The Systems Engineering Approach in Times of Large Language Models

Christian Cabrera; Victor Bastidas; Jennifer Schooling; Neil D. Lawrence

Back to publications

The Systems Engineering Approach in Times of Large Language Models

Christian Cabrera, Victor Bastidas, Jennifer Schooling, Neil D. Lawrence

58th Hawaii International Conference on System Sciences (HICSS-58).

Abstract

Using Large Language Models (LLMs) to address critical societal problems requires adopting this novel technology into socio-technical systems. However, the complexity of such systems and the nature of LLMs challenge such a vision. It is unlikely that the solution to such challenges will come from the Artificial Intelligence (AI) community itself. Instead, the Systems Engineering approach is better equipped to facilitate the adoption of LLMs by prioritising the problems and their context before any other aspects. This paper introduces the challenges LLMs generate and surveys systems research efforts for engineering AI-based systems. We reveal how the systems engineering principles have supported addressing similar issues to the ones LLMs pose and discuss our findings to provide future directions for adopting LLMs.

Links

Cite this Paper

BibTeX


@InProceedings{publications/the-systems-engineering-approach-in-times-of-large-language-models,
  title = 	 {The Systems Engineering Approach in Times of Large Language Models},
  author = 	 {Cabrera, Christian and Bastidas, Victor and Schooling, Jennifer and Lawrence, Neil D.},
  booktitle = 	 {58th Hawaii International Conference on System Sciences (HICSS-58)},
  url = 	 {/publications/the-systems-engineering-approach-in-times-of-large-language-models.html},
  abstract = 	 {Using Large Language Models (LLMs) to address critical societal problems requires adopting this novel technology into socio-technical systems. However, the complexity of such systems and the nature of LLMs challenge such a vision. It is unlikely that the solution to such challenges will come from the Artificial Intelligence (AI) community itself. Instead, the Systems Engineering approach is better equipped to facilitate the adoption of LLMs by prioritising the problems and their context before any other aspects. This paper introduces the challenges LLMs generate and surveys systems research efforts for engineering AI-based systems. We reveal how the systems engineering principles have supported addressing similar issues to the ones LLMs pose and discuss our findings to provide future directions for adopting LLMs.}
}

Endnote

%0 Conference Paper
%T The Systems Engineering Approach in Times of Large Language Models
%A Christian Cabrera
%A Victor Bastidas
%A Jennifer Schooling
%A Neil D. Lawrence
%B 58th Hawaii International Conference on System Sciences (HICSS-58)	
%F publications/the-systems-engineering-approach-in-times-of-large-language-models
%U /publications/the-systems-engineering-approach-in-times-of-large-language-models.html
%X Using Large Language Models (LLMs) to address critical societal problems requires adopting this novel technology into socio-technical systems. However, the complexity of such systems and the nature of LLMs challenge such a vision. It is unlikely that the solution to such challenges will come from the Artificial Intelligence (AI) community itself. Instead, the Systems Engineering approach is better equipped to facilitate the adoption of LLMs by prioritising the problems and their context before any other aspects. This paper introduces the challenges LLMs generate and surveys systems research efforts for engineering AI-based systems. We reveal how the systems engineering principles have supported addressing similar issues to the ones LLMs pose and discuss our findings to provide future directions for adopting LLMs.

RIS


TY  - CPAPER
TI  - The Systems Engineering Approach in Times of Large Language Models
AU  - Christian Cabrera
AU  - Victor Bastidas
AU  - Jennifer Schooling
AU  - Neil D. Lawrence
BT  - 58th Hawaii International Conference on System Sciences (HICSS-58)
DA  - false	
ID  - publications/the-systems-engineering-approach-in-times-of-large-language-models
UR  - /publications/the-systems-engineering-approach-in-times-of-large-language-models.html
AB  - Using Large Language Models (LLMs) to address critical societal problems requires adopting this novel technology into socio-technical systems. However, the complexity of such systems and the nature of LLMs challenge such a vision. It is unlikely that the solution to such challenges will come from the Artificial Intelligence (AI) community itself. Instead, the Systems Engineering approach is better equipped to facilitate the adoption of LLMs by prioritising the problems and their context before any other aspects. This paper introduces the challenges LLMs generate and surveys systems research efforts for engineering AI-based systems. We reveal how the systems engineering principles have supported addressing similar issues to the ones LLMs pose and discuss our findings to provide future directions for adopting LLMs.
ER  -

APA


Cabrera, C., Bastidas, V., Schooling, J. & Lawrence, N.D.. (false). The Systems Engineering Approach in Times of Large Language Models. 58th Hawaii International Conference on System Sciences (HICSS-58) Available from /publications/the-systems-engineering-approach-in-times-of-large-language-models.html.

Related People

Christian Cabrera Jojoa

Assistant Research Professor, Cambridge University

View Profile

Neil D. Lawrence

The DeepMind Professor of Machine Learning, Cambridge University

View Profile

Related Projects

AutoAI

While excitement about the potential of artificial intelligence (AI) technologies continues to build, a gap is emerging between our aspirations for the benefits of AI and our ability to deploy these technologies to tackle real-world challenges.

Interfaces

The Interfaces research programme develops interpretable, self-sustaining multi-agent AI systems, treating software as the interface between socio-technical needs and AI capabilities, with validation in healthcare and other high-stakes settings.