Search

Translating poetry has always been a challenging issue for some reasons. Firstly, it is accompanied by cultural challenges. Secondly, it is considered untranslatable due to its unique qualities. Thirdly, the poet’s style, if not fully captured in translation, becomes a pale substitute for the original. Fourthly, issues related to Artificial Intelligence (AI) also arise. This article tried to analyze some of these issues in the light of the Persian translations of the literary techniques of Shakespeare's Sonnet 62 in a qualitative-explanatory way and with the help of human and machine intelligence tools. The main goal was to pay attention to the upcoming challenges in the translation of literary techniques. Farzad provided a fluent translation, Moghadam provided a relatively free translation, Shafa provided a translation faithful to the content, and Tabibzadeh provided an accurate and accepted translation of the sonnet. Among the AI tools, Google Translate provided a literal translation close to the original text, Telegram Bot provided a more complete and fluent translation, and OpenAI GPT provided a more accurate and human-like translation of the sonnet. It seemed that literary translation, especially poetry, required human intelligence creativity in order to bring its "alternative" presence closer to the "original". Keywords: Human Intelligence, Artificial Intelligence (AI), Sonnet, Accuracy, Acceptability. IntroductionIt has been over a hundred years since Shakespeare’s works have been translated into Persian. During this time, Shakespeare's sonnets have also been translated and published in periodicals. Translators, such as Masoud Farzad, Majid Movaqqar, Shoja al-Din Shafa, Taghi Tafazzoli, Behnam Moghadam, Amrullah Abjadiyan, and Omid Tabibzadeh, are among those, who have translated Shakespeare's sonnets into Persian. Besides using human intelligence, Shakespeare's sonnets can also be translated into Persian through Artificial Intelligence (AI), which would be challenging and interesting in its own way. In this article, Sonnet 62, which had been translated into Persian by most of the aforementioned translators and AI tools, was examined from the perspectives of the proposed strategies for translating poetry. The discussion of translating the genre of poetry into other languages has always been raised alongside issues related to the original works themselves. In translating conventional texts generally and literary texts, especially poetry, we do not merely deal with translating linguistic items from one language to another. Since literary texts are considered an inseparable part of the cultures of nations and carry specific semantic loads, translation of these texts also involves particular difficulties and problems due to cultural issues. In the process of translating an English sonnet into a Persian ghazal, some issues arise that need attention. Can a sonnet be translated into a sonnet while preserving its formal and structural features or undergoing slight modifications and can it be translated into the form of a Persian ghazal? To what extent is it possible to transfer cultural elements in addition to poetic ones in the translation process? To what extent can AI succeed in conveying the poet’s most intimate states and feelings into another language, considering that AI, due to its structural nature, lacks the emotional intelligence that characterizes human intelligence? Materials & MethodsIn the common and traditional categorization that is theme-based rather than form-based, Shakespeare's sonnets are divided into three general categories: Sonnets 1-126 address the fair youth; Sonnets 127-152 deal with the dark lady; and Sonnets 153 and 154 are known as the Anacreontic sonnets (Anacreon 583 BC-485 BC), which have romantic themes (Abjadiayn, 2008; Tabibzadeh, 2017). Sonnet 62, along with Sonnets 59, 60, and 65, deals with the relationship between time and beauty (Abjadiyan, 2008, p. 205). According to Tabibzadeh, it is the first of the two sonnets about the poet's old age (p. 184). In this sonnet, Shakespeare first speaks of the sin of self-love, which has taken over his eyes and his entire being, rooting deeply in his heart (first quatrain). Then, in the second quatrain, he talks about his beauty, which is unparalleled in the world. However, in the third quatrain, he says that he sees himself as a very worn-out, old, and decrepit man when he looks into a mirror. Finally, in the couplet, he attributes all that splendor and beauty he has thought he has had to the fair youth and imagines his own old age to be beautiful in the light of the fair youth's youthful beauty. This sonnet was first translated by Masoud Farzad. Then, Majid Movaqqar translated it. The third translation was done by Shafa. The fourth translation, a prose translation, was done by Tafazzoli. Then, Behnam provided a rhythmic and rhymed translation of this sonnet. Finally, Tabibzadeh (2017) provided a sufficiently acceptable, though unrhymed and unmetered, translation of it. Additionally, the author translated this same sonnet into Persian using AI tools, such as Google Translate, and, more recently, ChatGPT. Research FindingsThe translations of Shakespeare's Sonnet 62 by various human translators and AI tools revealed interesting insights into the strengths and limitations of each approach. The human translators, including Farzad, Movaqqar, Shafa, Tafazzoli, Moghadam, and Tabibzadeh, had produced translations with varying degrees of fluency, faithfulness, and literary quality. Farzad and Movaqqar had prioritized fluency over fidelity, resulting in translations that had strayed from the original text. In contrast, Shafa and Tafazzoli had focused more on faithfulness, with Tafazzoli's prose translation staying very close to the original content. Moghadam had offered a relatively free but rhythmic and rhymed translation, while Tabibzadeh had presented a sufficiently accurate and acceptable unrhymed and unmetered version. When examining the translations produced by AI tools, some interesting patterns emerged. Google Translate, despite advancements in the field, generated a largely literal and close-to-the-original translation, focusing more on primary word meanings rather than secondary connotative meanings. On the other hand, the Telegram bot and OpenAI's GPT produced more accurate and human-like translations. The Telegram bot's translation was more complete and fluent than Google's but less comprehensive and precise than OpenAI's. Notably, OpenAI's translation was, in some cases, even more literary than human translations. Still, the assumption that AI cannot effectively translate literary texts due to the presence of emotion and feeling could be challenged. OpenAI's more complex algorithms enabled it to find more appropriate literary equivalents for certain words and provide a more coherent translation, particularly in the final lines of the sonnet. However, the issue of accurately translating certain literary qualities, such as the speaker’s voice and tone, remained problematic for AI tools. The melancholic and regretful tone of the poem's speaker lamenting the loss of youth was not adequately recreated in the machine translations. These findings suggested that human intelligence still played a crucial role in capturing the nuanced, emotional, and cultural aspects of literary works while AI tools could make significant strides in literary translation. The interplay between human and artificial intelligence in the translation of poetry and other literary genres warrants further exploration as it may lead to innovative approaches that combine the strengths of both. Discussion of Results & ConclusionFarzad, Movaqqar, Shafa, Tafazzoli, Moghadam, and Tabibzadeh as translators possessing human intelligence were found to have produced translations with various literary qualities of the mentioned Shakespearean sonnet: Farzad and Movaqqar had strived for a fluent but unfaithful translation to the original text; Shafa had provided a fluent and somewhat faithful translation; Tafazzoli had delivered a prose translation so faithful to the original poem in terms of content; Moghadam had offered a relatively free but rhythmic and rhymed translation; and Tabibzadeh had presented a sufficiently acceptable translation. However, this question arose: What similarities and distinctions may occur in the overall process of translating texts, particularly literary texts, and more specifically, translation of poetry, including the studied sample of Shakespearean sonnet when translation tools shift from human intelligence to artificial intelligence? Google, although said to have made significant advancements, was not very successful in translating the sonnet and produced a nearly literal and close-to-the-original translation, focusing more on the primary and dictionary meanings of words and phrases rather than their secondary and connotative meanings. On the other hand, the two other tools provided a more accurate and human-like translation of the sonnet. The translation offered by the Telegram bot was more complete and fluent than Google's but less complete and accurate than OpenAI's translation. Despite the fact that the Telegram bot and OpenAI tools apparently had the same origin, they did not translate the sonnet identically due to their different programming. Among these, OpenAI's translation was, overall, closer to human intelligence translation and, in some cases, even more literary. Perhaps, this could challenge the initial assumption that AI cannot translate literary texts effectively due to the presence of emotion and feeling and it might even be argued that this assumption was somewhat falsifiable. OpenAI showed that, due to its more complex algorithms, it had been programmed in a way that it could find more literary equivalents for some words. Furthermore, this tool demonstrated a more accurate understanding of the last lines of the sonnet compared to the other two tools and was able to provide a more coherent translation. However, the issue of translating certain qualities of literary texts, such as the speaker’s voice and tone, still remained problematic. A general look at the translations of the sonnet showed that machine translations were not able to adequately recreate the melancholic and regretful tone of the speaker of the poem, someone who lamented the lost days of youth. Nevertheless, addressing the challenges of human and artificial intelligence translations requires more space, which the author hopes to deal with in the future.

