迈向心理通用人工智能：大语言模型当前应用综述与未来展望
Towards a Psychological Generalist AI: A Survey of Current Applications of Large Language Models and Future Prospects
AI总结：
本文综述大语言模型等大规模AI在心理学中的应用、验证视角与代表性场景，并展望其推动心理通用AI、降低成本与缓解社会压力的前景及挑战。
摘要：
心理学原理的复杂性凸显了一项重大的社会挑战，因为心理问题具有广泛的社会影响。要弥合理解这些原理与其在临床和现实世界中的实际应用之间的鸿沟，需要严谨的探索和娴熟的实施。近来，高度自适应且可重复使用的人工智能（AI）模型迅速发展，成为释放心理学领域前所未有的能力的一条有前景的途径。本文强调了对这些大规模AI模型进行性能验证的重要性，并强调需要从不同视角对其验证提供全面评估。此外，我们回顾了这些大规模模型在心理学中的前沿进展和实际实施，重点介绍了涵盖社交媒体分析、临床护理洞见、警觉的社区监测以及对心理学理论的细致探索等领域的关键工作。基于我们的综述，我们预计在这些大规模AI模型的推动下，心理学领域的进展将会加速。这些未来的通用AI模型有潜力大幅削减劳动力成本并缓解社会压力。然而，这一前进势头并非没有一系列挑战，尤其是在考虑医疗仪器及相关应用所需的范式转变和升级时更是如此。
英文摘要：
The complexity of psychological principles underscore a significant societal challenge, given the vast social implications of psychological problems. Bridging the gap between understanding these principles and their actual clinical and real-world applications demands rigorous exploration and adept implementation. In recent times, the swift advancement of highly adaptive and reusable artificial intelligence (AI) models has emerged as a promising way to unlock unprecedented capabilities in the realm of psychology. This paper emphasizes the importance of performance validation for these large-scale AI models, emphasizing the need to offer a comprehensive assessment of their verification from diverse perspectives. Moreover, we review the cutting-edge advancements and practical implementations of these expansive models in psychology, highlighting pivotal work spanning areas such as social media analytics, clinical nursing insights, vigilant community monitoring, and the nuanced exploration of psychological theories. Based on our review, we project an acceleration in the progress of psychological fields, driven by these large-scale AI models. These future generalist AI models harbor the potential to substantially curtail labor costs and alleviate social stress. However, this forward momentum will not be without its set of challenges, especially when considering the paradigm changes and upgrades required for medical instrumentation and related applications.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
