With the introduction of the iPhone X, Apple brought to the forefront facial recognition technology, or what they call FaceID - a way for users to be able to unlock their phone just by looking at it. The technology has been around for decades, but not until now has it started raising questions about safety and security. Just recently, a controversial Stanford University study used face recognition to determine whether someone was gay or straight. Kathryn Ryan speaks with Clare Garvie - a privacy lawyer who researches the risks of face recognition technology at Georgetown University.
Listen:
Facial recognition tech
Uses
Law Enforcement:
1.
2.
Retail outlets
1.
2.
Social meid platforms
1.
2.
In Russia
1.
Apple and Facebook
1. information not __________ to anyone else
"Face First"
1. makes templates ___________________ -
2. Collects the information from _____________
What are the laws regulating use of face recognition tech?
What happens in practice?
Risk Factors
What makes face recognition so powerful?
1._________________
2. Often done ________________
3. Companies are started to adopt ___________
4. An Israeli company called ________________ market product that supposedly ______________
5. Even though the science is not proven _____________________
6. The Saudi Government uses _____________ and could use it to s________ visitors to the country or e________ or eligibility of citizens to _________.
7. Facial recognition tech is a H____ Gr____ for marketing.
8. It can give advertisers and retailers a _______________ about their customers.
Discuss
What issues does this technology raise?
Is there anything that could be done about the risk factors mentioned?
Can you think of any other uses and/or risk factors?
Revise Collocations
More on Face First here:
Face First
More on Faception:
Faceception
Kronos Quartet try out facial recognition technology
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An art project is looking at how machines might perceive the world compared to humans.
While the Kronos Quartet perform, the artificial intelligence (AI) Sight Machine uses algorithms to read the musicians' genders, ages and emotions.
A projection of what the AI is interpreting is displayed behind the musicians, but how reliable is the AI in what it sees?