When you read that critical powerpoint report last week at work, did you trust what the author had written?
How did you make the decision to trust the numbers that the author placed in the columns and rows chart on page 3?
Did you trust the author and source because of their previous track record of accuracy?
Did the numbers come from a sensor that has been tested in an independent lab to a 99% level of truth?
You trusted that report at work for a reason. It was a “Trust Decision”.
Why?
Have you personally tested the math? What is the source of the data?
So why do you trust Apple vs. Samsung? Verizon vs. AT&T?
Would you pay $100 for a machine that was 99% accurate or could you live with a machine that was 50% accurate and only cost $50?
Think about your mobile navigation mapping app. Where are you going?
These kind of discussions are fundamental yet necessary for us at this point in our digital innovation journey. Just as humans have since the inventions of the Personal Computer, Internet and Quantum Computing.
Trust Decisions are mathematical.
mathematical
adjective
1: of, relating to, or according with mathematics
2 a: rigorously exact : PRECISE
b: CERTAIN
3: possible but highly improbable
We have been trusting computers, data and all kinds of sensors as a result of established testing standards. You name it. ATM’s. Stock Markets. Airplanes. Rockets. Satellites.
Today, would you trust the answer of any question asked to your favorite Large Language Model (LLM)?
LLM’s will challenge your future digital “Trust Decisions” because you might decide whether you believe Chat-Brand A vs. Bard-Brand B vs. Claude-Brand C.
No different than your preference today on using Google search or Bing.
Are human lives at stake? How will we ensure the trust of our digital machines?
Into the future, our ability to produce high accuracy “Trust Decisions” will depend on your own “Augmented Intelligence” (Ai)...
