Thank you so much for joining us in this interview series. Before we dive into our discussion our readers would love to “get to know you” a bit better. Can you share with us the backstory about what brought you to your specific career path?
My journey as a business leader has been powered by three core drivers — a curiosity that fuels continuous learning, a deep-seated desire to solve impactful problems and enhance people’s lives, along with a strong belief in technology as a catalyst for change.
This journey includes a diverse career path as an emerging technology leader, impact driver and community builder for responsible innovations. Leveraging technologies like DLT, AI, the metaverse, clean tech and Web3, I’ve worked towards creating an efficient, green and inclusive financial system for all.
Along the way, I’ve led teams, developed products and initiated collaborative efforts at esteemed institutions like the World Bank, United Nations, Amazon Web Services, FinTech4Good, and AI 2030, all aimed at driving positive changes aligned with UN SDGs.
My firm belief is in people as the true agents of change. Much of my work revolves around empowering individuals through knowledge sharing, community and partnership building, collaborative initiatives, workforce development, entrepreneurship, and venture creation. I’m convinced that organizations, regardless of their size, have the potential to be responsible agents for positive change.
What do you think makes your company stand out? Can you share a story?
AI2030 is a member-based initiative aiming to harness the transformative power of AI to benefit humanity while minimizing its potential negative impact. Focused on Responsible AI, AI for All, and AI for Good, we aim to bridge awareness, talent, and resource gaps, enabling responsible AI adoption across public and private sectors. Our vision resonates widely, enabling us to attract a diverse group of over 500 responsible AI leaders and experts from over 30 countries in just a few months.
What truly distinguishes AI2030 is our proactive approach to fostering the next generation of AI leadership through the AI2030 Global Fellows program. This program attracts brilliant minds worldwide, fostering a diverse community dedicated to ethical AI development and use. Rapidly growing, we’ve welcomed over 100 Fellows from more than 10 countries, reflecting our global appeal and mission relevance. A prime example of our unique contribution is the initiation of eight cross-border responsible AI research projects by our Fellows and Associates. These projects unite AI researchers, ethicists, and practitioners from diverse backgrounds to formulate industry-specific responsible AI frameworks, open AI databases, and technical solutions to enhance the responsible design and deployment of AI.
You are a successful business leader. Which three-character traits do you think were most instrumental to your success? Can you please share a story or example for each?
1. Caring for Humanity: My career, rooted in a profound commitment to humanity, has been deliberately directed towards meaningful pursuits including poverty alleviation, climate change mitigation, advancing fintech for social benefit, and promoting responsible AI. This path has led me to work with prestigious organizations such as the World Bank, United Nations, Amazon Web Services, FinTech4Good, and AI 2030, where I’ve dedicated myself to leveraging technology and innovation for the greater good.
2. Think Big: Recognizing the urgent need for substantial investment in climate solutions, I spearheaded the formation of the “Billions for Trillions Climate Alliance,” launched at COP28. The goal was to pool resources and investments worth billions of dollars from various stakeholders to support AI and Web3-enabled, need-based climate innovations. This initiative aimed not only to propel existing solutions towards commercial viability but also to facilitate the emergence of groundbreaking frontier innovations.
3. Learn and Be Curious: The trait of “Learn and Be Curious” has fundamentally shaped my career, guiding me through diverse roles as an emerging technology leader, impact driver, and responsible innovation builder. This unwavering commitment to continual learning and exploration has allowed me to harness the potential of cutting-edge technologies like Distributed Ledger Technology (DLT), AI, the metaverse, clean tech, and Web3, while integrating insights from economics, public policy, ethics, and social science to propel my mission forward. It is this curiosity and relentless pursuit of knowledge that has been instrumental in shaping the professional I am today, enabling me to contribute meaningfully to the fields I am passionate about.
Let’s now move to the main point of our discussion about AI. Can you explain how AI is disrupting your industry? Is this disruption hurting or helping your bottom line?
Generative AI is the most disruptive. If not managed responsibly, it will hurt the bottom line of all industries. That’s why we work on responsible AI. When delving into the impact of AI on our industry, it’s crucial to acknowledge its dual nature. AI serves as a powerful tool, elevating efficiency, enabling professionals to excel, improving customer experiences, and revitalizing previously unsustainable business models through cost savings. However, this transformative force also introduces risks such as job displacement, deep fakes, environmental impact of AI training and concerns about transparency and fairness. The key lies in comprehending this dual nature and its impact to the bottom line, establishing appropriate frameworks, processes, and governance structures to minimize risks, while strategically harnessing the manifold benefits that AI offers.
