Uneasiness with AI
Abstract
Dianna and Fred discuss sources of uneasiness with AI and its use within industry.
Key Points
Join Dianna and Fred as they discuss sources of uneasiness with AI.
Topics include:
- The challenge of AI to authenticity.
- Integrating AI into our current processes and what that could mean for reliability.
- The availability of AI: it’s challenges for computing power and source data.
- How to approach AI right now for tomorrow.
- Artists, technical writing, flowcharts, and tomato processing.
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Show Notes
There is a general uneasiness with AI with some in industry, but it can be hard to really get to the root of why. Dianna and Fred discuss what they’ve been hearing from others.
- There’s an unease about authenticity.
- AI challenges the idea that humans are unique in thought and creativity in art, writing, and more.
- There is an increase practice of listing “this will be done by humans” in services and products (things like resumes, technical papers, and more).
- AI is forcing a restructuring of how professionals structure fees, from time-based to result-based.
- Integration of AI is becoming commonplace.
- The integration of AI in so many daily tools are now competing with each other.
- The interfaces of AI with other logic tools – what are the failure points?
- Using AI can complicate what should really be simple. Just because we can doesn’t mean it adds value.
- AI is available, or is it?
- There is a huge computational cost for using AI.
- Most are not really knowing what to use AI for and how. We’re still figuring it out.
- All knowledge is not available. Trade secrets are limiting databases.
- How can we approach AI right now for tomorrow?
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