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.

心理学中的复杂原理与广泛社会影响形成了一个重要的社会挑战。近年来，高度适应和可复用的人工智能模型在心理学领域崛起，强调了对这些大规模人工智能模型的性能验证的重要性，同时突出了这些模型在社交媒体分析、临床护理洞察、社区监测和心理学理论的细致探索等领域的前沿进展和实际应用。基于我们的综述，我们预示心理学领域将会加速发展，这源于这些大规模人工智能模型的推动。这些未来的综合型人工智能模型有望大幅降低劳动成本并缓解社会压力，然而，这种前进的势头在考虑到医疗仪器和相关应用所需的范式变革和升级时也面临一系列挑战。

迈向一种心理学通用人工智能：大型语言模型的现有应用和未来前景综述