Cited by 42Ethics and Social Impacts of AITopic ModelingArtificial Intelligence Applications

A Reasoning and Value Alignment Test to Assess Advanced GPT Reasoning

Open access
Mcintosh, Timothy R., Liu, Tong, Susnjak, Teo, Watters, Paul, Halgamuge, Malka N.·2024·ACM Transactions on Interactive Intelligent Systems

Abstract

In response to diverse perspectives on artificial general intelligence (AGI), ranging from potential safety and ethical concerns to more extreme views about the threats it poses to humanity, this research presents a generic method to gauge the reasoning capabilities of artificial intelligence (AI) models as a foundational step in evaluating safety measures. Recognizing that AI reasoning measures cannot be wholly automated, due to factors such as cultural complexity, we conducted an extensive examination of five commercial generative pre-trained transformers (GPTs), focusing on their comprehension and interpretation of culturally intricate contexts. Utilizing our novel “Reasoning and Value Alignment Test,” we assessed the GPT models’ ability to reason in complex situations and grasp local cultural subtleties. Our findings have indicated that, although the models have exhibited high levels of human-like reasoning, significant limitations remained, especially concerning the interpretation of cultural contexts. This article also explored potential applications and use-cases of our Test, underlining its significance in AI training, ethics compliance, sensitivity auditing, and AI-driven cultural consultation. We concluded by emphasizing its broader implications in the AGI domain, highlighting the necessity for interdisciplinary approaches, wider accessibility to various GPT models, and a profound understanding of the interplay between GPT reasoning and cultural sensitivity.

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Crossref · 10.1145/3670691

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Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • LLMs operate as black boxes with opaque internal mechanisms, making it difficult to interpret their decision-making processes and identify potential biases or ethical issues.

    “Furthermore, LLMs operate as black boxes with opaque internal mechanisms, making it difficult to interpret their decision-making processes and identify potential biases or ethical issues [4], [27].”
  • LLMs like Llama and GPT-4 are capable of understanding and generating human-like text, performing tasks ranging from translation to creative writing.

    “LLMs like Llama and GPT-4 are capable of understanding and generating human-like text, performing tasks ranging from translation to creative writing [1], [4].”
  • LLM benchmarks are constrained by the current limits of the benchmark creators' human knowledge, hindering their ability to fully assess and cultivate emerging AI capabilities that may surpass conventional human understanding, potentially stalling innovation in fields that rely on advanced AI insights.

    “LLM benchmarks are constrained by the current limits of the benchmark creators' human knowledge, hindering their ability to fully assess and cultivate emerging AI capabilities that may surpass conventional human understanding, potentially stalling innovation in fields that rely on advanced AI insights [4].”

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References 60 · Cited by 42

Authors
Mcintosh, T. R., Liu, T., Susnjak, T., Watters, P., & Halgamuge, M. N.
Affiliations
  • La Trobe University (AU)
  • Massey University (NZ)
  • Massey University, Albany, New Zealand
  • Cyberstronomy Pty Ltd, Ballarat, Australia
  • RMIT University (AU)
Venue
ACM Transactions on Interactive Intelligent Systems
Published
2024-08-02
Volume
14
Issue
3
Pages
1-37
ISSN
  • 2160-6455 (ISSN-L)
  • 2160-6463
OpenAlex
W4399285823
Cited by
42
References
60
Citations by year
2026: 21 · 2025: 10 · 2024: 11
FWCI
17.49
Type
journal article
Language
en
Open access
Locations
  • ACM Transactions on Interactive Intelligent Systems (publishedVersion, cc-by-nc-sa)
  • Figshare (submittedVersion, cc-by-nc-sa)
  • La Trobe University
Topics
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
Keywords
cultural sensitivity, AI safety evaluation, value alignment, generative pre-trained transformer, AI training

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