Background and Motivation: In recent years, the topic of applying videos in requirements engineering has been discussed and its contributions are of interesting potential. In the last 35 years, several researchers proposed approaches for applying videos in requirements engineering due to their communication richness and effectiveness. However, these approaches mainly use videos but omit the details about how to produce them. This lack of guidance is one crucial reason why videos are not an established documentation option for successful requirements communication and thus shared understanding. Software professionals are not directors and thus they do not necessarily know what constitutes a good video in general and for an existing approach. Therefore, this lack of knowledge and skills on how to produce and use videos for visual communication impedes the application of videos by software professionals in requirements engineering.
How to Create Effective Videos and Vision Videos?: This technical report addresses this lack of knowledge and skills by software professionals. We provide two guidelines that can be used as checklists to avoid frequent flaws in the production and use of videos respectively vision videos. Software professionals without special training should be able to follow these guidelines to achieve the basic capabilities to produce (vision) videos that are accepted by their stakeholders. These guidelines represent a core set of those capabilities in the preproduction, shooting, postproduction, and viewing of (vision) videos. We do not strive for perfection in any of these capabilities, .e.g., technical handling of video equipment, storytelling, or video editing. Instead, these guidelines support all steps of the (vision) video production and use process to a balanced way.
Requirements Practices and Gaps When Engineering Human-Centered Artificial Intelligence Systems
工程人工智能（AI）软件是一个相对较新的领域，有许多挑战，未知数和有限的证明最佳实践。谷歌、微软和苹果等大公司最近提供了一套指导方针，以帮助工程团队构建以人为本的人工智能系统。[目的]实践者目前所采用的开发这样的系统，特别是在需求工程（RE），很少研究和报告的日期。[方法]本文介绍了一项调查的结果，旨在了解当前的RE for AI（RE4AI）行业实践，并确定应遵循哪些关键的以人为本的AI指南。我们的调查是基于映射现有的行业准则，最佳实践和文献中的努力。[结果] 29名专业人士认为，RE中所有以人为本的方面都应该得到重视。此外，我们发现大多数参与者使用UML或Microsoft Office来呈现需求。[结论]我们发现，目前使用的大多数工具都不适合管理基于AI的软件，使用UML和Office可能会对AI捕获的需求质量造成问题。此外，从指南中映射的所有以人为本的实践都应该包括在RE中。