Which specific AI technology has had the most significant impact on your industry?
Generative AI has had a tremendous impact on many industries, emerging as a disruptive force with widespread applications. From synthesizing original content to generating complex code, from crafting personalized consumer services to pioneering new frontiers in research and development, Generative AI is reshaping traditional business models. Businesses eager to participate in the generative AI revolution often grapple with a fundamental lack of understanding regarding its associated risks. Addressing bias and ensuring inclusivity in AI requires deliberate actions to design algorithms that are representative and fair, actively working to eliminate prejudices within AI systems. Moreover, to mitigate the greenhouse gas (GHG) emissions from AI training, we must invest in green computing and energy-efficient AI infrastructures. Minimizing the negative impacts of AI-related incidents involves establishing comprehensive responsible AI guidelines and robust monitoring systems. As the landscape of AI’s impact continues to unfold, it is imperative that businesses and policymakers collaborate to navigate these uncharted territories responsibly.
Can you share a pivotal moment when you recognized the profound impact AI would have on your sector?
A pivotal moment that highlighted the profound impact AI would have on our sector came with the convergence of several key developments:
- The proliferation of deepfakes and a surge in AI-related incidents laid bare the critical need for responsible AI practices. These examples demonstrated not just the power of AI to innovate but also its potential to harm if not guided by responsible AI principles.
- Simultaneously, we observed a global trend towards the advancement of AI regulations. This marked a significant shift towards structured oversight and governance of AI technologies, underscoring the importance of aligning AI development with responsible AI frameworks.
- Additionally, the emergence of responsible AI awareness campaigns spearheaded by various organizations played a crucial role. These initiatives were instrumental in spreading knowledge about the importance of ethical and responsible AI practices, bridging the gap between technological advancement and ethical oversight across different geographies and industries.
How are you preparing your workforce for the integration of AI, and what skills do you believe will be most valuable in an AI-enhanced future?
Addressing the integration of AI into the workforce and the skills required for an AI-enhanced future requires a multifaceted approach. At AI 2030, we are deeply committed to bridging the Responsible AI skills gap by fostering an environment that prioritizes equal opportunities and inclusivity.
- Commitment to Skill Development: AI 2030 is dedicated to mitigating the Responsible AI skills gap, ensuring a diverse and inclusive AI workforce that represents a wide array of perspectives and talents.
- Tailored Educational Programs: We have curated a suite of courses tailored to various industries and job roles, ensuring that professionals from regulated industries have access to the necessary training in Responsible AI.
- Specialized Training for Financial Leaders: Our forthcoming course, Responsible AI for Financial Leaders, is designed to equip financial executives with a comprehensive understanding of Responsible AI principles, industry best practices, and the knowledge to become pioneers in Responsible AI leadership.
- Balancing Technical and Non-Technical Skills: While technical proficiency in AI is critical, non-technical skills such as governance, ethics, legal understanding, and social science acumen are equally vital in ensuring AI is used responsibly.
What are the biggest challenges in upskilling your workforce for an AI-centric future?
Upskilling a workforce for an AI-centric future presents several significant challenges:
- Building a Learning Culture: Cultivating an environment where continuous learning is valued and encouraged is pivotal. Employees must be motivated to embrace change and adapt to new technologies, which requires a shift in mindset from both management and staff.
- Addressing the Fear of Replacement by AI: Many employees fear obsolescence as AI technologies advance. To mitigate this, companies must communicate the complementary role of AI and highlight the new opportunities it creates, rather than simply the jobs it could replace.
- Supporting Those Negatively Impacted by AI: It’s crucial to recognize and address the concerns of employees who may be adversely affected by AI integration. Providing retraining and redeployment options can help transition these workers into new roles where they can excel alongside AI.
- Providing a Solid Learning Experience: Offering effective education and training that is engaging and relevant to the employees’ roles is essential. The content must not only be current but also designed to equip the workforce with practical skills that can be applied in an AI-enhanced workplace.
What ethical considerations does AI introduce into your industry, and how are you tackling these concerns?
