21–30 of 102 posts
False Positives don't matter. It's all about mitigating False negatives enough to lower shrinkage and justify the costs of the software.
False positives may cost more than the items being protected in diverse costs.
I'm not sure how many high intensity "you're stealing!" confrontations really occur.
As someone who has inadvertently stolen from Walmart on more than one occasion, I cant attest that their anti-shoplifting AI does not work.
How does one inadvertently steal?
Hire more humans. Problem solved.
False Positives don't matter. It's all about mitigating False negatives enough to lower shrinkage and justify the costs of the software.
False positives may cost more than the items being protected in diverse costs.
False Positives don't matter. It's all about mitigating False negatives enough to lower shrinkage and justify the costs of the software.
I know when the shops near me (UK) started rolling out automated checkouts I'd avoid the shops that had poorly calibrated systems that required frequent interventions because it was extremely annoying. False positives certainly had revenue implications for those shops.
And I don't understand what this has to do with COVID-19 at all in the article.
Finally, what do employees care about theft? It's not coming out of their paycheck. False positives from an anti-theft system seems like a small job nuisance at best -- not something to whistleblow with a "slickly produced video".
Nothing about this article makes sense to me, unless it's motivated by an Everseen competitor -- whether another company or an internal division of Wal-Mart that thinks they have a better solution. In either case, why would the general public care at all?
There is a lot of information in the article but little to draw a conclusion from. They bring up examples where the AI failed, but that alone does not indicate it doesn't work. An AI that fails to recognize some thefts but does recognize others can still be considered to work as long as enough thefts are caught. Imperfect, but given the low cost of a failure relative to not using an AI, imperfection seems quite toler…
So it's really a that the parameters of the tech are overlapping poorly with the parameters of customer convenience, perception, treatment, and other aspects of the next consumer experience and op. costs.
This is probably a great example of understanding the limitations and special needs of AI in the real world. It's not magic, it's just 'some magic' that we have to develop processes to work with.
There is a lot of information in the article but little to draw a conclusion from. They bring up examples where the AI failed, but that alone does not indicate it doesn't work. An AI that fails to recognize some thefts but does recognize others can still be considered to work as long as enough thefts are caught. Imperfect, but given the low cost of a failure relative to not using an AI, imperfection seems quite toler…
You can trick any system, but that's not telling on it's overall effectiveness.