Gullible? Asks Ben Rogers, Friend of Tom Sawyer. Who Me?
June 25, 2020
“Machine Learning Has A Flaw; It’s Gullible” forced me to think about Tom Sawyer and his snookering Ben Rogers into painting Aunt Polly’s fence.
The write up, without the flair of Samuel Langhorne Clemens, states:
Machine learning (ML) – technology in which algorithms “learn” from existing patterns in data to conduct statistically driven predictions and facilitate decisions – has been found in multiple contexts to reveal bias. An example is Amazon.com coming under fire for a hiring algorithm that revealed gender and racial bias. Such biases often result from slanted training data or skewed algorithms. And in other business contexts, there’s another potential source of bias. It comes when outside individuals stand to benefit from bias predictions, and work to strategically alter the inputs. In other words, they’re gaming the ML systems.
Snooze. Old news.
The write up adds in Theodore Mommsen Latin constructions inspired prose:
… patent applicants are permitted by law to create hyphenated words and assign new meaning to existing words to describe their inventions. It’s an opportunity, the researchers explain, for applicants to strategically write their applications in a strategic, ML-targeting way. The U.S. Patent and Trademark Office is generally wise to this. It has invited in ML technology that “reads” the text of applications, with the goal of spotting the most relevant prior art quicker and leading to more accurate decisions. “Although it is theoretically feasible for ML algorithms to continually learn and correct for ways that patent applicants attempt to manipulate the algorithm, the potential for patent applicants to dynamically update their writing strategies makes it practically impossible to train an ML algorithm to correct for this behavior,” the researchers write.
Surely the “impossible” word deserves a bit of emphasis. If the researchers are correct, the wonderful world of smart software is going to be a thrilling place: Redlining, job rejections, smart drones flying into Sunday school picnics, certain enthusiastic wedding receptions noted from a watcher, etc. etc.
Stephen E Arnold, June 25, 2020
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