5 ms·

Does anybody know of a facial recognition AI that actually classifies faces as (non)-liars as she claims? Not sure about this take. You need data at the end of

Does anybody know of a facial recognition AI that actually classifies faces as (non)-liars as she claims? Not sure about this take. You need data at the end of the day, to build good AI models. These days it feels like anyone's public takes are more or less just a means to promote their own cause. And I say this as a happy and long-time Signal user.

deleted 3y ago
[deleted]
jazzyjackson 3y ago
AOL keyword "deception analysis" There's no science behind it but that never stopped someone from selling software to the police, high tech polygraphs are probably out there. Closest thing I've found in production is more "nervous person recognition" used at airports for triggering secondary screening: >> the Department of Homeland Security (DHS) Science and Technology Directorate (S&T) seeks to improve DHS’s ability to quickly and objectively screen individuals for malintent. FAST combines cutting-edge behavioral and physiological science with deception detection theory and state-of-the-art sensor technologies. [0] I don't think her hot take is mere self-promotion, but rejection that building "good models" is necessary or helpful to average people, maybe there's some benefits but it increases the power of the state more than the individual (old debate in computing) [0] https://www.dhs.gov/sites/default/files/publications/Future%20Attribute%20Screening%20Technology-FAST.pdf https://www.dhs.gov/sites/default/files/publications/Future%...
mufasachan 3y ago
A simple research on Scholar with "facial recognition liars" leads to a few niche articles about the topic. So it seems that facial recognition for liars is a thing. After a quick look on the articles you can see those methods are very simple and they are not studied at the state of the arts level. It looks like much more an academic research field rather than an industrial field. So her claims are preventive alarmist. Although, I would say she is not the most informed person in surveillance task in AI. Another surveillance field in AI is the "person re-identification" task. It aims to determine if two pictures of a person from surveillance cameras depict the same person or not. This is my field of research and you have a tons of papers each year in big AI venues and also big company in the author (alibaba, tencent, mostly big chinese tech companies, I saw one paper with Google once on a related task). Also, I would like to highlight something. She said we need some people to annotate the datasets. For this surveillance task, actually, we have a bunch of methods that aims to less rely on human annotations : LUPerson and LUPerson-NL datasets and respective methods (CVPR 21 and 22) for example. Finally, I would like to conclude that I mostly agree with her. A bit of nuance would be to see the interaction with the nature of data and the surveillance capabilities. AI on camera data are obviously surveillance. When it comes more blur it's what "surveillance" is for "code taken from the internet to train Github copilot method"? Or what is the surveillance capability from database of digital arts? Those questions seem to be much more relevant and hard in regard of the use of data for surveillance. AI is just a name of a method that we use to process big data at scale in this context.
nonrandomstring 3y ago
> Not sure about this take. You need data at the end of the day, to build good AI models. I don't think she is saying that AI is predicated on surveillance as a source of training data (although that does happen in a few cases). She seems to be saying that surveillance is the primary use case for AI. Actually I don't think that's true, consider manufacturing robots. However, mass surveillance, a societal scourge and urgent threat to democracy, does seem to be greatly enhanced by AI, so I think this is a bit of worry take. > These days it feels like anyone's public takes are more or less just a means to promote their own cause. Wasn't it always true? Trivially all people advocate their beliefs, with a few marginal exceptions like the guy who reads the weather report.
- janAkali 3y ago
  > Actually I don't think that's true, consider manufacturing robots. We're long way from making fully AI-driven robots. But much closer to other uses. Our current world is very data-centric: companies have been collecting, selling, sharing and stashing metadata with websites, social media and smartphones for the last decade. Now, language models will help them process it. I have one question: for what cause? Surely, for the good of humanity. That's what the companies exist for, right? It's not like we need laws to force companies to not screw us over, or in America they need lobbyists to force politicians to force companies to not screw them over. Currently, AI is absolutely unregulated wild lawless west, and it's frightening. And not because of bad actors, but because of the 'pretending to be good' ones. > Wasn't it always true? Trivially all people advocate their beliefs.. You would be surprised, but people need constant reminders of that. Or they will start treating mega-corporations as privacy-respecting, consumer-oriented, eco-friendly or any other bullshit their PR-team trying to push today or will try tomorrow.
  - nonrandomstring 3y ago
