- April 7, 2021
- Bill Tolson|
- Data Privacy|
- Records Management|
- Information Management|
- Information Security|
- Information Technology|
In a couple of blogs over the last month, I have mentioned the possibility of Predictive Information Governance (PIG) - automated information governance based on unsupervised machine learning technology. Just like the name implies, unsupervised machine learning (computers teaching themselves) removes the iterative manual training cycles of the learning process and allows the system to automatically categorize, store, apply retention/disposition, and manage content as it flows within the system.
Moving from supervised to unsupervised machine learning conjures up thoughts of SkyNet, the conscious artificial intelligence that’s the main antagonist in the Terminator movies. In my opinion, the biggest mistake the SkyNet designers made was not including Asimov’s three laws of robotics. To review, here are Asimov’s 3 famous laws of robotics:
Based on the progress machine learning has made and its potential for predictive information governance, it may be time to include 3 laws for machine learning. So here are the top 3 suggestions based on a survey taken from a handful of clients at the Bung Hole Bar & Lounge late one night:
Once loosened up, the survey participants didn’t want to stop at just 3 so here are some additional laws (that can be printed):
If you have other suggested machine learning laws to contribute, please leave comments (I know this is dangerous). We hope you enjoyed our discussion and... “I’ll be back.”
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Bill is the Vice President of Global Compliance for Archive360. Bill brings more than 29 years of experience with multinational corporations and technology start-ups, including 19-plus years in the archiving, information governance, and eDiscovery markets. Bill is a frequent speaker at legal and information governance industry events and has authored numerous eBooks, articles and blogs.