Introduction
In an era of rapid advances in artificial intelligence (AI), many young people are wondering which fields of study will provide them with a stable career and resistance to automation. We increasingly hear that algorithms can perform tasks at the level of top experts — OpenAI’s CEO Sam Altman has even admitted that modern AI systems can solve Olympic-level math problems and produce PhD-quality research papers. Yet not all professions are destined to disappear. The key lies in choosing a career path where human creativity, complex reasoning, and interpersonal skills play an irreplaceable role.
In this article, we’ll explore the most future-proof IT degree programs in Poland that, according to experts, are highly resistant to automation. We’ll take into account current labor market demand (both domestic and global), development prospects, and required competencies — including soft skills, which often determine the human advantage over machines. The text is aimed at high school graduates and university students planning a career in IT. You’ll find here concrete examples of degree programs offered by Polish universities, data from reports, and practical advice on how to prepare for the job market in the age of AI.
Key IT Fields of the Future
Artificial Intelligence and Machine Learning
Paradoxically, one of the best ways to achieve resilience against AI is to specialize in AI itself. The IT industry — especially the field of artificial intelligence and machine learning — is evolving at a breathtaking pace. AI developers and specialists are among the most sought-after professionals on the market today. AI technologies and data analysis have a growing impact on the global economy, and demand for experts in these areas continues to rise. It is estimated that Data Science and Artificial Intelligence are among the fastest-growing branches of computer science, as companies increasingly rely on AI to automate processes and analyze big data in order to improve business decision-making.
Graduates of AI-related programs have numerous career opportunities ahead of them. Examples of AI-related positions include:
Machine Learning / AI Engineer – designing and implementing AI models across various industries.
Data Scientist – analyzing large datasets using AI algorithms to uncover trends and insights.
AI Developer – programming artificial intelligence systems, such as neural networks.
AI Researcher – conducting scientific research to develop new algorithms and AI methods.
Importantly, developing AI requires not only technical skills but also creativity and problem-solving abilities. Machines cannot replace humans in inventing new AI concepts or ensuring their ethical oversight. It’s no surprise, then, that demand for programmers and AI experts has surged dramatically — for example, in Poland, the demand for software developers has increased by 35% over the past five years. Admission to top programs (such as computer science with AI specialization) can be highly competitive, and success in programming or math competitions can significantly improve one’s chances of getting in.
Where to study AI? In response to this trend, many universities are launching dedicated programs in Artificial Intelligence and Data Science. For instance, Warsaw University of Technology has introduced a new AI & Data Science degree, which ranked 1st in the Perspektywy 2025 ranking. University of Warsaw (2nd place) and AGH University of Kraków (3rd place) also offer modern programs in this area. Additionally, traditional computer science programs at top institutions (such as the University of Warsaw, Warsaw University of Technology, and Jagiellonian University) increasingly include specializations in machine learning and data analytics.
Why choose AI? Beyond high demand and attractive salaries, it’s a field where humans play a crucial role as innovators and supervisors. Even the most advanced systems need engineers to design architectures, fine-tune models, and assess the ethical implications of AI behavior. These are the careers of the future — the very ones that, paradoxically, AI itself will not replace anytime soon.
Cybersecurity
In a digital world, the number of threats — from hacking attacks to cyber warfare — continues to grow, making cybersecurity one of the most future-oriented fields of study. Poland ranks 3rd in Europe in terms of frequency of cyberattacks (Microsoft Digital Defense Report), which has led to a threefold increase in job offers for cybersecurity specialists since 2020. Globally, the shortage of such experts is enormous — estimates suggest a gap of nearly 4.76 million cybersecurity professionals worldwide. In Poland, demand far exceeds supply: according to an interview with the CEO of Resilia, the workforce deficit amounts to 17,500 positions, with as many as seven open jobs per candidate.
This market gap translates into excellent employment prospects and career stability for graduates of information security–related programs. Moreover, the trend is expected to continue — the number of cyberattacks has risen by 300% over the past decade, and forecasts indicate that by 2025, 90% of companies will require at least one cybersecurity specialist.
