Act as a peer reviewer and write the detailed review of this research paper. Be strict and critical: Abstract: This article examines the impact of artificial intelligence on higher education in the humanities in the context of foreign language teaching. The application of artificial intelligence in teaching foreign languages is especially noteworthy, as this field has become a testing ground for tools with large language models. The objective of the study is to analyse the introduction of artificial intelligence technologies in foreign language teaching and to assess changes in the social practices of language department teachers and professors. To this end the authors apply interpretive approach using SWOT analysis and analysis of social practices based on Pierre Bourdieu's theory. The SWOT analysis has shown that, despite the existing disadvantages of artificial intelligence in education, such as ‘hallucination’, bias, training sets dependence and cybersecurity threats, its spread into foreign language teaching in higher schools will become more and more comprehensive due to the availability of state support measures, the development of the private sector and the activities of students who are already actively using artificial neural networks. The analysis of social practices has shown that foreign language teachers pass through an inevitable transformation, affecting their economic, social, cultural and symbolic capital, changing their habitus (established line of behaviour), as well as the entire social field of higher education in the humanities. The research contributes to the growing body of knowledge on the role of artificial intelligence in language learning by providing insights for researchers and practitioners, thus exploring the ‘lived experiences’ of foreign language teachers’ AI practices at the universities.
Keywords: artificial intelligence in education, artificial neural network, higher education, language education, SWOT analysis, social practice.
 


1. INTRODUCTION

November 2022 was marked by an event that many now call a turning point in the history of artificial intelligence (AI): ChatGPT, a generative neural network capable of writing coherent text at a very high level on demand, became freely available [Baidoo-Anu, 2023]. Around the same time, other generative AI tools that create high-quality images, music, programme code, and video content gained popularity. The importance of such technologies is growing every day in many spheres, including education, and the tools that make it possible to expand the possibilities of learning foreign languages are particularly popular.
Researchers and scholars dealing with the role of artificial intelligence in higher education usually present it as an assistant to students. AI is not expected to replace faculty members [Rezaev, 2023], but it can act as a personal tutor, a 24/7 teaching assistant that provides ‘mass personalisation’ of higher education by advising learners, explaining obscure topics, and creating individual assignments to automate necessary skills.
It is likely that such use of AI tools will become widespread in the future; at present, however, in humanities higher schools, teachers and professors most often do not use artificial intelligence, while students use it to write essays, research papers, term papers, final qualification papers and other written work, to obtain summaries of books, to translate texts from a foreign language into Russian and vice versa, and often without personally checking the outcome and editing it, which does not contribute to improving the quality of education.
It seems that the effective use of AI by learners will emerge only if two conditions are fulfilled: 1) the development of clear rules for students on the use of artificial intelligence by each higher school; 2) the change in the approach to teaching (on the one hand, AI tools will become part of the work of faculty members, on the other hand, the number of tasks that can be easily performed by neural networks will be reduced).
As for the first condition, many universities are developing their own rules for the use of artificial intelligence or have already done so [McDonald, 2024]. Teaching is also undergoing changes; many faculty representatives are experimenting with neural networks [Paskova, 2023], using them to create teaching materials, interactive assignments, syllabi and lesson plans, discussion topics and discussion questions, scenarios of business games and models, control questions and materials for knowledge testing [Kapustina, 2023], rapid translation of texts into foreign languages [Garkusha, 2023]. Shifting away from abstracts, essays, other types of written work and the return to the oral form of students' answers at “a new methodological and technological level” is also discussed [Ivakhnenko, 2023, 19].
According to most experts [Bahroun, 2023], the use of artificial intelligence by both students and teachers makes no sense without the formation of AI-literacy, which, for instance, may consist of several tiers [Ng, 2021]: 1) understanding of the basic concepts and principles of AI systems; 2) the ability to apply AI tools not only at the level of ‘know-how’, but also more systematically, with awareness of all the responsibility and probable consequences of its use; 3) turning AI users into developers and methodologists capable of making an objective assessment of this type of technology.
As for the effectiveness of AI tools in language learning, studies (most of which are based on the experience of teaching English as a foreign language) show that the use of AI as an additional tool contributes to the development of conversational skills, improving pronunciation [Rusmiyanto, 2023]. AI is also quite effective in training writing [Alharbi, 2023] and reading abilities [Huang, 2023]. The application of AI can raise student engagement [Lapina, 2023]. However, not for every learner, working with AI tools leads to better language proficiency [Wang, 2023]. As some scholars suggest, the greatest results can be achieved among students with intermediate language proficiency (A2-B1) [Burina, 2023]. For learners who just start out or lag behind the mainstream, the use of artificial intelligence may lead to a lower motivation due to a lack of basic language skills. Mechanical performance of tasks only exacerbates the situation [Zou, 2023]. For students with a high level of proficiency in the language, it is much more effective to refer to ‘live’ speech and texts of native speakers of the target language.
Thus, it can be argued that the role of the teacher in the learning process will remain central, and artificial intelligence will be used as an additional tool [Yang, 2024] to practice the knowledge and skills acquired in the classroom with the help of tasks selected by AI (including individually), taking into account the capabilities and interests [Avramenko, 2022] and the teacher's feedback on each of the students. 
Based on the above, it is worth analysing the introduction of artificial intelligence in the educational process of teaching foreign languages in higher schools, as well as considering how the work of a foreign language teacher in humanities higher schools changes when using artificial intelligence. Although studies in this field are being conducted quite extensively, using the interpretive qualitative methods is not really widely distributed. Thus, a systematic review of the first year of publications on ChatGPT and language education [Li, 2024] shows that researchers use quantitative or other qualitative methods (case studies, comparative analysis, descriptive research, netnography etc.). Our research question is ‘Are there any changes in the ‘lived experiences’ of foreign language teachers in the context of the increasing AI influence?’, and to answer it we use qualitative methods described below.

