Artificial Intelligence (AI)'s pervasive presence and variety necessitate diversity and inclusivity (D&I) principles in its design for fairness, trust, and transparency. Yet, these considerations are often overlooked, leading to issues of bias, discrimination, and perceived untrustworthiness. In response, we conducted a Systematic Review to unearth challenges and solutions relating to D&I in AI. Our rigorous search yielded 48 research articles published between 2017 and 2022. Open coding of these papers revealed 55 unique challenges and 33 solutions for D&I in AI, as well as 24 unique challenges and 23 solutions for enhancing such practices using AI. This study, by offering a deeper understanding of these issues, will enlighten researchers and practitioners seeking to integrate these principles into future AI systems.

翻译：人工智能的普遍存在和多样性要求在设计中融入多样性与包容性（D&I）原则，以确保公平、可信和透明。然而，这些考虑因素常常被忽视，导致偏见、歧视和感知上的不可信等问题。为此，我们进行了一项系统性综述，以揭示人工智能中与多样性与包容性相关的挑战和解决方案。严格的文献检索筛选出2017年至2022年间发表的48篇研究文章。对这些论文进行开放式编码后，发现了人工智能中多样性与包容性方面的55项独特挑战和33项解决方案，以及利用人工智能增强此类实践的24项独特挑战和23项解决方案。本研究通过深入理解这些问题，将为寻求在未来的AI系统中融入这些原则的研究人员和实践者提供启示。