Tiffany Qiao is a Senior Data Engineer at Pandora, the world-renowned jewellery company. With a unique background combining finance and computer science, Tiffany has worked for tech giants like Huawei and Coca-Cola before joining Pandora in early 2023.
Her role involves leading data products that feed into AI and innovation initiatives. Tiffany will speak on a panel at DTX London, which will take place on 2nd and 3rd October at ExCeL London.
The following interview has been edited for length and clarity.
Q: Can you tell us about your background and what attracted you to Pandora?
I initially pursued my degree in finance, but after visiting tech giants like Google, Facebook, and Apple in the United States, I was inspired by technology's potential to shape careers. This led me to pursue a master's degree in computer science, combining my financial knowledge with coding skills like Java, Python, and SQL.
After graduating, I started my career at Huawei, where I discovered my passion for the data world. When Pandora approached me, I was immediately intrigued. As a woman who loves jewellery, I often say that diamonds and data are my perfect combination.
But beyond the product, what really attracted me was Pandora's modern tech stack. The company were using all the trendy technologies I was eager to work with, and offered me the opportunity to go deeper into the entire data process, from infrastructure to architecture. It was a chance to build things end-to-end, which I found fascinating.
Q: What will you be speaking about at DTX London?
At DTX London, I'll be part of a panel discussion on the topic "From Governance to Guardrails: Building Trust and Transparency in AI". We'll be exploring how to establish robust governance frameworks for AI to ensure data integrity and accountability.
A key focus will be addressing the risks of "garbage in, ghost out" – the dangers of accepting AI outputs without understanding the data behind them. This is particularly relevant to my work at Pandora, where we prioritise data quality before feeding it into AI systems.
We'll also discuss the decision-making process for buying or building Large Language Models (LLMs), and share insights on safeguarding AI initiatives. This includes identifying biases, maintaining transparency, and setting up proper controls that allow businesses to maximise the benefits of AI while minimising risks.
Ultimately, we'll touch on real-world use cases and practical strategies for creating an AI environment where trust is earned, not assumed.
Q: Why should people listen to your session at DTX?
At Pandora, we often say that data is the new oil for a company, especially in competitive industries like luxury retail. AI is revolutionising how we unlock the value in this data, but it's critical to manage this power responsibly.
Our session will be valuable for anyone involved in AI or data-driven environments, whether they're building systems or making business decisions based on AI outputs. We'll provide insights into the practical challenges and solutions in implementing AI responsibly.
For example, at Pandora, we've established a self-service environment while we are also trying to use tools like Databricks' Genie, which integrates AI. While this opens up possibilities for non-technical stakeholders, it also presents challenges. We've seen instances where AI-generated results can be misleading if not properly understood or contextualised. These real-world examples highlight the importance of having robust governance and understanding the limitations of AI tools.
Q: If you could offer three takeaways from your speaking session, what would they be?
1. Establishing AI governance: It's crucial to learn the critical components of an AI governance framework that ensures data integrity, accountability, and compliance. This forms the foundation for responsible AI use.
2. Avoiding AI overtrust: It is vital to educate non-data teams on AI's limitations. Human oversight remains essential to avoid blind reliance on AI-generated results. I'll share examples from my real-world use case experiences that illustrate this point.
3. Building versus buying AI solutions: We'll provide insights into the key considerations for deciding whether to build in-house or buy AI solutions, focusing on mitigating risks while maximising value. I'll share insights and lessons learned from both approaches, drawing from real-world use cases.
Q: This will be your first time at DTX. What are you looking forward to about the event?
As a first-time attendee and speaker, I'm incredibly excited about DTX. I'm looking forward to sharing insights from my work at Pandora and connecting with other technology and AI professionals.
I've heard that DTX is a great platform to learn from industry experts, discover new technologies, and engage in discussions that can shape the future of AI and digital transformation. As someone passionate about the intersection of data, AI, and business, I'm eager to absorb as much knowledge as possible and contribute to these important conversations.
While I'm excited to share my experiences, I'm equally looking forward to learning from others. I'm particularly interested in how other companies tackle AI governance and transparency issues.
I hope to gain insights into innovative approaches to building trust in AI systems, especially in industries outside of retail. I'm also keen to learn about the latest developments in AI technologies and how they're being applied in real-world business contexts.
Additionally, I'm looking forward to networking with peers and potentially forming collaborations that could drive innovation in the AI and data space.
Q: Is there anything else you would like to add on this subject for business leaders or potential attendees?
I'd like to emphasise that while AI holds enormous potential, business leaders must focus on governance and transparency to build trust. This aspect can seem tedious, but it's absolutely essential. We must recognise that AI is only as good as the data it's built on and the guardrails in place to guide its usage.
For those attending our discussion, I encourage you to approach AI not just as a tool, but as a system that requires careful oversight, ethical considerations, and continual improvement. The challenges we face in implementing AI responsibly are significant, but so are the opportunities for innovation and growth.
At Pandora, we're constantly learning and adapting our approach to AI and data management. I believe that by sharing our experiences and learning from others, we can collectively push the boundaries of what's possible with AI while ensuring we use it ethically and responsibly.
Finally, I'd say that events like DTX are crucial for staying ahead in the rapidly evolving world of AI and digital transformation. The insights you gain and the connections you make here can be invaluable in shaping your organisation's AI strategy. Whether you're just starting your AI journey or are well on your way, there's always something new to learn in this dynamic field.
Tiffany Qiao will be speaking at DTX London, taking place on 2nd and 3rd October at ExCel London. For more information and to register – for free – please visit: https://dtx-london-2024.reg.buzz/
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