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Q3503338
Matemática
A seguinte matriz quadrada M = (mij )
3x3
foi construída de tal
maneira que mi3 = mi1 − mi2 , ∀i ∈ {1,2,3}.
O determinante de M vale
O determinante de M vale
Q3503336
Inglês
The speech “Don’t try to sneak a water bottle past security this
time” implies that the character in the cartoon
Q3503334
Inglês
Texto associado
Text I
Understanding bias in facial recognition technologies
Over the past couple of years, the growing debate around
automated facial recognition has reached a boiling point. As
developers have continued to swiftly expand the scope of these
kinds of technologies into an almost unbounded range of
applications, an increasingly strident chorus of critical voices has
sounded concerns about the injurious effects of the proliferation
of such systems on impacted individuals and communities. Critics
argue that the irresponsible design and use of facial detection and
recognition technologies (FDRTs) threaten to violate civil liberties,
infringe on basic human rights and further entrench structural
racism and systemic marginalisation. In addition, they argue that
the gradual creep of face surveillance infrastructures into every
domain of lived experience may eventually eradicate the modern
democratic forms of life that have long provided cherished means
to individual flourishing, social solidarity and human self-creation.
Defenders, by contrast, emphasise the gains in public safety,
security and efficiency that digitally streamlined capacities for
facial identification, identity verification and trait characterisation
may bring. These proponents point to potential real-world benefits
like the added security of facial recognition enhanced border
control, the increased efficacy of missing children or criminal
suspect searches that are driven by the application of brute force
facial analysis to largescale databases and the many added
conveniences of facial verification in the business of everyday life.
Whatever side of the debate on which one lands, it would
appear that FDRTs are here to stay.
Adapted from: understanding_bias_in_facial_recognition_technology.pdf
The word “like” in “like the added security of facial recognition”
(2nd paragraph) introduces a(n)
Q3503333
Inglês
Texto associado
Text I
Understanding bias in facial recognition technologies
Over the past couple of years, the growing debate around
automated facial recognition has reached a boiling point. As
developers have continued to swiftly expand the scope of these
kinds of technologies into an almost unbounded range of
applications, an increasingly strident chorus of critical voices has
sounded concerns about the injurious effects of the proliferation
of such systems on impacted individuals and communities. Critics
argue that the irresponsible design and use of facial detection and
recognition technologies (FDRTs) threaten to violate civil liberties,
infringe on basic human rights and further entrench structural
racism and systemic marginalisation. In addition, they argue that
the gradual creep of face surveillance infrastructures into every
domain of lived experience may eventually eradicate the modern
democratic forms of life that have long provided cherished means
to individual flourishing, social solidarity and human self-creation.
Defenders, by contrast, emphasise the gains in public safety,
security and efficiency that digitally streamlined capacities for
facial identification, identity verification and trait characterisation
may bring. These proponents point to potential real-world benefits
like the added security of facial recognition enhanced border
control, the increased efficacy of missing children or criminal
suspect searches that are driven by the application of brute force
facial analysis to largescale databases and the many added
conveniences of facial verification in the business of everyday life.
Whatever side of the debate on which one lands, it would
appear that FDRTs are here to stay.
Adapted from: understanding_bias_in_facial_recognition_technology.pdf
In the first sentence, when the author says that the debate
“has reached a boiling point”, he means that the debate is
Q3503332
Inglês
Texto associado
Text I
Understanding bias in facial recognition technologies
Over the past couple of years, the growing debate around
automated facial recognition has reached a boiling point. As
developers have continued to swiftly expand the scope of these
kinds of technologies into an almost unbounded range of
applications, an increasingly strident chorus of critical voices has
sounded concerns about the injurious effects of the proliferation
of such systems on impacted individuals and communities. Critics
argue that the irresponsible design and use of facial detection and
recognition technologies (FDRTs) threaten to violate civil liberties,
infringe on basic human rights and further entrench structural
racism and systemic marginalisation. In addition, they argue that
the gradual creep of face surveillance infrastructures into every
domain of lived experience may eventually eradicate the modern
democratic forms of life that have long provided cherished means
to individual flourishing, social solidarity and human self-creation.