AI indeed brings intricate ethical challenges across all industries. To navigate these, AI 2030 leadership has crafted the AI 2030 Responsible AI Framework, which is built on six foundational pillars, addressing key risks and providing measures for each:
- Safety and Security: We mandate rigorous testing and risk assessments to ensure AI systems are safe and secure, safeguarding against malfunctions and misuse.
- Transparency: Our framework requires AI systems to be transparent in their operations, providing clear explanations for decisions and processes to foster trust and accountability.
- Fairness: We employ tools and methodologies to detect and correct biases, aiming for equitable AI that treats all user groups fairly.
- Accountability: We have established protocols for AI accountability, ensuring there are measures in place to attribute responsibility for AI behavior and its consequences.
- Privacy: Our framework enforces strict data governance policies that prioritize user consent and data protection, ensuring AI respects privacy and confidentiality.
- Sustainability: We advocate for AI solutions that support environmental and social sustainability, promoting long-term beneficial impacts on society.
What are your “Five Things You Need To Do, If AI Is Disrupting Your Industry”?
In the face of AI disruption, we developed these five steps to navigate this transformation effectively:
- Embrace Continuous Learning: Stay abreast of AI advancements. For instance, finance professionals updating their skills with AI algorithms have gained a competitive edge.
- Commit to Our Responsible AI Pledge: Ensure your AI use aligns with a responsible AI framework, e.g., the AI 2030 Responsible AI Framework.
- Conduct a Responsible AI Maturity Assessment: Evaluate your responsible AI readiness to pinpoint strengths and areas for growth, guiding your strategic focus.
- Design Responsible AI Actions: Following the insights from your AI maturity assessment, craft targeted responsible AI strategies to effectively address challenges across people, processes, and technology, thereby steering your organization towards responsible AI leadership.
- Engage in Collaborative Initiatives: Join forces with others in your industry to share knowledge, tackle regulatory challenges, and innovate together.
What are the most common misconceptions about AI within your industry, and how do you address them?
In addressing common misconceptions about AI, it’s crucial to engage in informed discussions and educational efforts. Here is more detail:
Misconception: Development First, Consequences Later
- Reality: There’s a misconception that we can develop AI technologies without immediate concern for their broader impacts and risks, prioritizing innovation over responsible AI practices. This approach risks significant societal costs and potentially irreversible consequences.
- Addressing It: Emphasizing responsible AI development from the start is crucial to prevent negative outcomes and ensure that AI advancements benefit society without crossing a point of no return. Fostering awareness and understanding of responsible AI practices is key to navigating these challenges effectively
- Misconception: There’s a prevalent belief that bridging the AI talent gap should be a company’s primary focus, considering the gap in responsible AI talents as secondary and easier to address.
- Reality: In the current landscape of AI projects, the ratio often stands at 30 technical experts to just one specialist knowledgeable about ethics. This imbalance can lead to the development of unethical AI systems, resulting in adverse societal impacts, substantial compliance costs, and damage to the company’s customer brand image. A responsible AI specialist is required to possess not only technical knowledge of AI but also a robust understanding of ethics, legal standards, and compliance issues, making such talents even scarcer.
- Addressing It: To effectively bridge this gap, it’s crucial to integrate responsible AI education with general AI training. Enhancing the curriculum to include ethical, legal, and compliance considerations alongside technical skills will equip future AI professionals with the comprehensive expertise needed to develop AI responsibly.
- Misconception: Encoding moral and ethical principles into AI’s algorithms and data is a task for technical experts alone, without the need for extensive ethical or humanities expertise.
- Reality: This view significantly underestimates the complexity of embedding ethical and moral considerations into AI systems. It presumes that technical skills are enough to capture the depth and breadth of human ethics. However, ethical decision-making encompasses a vast array of human experiences, cultures, and values that cannot be adequately addressed through technical means alone. The real challenge is not just in the technical implementation but in understanding which ethical principles to encode and achieving this in a manner that respects and reflects the diversity of human values.
- Addressing It with a Plural Perspectives Approach: The incorporation of moral and ethical considerations into AI requires a multidisciplinary and pluralistic approach. This means bringing together technical experts with ethicists, philosophers, social scientists, cultural studies experts, and representatives from various communities and backgrounds. Such a diverse collaboration ensures that AI systems are developed with a rich understanding of global ethical norms and the plurality of human values. Recognizing the importance of plural perspectives is crucial for creating AI that is not only technically adept but also ethically robust, culturally sensitive, and socially inclusive.
