I am not the most AI savvy person, and I don’t pretend that I know it all.
Simple logic, common sense, and history make me worried about the danger of synthetic data, just like the toxic assets that caused prior financial crises.
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When AI uses synthetic data as the foundation for layer upon layer of algorithmic calculations, it reminds me of Norman Rockwell’s painting “The Gossips”:
What may have started as a “cat” might end up being an “elephant” after being copied, retold, re-described, misinterpreted, subjectified, altered, dramatized, reinvented, reimagined, and passed around 15 times.
So it is with synthetic data.
Gossip can be traced back to the first version, though it may be extremely difficult and time-consuming; to trace synthetic data’s origin is next to impossible since the speed and scope of computation is almost out of human’s control.
Just like the almost untraceable first rumor monger after gossip has taken on a life of its own, the toxic “asset” of subprime mortgages were sliced, diced, and mixed up in hedge funds, mutual funds, and all sorts of index funds, dumped into the global stock market. A financial mechanism that allowed subprime lenders, investment banks, and other financial institutions to sell loans on Wall Street, shifting risk to investors, eventually triggered the 2008 worldwide financial crisis.
The question is: does synthetic data possess similar toxicity?
If you have not been around as long as me, let me remind you about the “Black Monday” on Oct. 19, 1987 when the Dow Jones Industrial Average went down 508 points, which was 22.6%. Not coincidentally, there had been rampant junk bond market abuse and insider trading prior to the crash, by unethical and greedy investment banks like Drexell Burnham Lambert (which was forced into bankruptcy afterwards).
As a brand builder, I have a process to first collect raw materials relevant to the brand, before further research and analysis, to distill vast amounts of information into the brand essence. I tell each of my clients that “if the raw materials are tainted, your brand will be a tainted brand.”
It really does not take a genius to see that if synthetic data by its nature is not based on true, authentic, verifiable, auditable, trackable, and provable information, statistics, facts, with sources and origins, it can be just like the toxic subprime mortgages and the junk bonds that eventually took the whole system down.
Is it rocket science or just plain and simple common sense?
Again, I am not the smartest person who knows it all. I am sharing my worries with you so you can make your own judgement. Prior to all financial and economic crises, the vast majority of people just blindly let the so-called “experts” mislead them and the market. Everyone suffered as a consequence. Main Street always suffers far more than Wall Street.
Is history repeating itself soon?
Before it is too late, before the data lake is tainted, should there be laws to require labeling of data sources?
The danger is far reaching and fundamentally threatening: Anyone can manufacture “truth” and “facts” without being traced down, which severely compromises the integrity of information, the legal system, the financial system, media, and democracy.
It is going to be a global issue, since AI knows no borders.
If the US is sitting on its hands, are we leaving this for other countries, like China, to take the initiative to safeguard data? Do you trust a non-democratic system without a free press to protect data truthfulness with labeling requirements?
You may “label” me as an excessive worrier, and tell me that the sky will not fall. I hope I am wrong. Again, I am not an AI expert. If you are, if you know better, please be my guest and refute my worries.
©Joanne Z. Tan all rights reserved.
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