2. MATERIAL AND METHODS

	This paper uses qualitative research methods, such as SWOT analysis and analysis of social practices, due to the novelty of the area under study (artificial neural networks have only been massively used by non-professionals since 2023). There is currently no developed theoretical framework or general scientific system to interpret the numerous, narrowly focused quantitative studies. Furthermore, the use of AI in education, and particularly in foreign language teaching, has a significant impact on society and raises numerous ethical and value-based challenges. As the researchers note [Pilcher, 2024], in such circumstances, interpretive qualitative methods are extremely useful, as they allow for a deeper understanding of people's behavior and a more comprehensive view of their ‘lived experiences’ in a new social context.
SWOT analysis is used to evaluate the impact of AI introduction in foreign language teaching in humanities higher schools, and social practice analysis is used to identify changes in the work of foreign language teachers.
SWOT analysis is a method of analysis originally developed in business to set goals and align strategy. Nowadays it is also used in scientific research to evaluate new processes and situations. The methods, origins and practices of SWOT analysis, as well as advantages and disadvantages, are described in detail in numerous studies [ex. Gürel, 2017; Puyt, 2023; King, 2023]. Because of that we provide just a brief description with the emphasis on our research area. SWOT analysis consists of four parts: strengths, weaknesses, opportunities and threats [Benzaghta, 2021]. Strengths and weaknesses are internal factors, things that can favour or hinder development within the process or situation under study. Opportunities and threats are external and are environmental factors. SWOT analysis provides an opportunity to consider our personal experiences, as well as insights from experts and research from the scientific literature, through a clear lens, and evaluate the key factors that could impact the integration of artificial intelligence into the educational process for teaching foreign languages. The benefits of this approach have been recognized by the scientific community exploring the social implications of AI, with researchers actively using the SWOT framework since 2022 to analyse the application of AI in education [Humble, 2022; Alabool, 2023; Farrokhnia, 2024]; at the same time, none of the works directly addresses foreign language teaching in higher education.
The analysis of social practices is based on the approaches of philosopher and sociologist Pierre Bourdieu. The components proposed by the thinker - capital, habitus and social field - allow us to study any process quite deeply and accurately and to develop some recommendations on how to adapt to it. Capital is a resource that allow its owners to achieve their goals. According to Bourdieu, capital may be economic, social, cultural [Fedotova, 2017] (objectified, institutionalised, incorporated) and symbolic [Bourdieu, 1993], meanwhile, different types of capital can mix and move from one to another. Habitus according to Bourdieu is a path and a system of well-established habits that a person develops for interacting with society [Bourdieu, 1998; Bourdieu, 1998]. A social field can be understood as a place where different political, economic, and social institutions interact with each other in cooperation or competition, in the struggle for limited resources [Bourdieu, 2002]. 
The empirical basis for the analysis of social practices was gathered through ‘participant observation’ of university foreign language teachers, and this method allows us to understand the cultural and social foundations, ‘lived experiences’ of teaching [Kress, 2021], which is crucial in the context of the introduction of artificial intelligence. The use of AI has caused a lot of debate and emotional reactions, which must be taken into account when considering the potential of this technology. This is because the field of education, in general, and higher education, in particular, has always been a controversial and sensitive area, full of debate and resonance with the general public. It becomes even more vulnerable in a situation with large language models  altering the process of learning. Understanding how teachers' social practices are changing will allow us to better assess their future prospects in the evolving world of education, where artificial intelligence is beginning to play an increasingly significant role. This information can provide a basis for developing recommendations that will assist teachers in maintaining their position and effectively teaching students foreign languages, without fear of being replaced by neural networks.
Who participated? What questions were asked? How was the information synthesized and conceptualized? Were the results triangulated?
3. RESULTS AND DISCUSSION

