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Facial Recognition: Big Data Going Too Far?

by Dan Gray
May 26, 2020
in Machine Learning
Home Topics Data Science Machine Learning
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Facebook’s DeepFace technology is able to recognize faces 97.25% of the time, against 97.53% for a human. Such developments raise questions about the power of such tools and the implications for the future.

Selected use cases of facial recognition technology include:

* NameTag: Allows the user of Google Glass to take a picture of a stranger and check the person’s online profile.

* Amscreen: Cameras at supermarket checkouts ascertain age and gender of individual shoppers, and tailor advertisements accordingly.

* Emotient: Webcam on next-generation TVs monitors viewer engagement levels with content, to aid creative decisions on TV shows.


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* Scenetap: Offers real-time information on gender ratios and average age of patrons at bars in the area

Such applications naturally raise questions of privacy. However, while data mining is anonymized, facial recognition is anything but. Furthermore, it is difficult to ‘opt out’ since most surveillance takes place in public spaces.

Read the full article here.

In conjunction with Big Data Week, we compiled a list of the best Big Data articles here.

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