Questões de Concurso Público SME do Recife - PE 2023 para Professor II - Disciplina: Língua Inglesa

     Artificial intelligence still has difficulties processing requests in one language, without the additional complications of translation. Michael Housman, chief data science officer at RapportBoost.AI, explained that the ideal scenario for machine learning and artificial intelligence is something with fixed rules and a clear-cut measure of success or failure. He named chess as an obvious example. This happened faster than anyone anticipated because of the game’s very clear rules and limited set of moves. Housman elaborated, “Language is almost the opposite of that. There aren’t as clearly-cut and defined rules.”

      I asked Dr. Jorge Majfud, Associate Professor of Spanish, at Jacksonville University, to explain why consistently accurate language translation has thus far eluded AI. He replied, “The problem is that considering the ‘entire’ sentence is still not enough.” He noted that sarcasm and irony only make sense within this widened context. Similarly, idioms can be problematic for automated translations.

       Dr. Majfud warned, “We should be aware of the fragility of their ‘interpretation.’ Because to translate is basically to interpret, not just an idea but a feeling. Human feelings and ideas that only humans can understand — and sometimes not even we, humans, understand other humans.” He noted that cultures, gender, and even age can pose barriers to this understanding and also contended that an over-reliance on technology is leading to our cultural and political decline. Dr. Majfud mentioned that Argentinean writer Julio Cortázar used to refer to dictionaries as “cemeteries”. He suggested that automatic translators could be called “zombies”.

David Pring-Mill. Why Hasn’t AI Mastered Language Translation? Internet:<singularityhub.com>  (adapted).

         When it comes to the vocabulary of languages, is it true, as some suppose, that the vocabularies of so-called primitive languages are too small and inadequate to account for the nuances of the physical and social universes of their speakers? The answer is somewhat complicated. Because the vocabulary of a language serves only the members of the society who speak it, the question to be asked should be: Is a particular vocabulary sufficient to serve the sociocultural needs of those who use the language? When put like this, it follows that the language associated with a relatively simple culture would have a smaller vocabulary than the language of a complex society. Why, for example, should the Inuit people (often known by the pejorative term “Eskimo”) have words for chlorofluoromethane, dune buggy, or tae kwon do when these substances, objects, and concepts play no part in their culture? By the same token, however, the language of a tribal society would have elaborate lexical domains for prominent aspects of the culture although these do not exist in complex societies. The Agta of the Philippines, for example, are reported to have no fewer than thirty-one verbs referring to types of fishing, while in Munich, the terminology for the local varieties of beer is quite extensive, according to strength, color, fizziness, aging, and clarity, the full list exceeding seventy terms.

        However, even though no language spoken today may be labeled primitive, this does not mean that all languages do all things in the same way, or are equally influential in the modern transnational world. The linguistic anthropologist Dell Hymes claims that languages are not functionally equivalent because the role of speech varies from one society to the next. According to Hymes, though all languages “are potentially equal and hence capable of adaptation to the needs of a complex industrial civilization”, only certain languages have actually done so (Hymes 1961:77). These languages are more successful than others not because they are structurally more advanced, but because they happen to be associated with societies in which language is the basis of literature, education, science, and commerce.

Zdenek SALZMANN, James M. STANLAW and Nobuko ADACHI. Language, culture, and society: an introduction to linguistic anthropology. Boulder (CO): Westview Press, 2012. p. 6-7 (adapted).  

          As new technologies take on increasingly humanlike qualities, there’s been a push to make them genderless. Apple’s Siri digital assistant unveiled a gender-neutral option last year, and when asked about their gender identities, the AI chatbots ChatGPT and Google Bard each reply, “I do not have a gender.”

     There have been concerns over gendering technology, since doing so reinforces societal stereotypes. That happens because the stereotypes commonly associated with men, such as competitiveness and dominance, are more valued than those associated with women. That is likely true, says Ashley Martin, a professor at Stanford University. “People are stereotyping their gendered objects in very traditional ways,” she says.

          Removing gender from the picture altogether seems like a simple way to fix this. Yet, as Martin has found in her latest research, conducted with Malia Mason, of Columbia Universty, gender is one of the fundamental ways people form connections with objects, particularly those designed to evoke human characteristics.

          Throughout the experiments, Martin and Mason found that gender increased users’ feelings of attachment to devices such as digital voice assistants –– and their interest in purchasing them. For example, participants said they would be less likely to buy a genderless voice assistant than versions with male or female voices.

Hope Reese. Is That Self-Driving Car a Boy or a Girl? In: Insights by Stanford Business. Internet:<http://www.gsb.stanford.edu/>  (adapted)