By Aythami Morales, El País Retina
¿Qué tiene que ver la rivalidad de Cristiano y Messi o la de Nadal y Federer con los algoritmos? La respuesta es la competencia.
San Francisco is first US city to ban facial recognition
Face recognition technology is not bad itself. However, it is important to promote a discussion among users, scientific community, companies, and governmental agencies about its usage.
There are very interesting challenges to face up in next years. It is important to move in the correct way.
More details:
https://www.bbc.com/news/technology-48276660
The tech industry doesn’t have a plan for dealing with bias in facial recognition
By James Vincent , The Verge
We surveyed a dozen firms to see what they were doing about this problem. Experts say: not enough.
Read the complete article at [link]
Discriminating algorithms: 5 times AI showed prejudice
By Daniel Cossins.
Artificial intelligence is supposed to make life easier for us all – but it is also prone to amplify sexist and racist biases from the real world.
Read the complete article at [Link]
Biometric challenges in the age of GDPR
By Michiel van der Veen and Els Kindt.
Finding the right balance between technical, legal and ethical demands.
As the world is quickly moving into the Fourth Industrial Era, more people put more of their personal data and that of their devices online. In this vast digital landscape, a wide range of private companies and government agencies collect, process and (re-)sell this data, and establish digital identities around them. With fingerprints, face recognition and iris scan technology, biometric systems can then authenticate and verify individuals to allow or deny access to a wide array of services. But as always, all these new developments also present a whole new range of ethical, legal and technical difficulties. Overcoming them will be one of the main challenges of our times.
Read the complete article at [Link]
Facial Recognition Is Accurate, if You’re a White Guy
By Steve Lohr, The New York Times.
Facial recognition technology is improving by leaps and bounds. Some commercial software can now tell the gender of a person in a photograph.
When the person in the photo is a white man, the software is right 99 percent of the time.
But the darker the skin, the more errors arise — up to nearly 35 percent for images of darker skinned women, according to a new study that breaks fresh ground by measuring how the technology works on people of different races and gender.
Read the complete article at [Link]
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