4 ms·

The difference is automation, and the issues that come with that. If you look like someone the system is looking for, there's nothing you can do to whitelist y

The difference is automation, and the issues that come with that. If you look like someone the system is looking for, there's nothing you can do to whitelist yourself other than wear something on your face, you will be flagged, every single time until a human looks at it, and if they're stopping people, that means being stopped, every time. If the system has the wrong face in the database, bad luck. If someone finds a way of preventing detection, say, make up, or big glasses, the system doesn't work any more, as far as I know, even the best facial recognition that only relies on cameras and not depth cameras significantly lose accuracy with either of those. There are a lot of people in London, the false positive and negative rates aren't usually published and anything above zero means those technical problems happen an undisclosed amount too much. Did you ever hear the story of the guy with a very common name ending up on the no fly list? The no fly list was for a long time, and I think still now, literally only a list of names, meaning if someone with a common name goes on the list, everyone with that name gets stopped at the airport as the database gets checked to see if they're the same person. Now think what happens if someone with a generic looking face ends up in the police database.

drusepth 8y ago
>If you look like someone the system is looking for, there's nothing you can do to whitelist yourself other than wear something on your face, you will be flagged, every single time until a human looks at it, and if they're stopping people, that means being stopped, every time. Wouldn't such a system (ideally) learn the differences in [who it expected] and [who it found] and attempt to improve its accuracy to prevent false positives in the future? I don't know if this is too basic, but I'd assume training with a set of similar-but-not-an-exact-match data would be vital for accuracy at scale.
- ubernostrum 8y ago
  I read /r/legaladvice over on reddit. At least a couple times a month there's someone who has had repeated issues with law enforcement banging on their door, sometimes even with guns drawn, because someone with a similar name had a warrant out for their arrest, or a criminal background of some type, or someone the police wanted used to live at their address years ago. And there seems to be very little an average person can do to get "the system" to correct itself; even after multiple instances, the police keep coming back again and again and again and again because "the system said so". Massively scaled automated facial recognition will multiply that many times over, especially when officers are trained to just trust "the system" when "the system" says you're a criminal.
  - ddeck 8y ago
    Yep. One only needs to look at the recent story The Machine Fired Me[1] to see the potential impact of such system errors once things become connected and automated. That poor guy was effectively fired despite the fact that every human agreed that he actually wasn't and should still be employed. [1] https://news.ycombinator.com/item?id=17350645 https://news.ycombinator.com/item?id=17350645
  - drusepth 8y ago
    Thanks for sharing this. Perhaps I interpreted it wrong, but I think this speaks volumes for the amount of low-hanging fruit that exists for improvements in such a system: obviously, the above _shouldn't_ happen but does, which raises the question.. why? I may be (and probably am) wrong, but my guess is that many PDs are still using incredibly outdated systems (at least, mine is), and would vastly benefit from modernizing and improving their systems. There's many other possible reasons (improved systems don't fix this problem, or improved systems have other problems, or administration doesn't care about this problem, etc), but when I read stories like this I think "modern technology would help/fix that" rather than "adding/scaling technology would exacerbate existing problems".
56chan4 8y ago
The facial recognition can be improved automatically by hooking in mobile phone cell tower tracking (cell tower traffic management) in realtime which I believe the police here in the UK also have, then over time the realtime cctv's can also adjust for differences in the camera sensors, like colour hues and white balance, because not everyone is going to follow the same route at the same speed at the same time as everyone else. Its not hard to do if you join up the technology that is also in use, including cash machine usage, shopping payment systems, car park ticket machines, etc etc. Individually, facial recognition on its own has more weaknesses than if its joined up with other tech where users leave a digital footprint. If you take the new electricity smart meters being rolled out in the UK and elsewhere, over time, it would be possible to work out the devices in use by the amount of electricity that is used and the pattern or profile seen of electrical consumption. EG, if you saw a small increase in use of electricity at 4am for a about a minute, you could surmise that someone has turned a light on and possibly gone to the toilet. Over time, you will the same or similar amount of electricity used which could then be used to monitor the toilet habits of the individuals in the property. This could be a measure over the years for prostrate problems if its known a male lives in the property, as an example of how the data could be used to hilight medical problems. If you take a washing machine, this might be hot fill or cold fill, but you could watch the consistent increase & decrease of electricity as the washing machine goes through its cycle, finishing up with a spin cycle. Machines are excellent for consistent demand of electricity. In time, you could even work out what cycle or programme has been selected on the washing machine. When combined with other devices with their own electrical demand patterns, you could work out everything electrical in use, and also identify or predict faulting electrical devices. So the electrical companies could predict wasteful users as well as conservative users if other factors are known like the type of properties, useful or made easy on new build housing estates. This in turn can also be combined in realtime with police systems taking you closer to the fictional minority report, so police could be on hand to prevent a situation in the home or in the street, which I would hope they would be there to do, rather than just arrive after an event and pick up the pieces as this is also traumatic for them seeing as they are also human beings.

