How to you get AI generated models to forget information that it was trained on, when that information was later retracted by it's authors?

During a human lifetime we learn facts that are later determined to be incomplete or wrong.

We effectively mark in our memory that retraction or modification has taken place. 

Over the past year numerous research papers has be retracted due to errors or fraud by the authors.

How do we know that these retracted research papers have not been used during the AI training cycle?

Then how do we get the AI developed model to forget this defective information? 

Peter Brooks

Palm Bay Florida 

Parents
  • We effectively mark in our memory that retraction or modification has taken place.

    Only to some extent - even in traditional systems, incorrect or superseded information tends to hang around for quite a while - not just in collective memory (which can be surprisingly persistent) but in secondary texts (e.g. textbooks and other papers written when the original information what still thought to be current) - and we cope with that adequately. I suspect the situation with AI won't be much different. Some of the current publicly accessible AI models are based on a snapshot if the internet (from Sept 2021 IIRC) - so at some point they're be refreshed by taking a new shapshot - so removed information should then be lost from their knowledge. If they start to add to models continually rather than doing snapshots, then outdated information should gradually be filtered out.

       - Andy.

  • Training or retraining of AI systems is a very expensive proposition.

    As you correctly observed the incorrect information can live on in texts for a very long time. (The Bible is a good example)

    I personally remember attending a lecture by Fred Hoyle in the 1950's where he discussed his continuous creation theory of the universe, which was later retracted because of the Big Bang Theory. Now the Big Bang Theory is being question, as it doesn't consider quantum mechanics and virtual particles.

    What caused me to create this question was the recent retraction of a major medical research (often quoted) paper from 2005. How can we make sure that the AI systems are revised to eliminate this defective information?

    Peter Brooks

    Palm Bay Florida 

Reply
  • Training or retraining of AI systems is a very expensive proposition.

    As you correctly observed the incorrect information can live on in texts for a very long time. (The Bible is a good example)

    I personally remember attending a lecture by Fred Hoyle in the 1950's where he discussed his continuous creation theory of the universe, which was later retracted because of the Big Bang Theory. Now the Big Bang Theory is being question, as it doesn't consider quantum mechanics and virtual particles.

    What caused me to create this question was the recent retraction of a major medical research (often quoted) paper from 2005. How can we make sure that the AI systems are revised to eliminate this defective information?

    Peter Brooks

    Palm Bay Florida 

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