3.1 SWOT-analysis 
SWOT-analysis of the introduction of artificial intelligence in the educational process of teaching foreign languages in higher schools of humanitarian profile is presented in Table 1. 
Table 1: SWOT-analysis of the introduction of artificial intelligence in the educational process of teaching foreign languages in higher schools of humanitarian profile. Compiled by the authors.
Internal factors	Strengths

‘Mass personalisation’, i.e. the ability to create individual learning trajectories and support students even in large groups;
AI 24/7 application without days off and holidays;
Freeing up teachers' time for more important/creative tasks;
Raising students' motivation through gaming techniques with AI integration.	Weaknesses

Cybersecurity issue, likelihood of personal data leakage of students and faculty members;
‘Hallucination’ of AI;
Bias and ‘opacity’ of AI;
Rejection of AI by faculty members;
The need to change the formats for testing students' knowledge;
AI's lack of understanding of the social and cultural specificities of the linguistic context.
External factors	Opportunities

Support for AI introduction by public authorities;
Public interest supported by media;
Use of AI tools by commercial educational resources (Skyeng, Duolingo, etc.).	Threats

Negative public reaction;
Absence or small number of developed domestic AI products;
Dependence of AI on large data sets;
Lack of necessary infrastructure, computing power.



The application of interpretive methods involves uncovering the internal, subjective perspectives of individuals within the field of study. Based on the information presented in the table, we can conclude that the process of introducing artificial intelligence in foreign language teaching is complicated. On the one hand, the society quite often demonstrates negative reaction to AI in education: many teachers and professors, public figures, parents are not ready to use this technology in full force and effect, they see more dangers than opportunities. Thus, according to a survey conducted among teachers at several Russian universities, although most respondents expressed their willingness to revise their teaching methods in light of the emergence of artificial intelligence and use AI tools for assignments or monitoring academic performance, nearly 80% expressed distrust of this technology for revising educational programs, course content, and teaching methods [Sysoyev, 2023]. According to the SberUniversity study, more than half (51%) of teachers surveyed felt that artificial intelligence had a positive impact on education. While 67% said AI could increase student engagement, 72% expressed concern about the impact on learners' qualifications . And they have reasons for that, as at this stage artificial intelligence depends on training sets, computing power, software, and its use is insecure due to potential data leakage, ‘hallucination’ and bias. On the other hand, students are actively working with artificial neural networks, especially when it is necessary to translate a written text. According to a study by Idris et al., which assessed students' emotional response to artificial intelligence, approximately 70% of the respondents expressed interest, while only 13% expressed fear [Idroes, 2023]. As reported by Malmström et al., the majority of surveyed students have a positive view on the implementation of AI in higher education. [Malmström, 2023]. According to a survey conducted at Kazan Federal University, over 70% of respondents use automated translation systems when studying foreign languages [Tikhonova, 2024]. If we take into account the support of the state, the development of AI tools in the private sector for foreign language teaching, and the perception of artificial intelligence as a promising technology shaped by a significant number of media, it becomes clear that universities cannot ignore this phenomenon. The use of AI in education, despite its shortcomings, is inevitable, similar to the introduction of personal computers at its time. However, the use of AI will only be effective and beneficial if it is integrated into the learning process in a balanced and gradual manner as an additional tool for foreign language teachers to use alongside traditional methods.