Why AI won’t replace cybersecurity experts: first, cybercriminals are humans who constantly invent new attack methods — hence the need for creative defenders who can anticipate and counteract them. Second, AI is a double-edged sword: on the one hand, it supports analysts (for example, in automatically detecting network anomalies), while on the other, it becomes a tool for attackers (e.g., for generating malicious code). Humans must remain in control and respond to previously unseen attack vectors. Cybersecurity programs teach, among other things, system auditing, cryptography, digital forensics, and the psychology of cyberattacks — preparing students to deal with AI’s dual role in this field: both as a defensive ally and as a source of new threats.
Example Specializations and Positions in Cybersecurity
Security Analyst – monitoring systems and responding to incidents.
Penetration Tester (Pentester) – conducting controlled attacks to identify vulnerabilities.
Security Engineer – designing protection mechanisms for systems and networks.
Chief Information Security Officer (CISO) – managing an organization’s security strategy at the executive level.
In Poland, more and more universities are offering cybersecurity-related degree programs. For example, the Warsaw University of Technology offers a specialization in Security Systems Engineering, AGH University of Kraków runs a Cybersecurity program within its Faculty of Computer Science, and the University of Silesia offers studies in IT security. In addition, students interested in the legal aspects of cybersecurity can pursue programs such as Cyber Law (more on that in the law section).
Graduates of these fields can expect highly competitive salaries — the Polish market is currently a candidate’s market for cyber experts, with average monthly earnings around 15,000 PLN, and top specialists earning considerably more.
In summary, cybersecurity offers employment opportunities across nearly every industry — from banking and public administration to tech startups — along with continuous professional growth. It requires a combination of technical expertise, analytical thinking, and an understanding of human behavior, which makes it relatively resistant to automation.
Data Science and Data Analytics
Data analysis has become the foundation of modern business — it’s often said that data is the new oil. The ability to extract valuable insights from big data is highly prized, and the role of the Data Scientist consistently ranks among the top jobs of the future. According to one report, 97% of companies consider data analytics essential to their growth, which translates into huge demand for professionals in this field.
Although AI can automate some aspects of data analysis (such as generating charts or basic reports), it cannot replace humans in defining business problems, asking the right questions, or interpreting results within a broader strategic context. A data analyst must combine technical skills (e.g., proficiency in Python, R, SQL, Tableau) with strong communication abilities, since they often present findings to non-technical stakeholders. This mix of hard and soft skills makes skilled data professionals difficult to replace.
The Data Science curriculum typically combines computer science, mathematics, and statistics. Students learn advanced analytical methods, machine learning, data visualization, and business fundamentals to understand the context behind their analyses. Many Polish universities have created specialized programs in this area — for instance, SGH Warsaw School of Economics offers a well-regarded Big Data – Data Analytics program, while universities such as UW, PW, and UJ have introduced Data Science specializations within their computer science degrees. Notably, AI & Data Science programs have even been recognized as a separate category in educational rankings, highlighting their growing importance.
Data Science graduates find employment across diverse sectors: finance (risk modeling, algorithmic trading), marketing (customer behavior analysis), manufacturing (process optimization), healthcare (medical data analysis), and more. Example job roles include:
Business Data Analyst – processing company data and recommending strategic actions.
Data Scientist at a tech company – building predictive models for e-commerce or social media.
Data Engineer – creating and maintaining data infrastructure for big data processing.
Business Intelligence (BI) Specialist – preparing reports and dashboards for management teams.
High demand translates into strong salaries. Graduates of top analytical programs (e.g., SGH) can expect starting salaries of 8,000–10,000 PLN gross per month, which grow significantly with experience. A skilled data analyst is often worth their weight in gold to an organization. However, continuous learning is essential — new analytical tools and methods evolve rapidly in this field.
In summary, Data Science is ideal for people who enjoy working with numbers, tackling intellectual challenges, and bridging technology with business. While AI can assist analysts by speeding up computations, it is still humans who ask the questions and make the decisions — making this career both future-oriented and relatively resistant to automation.
Software Engineering and Systems Architecture
General computer science, and especially software engineering, has long been one of the most popular and promising fields of study. Despite fears that AI (for example, coding assistants like GitHub Copilot) might automate programming, the role of a skilled software engineer remains crucial. Automated code generators can help with routine tasks but cannot replace humans in designing complex systems, analyzing requirements, debugging intricate issues, or making architectural decisions. These tasks demand deep contextual understanding, creativity, and experience — all inherently human qualities.
