encouraging diverse perspectives, prioritizing continuous learning, and crafting a forward-thinking mindset.
• Chapter 10: Model Evaluation and Selection: Ensuring Accuracy and Performance Demystify the complexities of responsible model management, from leveraging open-source AI and maintaining integrity to ensuring fairness, planning updates, utilizing top tools, and proactively preparing for future changes.
• Chapter 11: Bias and Fairness: Building AI That Serves Everyone Confront how bias manifests in AI systems and explore strategies to detect unfairness, increase transparency, mitigate harm, comply with evolving regulations, and ultimately build inclusive AI that serves all equitably.
• Chapter 12: Responsible AI at Scale: Growth, Governance, and Resilience Illuminate the nuances of scaling AI ethically and securely through robust governance frameworks, regulatory navigation, handling disruptions, and ultimately cultivating organizational resilience and adaptability.
• Chapter 13: Looking Back: Lessons Learned and Insights Gained Reflect on lessons learned, gain wisdom from AI experts, and explore strategies like embracing collaborative ecosystems,...

Produkt-Details

• Erscheint lt. Verlag: 18.3.2025
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Theorie / Studium
• Schlagworte: ai execution • AI implementation • AI Risk Management • AI Risk Mitigation • AI risks • artificial intelligence risk management • artificial intelligence risks • ethical AI • Ethical Artificial Intelligence • Responsible Artificial Intelligence
• ISBN-10: 1-394-28965-0 / 1394289650
• ISBN-13: 978-1-394-28965-3 / 9781394289653