mlsanityData to 7 Oct 2026

ChatGPT Needs SPADE (Sustainability, PrivAcy, Digital divide, and Ethics) Evaluation: A Review

arXiv 2305.03123 ↗First posted 13 Apr 2023cs.CY cs.AI cs.CLcited by 28

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Abstract (arXiv)

ChatGPT is another large language model (LLM) vastly available for the consumers on their devices but due to its performance and ability to converse effectively, it has gained a huge popularity amongst research as well as industrial community. Recently, many studies have been published to show the effectiveness, efficiency, integration, and sentiments of chatGPT and other LLMs. In contrast, this study focuses on the important aspects that are mostly overlooked, i.e. sustainability, privacy, digital divide, and ethics and suggests that not only chatGPT but every subsequent entry in the category of conversational bots should undergo Sustainability, PrivAcy, Digital divide, and Ethics (SPADE) evaluation. This paper discusses in detail the issues and concerns raised over chatGPT in line with aforementioned characteristics. We also discuss the recent EU AI Act briefly in accordance with the SPADE evaluation. We support our hypothesis by some preliminary data collection and visualizations along with hypothesized facts. We also suggest mitigations and recommendations for each of the concerns. Furthermore, we also suggest some policies and recommendations for EU AI policy act concerning ethics, digital divide, and sustainability

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). Builds on 22 of its 78 references that are in the map. First posted on arXiv 13 Apr 2023.

Builds on

22 of 78 references.

References · 22

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Citing papers per year: 2023: 7; 2024: 17; 2025: 4.

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  1. 2024Large Language Models and Games: A Survey and Roadmapcited by 91
  2. 2024Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systemscited by 63
  3. 2024Navigating LLM Ethics: Advancements, Challenges, and Future Directionscited by 28
  4. 2023AI-native Interconnect Framework for Integration of Large Language Model Technologies in 6G Systemscited by 19
  5. 2024Mapping the Ethics of Generative AI: A Comprehensive Scoping Reviewcited by 19
  6. 2023ChatGPT is a Remarkable Tool -- For Expertscited by 16
  7. 2023Watt For What: Rethinking Deep Learning's Energy-Performance Relationshipcited by 16
  8. 2023Friend or Foe? Exploring the Implications of Large Language Models on the Science Systemcited by 15
  9. 2023Bridging the Digital Divide: Performance Variation across Socio-Economic Factors in Vision-Language Modelscited by 11
  10. 2024Blind Spots and Biases: Exploring the Role of Annotator Cognitive Biases in NLPcited by 11
  11. 2023ChatGPT in the Age of Generative AI and Large Language Models: A Concise Surveycited by 10
  12. 2024Automated Text Scoring in the Age of Generative AI for the GPU-poorcited by 10
16 more
  1. 2025SPHERE: An Evaluation Card for Human-AI Systemscited by 9
  2. 2024Fine-Tuning a Local LLaMA-3 Large Language Model for Automated Privacy-Preserving Physician Letter Generation in Radiation Oncologycited by 8
  3. 2024Exploring ChatGPT and its Impact on Societycited by 6
  4. 2024Generative AI for RF Sensing in IoT systemscited by 6
  5. 2024Enabling Energy-Efficient Deployment of Large Language Models on Memristor Crossbar: A Synergy of Large and Smallcited by 4
  6. 2023LinguaLinked: A Distributed Large Language Model Inference System for Mobile Devicescited by 3
  7. 2024The Rise of Artificial Intelligence in Educational Measurement: Opportunities and Ethical Challengescited by 3
  8. 2024The Emerging Generative Artificial Intelligence Divide in the United Statescited by 2
  9. 2024Return of EM: Entity-driven Answer Set Expansion for QA Evaluationcited by 2
  10. 2025"We are not Future-ready": Understanding AI Privacy Risks and Existing Mitigation Strategies from the Perspective of AI Developers in Europecited by 2
  11. 2024Multidimensional Human Activity Recognition With Large Language Model: A Conceptual Frameworkcited by 1
  12. 2024Double Jeopardy and Climate Impact in the Use of Large Language Models: Socio-economic Disparities and Reduced Utility for Non-English Speakerscited by 1
  13. 2024AccessShare: Co-designing Data Access and Sharing with Blind Peoplecited by 0
  14. 2024Insights into resource utilization of code small language models serving with runtime engines and execution providerscited by 0
  15. 2025EdgeAIGuard: Agentic LLMs for Minor Protection in Digital Spacescited by 0
  16. 2025Framework, Standards, Applications and Best practices of Responsible AI : A Comprehensive Surveycited by 0