241–250 of 463 posts
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Anyone want to recommend a book? Let me join in by suggesting the Asimov robot books, which I’ve just begun
Brave New World by far is the most accurate book to date of what the modern world looks like. That's my strongest recommendation. Fahrenheit 451 is also a solid read.
I think the responses to this can be broken down into a 2x2 matrix: level of concern vs. understanding of technology. 1) Don't understand ML; not concerned - "I have nothing to hide." 2) Don't understand ML; concerned - "I bought this device and now people are spying on me!" 3) Understand ML; not concerned - "Of course, Google needs to label its training data." 4) Understand ML; concerned - "How can we train models/c…
I think that issue is much bigger than just training ML based off real world data.
Laws might give you some recourse if you can prove this is happening or not. But really we need to start thinking about ways we can ensure the entire stack is under the users control.
I have said this in the past. Free software and open sourc movements have worked decades to open up software and hardware for greater transparency and user control. Yet within a few years we have wiped that out with all the closed hardware and software we happily hold in out hands and place in our homes.
We need more open source hardware and software projects offering alternatives to these systems that have become a daily part of our lifes.
I think the responses to this can be broken down into a 2x2 matrix: level of concern vs. understanding of technology. 1) Don't understand ML; not concerned - "I have nothing to hide." 2) Don't understand ML; concerned - "I bought this device and now people are spying on me!" 3) Understand ML; not concerned - "Of course, Google needs to label its training data." 4) Understand ML; concerned - "How can we train models/c…
>Tech workers have a responsibility not just (to) understand the technologies that they work with Ok, I agree completely with you, 100%. However, based on my limited worldview, tech workers barely understand the tech they work with at all [0]. Asking for the ethical implications to be mulled over is unlikely to happen considering the near-weekly HN threads on "interviewing sucks, heres how to fix it, lol". We can't e…
The main problem here is that Google hired someone like this person who leaked days they were trusted to protect. It's a concern for users (Insider Risk at Google), and something we need laws to protect. Surely if Google Corporation is a poor steward of this data, the specific malicious actor here who violated both his employment policy and his users' trust is especially bad.
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I like that matrix! One thing that I think gets lost in engineers (and humans) is scale. Googazon doing {thing} might be "meh" for 10 people. But the implications look very different when it's doing {thing} for 10%+ of a country's population. At 10 people, I may find out Ted likes to eat Italian. At 10%, I may find out an Italian chain has a sudden health issue and short their stock. Which is in essence their origina…
> At 10%, I may find out an Italian chain has a sudden health issue and short their stock. Let's use scale at both ends please. At 10% of the population a nation state may ask Googazon to silently make changes to identify troublemakers.
The person in the story said they thought they heard domestic violence in some of the recordings.
I know some people who are into “consensual nonconsent“, a form of BDSM which I do not understand, but as these acquaintances tell me they like being on the receiving end I have reason to trust them.
Any system or person which incorrectly identifies one of these groups as the other, in either direction, has life-altering negative consequences. Note that in the UK, some forms of consensual BDSM have been prosecuted as serious assault, and the person on the receiving end has been prosecuted for conspiracy to commit assault because they consented to it.
Any system which prevents DV information reaching the police is bad. Any system which reports BDSM to the police as DV is bad. I don’t even know what the relative frequencies of the two acts are, so I cannot even make a utilitarian ethical judgement.
I think the responses to this can be broken down into a 2x2 matrix: level of concern vs. understanding of technology. 1) Don't understand ML; not concerned - "I have nothing to hide." 2) Don't understand ML; concerned - "I bought this device and now people are spying on me!" 3) Understand ML; not concerned - "Of course, Google needs to label its training data." 4) Understand ML; concerned - "How can we train models/c…
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We test our medicines on a small group that is representative of the entire worlds population. We build soil models based on sampling a small region. We don't test your entire blood to do a medical test. I don't know what you mean by "real data", but representative sampling is how work gets done in every single domain in the world. Google can do this.
Yeah no. Representative sampling is how we formerly did this kind of work. It wasn't particularly good or effective, but we didn't have the methods or compute to go beyond that. No longer.
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Face coverings are not legal in public in all countries, but even where they are, why should someone concerned about creeping surveillance go to great lengths to modify their own behaviour because someone else is unwittingly breaking the law because a product they bought was made by someone who couldn’t be bothered to do it right?
> Face coverings are not legal in public in all countries, And that of course is the point.
Should Voice Assistants be required to annoy that they are recording every time they received an activation? Until the user explicitly approves long term? Should that approval require daily or monthly renewal? Should the device detect new voices and give them the same warning? Should these recommendations become law?
I think the responses to this can be broken down into a 2x2 matrix: level of concern vs. understanding of technology. 1) Don't understand ML; not concerned - "I have nothing to hide." 2) Don't understand ML; concerned - "I bought this device and now people are spying on me!" 3) Understand ML; not concerned - "Of course, Google needs to label its training data." 4) Understand ML; concerned - "How can we train models/c…
The reason companies use lots of live data is because people get upset when facial recognition doesn't work on people with different skin colors, voice recognition doesn't work for people with accents, etc. Doing #3 is literally the result of #4.