mlsanityData to 14 Oct 2026

Thorns and Algorithms: Navigating Generative AI Challenges Inspired by Giraffes and Acacias

arXiv 2407.11360 ↗First posted 16 Jul 2024cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

The interplay between humans and Generative AI (Gen AI) draws an insightful parallel with the dynamic relationship between giraffes and acacias on the African Savannah. Just as giraffes navigate the acacia's thorny defenses to gain nourishment, humans engage with Gen AI, maneuvering through ethical and operational challenges to harness its benefits. This paper explores how, like young giraffes that are still mastering their environment, humans are in the early stages of adapting to and shaping Gen AI. It delves into the strategies humans are developing and refining to help mitigate risks such as bias, misinformation, and privacy breaches, that influence and shape Gen AI's evolution. While the giraffe-acacia analogy aptly frames human-AI relations, it contrasts nature's evolutionary perfection with the inherent flaws of human-made technology and the tendency of humans to misuse it, giving rise to many ethical dilemmas. Through the HHH framework we identify pathways to embed values of helpfulness, honesty, and harmlessness in AI development, fostering safety-aligned agents that resonate with human values. This narrative presents a cautiously optimistic view of human resilience and adaptability, illustrating our capacity to harness technologies and implement safeguards effectively, without succumbing to their perils. It emphasises a symbiotic relationship where humans and AI continually shape each other for mutual benefit.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 32 of its 107 references that are in the map. First posted on arXiv 16 Jul 2024.

Builds on

32 of 107 references.

References · 32

  1. 2023GPT-4 Technical Reportcited by 18,396
  2. 2022Training language models to follow instructions with human feedbackcited by 15,971
  3. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
  4. 2022Constitutional AI: Harmlessness from AI Feedbackcited by 3,050
  5. 2022Scaling Instruction-Finetuned Language Modelscited by 3,024
  6. 2022Emergent Abilities of Large Language Modelscited by 2,512
  7. 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,212
  8. 2021A General Language Assistant as a Laboratory for Alignmentcited by 1,055
  9. 2021Ethical and social risks of harm from Language Modelscited by 966
  10. 2023Whose Opinions Do Language Models Reflect?cited by 773
  11. 2022Improving alignment of dialogue agents via targeted human judgementscited by 531
  12. 2023Are Emergent Abilities of Large Language Models a Mirage?cited by 523
20 more
  1. 2023Analyzing Leakage of Personally Identifiable Information in Language Modelscited by 285
  2. 2023Model evaluation for extreme riskscited by 177
  3. 2023Auditing large language models: a three-layered approachcited by 137
  4. 2024Evaluating Frontier Models for Dangerous Capabilitiescited by 128
  5. 2024The Ethics of Advanced AI Assistantscited by 107
  6. 2023Regulating ChatGPT and other Large Generative AI Modelscited by 104
  7. 2020Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Databasecited by 96
  8. 2024Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systemscited by 96
  9. 2023Art and the science of generative AI: A deeper divecited by 95
  10. 2024"I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trustcited by 67
  11. 2024Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systemscited by 66
  12. 2023GenAI Against Humanity: Nefarious Applications of Generative Artificial Intelligence and Large Language Modelscited by 42
  13. 2023The Unfairness of Fair Machine Learning: Levelling down and strict egalitarianism by defaultcited by 36
  14. 2023A Survey on ChatGPT: AI-Generated Contents, Challenges, and Solutionscited by 35
  15. 2024RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processingcited by 25
  16. 2024Generative AI in EU Law: Liability, Privacy, Intellectual Property, and Cybersecuritycited by 21
  17. 2023The Rise of the AI Co-Pilot: Lessons for Design from Aviation and Beyondcited by 15
  18. 2022AI Ethics Issues in Real World: Evidence from AI Incident Databasecited by 14
  19. 2024Interoperable Provenance Authentication of Broadcast Media using Open Standards-based Metadata, Watermarking and Cryptographycited by 6
  20. 2024Operationalising AI governance through ethics-based auditing: An industry case studycited by 6

Built on by

Not cited yet.