Software engineering programs (often offered as part of computer science) focus on learning various programming languages, algorithms, data structures, as well as system design (e.g., microservices, distributed applications), project management, and software development methodologies. This prepares graduates for many roles in IT, such as:
IT Systems Architect – designing the technical structure of large projects (e.g., banking systems, e-commerce platforms).
Senior Software Developer / Tech Lead – an experienced programmer leading a team and making key technical decisions.
DevOps Engineer – combining programming and system administration to automate deployment and maintenance processes — a role that’s hard to automate due to its holistic, strategic nature.
QA / Automation Tester – while some testing is automated, designing intelligent test scenarios and ensuring overall product quality remain complex human tasks.
Nearly every Polish technical university offers Computer Science or Software Engineering programs, and the best maintain consistently high standards. According to the Perspektywy 2025 ranking, the University of Warsaw topped the list for master’s studies in Computer Science, while the Warsaw University of Technology leads among engineering programs. Other strong centers include AGH University of Kraków, Wrocław University of Science and Technology, and Gdańsk University of Technology. Computer science provides a solid foundation for growth in both specialized and interdisciplinary directions.
An important aspect of being a great software engineer is possessing soft skills — teamwork, client communication, and understanding business needs. These abilities, combined with logical thinking, make experienced engineers hard to replace. AI can generate code snippets, but it cannot lead projects or negotiate requirements with clients. Therefore, individuals who combine technical expertise with interpersonal skills will continue to be highly sought after.
Automation and Robotics
Automation and Robotics sits at the intersection of computer science, electronics, and mechanics — and this interdisciplinarity makes it a future-proof field, resistant to full automation. Paradoxically, specialists in automation are essential for building and maintaining automation systems themselves. As one educational blog aptly put it, automation and robotics represent the future of production and industry. Factory robots and intelligent control systems are becoming standard, improving efficiency and reducing costs — but someone still needs to design, program, and supervise them. That’s where skilled robotics engineers come in.
Automation and Robotics programs (often abbreviated as AiR in Poland) offer a broad curriculum covering microcontroller programming, control theory, and mechanical design. Students also learn to integrate IoT (Internet of Things) systems — connecting devices into smart networks, another trend that enhances their employability. Graduates can design both industrial robots and advanced autonomous systems such as drones or vehicles.
Demand for these skills is increasing rapidly with the rise of Industry 4.0 and the global shift toward production automation.
**Example Career Paths for Automation and Robotics Graduates ** Robotics Engineer – designing and programming robots (e.g., robotic arms in car manufacturing plants).
Automation Engineer – developing control systems for production lines and automating industrial processes.
IoT Specialist – integrating devices and sensors into smart networks, building intelligent home or city systems (smart home, smart city).
Maintenance Engineer – overseeing automated machinery, diagnosing issues, and optimizing system performance.
In Poland, Automation and Robotics (AiR) can be studied at many leading technical universities, including the Warsaw University of Technology, Wrocław University of Science and Technology, AGH University of Kraków, Poznań University of Technology, Gdańsk University of Technology, and others. Programs often offer specializations such as mobile robotics, mechatronics, or vision systems. The job market for such engineers is thriving — not only large industrial plants but also high-tech sectors (medical robotics, military robotics, drone development) are actively recruiting these specialists.
Salaries in this industry are competitive. According to data from the educational portal MaturaMinds, typical starting salaries for AiR graduates range from 5,000 to 7,000 PLN gross per month, while experienced specialists in major cities can earn around 10,000 PLN or more. Beyond financial rewards, however, this career offers the unique satisfaction of working on tangible creations — robots and devices that shape our reality. That’s something no cloud-based algorithm can replace.
In summary, Automation and Robotics is ideal for those interested in both software and hardware. It requires an analytical mind and continuous learning, but offers strong job security. While AI may take over some tasks (e.g., automatic control optimization), humans will remain essential for creating, supervising, and improving autonomous systems — at least for the foreseeable future.
Interdisciplinary Career Paths Combining IT with Other Fields
Information technology now permeates nearly every aspect of modern life. As a result, professionals who combine IT expertise with another domain — such as social sciences, law, medicine, or biology — are becoming increasingly valuable. These interdisciplinary profiles are often more resistant to automation, since they require unique skill sets and multidimensional thinking. Below are several examples of future-oriented fields that merge computer science with other disciplines.
