Questões Militares de Inglês - Vocabulário | Vocabulary

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Because we all have different styles of teaching, and therefore planning, orientations about course planning and delivery should not be meant to be prescriptive. As Bailey (1996) points out, a lesson plan is like a road map “which describes where the teacher hopes to go in a lesson, presumably taking the students along”. It is the latter part of this quote that is important for teachers to remember, because they may need to make “in-flight” changes in response to the actuality of the classroom. As Bailey (1996) correctly points out, “In realizing lesson plans, part of a skilled teacher’s logic in use involves managing such departures to maximimize teaching and learning opportunities”. Clearly thought-out lesson plans will more likely maintain the attention of students and increase the likelihood that they will be interested.

(RICHARDS, Jack C.; RENANDYA, Willy A.(Ed.). Methodology in language teaching: an anthology of current practice. Cambridge: Cambridge University Press, 2002. p. 36. Adaptado) 

How facial recognition technology aids police

Police officers’ ability to recognize and locate individuals with a history of committing crime is vital to their work. In fact, it is so important that officers believe possessing it is fundamental to the craft of effective street policing, crime prevention and investigation. However, with the total police workforce falling by almost 20 percent since 2010 and recorded crime rising, police forces are turning to new technological solutions to help enhance their capability and capacity to monitor and track individuals about whom they have concerns.

One such technology is Automated Facial Recognition (known as AFR). This works by analyzing key facial features, generating a mathematical representation of them, and then comparing them against known faces in a database, to determine possible matches. While a number of UK and international police forces have been enthusiastically exploring the potential of AFR, some groups have spoken about its legal and ethical status. They are concerned that the technology significantly extends the reach and depth of surveillance by the state.

Until now, however, there has been no robust evidence about what AFR systems can and cannot deliver for policing. Although AFR has become increasingly familiar to the public through its use at airports to help manage passport checks, the environment in such settings is quite controlled. Applying similar procedures to street policing is far more complex. Individuals on the street will be moving and may not look directly towards the camera. Levels of lighting change, too, and the system will have to cope with the vagaries of the British weather.

[…]

As with all innovative policing technologies there are important legal and ethical concerns and issues that still need to be considered. But in order for these to be meaningfully debated and assessed by citizens, regulators and law-makers, we need a detailed understanding of precisely what the technology can realistically accomplish. Sound evidence, rather than references to science fiction technology --- as seen in films such as Minority Report --- is essential.

With this in mind, one of our conclusions is that in terms of describing how AFR is being applied in policing currently, it is more accurate to think of it as “assisted facial recognition,” as opposed to a fully automated system. Unlike border control functions -- where the facial recognition is more of an automated system -- when supporting street policing, the algorithm is not deciding whether there is a match between a person and what is stored in the database. Rather, the system makes suggestions to a police operator about possible similarities. It is then down to the operator to confirm or refute them.

By Bethan Davies, Andrew Dawson, Martin Innes (Source: https://gcn.com/articles/2018/11/30/facial-recognitionpolicing.aspx, accessed May 30th, 2020)