    > I have one question: for what cause? Someone else asked that question in this same thread [0]. It's a good question. The purposelessness of much technology is a problem Neil Postman addressed very robustly in "Technopoly" [1]. To date I have not heard any sane responses to his "Six Questions Regarding Technology" [2]. > not because of bad actors, but because of the 'pretending to be good' ones. When you don't have any reason at all for doing something, and you're challenged, one tends to use imagination to dream up a plausible "good" reason. [0] https://news.ycombinator.com/item?id=37656891 https://news.ycombinator.com/item?id=37656891 [1] https://en.wikipedia.org/wiki/Technopoly https://en.wikipedia.org/wiki/Technopoly [2] https://cyber.harvard.edu/node/95930 https://cyber.harvard.edu/node/95930
michaelt 3y ago
Well, the full quote from Whittaker is: > “You know, you walk past a facial recognition camera that’s instrumented with pseudo-scientific emotion recognition, and it produces data about you, right or wrong, that says ‘you are happy, you are sad, you have a bad character, you’re a liar, whatever.’ While I'm not aware of any technology that claims to classify faces as liars the rest of the statement is broadly true. And if you wanted to cross-check a face against a database of known liars, the entire statement is true. According to https://www.cyberlink.com/faceme/insights/articles/363/smart-retail-with-facial-recognition https://www.cyberlink.com/faceme/insights/articles/363/smart... "It can be difficult to discern how consumers feel about a retail experience, or about the products they are buying or avoiding. Facial recognition can help with this by assessing and charting emotions: happy, sad, angry, surprised, indifferent, etc." It also says "By cross-checking everyone who enters the store against a database of identified shoplifters and unruly customers, facial recognition can detect and deter repeat offenders" and "Using facial recognition, retailers can know precisely when an employee arrives, takes breaks, and leaves for the day" Personally a lot of this technology seems pretty doubtful to me - don't shoplifters wear hats to keep their faces off CCTV? And every 'emotion recognition' system demo I've seen has used faces with emotions so ridiculously exaggerated they look like they belong in a youtube thumbnail.
- jdthedisciple 3y ago
  > It also says "By cross-checking everyone who enters the store against a database of identified shoplifters and unruly customers, facial recognition can detect and deter repeat offenders" and "Using facial recognition, retailers can know precisely when an employee arrives, takes breaks, and leaves for the day" Ofc you "can" - in principle. Is any of this currently being done, however?
  - janAkali 3y ago
    > Is any of this currently being done, however? Companies aren't obligated to disclose the training process. So, we can't tell. Until, in the matter of months, it is available, accessible and almost impossible to regulate. And every company will start using it to not fall behind.
jollofricepeas 3y ago
"data can either be useful or perfectly anonymous but never both" Therefore… AI is fundamentally a surveillance technology. SOURCE: https://arstechnica.com/tech-policy/2009/09/your-secrets-live-online-in-databases-of-ruin/amp/ https://arstechnica.com/tech-policy/2009/09/your-secrets-liv...
johnnyworker 3y ago
The point isn't whether those things are correct. They are used as tools of surveillance and oppression. > These are ultimately surveillance systems that are being marketed to those who have power over us generally: our employers, governments, border control, etc., to make determinations and predictions that will shape our access to resources and opportunities. And hey, the more arbitrary or even false something is, the more obedience you can demonstrate by going along with it just because computer said no, so that's another "bonus". Here's a chilling real-life example: https://www.politico.eu/article/dutch-scandal-serves-as-a-warning-for-europe-over-risks-of-using-algorithms/ https://www.politico.eu/article/dutch-scandal-serves-as-a-wa... > In 2019 it was revealed that the Dutch tax authorities had used a self-learning algorithm to create risk profiles in an effort to spot child care benefits fraud. > Authorities penalized families over a mere suspicion of fraud based on the system’s risk indicators. Tens of thousands of families — often with lower incomes or belonging to ethnic minorities — were pushed into poverty because of exorbitant debts to the tax agency. Some victims committed suicide. More than a thousand children were taken into foster care. Let that sink in.
- mavhc 3y ago
  "Authorities penalized families over a mere suspicion of fraud based on the system’s risk indicators" Don't do that part, nothing to do with AI, it's about humans being lazy
  - notRobot 3y ago
    And AI enables it to greater ex extents then ever before.
    - mavhc 3y ago
      So do computers, still the humans to blame
      - pixl97 3y ago
        And technology changes the scale of the buy in of that single human you have to blame. Generally a country has to follow some terrible authoritarian leader before horrific things start to happen, but when software causes the problem, even the most open democracies give up and say "Well the software told me so"
cratermoon 3y ago
> Does anybody know of a facial recognition AI that actually classifies faces as (non)-liars as she claims? https://www.technologyreview.com/2020/03/13/905323/ai-lie-detectors-polygraph-silent-talker-iborderctrl-converus-neuroid/ https://www.technologyreview.com/2020/03/13/905323/ai-lie-de...

