> Amazon is stuck battling all kinds of fraud and it can be hard to differentiate

They have every byte of data ever gathered from all their platforms: IP addresses, network scans from Echo, information from caching servers at ISPs, device fingerprints, site/API access patterns, typing cadences, mouse dwell fingerprinting, timing analysis of orders vs reviews, customer data access patterns vs customer reviews, description text and image analysis, product change timelines, buyer and reviewer clustering, banking details, registration and tax documents, all of it and more. They are one of the biggest data processing technology companies in the world (various flavours of "AI" and otherwise). They even have regulatory carve-outs for using PII for fraud prevention.

I am completely sure you could shine a great big data science floodlamp at all that data and have a vast number of scammers stand out in stark relief. It does feel a bit like the scammers are being tolerated to the extent that they don't drive customers away (and I am very sure the data for that is carefully monitored) or attract regulatory attention they can't lobby away.

Then again, who would win, one of the world's biggest AI company or the word "without": https://www.amazon.com/s?k=shirt+without+stripes

The problem is that they have an obvious incentive to err on the side of positive reviews. Because if every product on the site has a 1 star review few people will buy anything. But if most of them have 5 stars people will be much more eager to purchase.

> Not am Amazon fan, and please let’s not do the Reddit “understanding something is the same as excusing it” thing.

That's a general social media thing and it's annoying as hell. Means every statement that corrects falsehoods and misconceptions against something that you yourself don't like needs to come with a disclaimer that you don't actually like it.

Yeah, they can't always get it right but something that would go a long way towards combatting it: Reputation scores on reporting. Accounts that have spent a fair amount of money over a fair amount of time and which do not have a track record of making false reports should be allowed to flag things. And if a product gets enough flags a human looks into it. The more times you flag something that is deemed wrong the more your vote counts in the future. The more times they decide it's clearly legit the less your vote counts. (And there would be a not sure range in the middle that produces no change.)

And let me flag this is a that. Many years ago I reported a search that returned three pages of results for one product that only comes by the box and by the case. Last I looked it was still three pages.

You make good points, but I'm not convinced this isn't deliberate on the part of Amazon. First, Amazon deliberately keeps buyers in the dark - e.g. sellers can pay extra to avoid comingling, but Amazon gives buyers no way to find this out. Second, this kind of reckless approach to fakes is what enabled Amazon's rapid growth over traditional retailers with hand-picked, verified goods. It's not surprising they try to sweep problems with their approach under the rug.

Perhaps not 'complicit', but with a reckless disregard towards fraud.

> It’s fun to be outraged but a more nuanced read is that Amazon is stuck battling all kinds of fraud and it can be hard to differentiate.

Well that's on Amazon then. They could go the Walmart route and enforce in-house random testing on the stuff they sell. Walmart, for all the rightful hate they get, Aldi, Lidl, Costco, Coop, they all have very strict and extensive negotiations for purchase, and they can, do and will refuse shipments from vendors that fail to meet QA.

But they don't, that's how Bezos got one of the richest men in the world. And Amazon got entrenched way too fast for regulators to ever meaningfully catch up.

Sorting out all the fraud Amazon faces is tricky and frustrating. You might find Hifivestar useful since it helps track and manage fake reviews better. It made spotting false feedback easier for me.

There’s an old law school adage that A students become professors, B students go to work for C students.

It's similar for "shark attorneys," who will typically hail from tier 2 and 3 schools. They're the aggressive hustlers.