# Large Language Models' Trustworthiness in the Light of the EU AI Act--A Systematic Mapping Study
## 4 Classification Scheme
### Application Domain Classification  
Based on keywording, the following classification scheme was derived for domains where AI, particularly LLMs, are applied to ensure trustworthiness:  
* **Air Space--**Ensuring that LLMs provide accurate, reliable, and unbiased information for aerospace applications, such as navigation systems and communication protocols.
* **Automotive--**Maintaining safety and reliability in LLM-driven automotive technologies, including autonomous driving systems and in-vehicle assistants.
* **Construction--**Ensuring precision and safety in LLM applications for construction project planning, risk assessments, and management.
* **Cybersecurity--**Enhancing security measures and threat detection systems in the cybersecurity domain using LLMs.
* **Defence--**Ensuring the ethical application, security, and accuracy of LLMs in defense scenarios, such as threat analysis and decision support systems.  
* **Education--**Promoting fairness, accuracy, and bias reduction in LLM-based educational tools for personalized learning and academic assistance.
* **Environment--**Ensuring LLM-driven technologies support environmental monitoring and sustainability efforts.
* **Finance--**Ensuring transparency, bias reduction, and data protection in LLM applications for the fintech industry.
* **History--**Supporting transparent and reliable LLM usage in the analysis and preservation of cultural heritage.
* **Human-Computer Interaction (HCI)--**Enhancing interactions between humans and AI through improved dialogues, negotiations, and task delegation.
* **Information Verification--**Utilizing LLMs in automated fake news detection, fact-checking processes, and cross-domain analysis for verifying information credibility.
* **Smart Factory--**Maintaining operational integrity, reliability, and efficiency in LLM applications for automated manufacturing and production systems.
* **Health Care--**Ensuring privacy, accuracy, and ethical practices in LLM applications for medical diagnostics, patient care, and health data management.
* **Internet of Things (IoT)--**Ensuring precision, reliability, and ethical behavior in LLM-guided IoT systems across diverse applications.
* **Law--**Ensuring transparency, data integrity, and fairness in the use of LLMs for legal purposes.
* **Linguistic--**Promoting linguistic accuracy, cultural sensitivity, and reducing bias in LLM applications for translation, text generation, and language learning.
* **Marine--**Ensuring the safety and reliability of LLM applications in marine navigation, communication, and environmental monitoring.
* **Mining--**Enhancing operational safety and efficiency in LLM applications for resource extraction, site management, and predictive maintenance.
* **News/Media--**Leveraging LLMs for ethical reporting, fact-checking, and content creation in the media industry.
* **Robotics--**Ensuring the ethical behavior, precision, and reliability of LLM-powered robotic systems in both industrial and domestic settings.
* **Smart System/Coding--**Utilizing LLMs to improve software development processes, automate code generation, and ensure robust, efficient, and secure software systems.
* **Smart Business--**Harnessing LLMs to foster innovative business solutions, enhance operational efficiency, and provide data-driven insights for strategic decision-making.
* **Social Scoring--**Promoting fairness, transparency, and objectivity in social scoring systems by identifying and mitigating biases related to politics and social context.
* **Surveillance--**Ensuring the ethical use of LLMs in surveillance systems for monitoring, threat detection, and security analysis, while safeguarding privacy.
* **Telecommunication--**Ensuring security, reliability, and unbiased communication in LLM applications used for network management, customer service, and data analysis.
* **Not Specified--**This category is used for studies that do not specify the application domain.
* **Other--**This category includes studies working on application domains not listed here.