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Building Trustworthy, Scalable Generative AI

By Jean-Philippe Desbioles | Managing Director Financial Services & Generative AI EMEA Leader, IBM
September 26, 2024

I recently had the privilege of moderating a thought-provoking conversation on generative artificial intelligence (AI) at the prestigious Canada FinTech Forum in Montreal. Joining me were industry...

I recently had the privilege of moderating a thought-provoking conversation on generative artificial intelligence (AI) at the prestigious Canada FinTech Forum in Montreal. Joining me were industry leaders Julie Lévesque, EVP, Technology & Operations at National Bank of Canada, and Johanne Duhaime, Executive Vice-President, Technology and Projects at Desjardins. Our discussion centered on the challenges and opportunities presented by generative AI, and how we can work together to build trustworthy and scalable models.

In the last decade, AI has evolved significantly, with thousands of production models and several patents filed. This technological advancement is poised to revolutionize industries from finance to education, unlocking boundless opportunities for growth and innovation. However, the successful adoption of AI requires a multidisciplinary approach, prioritizing human validation, trust, and transparency.

The Human Factor: Trust and Transparency

Human validation is essential for building trustworthy models. Ensuring accuracy, transparency, and explainablity requires a collaborative between humans and machines. This collaboration highlights the need for education, training, and upskilling, enabling employees to work seamlessly with AI tools. 

Augmenting work with AI

As technology continues to advance, the need for a balanced collaboration between humans and machines becomes even more important. While AI can make optimal decisions in some situations, human judgment is irreplaceable in others. In many cases, combining the strengths of both leads to the best outcomes. Generative AI can automate routine tasks, allowing employees to focus on higher-value work. For instance, customer service representatives can use AI to handle common inquiries efficiently, allowing them to address more complex issues that require empathy and critical thinking. Similarly, data analysts can leverage AI to identify trends and patterns, providing actionable insights to inform business decisions.  

To thrive in this new era, we must embrace and enhance The qualities that set us apart from machines. Striking a balance between differentiation and collaboration is essential. This theme is explored in depth in my latest book, Human or AI – Who Will Decide the Future, published last year. 

Democratizing Technology and Regulatory Frameworks

Generative AI has the potential to make technology more accessible to people and organizations, but it also demands specialized skills and expertise. To address this skills gap, companies must prioritize investments in AI talent, infrastructure, and processes. At the same time, regulatory frameworks are crucial to ensure the safe and responsible use of AI. Organizations should adopt ethical guidelines, such as an ethical charter for responsible AI, to ensure transparency, fairness, and accountability. Compliance with existing regulations, along with active participation in shaping new ones should be a priority for all organizations. 

As we continue to navigate the evolving landscape of generative AI, it's essential to prioritize human validation, trust, transparency, and regulatory frameworks. By working together, we can unlock the full potential of this technology and drive innovation and growth in the financial services sector. 

Click here to watch the full panel discussion.

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