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In the age of ML era, we are going to see more and more cases like this. Few people will be able to successfully get the attention of our AI overlord. There nee

In the age of ML era, we are going to see more and more cases like this. Few people will be able to successfully get the attention of our AI overlord. There needs a way for customers/users to have a voice.

foobar33333 5y ago
Whenever a service becomes so large that it is not realistic to chose an alternative, the government should take action and either regulate it like a utility or set up a complaints regulator and fine the company for unhandled legitimate complaints.
- peter37205 5y ago
  I believe network effects are what creates this really strong draft that keeps you on top once you're there. Hosts want to list their places where they have the most possible guests – and guests want to book where they have the largest selection of listings. Hard to break that cycle, even if the company makes mistakes that would be punished if it was easier for competitors to grab market share.
peter37205 5y ago
Yeah I have a strong suspicion that an ML model mistakenly flagged me in some form. I believe that reasonably any bans/blocks/other important decisions should only be augmented by ML and always, in 100% of the cases, need human review. You're going to have false positives, and that's okay, no model is perfect – but that needs to be taken into account when making decisions based on its output. I read about a case here on Hacker News a while ago – I can't seem to find the link again – where the police arrested a guy for committing a crime because they had ran a face detection model over drivers license pictures and CCTV footage and it flagged the guy. Problem was – he didn't look like the perpetrator at all, it was clearly just a fluke. But since the police was not trained to scrutinize the face detection results, they arrested him and had him in custody for a good while. Another thing that gets more and more common is that when traveling in a foreign country and using a foreign credit card, transactions at tourist-heavy businesses like restaurants or rental car companies go through smoothly. But try to order a T-shirt online? Oh no, that must be fraud! It's constantly blocked, and always on the merchant side, my bank knows about my traveling. Turns out, many fraudulent transactions are made with stolen, foreign cards, and so a primitively trained model might look successful enough if it simlply blocks all transactions with foreign cards. But of course it could have also been some other mistake that lead to this. ML is a good possibility though.

foobar33333 5y ago

Whenever a service becomes so large that it is not realistic to chose an alternative, the government should take action and either regulate it like a utility or set up a complaints regulator and fine the company for unhandled legitimate complaints.

peter37205 5y ago
I believe network effects are what creates this really strong draft that keeps you on top once you're there. Hosts want to list their places where they have the most possible guests – and guests want to book where they have the largest selection of listings. Hard to break that cycle, even if the company makes mistakes that would be punished if it was easier for competitors to grab market share.

peter37205 5y ago

Yeah I have a strong suspicion that an ML model mistakenly flagged me in some form. I believe that reasonably any bans/blocks/other important decisions should only be augmented by ML and always, in 100% of the cases, need human review. You're going to have false positives, and that's okay, no model is perfect – but that needs to be taken into account when making decisions based on its output. I read about a case here on Hacker News a while ago – I can't seem to find the link again – where the police arrested a guy for committing a crime because they had ran a face detection model over drivers license pictures and CCTV footage and it flagged the guy. Problem was – he didn't look like the perpetrator at all, it was clearly just a fluke. But since the police was not trained to scrutinize the face detection results, they arrested him and had him in custody for a good while. Another thing that gets more and more common is that when traveling in a foreign country and using a foreign credit card, transactions at tourist-heavy businesses like restaurants or rental car companies go through smoothly. But try to order a T-shirt online? Oh no, that must be fraud! It's constantly blocked, and always on the merchant side, my bank knows about my traveling. Turns out, many fraudulent transactions are made with stolen, foreign cards, and so a primitively trained model might look successful enough if it simlply blocks all transactions with foreign cards. But of course it could have also been some other mistake that lead to this. ML is a good possibility though.