Computer Science + Psychology (UX, HCI, Cognitive Science)
At first glance, psychology and computer science may seem worlds apart, yet their intersection forms the foundation of fields like UX (User Experience) Design, HCI (Human–Computer Interaction), and Cognitive Science. At the heart of these areas lies the human being and their interaction with technology. UX/HCI specialists design systems and interfaces that are intuitive, user-friendly, and aligned with human needs and limitations. This work requires empathy, creativity, and a deep understanding of human psychology — precisely the qualities machines lack.
AI cannot replace UX designers or user behavior researchers, because crafting excellent user experiences demands insight into human emotions, motivations, and frustrations. While AI can analyze behavioral patterns (e.g., cursor movements or click heatmaps), understanding why users feel frustrated or what they expect still requires human intuition. This is why new roles such as AI Experience Designer are emerging — professionals who ensure that interactions between humans and AI systems remain clear, ethical, and comfortable.
University programs combining IT and psychology come in various forms. Some institutions offer specializations like Psychology in IT or UX Design within computer science or cognitive science programs. For instance, SWPS University offers User Experience Design specializations within its design studies, and AGH University of Kraków includes HCI modules in its computer science curriculum. Classic Cognitive Science programs (available at the University of Warsaw, Adam Mickiewicz University in Poznań, and Jagiellonian University) blend cognitive psychology, neuroscience, philosophy of mind, and artificial intelligence. Graduates understand both how the brain works and how to program intelligent systems, enabling them to help design human-centered AI technologies.
**Potential career paths for IT + psychology graduates include: ** UX/UI Designer – designing user interfaces for applications and websites, grounded in knowledge of human perception and behavior.
UX Researcher – conducting usability tests, interviews, and data analyses to improve digital products.
Accessibility and Ergonomics Specialist – ensuring that technologies are inclusive and accessible to diverse groups (including people with disabilities).
User Behavior Analyst – interpreting behavioral data (e.g., from Google Analytics or heatmaps) to optimize user experience and engagement.
Soft skills are crucial here: communication, teamwork (UX designers often mediate between IT and business teams), and empathy. AI can accelerate data analysis but cannot design empathetic, human-centered experiences. Therefore, professionals who combine technology and psychology will remain in high demand. Even technical departments such as cybersecurity teams increasingly value psychological expertise — for example, in understanding social engineering tactics or training staff. Diversity of skills (psychology, data analysis, education) within IT teams is now seen as a key strength.
Computer Science + Law (Technology and Digital Law)
The rise of new technologies brings with it complex legal and ethical challenges. Technology Law (or Digital Law) is a growing field where legal frameworks must keep pace with innovation — and often struggle to do so. That’s why experts who combine legal training with technological understanding are becoming indispensable. Tech companies, law firms, government agencies, and international organizations are all seeking specialists capable of interpreting and shaping regulations on AI, data, and intellectual property.
Key issues at the intersection of IT and law include data protection (e.g., GDPR compliance in IT systems), intellectual property in the age of AI (when an algorithm generates a creative work — who owns it?), copyright and AI-generated content, and AI accountability (e.g., who is responsible for a medical algorithm’s mistake?). Since there are still no unified international standards, this field is rapidly evolving, giving LegalTech professionals the opportunity to help define new legal norms from the ground up.
Programs combining law and IT may take the form of traditional law studies with specializations in Technology Law, Internet Law, or Cyber Law. Increasingly, postgraduate and MBA programs in LegalTech are also available. In Poland, several universities have recognized this niche — for example, the University of Warsaw offers AI Law courses within its legal clinics, Kozminski University and SWPS University have postgraduate programs in Technology Law, and even technical schools like the Warsaw University of Technology and AGH are introducing legal and ethical modules into their computer science programs. Dedicated degrees such as Intellectual Property and New Technologies Law are also emerging (e.g., at the Higher School of Professional Education).
Students in such programs learn topics such as IT legal risk management, telecommunications law, data protection law, cybersecurity fundamentals for lawyers, AI ethics, and software licensing agreements. This prepares them to work in a fast-changing sector where legal frameworks are still being formed.
Possible career paths include:
Technology Lawyer – working in a law firm or corporate legal department, advising on IT contracts, AI, or blockchain compliance.
Data Protection Officer (DPO) – ensuring organizational compliance with data protection regulations such as GDPR.
