topic


Integrating Large Language Models (LLMs) into socio-technical systems presents significant challenges, but a systems engineering approach, prioritizing problem understanding and context, can help mitigate these issues and ensure reliable, accountable, and sustainable AI-based systems.


coremsg

The Systems Engineering Approach in Times of Large Language Models

### title_rewrite
The Systems Engineering Approach to Integrating Large Language Models into Socio-Technical Systems: A Survey of Challenges and Solutions 

### category
SoftwareDevelopment

### topic
Large Language Model Integration

### coremsg
Integrating Large Language Models (LLMs) into socio-technical systems presents significant challenges, but a systems engineering approach, prioritizing problem understanding and context, can help mitigate these issues and ensure reliable, accountable, and sustainable AI-based systems. 

### note
### Bibliographic Information:
Cabrera, C., Schooling, J., Bastidas, V., & Lawrence, N. D. (2024). The Systems Engineering Approach in Times of Large Language Models. *arXiv preprint arXiv:2411.09050v1*.

### Research Objective:
This paper examines how the systems engineering approach can be applied to address the unique challenges posed by integrating Large Language Models (LLMs) into socio-technical systems. The authors aim to understand how current research utilizes systems engineering principles to tackle issues similar to those LLMs introduce in complex systems.

### Methodology:
The authors conducted a semi-automatic literature survey using a tool to identify relevant papers published since 2017. They searched across multiple databases using specific keywords related to systems engineering and AI. After filtering and manually reviewing the retrieved papers, they analyzed 24 papers that apply systems engineering approaches to address challenges in AI-based systems, focusing on those relevant to LLMs.

### Key Findings:
- The most common challenges identified in integrating LLMs into socio-technical systems are related to systems alignment and reliability, followed by interpretability and accountability.
- The most frequently applied systems engineering principles in the analyzed papers are Systems Views, Top-Down approach, and Problem-Solving Cycle.
- The authors identify a need for more research on applying dynamic and flexible principles like Agility Systems, System Dynamics, and Variant Creation to address the evolving nature of LLMs.

### Main Conclusions:
The systems engineering approach provides a valuable framework for mitigating the challenges of integrating LLMs into socio-technical systems. The authors advocate for a shift in organizational culture towards prioritizing planning and a more balanced approach between planning and production phases. They also highlight the need for future research to address the dynamic nature of LLM technology and the importance of inclusive requirements gathering involving all stakeholders.

### Significance:
This research contributes to the growing field of AI Systems Engineering by providing a timely analysis of the challenges and potential solutions for integrating LLMs into complex systems. It highlights the importance of a structured, systems-level approach to ensure the responsible and beneficial use of LLMs in real-world applications.

### Limitations and Future Research:
The study focuses on research published since 2017, potentially missing earlier work. Future research could explore the application of specific systems engineering methodologies and tools for LLM integration and investigate the social and ethical implications of these systems in more depth. 

### data_sheet
- Around 87% of the surveyed papers (21 out of 24) address alignment and reliability issues when integrating LLMs into systems.
- Six of the surveyed papers focus on addressing interpretability and accountability challenges.
- Three papers propose using cost-benefit analysis to support effective resource management and address maintainability and sustainability concerns.
- Eight out of the 24 papers propose approaches to address security and privacy issues related to LLM integration.

### quotes
- "The systems engineering approach is equipped with principles to facilitate this alignment by prioritising the problems and their context before considering the technologies for their resolution."
- "We envisage an ecosystem where systems engineering and LLMs mutually benefit instead of the naive belief that benefits come from the LLMs to the domains in one direction."
- "Organisations need a shift towards methodologies that balance or even prioritise planning phases against production phases."

### further_questions
- How can we develop standardized testing and evaluation frameworks for AI-based systems that incorporate LLMs, ensuring their reliability and safety across different application domains?
- While a systems engineering approach emphasizes structure and planning, could it potentially stifle the creativity and innovation often associated with LLM development and application, particularly in rapidly evolving fields?
- As LLMs become increasingly integrated into our daily lives, how might the traditional boundaries between "systems" and "users" blur, and what new challenges and opportunities might arise from this paradigm shift? 


Large Language Model Integration

the-systems-engineering-approach-to-integrating-large-language-models-into-socio-technical-systems-a-survey-of-challenges-and-solutions-

note


This paper examines how the systems engineering approach can be applied to address the unique challenges posed by integrating Large Language Models (LLMs) into socio-technical systems. The authors aim to understand how current research utilizes systems engineering principles to tackle issues similar to those LLMs introduce in complex systems.


Research Objective:


Cabrera, C., Schooling, J., Bastidas, V., & Lawrence, N. D. (2024). The Systems Engineering Approach in Times of Large Language Models. arXiv preprint arXiv:2411.09050v1.


Bibliographic Information:


The Systems Engineering Approach to Integrating Large Language Models into Socio-Technical Systems: A Survey of Challenges and Solutions


The Systems Engineering Approach to Integrating Large Language Models into Socio-Technical Systems: A Survey of Challenges and Solutions

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