Enunciado

About seven years ago, three researchers at the University of Toronto built a system that could
analyze thousands of photos and teach itself to recognize everyday objects, like dogs, cars and flowers.
The system was so effective that Google bought the tiny start-up these researchers were only just
getting off the ground. And soon, their system sparked a technological revolution. Suddenly, machines
could "see" in a way that was not possible in the past.
This made it easier for a smartphone app to search your personal photos and find the images you were
looking for. It accelerated the progress of driverless cars and other robotics. And it improved the
accuracy of facial recognition services, for social networks like Facebook and for the country's law
enforcement agencies. But soon, researchers noticed that these facial recognition services were less
accurate when used with women and people of color. Activists raised concerns over how companies
were collecting the huge amounts of data needed to train these kinds of systems. Others worried these
systems would eventually lead to mass surveillance or autonomous weapons.
Fonte: Matz, Cade. Seeking Ground Rules for A. I. www.nytimes.com, 01/03/2019. Adaptado.
Acessado em Agosto/2019.)

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afirmação: The new system proved to be less precise when