AI Compliance Officer – a new role ensuring that AI systems operate ethically and in line with upcoming regulations (such as the EU’s AI Act).
Intellectual Property Advisor – specializing in patents, licensing, and copyright in IT and R&D contexts.
From an automation-resistance perspective, tech-law professions are relatively safe. They require interpretation of complex situations, ethical reasoning, and an understanding of justice — tasks that cannot be entrusted entirely to machines. AI can assist lawyers (e.g., in case law searches) but cannot replace them in court or contract negotiations. With the European Union now finalizing the AI Act, demand for specialists who can help organizations comply with new AI-related regulations is set to surge.
For individuals who are drawn to both technology and social sciences, Technology Law represents an exciting and future-proof niche.
Computer Science + Biotechnology (Bioinformatics and Digital Medicine)
Combining computer science with the natural sciences opens up fascinating opportunities in areas such as bioinformatics, biotechnology, telemedicine, and digital medicine in general. This path is ideal for those who, besides computers, are passionate about biology, chemistry, or medicine. Bioinformatics—often called a field of the future—merges knowledge of programming, data analysis, and genetics, enabling, for example, genome analysis, drug discovery through computer simulations, or protein studies using algorithms. With the development of DNA sequencing technologies, personalized medicine, and biotechnology, the demand for specialists capable of processing massive amounts of biological data is growing exponentially.
The global biotechnology market is expanding at around 10% annually, illustrating the dynamic pace of this sector. New civilizational challenges are emerging—from pandemics and genetic diseases to the climate crisis—all of which require innovative, multidisciplinary solutions. Gene therapies, mRNA vaccines, and organ bioprinting are just a few examples where IT specialists collaborate with biologists and physicians. AI also plays a role here, for instance, in drug molecule design or medical image analysis—but it cannot replace scientists who formulate research hypotheses and interpret experimental results.
Polish universities are offering more and more programs that combine computer science and biology. Jagiellonian University has been training bioinformaticians for years (e.g., through cooperation between the Faculty of Biochemistry, Biophysics and Biotechnology and the Faculty of Mathematics and Computer Science). Lodz University of Technology offers a Biotechnology program that includes bioinformatics components (Faculty of Biotechnology and Biochemical Engineering), while University of Warsaw enables students to study Bioinformatics and Systems Biology, among others. Additionally, medical universities are introducing medical informatics specializations—such as clinical data analysis, telemedicine systems, or imaging.
Possible career paths in this domain include:
Bioinformatician in a research center – analyzing genomic data, evaluating new therapies, collaborating with biologists to uncover disease mechanisms.
IT specialist in a pharmaceutical company – supporting drug research through computer modeling, managing large experimental databases.
Medical software engineer – developing healthcare applications (e.g., diagnostic systems, remote patient monitoring tools) where both IT and medical knowledge are essential.
Medical data analyst – processing hospital or imaging data (e.g., X-rays, MRIs) using AI to support diagnostics, with humans still involved in the decision-making loop.
These professions are future-proof because they combine two rapidly evolving domains—technology and the life sciences. AI will not exclude the human role here; rather, it will provide tools, while experts remain indispensable for their correct use. For example, an algorithm may find correlations in medical data, but it will be the doctor or biologist–decision-maker (supported by an IT analyst) who evaluates the clinical significance of the discovery.
The job market for such interdisciplinary experts is international. Polish bioinformaticians and medical IT specialists work not only in Poland (e.g., in oncology centers, PAN institutes, and pharmaceutical companies) but also abroad, where they are often highly valued. Salaries depend on the sector—very competitive in business (Big Pharma, biotech companies), lower in academia but compensated by other advantages (participation in groundbreaking projects, prestige). Still, even young researchers in this field can obtain grants and funding for their ideas, as it is considered a strategic discipline. The bioinformatics major is being offered by an increasing number of universities and is undoubtedly regarded as a future-oriented field meeting real market needs.
The Importance of Soft Skills and Lifelong Learning
When analyzing the above fields, a clear pattern emerges: success in the future requires not only technical expertise but also soft skills and a willingness to learn continuously. According to a 2024 Statistics Poland (GUS) report, the number of jobs requiring so-called transversal skills (including communication, data analysis, and adaptability) is growing faster than traditional occupations. This means employers value people who can collaborate in teams, quickly adapt to new tools and environments, and combine competencies from different domains.
