Bad data in, bad results out
The team discusses the power of AI to automate procedures, but the risks of spoiling things with bad data.
Podcast Overview
This weeks guests
In this week's episode, we discuss the impact of bad data on AI, highlighting the definition of bad data, examples of bad data in AI, and the risks and challenges associated with bad data.
The conversation delves into the challenges and implications of AI in decision-making, the impact of bias in AI applications, the technical hurdles in AI implementation, the importance of data structure in AI transformation, and the concept of setting guardrails for AI systems.
Takeaways
AI Tool Preference
Data Quality and AI
AI as a Managerial Tool AI and bias
Data structure and AI
Friction in AI systems
