facial recognition
In plain wordsTechnology that identifies or checks who someone is by comparing a picture of their face with stored photos, used by phones, passport gates and police databases.
The automated identification or verification of people from images or video of their faces. A system detects and aligns a face, then uses a deep neural networkdeep learning, n.: Machine learning done with neural networks built from many stacked layers: raw data such as pixels, sound or text goes in at one end, and each layer turns what it receives into something more abstract. to map it to an embeddingembedding, n.: A list of numbers that stands for a word, picture or other item, arranged so that similar items get similar lists. It lets a computer measure similarity of meaning as distance. (a 'faceprint'). Verification (one-to-one) compares it with a single claimed identity, as when a phone checks that its owner is holding it; identification (one-to-many) searches a gallery of enrolled faces, as in police and border systems. Accuracy improved sharply with deep networks such as DeepFace (2014) and FaceNet (2015), and the US National Institute of Standards and Technology benchmarks commercial algorithms. Concerns include demographic differences in error rates (see Gender ShadesGender Shades, prop. n.: A 2018 study showing that commercial face-analysis software guessed the gender of darker-skinned women far less accurately than that of lighter-skinned men.), wrongful arrests from false matches, mass surveillanceAI surveillance, n.: Using AI to watch, identify, track or profile people on a scale no team of humans could manage, for example by scanning camera feeds or analyzing phone and online data. of public spaces, and databases built by scraping photos without consent. The EU AI ActEU AI Act, prop. n.: The European Union's law on artificial intelligence, the first broad AI law anywhere: it bans some uses, sets strict checks for risky ones and puts duties on the makers of the biggest AI models. bans untargeted scraping to build such databases and strictly limits real-time remote biometric identificationremote biometric identification, n.: Using AI to recognize people at a distance — usually by matching faces in camera footage against a database — without their taking part. The EU strictly limits live police use of it in public places. by police in public places.
Investigators ran the CCTV still through facial recognition and got three candidate matches to check by hand.
Origin
Woody Bledsoe, Helen Chan and Charles Bisson built semi-automated face matching in 1964–1966; Takeo Kanade's 1973 doctoral work described a fully automatic system, and Matthew Turk and Alex Pentland's 'eigenfaces' (1991) made statistical methods practical. Public controversy intensified after January 2020 reporting on Clearview AI, which had scraped billions of online photos for police use.
Usage note
Distinct from face detection (finding faces in an image) and from facial analysis, which estimates attributes such as age or expression (see emotion recognition systememotion recognition system, n.: AI that tries to work out how people feel or what they intend from their faces, voices or bodies. The EU bans it at work and in schools and tightly regulates it elsewhere.). San Francisco became the first large US city to ban government use in 2019; in June 2020 IBM, Amazon and Microsoft ended or paused police sales.
Related
- remote biometric identificationremote biometric identification, n.: Using AI to recognize people at a distance — usually by matching faces in camera footage against a database — without their taking part. The EU strictly limits live police use of it in public places.
- AI surveillanceAI surveillance, n.: Using AI to watch, identify, track or profile people on a scale no team of humans could manage, for example by scanning camera feeds or analyzing phone and online data.
- Gender ShadesGender Shades, prop. n.: A 2018 study showing that commercial face-analysis software guessed the gender of darker-skinned women far less accurately than that of lighter-skinned men.
- biometric categorisationbiometric categorisation, n.: Using AI to sort people into groups — by age, sex, ethnicity and the like — from their faces, voices or other body features. The EU bans using it to guess sensitive traits such as religion or sexuality.
- computer visioncomputer vision, n.: The part of AI that lets computers make sense of images and video: recognizing faces, reading signs, spotting tumors on scans or judging how far away a car is.
- algorithmic biasalgorithmic bias, n.: Unfairness in software that judges or serves people: it consistently produces worse results for some groups, such as women, older people or ethnic minorities, often because it learned from skewed or incomplete records.
- predictive policingpredictive policing, n.: Using computer programs to forecast where crimes are likely to happen, or who is likely to be involved, so that police can decide where to patrol or whom to watch.
- emotion recognition systememotion recognition system, n.: AI that tries to work out how people feel or what they intend from their faces, voices or bodies. The EU bans it at work and in schools and tightly regulates it elsewhere.
Sources
- Turk, M. & Pentland, A. (1991). Eigenfaces for Recognition. Journal of Cognitive Neuroscience 3(1), 71–86.
- Taigman, Y., Yang, M., Ranzato, M. & Wolf, L. (2014). DeepFace: Closing the Gap to Human-Level Performance in Face Verification. Proc. CVPR 2014.
Mentioned in
false positivefalse positive, n.: A false alarm: a test or AI system raises a flag, for example for illness, fraud or danger, when nothing of the kind is really there., privacyprivacy, n.: Your ability to control who knows what about you. AI raises new privacy questions because it learns from huge amounts of personal data and can infer things about people they never shared., affective computingaffective computing, n.: Technology that tries to read people's emotions — from their faces, voices or words — or to display emotions of its own, like software that guesses your mood or a robot that seems to show feelings., AI incidentAI incident, n.: A real-world case in which an AI system, through a flaw, a breakdown or the way someone used it, ends up hurting people, property or rights, as in an injury, a wrongful arrest or a privacy breach., AI surveillanceAI surveillance, n.: Using AI to watch, identify, track or profile people on a scale no team of humans could manage, for example by scanning camera feeds or analyzing phone and online data., biometric databiometric data, n.: Information about your body or behavior — your face, fingerprints, voice, eyes or the way you walk — measured by technology and used to recognize who you are or to guess things about you., face detectionface detection, n.: Finding where the faces are in a photo or video, without working out whose faces they are: the step that lets a camera focus on people or blur them out., Gender ShadesGender Shades, prop. n.: A 2018 study showing that commercial face-analysis software guessed the gender of darker-skinned women far less accurately than that of lighter-skinned men., Joy BuolamwiniJoy Buolamwini, prop. n.: A Canadian-American computer scientist and activist whose research showed that face-analysis software works far worse on darker-skinned women, and who founded the Algorithmic Justice League., predictive policingpredictive policing, n.: Using computer programs to forecast where crimes are likely to happen, or who is likely to be involved, so that police can decide where to patrol or whom to watch., remote biometric identificationremote biometric identification, n.: Using AI to recognize people at a distance — usually by matching faces in camera footage against a database — without their taking part. The EU strictly limits live police use of it in public places., speaker verificationspeaker verification, n.: Checking whether a voice really belongs to the person it claims to be, as when a bank confirms your identity by the sound of your voice on the phone., Algorithmic Justice LeagueAlgorithmic Justice League, prop. n.: Joy Buolamwini's organization, known for showing that face-analysis software made far more mistakes with darker-skinned women, which campaigns to hold the makers of biased AI systems accountable., biometric categorisationbiometric categorisation, n.: Using AI to sort people into groups — by age, sex, ethnicity and the like — from their faces, voices or other body features. The EU bans using it to guess sensitive traits such as religion or sexuality., Clearview AIClearview AI, prop. n.: A US company that collected billions of photos from the internet without permission to build a face-search tool for police, the best-known example of controversial facial recognition., emotion recognition systememotion recognition system, n.: AI that tries to work out how people feel or what they intend from their faces, voices or bodies. The EU bans it at work and in schools and tightly regulates it elsewhere., Siamese networkSiamese network, n.: A matching machine built from twin copies of one neural network: each copy turns one of two inputs, say two signatures or two face photos, into a summary, and the two summaries are compared.