AI 2030 has crafted targeted programs designed to dismantle these misconceptions, aiming to cultivate a nuanced comprehension of AI’s capabilities and its transformative potential within our industry.
Can you please give us your favorite “Life Lesson Quote”? Do you have a story about how that was relevant in your life?
My favorite life lesson quote, “Let your dreams be the wings that lift others from adversity; the bigger your dream, the higher they soar,” has been a guiding light throughout my journey, both personally and professionally. Initially, my career was focused on assisting individual companies in their transition to greener practices. Yet, I quickly realized that the challenge of achieving low emissions and climate resilience demanded a broader, more ambitious approach.
Driven by the mantra to ‘dream big,’ I seized the opportunity to serve national climate negotiations at the United Nations. This role expanded to supporting numerous countries in their national climate investment planning at the World Bank. My aspirations did not stop there; fueled by a commitment to substantial change, I recently spearheaded the launch of the Billions for Trillions Climate Alliance at COP28. Each step of my journey was motivated by a singular vision: to dream big enough to address global challenges and uplift humanity.
Off-topic, but I’m curious. As someone steering the ship, what thoughts or concerns often keep you awake at night? How do those thoughts influence your daily decision-making process?
Navigating the rapid advancements in artificial intelligence, particularly in the realm of general AI deployment, often occupies my thoughts late into the night. The excitement surrounding AI’s potential is undeniable, yet it’s the pace at which it’s evolving — often without adequate consideration for the essential principles of responsible AI — that raises concern. These principles, including fairness, privacy, accountability, transparency, sustainability, safety, and security, are crucial. Without them, we risk amplifying AI’s potential negative impacts on humanity and the environment exponentially.
The challenge lies not just in advancing innovation but in managing the risks associated with it. The gaps in awareness, talent, and the necessary tools for ensuring responsible AI development are significant hurdles. These concerns deeply influence my daily decision-making process, emphasizing the urgency and importance of addressing these issues head-on.
This realization was a driving force behind the creation of the AI 2030 Initiative. Our goal is to bridge these gaps by fostering a bottom-up, expert-driven community committed to the responsible development and deployment of AI. Through this initiative, we aim to collaboratively tackle the challenges at hand, ensuring that the transformative power of AI benefits society in a manner that is ethical, equitable, and sustainable. It’s a mission that not only guides our strategic objectives but also serves as a constant reminder of the responsibility we hold in shaping the future of AI.
You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people, what would that be? You never know what your idea can trigger. 🙂
Our goal this year is to launch the Responsible AI Pledge (RAIP), a cornerstone of our mission to shape a future where artificial intelligence is developed and deployed with ethical responsibility at its core. As we introduce RAIP alongside the Responsible AI Certificate (RAIC), we are setting in motion a global movement that stands as a beacon for change. This initiative aims to galvanize both corporations and individuals, encouraging a unified commitment to the responsible research, development, deployment and use of AI technologies.
By championing RAIP, we are not just mapping out a set of actions but are laying down clear pathways for entities to align their AI practices with principles that are beneficial, equitable, and sustainable. The RAIC further solidifies this commitment, serving as a tangible measure of adherence to the AI 2030 Responsible AI Framework. Through these efforts, we aim to catalyze a global movement that will drive the adoption of ethical principles in AI across industries, ultimately supporting our mission to mainstream responsible AI by 2030.
How can our readers further follow you online?
To stay updated on our latest initiatives and join the conversation on responsible AI development, you can follow us through the following platforms:
- Website: Visit our website for in-depth information about our programs, upcoming events, and the latest news on responsible AI.
- LinkedIn: Follow me on LinkedIn to connect with our community of AI professionals, share insights, and discover collaborative opportunities.
- LinkedIn Group: Join our LinkedIn Group to be part of a dedicated space for sharing knowledge, best practices, and networking with like-minded individuals.
- X (Twitter): For real-time updates and engaging discussions, follow me on Twitter.
- Meet me in person and join other responsible AI Leaders at the Chicago AI Week event in June.
- Join AI 2030: To become an active member of our initiative and contribute to shaping the future of AI, sign up here.
Thank you for the time you spent sharing these fantastic insights. We wish you only continued success in your great work!
Thank you, Cynthia, for the opportunity to discuss this critically important topic.