drusepth 8y ago

>If you look like someone the system is looking for, there's nothing you can do to whitelist yourself other than wear something on your face, you will be flagged, every single time until a human looks at it, and if they're stopping people, that means being stopped, every time. Wouldn't such a system (ideally) learn the differences in [who it expected] and [who it found] and attempt to improve its accuracy to prevent false positives in the future? I don't know if this is too basic, but I'd assume training with a set of similar-but-not-an-exact-match data would be vital for accuracy at scale.

ubernostrum 8y ago
I read /r/legaladvice over on reddit. At least a couple times a month there's someone who has had repeated issues with law enforcement banging on their door, sometimes even with guns drawn, because someone with a similar name had a warrant out for their arrest, or a criminal background of some type, or someone the police wanted used to live at their address years ago. And there seems to be very little an average person can do to get "the system" to correct itself; even after multiple instances, the police keep coming back again and again and again and again because "the system said so". Massively scaled automated facial recognition will multiply that many times over, especially when officers are trained to just trust "the system" when "the system" says you're a criminal.
- ddeck 8y ago
  Yep. One only needs to look at the recent story The Machine Fired Me[1] to see the potential impact of such system errors once things become connected and automated. That poor guy was effectively fired despite the fact that every human agreed that he actually wasn't and should still be employed. [1] https://news.ycombinator.com/item?id=17350645 https://news.ycombinator.com/item?id=17350645
- drusepth 8y ago
  Thanks for sharing this. Perhaps I interpreted it wrong, but I think this speaks volumes for the amount of low-hanging fruit that exists for improvements in such a system: obviously, the above _shouldn't_ happen but does, which raises the question.. why? I may be (and probably am) wrong, but my guess is that many PDs are still using incredibly outdated systems (at least, mine is), and would vastly benefit from modernizing and improving their systems. There's many other possible reasons (improved systems don't fix this problem, or improved systems have other problems, or administration doesn't care about this problem, etc), but when I read stories like this I think "modern technology would help/fix that" rather than "adding/scaling technology would exacerbate existing problems".

56chan4 8y ago

The facial recognition can be improved automatically by hooking in mobile phone cell tower tracking (cell tower traffic management) in realtime which I believe the police here in the UK also have, then over time the realtime cctv's can also adjust for differences in the camera sensors, like colour hues and white balance, because not everyone is going to follow the same route at the same speed at the same time as everyone else. Its not hard to do if you join up the technology that is also in use, including cash machine usage, shopping payment systems, car park ticket machines, etc etc. Individually, facial recognition on its own has more weaknesses than if its joined up with other tech where users leave a digital footprint. If you take the new electricity smart meters being rolled out in the UK and elsewhere, over time, it would be possible to work out the devices in use by the amount of electricity that is used and the pattern or profile seen of electrical consumption. EG, if you saw a small increase in use of electricity at 4am for a about a minute, you could surmise that someone has turned a light on and possibly gone to the toilet. Over time, you will the same or similar amount of electricity used which could then be used to monitor the toilet habits of the individuals in the property. This could be a measure over the years for prostrate problems if its known a male lives in the property, as an example of how the data could be used to hilight medical problems. If you take a washing machine, this might be hot fill or cold fill, but you could watch the consistent increase & decrease of electricity as the washing machine goes through its cycle, finishing up with a spin cycle. Machines are excellent for consistent demand of electricity. In time, you could even work out what cycle or programme has been selected on the washing machine. When combined with other devices with their own electrical demand patterns, you could work out everything electrical in use, and also identify or predict faulting electrical devices. So the electrical companies could predict wasteful users as well as conservative users if other factors are known like the type of properties, useful or made easy on new build housing estates. This in turn can also be combined in realtime with police systems taking you closer to the fictional minority report, so police could be on hand to prevent a situation in the home or in the street, which I would hope they would be there to do, rather than just arrive after an event and pick up the pieces as this is also traumatic for them seeing as they are also human beings.