Artificial intelligence is one of the most basic and serious topics of research and investigation in the world today. Artificial intelligence is progressing and developing in a lightning-fast and amazing manner in the current era. Very soon, we will see huge changes and developments in this type of new technology. This new technique and technology has been widely used internationally in various professions and industries. The profession of law, law, and distributive justice is not exempt from this issue; now this question is raised, which of the tools will be more useful and appropriate to achieve distributive justice; Human intelligence or artificial intelligence? Is it possible to bring society closer to real justice and fairness with this new technology in this modern era? What is certain is that artificial intelligence with the behavior of human intelligence strengthens capabilities and increases efficiency. Therefore, the findings using descriptive, analytical, and argumentative methods show that artificial intelligence in terms of speed, accuracy, and decision-making power in analysis and problem analysis is more effective and efficient compared to human intelligence. Thus, the use of this new technology helps a lot in the fair distribution of incomes, opportunities, and important economic issues in society. Although the negative effects caused by the expansion of this new technology cause economic, educational, moral, and other discriminations and inequalities; however, it is possible to reduce the negative effects of these inequalities caused by the development of this new technology by exercising caution, carefully managing and monitoring data, creating programs and supporting laws, and using artificial intelligence technology based on the principles of distributive justice.

Translating poetry has always been a challenging issue for some reasons. Firstly, it is accompanied by cultural challenges. Secondly, it is considered untranslatable due to its unique qualities. Thirdly, the poet’s style, if not fully captured in translation, becomes a pale substitute for the original. Fourthly, issues related to Artificial Intelligence (AI) also arise. This article tried to analyze some of these issues in the light of the Persian translations of the literary techniques of Shakespeare's Sonnet 62 in a qualitative-explanatory way and with the help of human and machine intelligence tools. The main goal was to pay attention to the upcoming challenges in the translation of literary techniques. Farzad provided a fluent translation, Moghadam provided a relatively free translation, Shafa provided a translation faithful to the content, and Tabibzadeh provided an accurate and accepted translation of the sonnet. Among the AI tools, Google Translate provided a literal translation close to the original text, Telegram Bot provided a more complete and fluent translation, and OpenAI GPT provided a more accurate and human-like translation of the sonnet. It seemed that literary translation, especially poetry, required human intelligence creativity in order to bring its "alternative" presence closer to the "original". [ABSTRACT FROM AUTHOR]