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quotient commented on Ask HN: Does My Company Think I'm a Cybersecurity Risk?    · Posted by u/lovatsofa
lovatsofa · a year ago
{MOVED TO COMMENTS}

1. I’ve been asked to keep my camera on in most meetings. 2. Like many in the tech world, I generally prefer to keep it off. 3. I was pulled aside over concerns that my LinkedIn profile "looked suspicious." 4. Admittedly, my LinkedIn does look suspicious to anyone who doesn’t communicate with me regularly or hasn't met me recently. 5. As with many developers, I place a premium on privacy, and some of my actions to safeguard it might appear suspect. 6. I’m involved in the cybersecurity community, participating in conferences and learning platforms. 7. The individual who asked me to remove the repository is non-technical. 8. The company I work for is not a tech company. 9. My direct supervisors and decision-makers are also non-technical. 10. I maintain strong relationships with technical team members. 11. I’ve had difficulties navigating remote work dynamics with non-technical colleagues. 12. I speak up less than I used to—this could be interpreted as disengagement. 13. In the past, I struggled to make measurable progress or explain setbacks, which hasn’t reflected well on me. 14. I’ve made no secret of the fact that Quality Engineering is not my passion, preferring development work instead—a comment that’s occasionally thrown back at me: "I know you’d rather be doing X, but..." 15. I have fewer than 10 years of experience in the industry and appear quite young. 16. I’ve been with the company for several years. 17. I work remotely. 18. I attempted to explain our CI/CD pipelines, the importance of QE, and why I believe I need access to the repo.

quotient · a year ago
They don't trust you. You should go and look for a new job.
quotient commented on The Department of Everything – Dispatches from the telephone reference desk   hedgehogreview.com/issues... · Posted by u/pseudolus
ThomasBHickey · a year ago
I was a Science Reference Librarian at John Crerar Library in Chicago in the early 70's, and this sounds very familiar, although we tended to get a slightly more focused set of questions (and our boss Mr. Quinn was much more pleasant!). I love Wikipedia, but the books in our Reference Collection were remarkable.
quotient · a year ago
I studied in Crerar many joyful times, though long after your tenure there, in the 2010s. It's a great, quiet library. One of my favorites on campus.
quotient commented on OpenAI board in discussions with Sam Altman to return as CEO   theverge.com/2023/11/18/2... · Posted by u/medler
x86x87 · 2 years ago
one thing that I am curious about: aren't there non-competes in place here? and even without them, you just cannot start your own thing that just replicates what your previous employer does - this has lawsuit written all over it.
quotient · 2 years ago
It's California. Non-competes are void. It is one of the few states where non-competes are not legally enforceable.
quotient commented on Google Brain founder says big tech is lying about AI danger   afr.com/technology/google... · Posted by u/emptysongglass
habitue · 2 years ago
There are two dominant narratives I see when AI X-Risk stuff is brought up:

- it's actually to get regulatory capture

- it's hubris, they're trying to seem more important and powerful than they are

Both of these explanations strike me as too clever by half. I think the parsimonious explanation is that people are actually concerned about the dangers of AI. Maybe they're wrong, but I don't think this kind of incredulous conspiratorial reaction is a useful thing to engage in.

When in doubt take people at their word. Maybe the CEOs of these companies have some sneaky 5D chess plan, but many many AI researchers (such as Joshua Bengio and Geoffrey Hinton) who don't stand to gain monetarily have expressed these same concerns. They're worth taking seriously.

quotient · 2 years ago
Besides the point, but FYI you are misusing the term parsimonious.
quotient commented on Causal inference as a blind spot of data scientists   dzidas.com/ml/2023/10/15/... · Posted by u/Dzidas
Anon84 · 2 years ago
For a hands on introduction to Causality, I would recommend “Causal Inference in Python” by M. Facure https://amzn.to/46byWnl Well written and to the point.

<ShamelessSelfPromotion> I also have a series of blog posts on the topic: https://github.com/DataForScience/Causality where I work through Pearls Primer: https://amzn.to/3gsFlkO </ShamelessSelfPromotion>

quotient · 2 years ago
The Facure text is good, can confirm
quotient commented on Lost Civilizations of the Andes   davidpratt.info/andes2.ht... · Posted by u/iamben
sinkasapa · 11 years ago
I think I'd take this with a couple of bags of salt without some sign of peer review.

Edit: look at his sources.

quotient · 11 years ago
You're being overly dismissive. There's quite clearly a substantial amount of research here, and in a cursory reading I detected no explicitly bombastic claims, which are usually indicative of crankwork.

Sure, it's not peer-reviewed, and his other articles might look quite loony, but he does highlight some anthropological discrepancies in this piece. Not everyone can have their articles peer-reviewed.

u/quotient

KarmaCake day234April 11, 2014
About
I've been reading HN since January 2012. Recently I decided to begin contributing to the discussion.

I work and do research in Mathematics, Statistics, and Computer Science. I also have a thorough background in the humanities and arts.

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