In the AI era, lifelong learning has become essential. Experts advise young people to invest in their development during and right after their studies through practical projects, online courses, internships, and hackathons. Building a portfolio with tangible achievements (e.g., an app, analysis, or research project) can be more convincing to employers than a diploma alone. It’s also worth participating actively in communities—attending meetups, IT conferences, and joining thematic groups. Networking helps exchange knowledge and spot emerging trends before they become mainstream.
Soft skills such as communication, teamwork, time management, creativity, and critical thinking are our competitive edge over machines. AI can compute billions of combinations, but it cannot think creatively beyond the data it has, nor can it feel empathy toward a client or colleague. Therefore, developing these skills—though less tangible than learning another programming language—is equally important. Students of future-oriented majors should take advantage of university opportunities in this regard (communication workshops, project work, student organizations, scientific clubs) to hone their leadership and innovation qualities.
Ethical and social awareness is equally crucial. The technologies young IT specialists will create are shaping the world of tomorrow. The ability to see the bigger picture, assess a system’s impact on users, protect privacy, and ensure equal access—these are all aspects that machines won’t consider unless we teach them to. Hence, the growing emphasis on digital responsibility among engineers, with competencies like AI ethics and philosophy of technology becoming part of education programs. A graduate who understands both what can be done and what should be done will be invaluable in the job market of the future.
To summarize this section: choosing a major is only the beginning. What matters is how versatile and adaptable you become as a professional. Instead of fearing that AI will take your job, start learning how to collaborate with it today—treat it as a tool that enhances your efficiency. Such a proactive attitude, combined with solid education in a future-oriented field, will give you a competitive edge in the world of tomorrow.
Summary and Advice for Young People in the AI Era
The world stands on the brink of a revolution where artificial intelligence will play a major role across all sectors of the economy. For today’s high school graduates and university students, this means the need for thoughtful career planning. As we’ve seen, there are many IT study paths that offer resistance to automation—from purely technical ones like AI, cybersecurity, or data science, to interdisciplinary fields combining IT with psychology, law, or biotechnology. The choice depends on individual interests and aptitudes, but several universal principles are worth keeping in mind:
Follow your passion—but stay aware of trends. Ideally, your future-proof major should align with what truly excites you. If you love biology, consider bioinformatics; if you enjoy working with people, look into UX or product design. Still, check job market forecasts and reports (e.g., Future of Jobs) and try to identify emerging niches.
Be open to interdisciplinarity. The boundaries between professions are blurring. Engineers collaborate with psychologists, lawyers with programmers, doctors with data scientists. Combine competencies—it makes you more unique. You can, for instance, complete a computer science degree and then take a course in IT law—or vice versa. Or choose a major that already blends multiple fields (such as cognitive science or cyberpsychology).
Develop soft skills and keep learning. A master’s degree is the beginning, not the end, of education. In the AI era, technologies evolve rapidly—you must keep up. Learn new programming languages and frameworks, but also work on communication, leadership, and adaptability. Lifelong learners will handle any change in the job market.
Leverage both academic and external resources. Participate in internships, research projects, and competitions. A diploma from a top university (technical or general) opens doors—but practical experience and networking open them even wider. Use your student years to build both hard and soft skills to the fullest.
Don’t fear AI—collaborate with it. Instead of seeing artificial intelligence as a threat, treat it as a tool that can make you a better specialist. Future programmers will use AI for code testing, analysts for generating reports, lawyers for legal research—but the final judgment and oversight remain human. Your role is to be the smart supervisor of AI.
Finally, remember that the future starts today—the choices you make at the beginning of your journey (what you study, what internships you take, what languages you learn) will pay off in the coming years. The job market in 5–10 years will undoubtedly change, but the foundations described in this article will remain valid: deep, unique expertise combined with adaptability. By choosing a future-proof IT major and investing in your growth, you’re giving yourself a solid safeguard against the potential effects of automation. Technology will evolve, but your passion, knowledge, and human mind will remain your greatest assets.
Good luck on your path toward a dream career in a world where humans and artificial intelligence work hand in hand!
Sources: The reports and data cited in this text come from, among others, Forbes (2025), Forsal (2025), MaturaMinds (2025), and other studies referenced throughout. All quoted fragments are cited and linked to their original sources for readers interested in further exploration.