128 / Trusting Data Quality: The Key to AI’s Future, with Scott Ambler

Product Momentum Podcast

Trust is the glue that sustains personal relationships. Likewise, trust in AI’s source data holds the key to its future and our confident use of it, says Scott Ambler, Agile data strategist, consulting methodologist, author, and keynote speaker. Trust takes years to build, seconds to break, and forever to repair.

In this episode of Product Momentum, Scott joins Sean and Paul to dig into the importance of data quality in AI applications, understanding and managing bias in AI, and the essential role humans play in harnessing AI’s potential – and its risks.

“If you’re trying to use AI to make data-driven decisions, it becomes a garbage in, garbage out situation,” Scott offers. “It’s really that straightforward. A lot of organizations have let their data debt increase over the years. As AI ingests low-quality data, you’ll get a low-quality answer.” That’s when fractures appear in your hard-earned trust.

Scott also explores the issue of pervasive bias in AI systems and pinpoints its source, underscoring the need for us humans to develop ethical practices that ensure fairness and equity in AI-driven outcomes.

“There will always be bias in your data,” Scott adds. “Humans are biased; it is what it is. And your data will reflect that bias in your business processes. So when you train your AI on that, part of the training process has to be to detect whatever biases are there.”

The key, Scott says, is to understand how humans can effectively leverage AI technologies. While AI offers tremendous potential for augmenting human capabilities and streamlining processes, it is not a panacea.

“When you look at it at a high level, AI is magical. Some of these Gen AIs are just incredible,” Scott concludes. We want to think it’s magic. But it’s not magic. It’s just hard work.”

Scott cautions against blind reliance on AI-generated outputs and emphasizes human oversight and judgment in validating and contextualizing AI-driven insights. Before AI, there was a human in that “last mile” who could filter out the garbage from the good stuff. And the problem now that AI can’t do that.”

This human-centric approach may be the key to AI’s future. If we acknowledge the complementary relationship between AI and human intelligence, maybe we’ll also recognize – and trust – that AI technologies will enhance human endeavors rather than replace them.

Be sure to check out our conversation with Scott Ambler on the Product Momentum YouTube channel!

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