We discussed the implications of chat GPT for it and the industry.
In today’s episode, we spend a lot of time figuring out how data provenance governance, bias, and ownership will impact chat GPT in IT and technology and cloud contexts. This discussion really looks into how chat GPT can be used in disruptive ways, but also in protective ways as what we describe as guardrails for how these systems are going to get built.
We come to some very interesting conclusions.
Transcript: otter.ai/u/aETNeRoDnspFnmPT3KcjBuHQTzE
Image: www.pexels.com/photo/surprised-y…le-phone-3771127/
Rob’s Hot Take:
In the Cloud 2030 podcast’s January fifth episode, CEO Rob Hirschfeld explores the complexities of data provenance in ChatGPT, questioning ownership and control of the generated content. He emphasizes the need to understand the sources of data, pondering whether the output belongs to users, the algorithm, or no one, highlighting the challenges of systems that belong to nobody. Hirschfeld also connects this issue with Software Bill of Materials, emphasizing the importance of knowing the components of systems for accuracy and confidence. He encourages listeners to delve into the full episode for valuable insights and invites them to engage further in discussions at 2030.Cloud.