Saturday 23rd March 2024

Topics:

• A good data model is supposed to represent something in the real world.
• However, many data models are based on data exclusively from the internet.
• Just image the downstream consequences of that.
• For example, a data model based upon social media user-generated content will be full of:
  1. Bias.
  2. Miss-truths and half-truths.
  3. Opinions (some of them dangerous).
  4. Invalidate data with no sources, no peer review...
• If a data model is built off bad data, and then that data is used to train an AI, that AI will contain the same bias, miss-truths, dangerous opinions etc.
• Getting clean data to drive good decisions, be they human or AI, is becoming increasingly difficult.
• We are swamped in data, but the signal-to-noise ratio is low.
• The garbage in/garbage out problem has never been greater, and thanks to AI, the downstream consequences have never been higher.
• The business opportunity here is great however: a marketplace for high-quality training data models for AI is about to emerge, and it will be extremely lucrative.
• Ironically, a return to offline data such as peer-reviewed papers and books may the solution.
• Such legacy silos of data will become the new gold rush.
• In such a market place, the quality of an AI will be judged by the quality of it's training data.
• What I am working on this week:
  • Designing an internet search indexer for the Alpha Framework.
• Media I am enjoying this week:
  • Diaspora by Greg Egan.

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techleaderpro-2024-week-12.mp3

File details: 7.6 MB MP3, 5 mins 16 secs duration.

Title music is "Hidden Beyond" by Aiyo, licensed via www.epidemicsound.com

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