3.2. Analysing social practices
When analysing the social practices of foreign language teachers in humanities higher schools, the point of reference is capital. The teacher's economic capital will undergo changes when AI is introduced into the educational process, but it is difficult to predict whether it will increase or decrease, since everything will depend on the AI strategy chosen by a particular higher school and the specialist's behaviour. If the higher school supports AI tools, the teacher's interest in this technology and active work in this area should add up to economic capital. 
Objectified cultural capital (libraries, databases, museums, galleries, theatres, etc.) has been enriched with the emergence of artificial neural networks in new forms and directions, e.g. NFT-art, virtual and augmented reality (VR and AR), AI-restoration of manuscripts. Exposure to AI-inspired approaches in art and science can inspire teachers to create new educational methodologies. In particular, it is possible to combine AI tools with VR and AR to teach foreign languages, for example, through the use of metaverse [Aydin, 2022, Wu, 2023]. Although this approach may seem rather theoretical, systematic reviews of the subject have already pointed out that using virtual reality for teaching foreign languages leads to the development of oral skills, communicative competence, acquisition of vocabulary, cultural learning, increased student autonomy, and reduced anxiety about the foreign language [Parmaxi, 2020; Hua, 2023; Zheng, 2023].
Institutionalized cultural capital of teachers, already extensive and significant, is likely to be enhanced by additional training certificates on topics related to artificial intelligence in general and AI in education in particular. Researchers emphasize the need for foreign language teachers to develop metaskills, as not all teachers have experience working with large language models. Although they may have heard about this technology and express a willingness to learn how to use artificial intelligence, they may lack the necessary skills [Avramenko, 2024].
Incorporated cultural capital, learning new skills, will undergo quite strong changes. The introduction of artificial intelligence in education leads to the need to seriously revise the existing practices of a foreign language teacher, to abandon the usual methods of testing (essays, written translations, answers to questions) or to significantly transform them (for instance, to use AI text recognition technologies). 
Social capital, ‘determining trust in society’ [Fedotova, 2016, 320], will play an important role in teachers' adaptation to the ongoing changes. It can be assumed that social ties with colleagues, interaction during professional development courses on AI, as well as various forms of informal communication with faculty members who are ready to use new technologies and can help others to do so, will contribute to an easier transition to teaching using new tools.
Symbolic capital in the form of a teacher's name and professional reputation can be developed not only through classical techniques, such as memorable classes, the ability to explain complex topics in a clear and interesting way, to assess students' progress objectively, but also through the use of AI tools, which will take over part of the routine burden of explanation and assessment, freeing up time for the development of the art of teaching.
Habitus is responsible for the continuity of social behaviour. Education is one of the rather conservative spheres of social life, therefore, in connection with the emergence of artificial intelligence, we can observe ‘habitus hysteresis’ [Fedotova, 2016, 54], i.e. the inconsistency in the behavior of some teachers in terms of their response to new realities is evident in the fact that university staff are not prepared to work in a digital environment and lack the necessary skills. At times, they unconsciously perceive artificial intelligence as a threat. [Crompton, 2023]. However, it is worth noting that the main concern is not the technology itself but rather the reluctance to use AI tools in education. In the coming years, artificial intelligence will be integrated into the learning process, and the chance to master these tools now, when there are no mandatory high qualification requirements for teachers, could be missed. On the other hand, if an educational institution consistently pursues a policy of rejecting artificial intelligence, such a line of behaviour may be quite successful.
