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How three years at McKinsey shaped my second startup

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181–190 of 192 posts

Re: How three years at McKinsey shaped my second startup

#181

Article is interesting on the whole (I have no experience with "professional" work, and would love for suggestions as to how to be more familiar), but I latched onto this nugget: > Our vision at Meanwhile is to build the world's largest life insurer as measured by customer count, annual premiums sold, and total assets under management. We aim to serve a billion people, using digital money to reach policyholders and a…

Couldn't they have contractors doing that ? Be it sub insurance companies or freelancers.

> Completely separate from the potential ethical issues and economic implications of putting 100k people out of a job

Less work is... good ? Ethics are positive here. More work, more pain

Re: How three years at McKinsey shaped my second startup

#182
post #143

Earlier quoted context omitted.

No one is going to accept a claim rejection from AI. Everyone will want to dispute, which will have to go to a human to review. At the end of the day I don’t see how 100 people is realistic.

This reaction is primarily an emotional one. Why is a human rejecting a claim better than an AI rejecting a claim? Presumably the AI will one day -- if not today -- be more accurate in following decisioning logic than humans, who will continue to make human errors.

The AI won't reject a claim because that's easier than doing the paperwork to approve the claim and it's 4:30 on a Friday.

It also won't approve it because despite not putting the "magic words" on the form it's clear from the situation that you'll get approved regardless and it's a waste of the company's labor to have you file an appeal that they then have to review.

I'm not sure which case is more common though.

Re: How three years at McKinsey shaped my second startup

#183

Earlier quoted context omitted.

I agree. And then I recall my last few interactions with insurance companies. Dealing with a machine is unlikely to be worse.

My knee-jerk reaction is to think that the prospect of an insurance company handing support over to machines is a terrible development. But it was already the case that they just arbitrarily do WTF ever they want, that outside a small set of actions that "bots" can perhaps handle fine they aren't going to do anything for you, and that the only way to get actual support for a real problem involves something being sent…

>and that the only way to get actual support for a real problem involves something being sent from a .gov email address or on frightening letterhead.

What you really mean is that the only way to get them to honor their deal is credible threat of violence.

There might be a million intermediary steps spread across just as many parties but that's what it is at the end of the day.

Re: How three years at McKinsey shaped my second startup

#184
post #164
post #155

Earlier quoted context omitted.

If it is a choice between progress unfettered by concern for your "competitor's labor" or farming berries, I choose berries. However, I believe there's a middle ground and endeavor to find it. Based on your response it doesn't appear as though you believe a middle ground exists.

Choosing berries (ie not progressing to "protect jobs" - no jobs are protected, we have close to full employment worldwide) is choosing avoidable deaths. Child mortality rate in a "choose berries" world is just one example that makes me triggered by those that have that position. And you get nothing in return for protecting those jobs, as I said, the world is "employed" and we've killed many industries already over t…

I believe in, and am searching for the middle ground. I am not interested in discussing hypothetical extremes. I do not believe they are relevant.

Re: How three years at McKinsey shaped my second startup

#185
post #174
post #162

Earlier quoted context omitted.

Why wouldn't they be? LLMs need a lot of content for training and there's multiple orders of magnitude less to train on of if you limited it to insurance-specific content, so you'd probably get a really crappy LLM. And training from scratch is really expensive anyway. At best they'll be using fine tuned enterprise OpenAI / Anthropic models, more likely a regular model with a custom prompt.

They use actual production claims data and policy documents for training. Not random garbage from the Internet.

That’s not how LLMs work.

Re: How three years at McKinsey shaped my second startup

#186

Earlier quoted context omitted.

Without googling I have no clue what that sentence means: "I wanted to derisk my resume by working somewhere with high signaling."

It means he wanted somewhere impressive on his resume so people trusted him more.

In my opinion, this is an example of using fancy words to explain something simple that not only hides the meaning, but is actually less precise. The use of de-risk just doesn't work in the context of a resume. It's not "risky" to have a less impressive resume. it's just less impressive.

Re: How three years at McKinsey shaped my second startup

#187

Insurance business is mostly about hoarding and investing money so you can actually pay when you have to. Unless you can solve that part of the problem as well as the big players, you will run into problems at some point, using extrem value theory you can even estimate when.

>Insurance business is mostly about hoarding and investing money so you can actually pay when you have to.

In Crypto this mean rugpull time

Re: How three years at McKinsey shaped my second startup

#188
post #184
post #164

Earlier quoted context omitted.

Choosing berries (ie not progressing to "protect jobs" - no jobs are protected, we have close to full employment worldwide) is choosing avoidable deaths. Child mortality rate in a "choose berries" world is just one example that makes me triggered by those that have that position. And you get nothing in return for protecting those jobs, as I said, the world is "employed" and we've killed many industries already over t…

I believe in, and am searching for the middle ground. I am not interested in discussing hypothetical extremes. I do not believe they are relevant.

I think the middle ground is not being concerned about your competitor’s labor, to use my original phrasing.

Re: How three years at McKinsey shaped my second startup

#189

Article is interesting on the whole (I have no experience with "professional" work, and would love for suggestions as to how to be more familiar), but I latched onto this nugget: > Our vision at Meanwhile is to build the world's largest life insurer as measured by customer count, annual premiums sold, and total assets under management. We aim to serve a billion people, using digital money to reach policyholders and a…

Couldn't they have contractors doing that ? Be it sub insurance companies or freelancers. > Completely separate from the potential ethical issues and economic implications of putting 100k people out of a job Less work is... good ? Ethics are positive here. More work, more pain

> Couldn't they have contractors doing that ? Be it sub insurance companies or freelancers.

That's a huge assumption that has no supporting evidence.

> Less work is... good ? Ethics are positive here. More work, more pain

No. Work allows people to earn money and survive. Ethics are not obviously positive. Up for debate, but this is not the place.

Re: How three years at McKinsey shaped my second startup

#190
post #186

Earlier quoted context omitted.

It means he wanted somewhere impressive on his resume so people trusted him more.

In my opinion, this is an example of using fancy words to explain something simple that not only hides the meaning, but is actually less precise. The use of de-risk just doesn't work in the context of a resume. It's not "risky" to have a less impressive resume. it's just less impressive.

Agreed. "I wanted to buff my resume."
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