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English as a Lingua Franca

A number of researchers have studied conversations in English as a Lingua Franca and have noted a number of somewhat surprising characteristics, including:

•  Non-use of third person present simple tense -s (She look very sad).

•  Interchangeable use of the relative pronouns who and which (a book who, a boy which).

•  Omission of articles where they are mandatory in native-speaker English.

•  Increasing of redundancy by adding “inexistent” prepositions (We have to study about…, The article treats of…).

•  Pluralisation of nouns which are considered uncountable in native-speaker English (informations, staffs).

The evidence suggests that non-native speakers are not conforming to a native English standard. Indeed they seem to get along perfectly well despite the fact that they miss things out and put things in which they ‘should not do’. Not only this, but they are actually better at ‘accommodating’ - that is, negotiating shared meaning through helping each other in a more cooperative way - than, it is suggested, native speakers are when talking to second language speakers (Jenkins 2004). In other words, non-native speakers seem to be better at ELF communication than native speakers are.

(Jeremy Harmer, The practice of English language teaching. 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)

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)