The social field of higher education introducing artificial intelligence tools becomes quite ambivalent. One can observe a certain dissonance between political and economic institutions (for example, the project ‘Artificial Intelligence’ in Russia or international initiatives of UNESCO), which rather favour the integration of AI in education due to its potential benefits like facilitating the management of education or providing every learner with personalized lifelong education, and social institutions, which often broadcast a negative attitude towards this process. 
Capital, habitus, and social field give an idea of social practice - the actions of people to transform the world around them in line with their ideas about it [Bourdieu, 1994]. Under the influence of artificial intelligence, the social field of higher education, including the process of teaching foreign languages, is changing towards increased structural heterogeneity and uncertainty in ongoing processes. Therefore, social practices are also significantly transformed. The response to these rapid changes can only come from increased efforts by teachers, as well as support from the state and society. This support should focus on identifying and nurturing the creative potential of individuals based on their personal experiences. Educational programs should aim to foster uniqueness and engagement in various sustainable directions of technological and cultural development. [Glagolev, 2024]. Moreover, social practices should become more flexible and balanced, combined with the diversification of resources both in real and digital life [Ulanova, 2024]. It seems possible to say that only if these conditions are fulfilled, foreign language teachers at the universities of humanitarian profile will be able to overcome the crisis caused by the latest round of AI development and to emerge from it with a positive result.
The section does not work at the level of results or their discussions. Since the Materials and Methods section does not clarify how the data were collected, validated, and conceptualized, it is unclear how the results were ultimately formulated and how reliable they are. The discussion of the results is extremely vague. In fact, there is no discussion at all. The authors refer to previous studies only to illustrate their point. However, the purpose of the discussion section is to engage in a dialogue with previous research and demonstrate how the authors' results differ from what is already known, showing what they contribute to the existing body of knowledge in the field. Otherwise, this is not a discussion of the results, but a monologue where the authors reflect on their perception of the findings. This is incorrect: it is necessary to place the authors' results within the existing knowledge on the topic.

4. CONCLUSION

Nowadays, due to the rapid development of artificial neural networks, large language models and generative AI technologies, many spheres of life, including higher education in the humanities, are experiencing transformation. Foreign language teaching is the part of it where the most striking traces of these changes can be found.
The results of the study have shown that the introduction of AI in education is most likely irreversible and, despite all the difficulties, this process will only speed up and the impact on foreign language learning will increase. The consequence will be a change in the ‘lived experiences’ of foreign language teachers. It seems that the smoothest and most painless transition to the educational process, where artificial intelligence acts as an important additional tool for teaching foreign languages, requires the development of clear rules (for education in general and for higher schools in particular), improved AI-literacy of teachers and students, the reduction in cybersecurity risks and, most importantly, the preservation of a human-centred approach in education, where human is not a means but an end.
In its current format, the section does not fulfill its functions. Please follow these steps to improve it:

Step 1: Generalizing results Presents general claims or conclusions.
Step 2: Stating the value Presents specific claims of importance.
Step 3: Noting implications Presents specific claims of impact.
Step 4: Proposing directions Presents recommendations for future work.

Conflict of Interest
The authors declare no conflict of interest.

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