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AI Now pide al gobierno que restrinja el uso de tecnología para detectar emociones (7 respuestas)
1 :
root@bienvenidoainternet.org:~#
: 14/12/19(sab)06:56:10
ID:jaSyL8Wz0
Systems are already on sale to help vet job seekers, test criminal suspects for signs of deception, and set insurance prices. They want such software to be banned from use in important decisions that affect people's lives and/or determine their access to opportunities.
AI Now refers to the technology by its formal name, affect recognition, in its annual report. It says the sector is undergoing a period of significant growth and could already be worth as much as $20 billion. "It claims to read, if you will, our inner-emotional states by interpreting the micro-expressions on our face, the tone of our voice or even the way that we walk," explained co-founder Prof Kate Crawford.
"It's being used everywhere, from how do you hire the perfect employee through to assessing patient pain, through to tracking which students seem to be paying attention in class.
https://www.bbc.com/news/technology-50761116
2 :
root@bienvenidoainternet.org:~#
: 14/12/19(sab)08:09:58
ID:JA3YtmVva
Otra vez cagándose a los autistas e introvertidos.
3 :
root@bienvenidoainternet.org:~#
: 14/12/19(sab)12:20:09
ID:PAhTVqGGa!
Los sociópatas volvemos a ganar.
4 :
root@bienvenidoainternet.org:~#
: 14/12/19(sab)20:34:45
ID:kfKgYDvyT
La tecnología fue un error. La civilización fue un error. La humanidad fue un error.
El hecho de que un montón de nucleótidos y elementos específicos se ordenaran de forma específica en un caldo primigenio para dar lugar a la vida fue un error.
Porque tarde que temprano los humanos hubiéramos aparecido de una forma u otra :)
Cada día es más difícil no ser un nihilista.
7 :
root@bienvenidoainternet.org:~#
: 16/12/19(lun)02:04:21
ID:vZnOQiidT
Las redes neuronales nos acercan cada vez más a la distopía.
> Machine learning systems are pretty good at finding hidden correlations in data and using them to infer potentially compromising information about the people who generate that data: for example, researchers fed an ML system a bunch of Google Play reviews by reviewers whose locations were explicitly given in their Google Plus reviews; based on this, the model was able to predict the locations of other Google Play reviewers with about 44% accuracy. https://boingboing.net/2019/10/02/mockingbird-and-attriguard.html
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