Skip Navigation
Play Video

Balancing People, Processes, and Artificial Intelligence

Listen
Share
LinkedInFacebookTwitter

Episode Summary

In this episode of Behind the Growth, host Imran Mian sits down with Kathryn Hume, VP of Digital Channels Technology at RBC. Kathryn shares her unique career path, blending math, literature, and philosophy, leading her into the field of AI and technology. She discusses the importance of pairing technical knowledge with deep business understanding to apply machine learning effectively.

Kathryn highlights the challenges and strategies of integrating AI within RBC, emphasizing the need for strong partnerships between technical experts and business leaders. She explains how Borealis AI, RBC’s research institute, focuses on practical solutions, innovative POCs, and long-term research goals to drive AI adoption in banking.

The conversation also dives into ethical AI, data privacy, and the importance of diversity in tech teams. Kathryn shares her approach to people management, stressing the value of understanding individual team members’ strengths and interests to foster high performance. She concludes with advice for young professionals: focus on excelling in your current role rather than over-optimizing future career moves.

Featured Guest

  • Name: Kathryn Hume
  • What she does: VP of Digital Channels Technology
  • Company: RBC
  • Noteworthy: Kathryn Hume is the Vice President of Digital Channels Technology at the Royal Bank of Canada. She has led multiple technology teams at RBC, including the personal investments development team and the Borealis AI machine learning team. Prior to joining RBC, Kathryn held leadership positions at Integrate.ai and Fast Forward Labs, where she helped over 50 Fortune 500 organizations develop and implement AI programs. She is a widely respected author and educator on technology and innovation, with work appearing at TED, HBR, the Globe and Mail, Harvard, MIT, the University of Toronto and more. She holds a PhD in Comparative Literature from Stanford University and speaks seven languages.

Connect on Linkedin

Key Insights

Strong Business-Technical Partnerships Drive AI Success
Pairing technical expertise with deep business understanding is crucial for successful AI applications. Businesses need both algorithm designers and domain experts who understand the data, its origins, and the company’s objectives. This collaboration ensures that machine learning solutions are practical and effective. For instance, at RBC, building strong partnerships between technical teams and business units, like retail banking and capital markets, has been essential. These partnerships allow for better problem definition, data interpretation, and algorithm implementation. This strategy leads to AI applications that provide real business value and align closely with the company’s goals. A clear, iterative design process that involves regular feedback and adjustments further enhances the chances of success.

Ethical Considerations Are Essential in AI Development
Ethical AI development must address privacy, bias, and the impact of historical data. Privacy is paramount, and techniques should be used to anonymize data to prevent individual identification. Bias in AI can result from unrepresentative training data, so it is crucial to oversample underrepresented groups to improve algorithmic fairness. Additionally, AI systems should not simply replicate past behaviors if those behaviors are not desirable; instead, they should be designed with progressive goals in mind. This approach may involve trade-offs between accuracy and ethical considerations, but it is necessary to ensure that AI systems contribute positively to society. Developers must engage in interdisciplinary discussions to navigate these complexities effectively.

AI Innovation Requires a Balance of Long-term Research and Immediate Applications
Balancing long-term research with immediate applications is key to driving AI innovation. Companies should adopt a strategy that includes working on immediate, market-ready algorithms, exploring bottom-up ideas through proofs of concept (POCs), and engaging in North Star research focused on solving open machine learning questions with significant potential impact. This multi-horizon approach allows teams to address current business needs while also pushing the boundaries of AI capabilities. It fosters an environment where team members can contribute to both short-term projects and long-term research, keeping the work dynamic and innovative. This balance ensures that AI development remains relevant and continues to advance, providing sustained value over time.

No matter how the technologies change or how intelligent the machines get, when push comes to shove, humans will always be seeking a connection with another human.

Episode Highlights

Unique Career Path Blending STEM and Humanities

Kathryn Hume’s career path blends STEM and humanities, starting with her early interest in both math and literature. She pursued an undergraduate degree in math and literature at the University of Chicago, where she was encouraged to explore humanities deeply. This interdisciplinary background influenced her approach to technology and AI, emphasizing the importance of integrating technical skills with a broader understanding of human experiences.

“I’ll always remember when I did my undergraduate degree at the University of Chicago, starting off in math and then ended up with a joint degree in math and literature […] I think that in a nutshell, that experience with my advisor almost captures the thrust of my career thereafter, where I’ve always approached the technical side of things with an eye of a humanities.”

Challenges and Opportunities in a Non-linear Career

Kathryn discusses the challenges and opportunities of her non-linear career, including overcoming imposter syndrome and leveraging her humanities background for strategic thinking. Her journey from marketing and sales engineering to leading roles in AI underscores the value of diverse experiences and the ability to approach problems from various perspectives.

“I didn’t come up starting off as a developer and moved into a senior developer role […] I just tried to put myself into their shoes […] I actually find that mindset is quite useful in executive work in sales work.”

Importance of Human Connection in AI

Kathryn emphasizes the enduring importance of human connection, regardless of technological advancements. She believes that no matter how intelligent machines become, human interactions and meaningful lives will always be paramount. This perspective shapes her approach to AI, balancing technical innovation with human-centric values.

“No matter how the technologies change, no matter how intelligent the machines get, when push comes to shove, humans will always be seeking a connection with another human we humans working in companies have, and leaders have the responsibility of helping other humans lead meaningful lives.”

Managing Change During RBC’s Acquisition of HSBC

Kathryn outlines the challenges and strategies involved in RBC’s acquisition of HSBC Canada. This major operation required precise technical execution and effective team collaboration. The process involved converting data systems over a single weekend and integrating new customers and employees, highlighting the importance of preparation, monitoring capabilities, and adaptability in managing large-scale changes.

“Because HSBC Global remains an international functioning entity and it was only divesting itself of the Canadian business, we basically had to convert all of the data into our systems over one weekend […] we improved a lot on our monitoring capabilities.”

Get new Behind the Growth episodes — right in your inbox

By submitting this information, you agree to receive episode updates from the Behind the Growth podcast. We take your privacy seriously, keep the information you share confidential, and never send any unwanted emails. Check out our privacy policy to learn how we use your details.

Thank You!

We have sent you a confirmation email.
Please check your inbox.

More Episodes

chatsimple