deleted 3y ago

[deleted]

jazzyjackson 3y ago

AOL keyword "deception analysis" There's no science behind it but that never stopped someone from selling software to the police, high tech polygraphs are probably out there. Closest thing I've found in production is more "nervous person recognition" used at airports for triggering secondary screening: >> the Department of Homeland Security (DHS) Science and Technology Directorate (S&T) seeks to improve DHS’s ability to quickly and objectively screen individuals for malintent. FAST combines cutting-edge behavioral and physiological science with deception detection theory and state-of-the-art sensor technologies. [0] I don't think her hot take is mere self-promotion, but rejection that building "good models" is necessary or helpful to average people, maybe there's some benefits but it increases the power of the state more than the individual (old debate in computing) [0] https://www.dhs.gov/sites/default/files/publications/Future%20Attribute%20Screening%20Technology-FAST.pdf https://www.dhs.gov/sites/default/files/publications/Future%...

mufasachan 3y ago

A simple research on Scholar with "facial recognition liars" leads to a few niche articles about the topic. So it seems that facial recognition for liars is a thing. After a quick look on the articles you can see those methods are very simple and they are not studied at the state of the arts level. It looks like much more an academic research field rather than an industrial field. So her claims are preventive alarmist. Although, I would say she is not the most informed person in surveillance task in AI. Another surveillance field in AI is the "person re-identification" task. It aims to determine if two pictures of a person from surveillance cameras depict the same person or not. This is my field of research and you have a tons of papers each year in big AI venues and also big company in the author (alibaba, tencent, mostly big chinese tech companies, I saw one paper with Google once on a related task). Also, I would like to highlight something. She said we need some people to annotate the datasets. For this surveillance task, actually, we have a bunch of methods that aims to less rely on human annotations : LUPerson and LUPerson-NL datasets and respective methods (CVPR 21 and 22) for example. Finally, I would like to conclude that I mostly agree with her. A bit of nuance would be to see the interaction with the nature of data and the surveillance capabilities. AI on camera data are obviously surveillance. When it comes more blur it's what "surveillance" is for "code taken from the internet to train Github copilot method"? Or what is the surveillance capability from database of digital arts? Those questions seem to be much more relevant and hard in regard of the use of data for surveillance. AI is just a name of a method that we use to process big data at scale in this context.

nonrandomstring 3y ago

> Not sure about this take. You need data at the end of the day, to build good AI models. I don't think she is saying that AI is predicated on surveillance as a source of training data (although that does happen in a few cases). She seems to be saying that surveillance is the primary use case for AI. Actually I don't think that's true, consider manufacturing robots. However, mass surveillance, a societal scourge and urgent threat to democracy, does seem to be greatly enhanced by AI, so I think this is a bit of worry take. > These days it feels like anyone's public takes are more or less just a means to promote their own cause. Wasn't it always true? Trivially all people advocate their beliefs, with a few marginal exceptions like the guy who reads the weather report.

janAkali 3y ago
> Actually I don't think that's true, consider manufacturing robots. We're long way from making fully AI-driven robots. But much closer to other uses. Our current world is very data-centric: companies have been collecting, selling, sharing and stashing metadata with websites, social media and smartphones for the last decade. Now, language models will help them process it. I have one question: for what cause? Surely, for the good of humanity. That's what the companies exist for, right? It's not like we need laws to force companies to not screw us over, or in America they need lobbyists to force politicians to force companies to not screw them over. Currently, AI is absolutely unregulated wild lawless west, and it's frightening. And not because of bad actors, but because of the 'pretending to be good' ones. > Wasn't it always true? Trivially all people advocate their beliefs.. You would be surprised, but people need constant reminders of that. Or they will start treating mega-corporations as privacy-respecting, consumer-oriented, eco-friendly or any other bullshit their PR-team trying to push today or will try tomorrow.
- nonrandomstring 3y ago
  > I have one question: for what cause? Someone else asked that question in this same thread [0]. It's a good question. The purposelessness of much technology is a problem Neil Postman addressed very robustly in "Technopoly" [1]. To date I have not heard any sane responses to his "Six Questions Regarding Technology" [2]. > not because of bad actors, but because of the 'pretending to be good' ones. When you don't have any reason at all for doing something, and you're challenged, one tends to use imagination to dream up a plausible "good" reason. [0] https://news.ycombinator.com/item?id=37656891 https://news.ycombinator.com/item?id=37656891 [1] https://en.wikipedia.org/wiki/Technopoly https://en.wikipedia.org/wiki/Technopoly [2] https://cyber.harvard.edu/node/95930 https://cyber.harvard.edu/node/95930

