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Earlier quoted context omitted.
The machine learning models with false positives aren't the problem. The lack of a timely appeals process that involves a human is.
But that’s why the prices are so low. Society will put up with it as long as it works most of the time, because algorithms without humans are cheap.
Earlier quoted context omitted.
The machine learning models with false positives aren't the problem. The lack of a timely appeals process that involves a human is.
But that’s why the prices are so low. Society will put up with it as long as it works most of the time, because algorithms without humans are cheap.
I guess stripe wasn't kidding when they said they would disrupt online payments. On a more serious note; How much further is society going to allow this kind of thing? Hiding behind templated e-mails without any explanation. Disrupting people's lives who become collateral damage with no way out.
These types of problems could be fixed by doing the three things big tech hates: 1. Hire human beings 2. Empower them to fix problems 3. Let your users talk to them
Ideally, good companies will find a balance with AI and human operators that's also sustainable as a business.
I have a hunch their main concern is this kind of marketing on your site: "Access the American market Our credit card comes with a U.S. billing address, so you can unlock features restricted to the U.S or Western markets especially if you don't live there." https://justuseapp.com/free-trial-card
If you set up your ML so that it works x% of the time, you might very well have a profitable business even if you end up accidentally screwing over a bunch of folks. But no competitor can challenge you in the marketplace because the human cost of answering phones and emails to find that last little bit of efficiency is overwhelmingly disproportionate to any economic value the business would gain.
Many of us like to bang on businesses as being amoral and impersonal, but most are trying to do something people want, only better and more efficiently. ML may be providing an upper limit to efficiency by taking out any opportunity to do some serious analysis. Because in many cases removing that last 1-5% in inefficiency is the bit that leads to a completely new way of working, in many areas we may be boxing ourselves in to a very long-term status quo.
They arbitrarily closed my account a while ago, and after following their draconian re-activation process (somehow my government issued ID is not good enough to identify me, they need to verify the same information and ID in a video call) I think we’re now at 20+ emails and counting.
I just gave up and will go with a different provider or open a new account since it’s easier.
At some point Stripe was the provider that took everyone, but they’ve become allergic to any kind of risk and trust nothing.
These types of problems could be fixed by doing the three things big tech hates: 1. Hire human beings 2. Empower them to fix problems 3. Let your users talk to them
Hiring humans is not as scalable as technology is. You can't just hire 150 more customer support agents _each month_ like you can fire up another Kubernetes cluster. They need training, middle managers, leads, special training, good tooling, office space, adjusted KPI-s, etc. Ideally, good companies will find a balance with AI and human operators that's also sustainable as a business.