[论文解读] Transformation vs Tradition: Artificial General Intelligence (AGI) for Arts and Humanities

Zhengliang Liu, Yiwei Li+10 more|arXiv (Cornell University)|Oct 30, 2023

Aesthetic Perception and Analysis被引用 16

一句话总结

本论文综述了AGI与大型语言/图像模型如何影响艺术与人文领域的文本、图形、音频和视频，讨论风险（事实性、毒性、偏见）及缓解措施，并倡导多方利益相关者共同推动负责任的进步。

ABSTRACT

Recent advances in artificial general intelligence (AGI), particularly large language models and creative image generation systems have demonstrated impressive capabilities on diverse tasks spanning the arts and humanities. However, the swift evolution of AGI has also raised critical questions about its responsible deployment in these culturally significant domains traditionally seen as profoundly human. This paper provides a comprehensive analysis of the applications and implications of AGI for text, graphics, audio, and video pertaining to arts and the humanities. We survey cutting-edge systems and their usage in areas ranging from poetry to history, marketing to film, and communication to classical art. We outline substantial concerns pertaining to factuality, toxicity, biases, and public safety in AGI systems, and propose mitigation strategies. The paper argues for multi-stakeholder collaboration to ensure AGI promotes creativity, knowledge, and cultural values without undermining truth or human dignity. Our timely contribution summarizes a rapidly developing field, highlighting promising directions while advocating for responsible progress centering on human flourishing. The analysis lays the groundwork for further research on aligning AGI's technological capacities with enduring social goods.

研究动机与目标

• 评估AGI和AIGC技术在文本、图形、音频和视频领域对艺术与人文任务的影响。
• 识别将AGI应用于文化敏感领域的机遇、挑战与伦理考量。
• 提出缓解策略与利益相关者协作，以在促进创造力、知识与文化价值的同时维护真实性与人类尊严。
• 概述将AGI能力与艺术与人文领域的社会福祉对齐的方向。

提出的方法

• 评估前沿的AGI系统及其在诗歌、历史、市场营销、电影、传播和古典艺术中的应用。
• 综合生成模型（GAN、扩散、 transformers）的文献及其在单模态和多模态环境中的应用。
• 讨论包括事实性、毒性、偏见和公共安全在内的实际与伦理挑战。
• 提出缓解策略并呼吁多方治理。

Figure 1 : Some examples of AGI-generated images. Left : A heavily deep-dream-style photograph expressing "three men in a pool", which is difficult for humans to understand. Middle : An image generated by DALL-E through translation from "an illustration of a baby hedgehog in a christmas sweater walk

实验结果

研究问题

• RQ1 当前AGI系统在艺术与人文领域的文本、图形、音频和视频方面如何被使用？
• RQ2 在文化意义重大的领域部署AGI时，主要风险和伦理问题有哪些，以及如何进行缓解？
• RQ3 哪些治理或协作方法可以在保护真实性与人类尊严的同时，使AGI发展与创造力、知识和文化价值保持一致？
• RQ4 未来研究的哪些方向有望将AGI的能力与艺术与人文领域的持久社会福祉结合起来？

主要发现

• AGI与AIGC能够在文学、语言学和创造性实践中实现快速分析、生成以及跨模态应用。
• 对AGI输出的事实性、毒性、偏见和公共安全存在重大担忧，需要缓解。
• 负责任的进展需要多方利益相关者合作，在创造力、真实与人类尊严之间取得平衡。
• 该领域正在快速发展，AGI有望影响艺术与人文的解读与创造性实践，需为与社会福祉对齐打下基础。
• 论文强调了将AGI技术与持久的文化和社会价值对齐的未来研究方向。

Figure 2 : An example of using GPT-3.5 for learning history. The right part shows a follow-up question regarding the answer of the first question in the left part.