Defenders, by contrast, emphasise the gains in public safety,
security and efficiency that digitally streamlined capacities for
facial identification, identity verification and trait characterisation
may bring. These proponents point to potential real-world benefits
like the added security of facial recognition enhanced border
control, the increased efficacy of missing children or criminal
suspect searches that are driven by the application of brute force
facial analysis to largescale databases and the many added
conveniences of facial verification in the business of everyday life.
Whatever side of the debate on which one lands, it would
appear that FDRTs are here to stay.
Adapted from: understanding_bias_in_facial_recognition_technology.pdf
In the last sentence, the author states that facial detection and
recognition technologies
Q3503331
Inglês
Texto associado
Text I
Understanding bias in facial recognition technologies
Over the past couple of years, the growing debate around
automated facial recognition has reached a boiling point. As
developers have continued to swiftly expand the scope of these
kinds of technologies into an almost unbounded range of
applications, an increasingly strident chorus of critical voices has
sounded concerns about the injurious effects of the proliferation
of such systems on impacted individuals and communities. Critics
argue that the irresponsible design and use of facial detection and
recognition technologies (FDRTs) threaten to violate civil liberties,
infringe on basic human rights and further entrench structural
racism and systemic marginalisation. In addition, they argue that
the gradual creep of face surveillance infrastructures into every
domain of lived experience may eventually eradicate the modern
democratic forms of life that have long provided cherished means
to individual flourishing, social solidarity and human self-creation.
Defenders, by contrast, emphasise the gains in public safety,
security and efficiency that digitally streamlined capacities for
facial identification, identity verification and trait characterisation
may bring. These proponents point to potential real-world benefits
like the added security of facial recognition enhanced border
control, the increased efficacy of missing children or criminal
suspect searches that are driven by the application of brute force
facial analysis to largescale databases and the many added
conveniences of facial verification in the business of everyday life.
Whatever side of the debate on which one lands, it would
appear that FDRTs are here to stay.
Adapted from: understanding_bias_in_facial_recognition_technology.pdf
Based on Text I, analyze the assertions below:
I. Critics are concerned about the pervasiveness of facial recognition technology.
II. Facial recognition systems may reduce the efficiency and security of border control.
III. Some argue that the new technology could undermine the stability of modern democracy.
Choose the correct answer:
Q3503330
Português
Os vocábulos abaixo aparecem acentuados, mas um deles está acentuado de forma incorreta.
Assinale a opção em que esse vocábulo aparece.
Q3503329
Português
As frases a seguir trazem nomes de especialidades médicas.
Assinale a frase cuja especialidade tem seu objeto corretamente
definido.
Q3503328
Português
Assinale a frase em que há erro no emprego do acento grave
indicativo da crase.
Q3503327
Português
Assinale a frase em que “um/uma” é classificado como numeral e
não como artigo.
Q3503326
Português
Assinale a frase a seguir em que a troca de posição entre
substantivo e adjetivo provoca modificação de sentido.
Q3503325
Português
Assinale a frase em que a expressão “graças a” está empregada de
forma adequada.
Q3503324
Português
Assinale a afirmativa correta sobre os elementos de uma das frases
a seguir.
Q3503323
Português
Assinale a frase em que a forma sublinhada está grafada
corretamente.
Q3503322
Português
Assinale a frase em que houve troca indevida entre “senão” e “se
não”.
Q3503321
Português
Assinale a frase em que o termo, de valor adverbial, foi
corretamente substituído por um advérbio de sentido equivalente.
Q3503320
Português
Assinale a opção em que a palavra “só” é classificada como na frase
“Para assistirem a este filme, só entram os maiores de dezoito
anos”.
Q3503319
Português
Assinale a opção em que a palavra “mais” mostra uma classe
gramatical diferente das demais.
Q3503318
Português
Assinale a frase que se estrutura por meio de antônimos.
Q3503317
Português
Um código indiano de leis registra o seguinte:
Toda vez que o homem reconhece e confessa ter pecado, libera-se do próprio pecado como uma serpente, da pele velha.
Sobre o significado e a estruturação desse segmento textual, é correto afirmar que
Toda vez que o homem reconhece e confessa ter pecado, libera-se do próprio pecado como uma serpente, da pele velha.
Sobre o significado e a estruturação desse segmento textual, é correto afirmar que
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