The systems that no one will test

Relevant:

https://www.reddit.com/r/YouShouldKnow/comments/1wssf4u/ysk_...

https://imgur.com/a/6FaQQhb (original post before being taken down by mods)

>The Work Number is an Equifax (who famously had a massive data breach a few years back) owned database with employment and pay information.

>You can create a login on theworknumber .com and pull your report. Mine is seventy four pages and had info from every company I've worked at in the last 13 years including every paycheck I had received with the exact dollar amount (both net and gross) and hours worked. It has employment start/end dates, termination reason, details about withholdings, benefit enrollment, union affiliation, etc etc etc.

>This data is sourced directly from the HR platform your employees use (ADP, Rippling, Gusto, iSolved, etc). Equifax sells your data for things like employment background checks.

>You cannot have your data removed from The Work Number. You can freeze your report (much like a credit report) but if a potential employer cannot access your frozen report that may disqualify you.

>Why YSK: If you're interviewing for a job you can be at a significant disadvantage especially for things like salary negotiations because they can literally see how much you make including your most recent paycheck. Creditors also can access these reports.

>This is the biggest privacy violation I have ever seen and almost nobody is even aware of it. Certainly none of us consented to having our employment and income data harvested and sold, especially since we get nothing in return. At a minimum, people should know about how this data can impact you.

>Edit: The Work Number is primarily for the US, but there are similar services for other countries.

The narrative around security and LLMs doesn't make sense to me.

I think we've created a self-fulfilling prophecy. Everyone involved is acting with the best of intentions, but in avoiding what they fear, they've give shape and realized their fears. Much like a greek tragedy.

An example of this is the story of Oedipus Rex, in the story Laius, the king, is told that he is "doomed to perish by the hand of his own son." (and wed his mother) And so to avoid this fate he decides to kill the infant. The person assigned to abandon him in the woods takes pity on the baby and gives the baby away. Thereby ensuring that Oedipus knows neither his mother or his father (and arguably giving him a reason to kill his father).

The child grows up and hears the same prophecy again and the child tries to avoid the prophecy as well, as he loves his adoptive parents. So he leaves them and travels to Laius' kingdom, where he runs into Laius. Neither recognizes the other. As Laius is the type of man to kill an infant, they end up in an argument, whereupon Oedipus kills him.

I think the ancients were on to something, because if Laius had reacted to the prophecy with courage, he would have been saved. I would like to argue that if he had faced his fear and raised Oedipus with love, then the necessary preconditions for the prophecy to come true wouldn't have taken root. But that's not what happens.

By being driven by his neuroses and in acting with cruelty out of fear, Laius makes the prophecy real.

To quote Heraclitus, ethos is fate. Or, character is fate.

I think a lot of people in this AI research sub-culture would be served well by reading these classics, because they are making their self-prophesied doom come true.

They have been convinced for years (GPT-2 was released in Feb 2019) that AI is dangerous. A tremendous threat. An apocalyptic threat.

One dimension of this fear has been the idea that a super smart AI will take over our digital infrastructure and be responsible for the digital apocalypse. That would be terrible!

So what do they do?

They try to make a counter to their fears by teaching models how to exploit vulnerabilities.

How dangerous is such an entity? Very!

Convinced of this danger, they start testing their models as if they were weapons with offensive capability. And then they create models that can be used as weapons.

And because they don't want to release a dangerous weapon out into the world (oh no!), they restrict access to their AI, thereby depriving everyone of tools they can use to improve their security...

Ethos anthropoi daimon.

Can't escape the feeling that the original vulnerability was deliberately planted as a mechanism for law enforcement (or maybe criminal orgs) to "expedite" investigations.

> I honestly don’t blame them: [...] software is software

That attitude is the problem. Why does our industry have that attitude towards quality? Every bike shop in my little town is better with quality than the average software shop in the world. Yes, software is more complex than bicycle. But a software engineer also gets paid 10x and has the luxury of spending substantial time on their product, compared to the 10 minutes it takes the bike guy down the street to diagnose and then fix an issue with my bike which I then trust my life with once they are done and I bike through traffic.

We need to treat software differently. "Oh well, it's just software shrug" does not cut it anymore, if it even ever did.

Is it just me that has a constant dribble of other people's private data coming to me from government agencies?

This year, I've had the UK variously send me someone else's court summons, someone else's tax documentation (not address error - just inadvertently included as attatchments on emails to me).

I've had portugal disclose property taxation information on any subject to me, through a simple enumeration hole.

And last week I had brazil's ministry of agriculture send me details on other peoples' livestock shipments.

Our information environment is unbelievably porous. There would be no secrets from an unshackled AI.

[flagged]

[flagged]

i am also worried that all my private data might eventually (once tech is advanced enough) be surfaced somewhere: photos, chats, emails. wondering if i should start cleaning up now or just give up

Is "ML" some UK-ism? I sort of see the connection between machine learning and LLMs but it doesn't seem too obvious to me. And certainly it's not the common nomenclature.