michaelt 3y ago

Well, the full quote from Whittaker is: > “You know, you walk past a facial recognition camera that’s instrumented with pseudo-scientific emotion recognition, and it produces data about you, right or wrong, that says ‘you are happy, you are sad, you have a bad character, you’re a liar, whatever.’ While I'm not aware of any technology that claims to classify faces as liars the rest of the statement is broadly true. And if you wanted to cross-check a face against a database of known liars, the entire statement is true. According to https://www.cyberlink.com/faceme/insights/articles/363/smart-retail-with-facial-recognition https://www.cyberlink.com/faceme/insights/articles/363/smart... "It can be difficult to discern how consumers feel about a retail experience, or about the products they are buying or avoiding. Facial recognition can help with this by assessing and charting emotions: happy, sad, angry, surprised, indifferent, etc." It also says "By cross-checking everyone who enters the store against a database of identified shoplifters and unruly customers, facial recognition can detect and deter repeat offenders" and "Using facial recognition, retailers can know precisely when an employee arrives, takes breaks, and leaves for the day" Personally a lot of this technology seems pretty doubtful to me - don't shoplifters wear hats to keep their faces off CCTV? And every 'emotion recognition' system demo I've seen has used faces with emotions so ridiculously exaggerated they look like they belong in a youtube thumbnail.

jdthedisciple 3y ago
> It also says "By cross-checking everyone who enters the store against a database of identified shoplifters and unruly customers, facial recognition can detect and deter repeat offenders" and "Using facial recognition, retailers can know precisely when an employee arrives, takes breaks, and leaves for the day" Ofc you "can" - in principle. Is any of this currently being done, however?
- janAkali 3y ago
  > Is any of this currently being done, however? Companies aren't obligated to disclose the training process. So, we can't tell. Until, in the matter of months, it is available, accessible and almost impossible to regulate. And every company will start using it to not fall behind.

jollofricepeas 3y ago

"data can either be useful or perfectly anonymous but never both" Therefore… AI is fundamentally a surveillance technology. SOURCE: https://arstechnica.com/tech-policy/2009/09/your-secrets-live-online-in-databases-of-ruin/amp/ https://arstechnica.com/tech-policy/2009/09/your-secrets-liv...

johnnyworker 3y ago

The point isn't whether those things are correct. They are used as tools of surveillance and oppression. > These are ultimately surveillance systems that are being marketed to those who have power over us generally: our employers, governments, border control, etc., to make determinations and predictions that will shape our access to resources and opportunities. And hey, the more arbitrary or even false something is, the more obedience you can demonstrate by going along with it just because computer said no, so that's another "bonus". Here's a chilling real-life example: https://www.politico.eu/article/dutch-scandal-serves-as-a-warning-for-europe-over-risks-of-using-algorithms/ https://www.politico.eu/article/dutch-scandal-serves-as-a-wa... > In 2019 it was revealed that the Dutch tax authorities had used a self-learning algorithm to create risk profiles in an effort to spot child care benefits fraud. > Authorities penalized families over a mere suspicion of fraud based on the system’s risk indicators. Tens of thousands of families — often with lower incomes or belonging to ethnic minorities — were pushed into poverty because of exorbitant debts to the tax agency. Some victims committed suicide. More than a thousand children were taken into foster care. Let that sink in.

mavhc 3y ago
"Authorities penalized families over a mere suspicion of fraud based on the system’s risk indicators" Don't do that part, nothing to do with AI, it's about humans being lazy
- notRobot 3y ago
  And AI enables it to greater ex extents then ever before.
  - mavhc 3y ago
    So do computers, still the humans to blame
    - pixl97 3y ago
      And technology changes the scale of the buy in of that single human you have to blame. Generally a country has to follow some terrible authoritarian leader before horrific things start to happen, but when software causes the problem, even the most open democracies give up and say "Well the software told me so"

cratermoon 3y ago

> Does anybody know of a facial recognition AI that actually classifies faces as (non)-liars as she claims? https://www.technologyreview.com/2020/03/13/905323/ai-lie-detectors-polygraph-silent-talker-iborderctrl-converus-neuroid/ https://www.technologyreview.com/2020/03/13/905323/ai-lie-de...