Vilans Centre of Expertise of Long Term Care, Utrecht, Netherlands.
Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, Netherlands.
JMIR Hum Factors. 2024 Jul 31;11:e55961. doi: 10.2196/55961.
Emerging technologies such as artificial intelligence (AI) require an early-stage assessment of potential societal and ethical implications to increase their acceptability, desirability, and sustainability. This paper explores and compares 2 of these assessment approaches: the responsible innovation (RI) framework originating from technology studies and the co-design approach originating from design studies. While the RI framework has been introduced to guide early-stage technology assessment through anticipation, inclusion, reflexivity, and responsiveness, co-design is a commonly accepted approach in the development of technologies to support the care for older adults with frailty. However, there is limited understanding about how co-design contributes to the anticipation of implications.
This paper empirically explores how the co-design process of an AI-based decision support system (DSS) for dementia caregivers is complemented by explicit anticipation of implications.
This case study investigated an international collaborative project that focused on the co-design, development, testing, and commercialization of a DSS that is intended to provide actionable information to formal caregivers of people with dementia. In parallel to the co-design process, an RI exploration took place, which involved examining project members' viewpoints on both positive and negative implications of using the DSS, along with strategies to address these implications. Results from the co-design process and RI exploration were analyzed and compared. In addition, retrospective interviews were held with project members to reflect on the co-design process and RI exploration.
Our results indicate that, when involved in exploring requirements for the DSS, co-design participants naturally raised various implications and conditions for responsible design and deployment: protecting privacy, preventing cognitive overload, providing transparency, empowering caregivers to be in control, safeguarding accuracy, and training users. However, when comparing the co-design results with insights from the RI exploration, we found limitations to the co-design results, for instance, regarding the specification, interrelatedness, and context dependency of implications and strategies to address implications.
This case study shows that a co-design process that focuses on opportunities for innovation rather than balancing attention for both positive and negative implications may result in knowledge gaps related to social and ethical implications and how they can be addressed. In the pursuit of responsible outcomes, co-design facilitators could broaden their scope and reconsider the specific implementation of the process-oriented RI principles of anticipation and inclusion.
人工智能(AI)等新兴技术需要对其潜在的社会和伦理影响进行早期评估,以提高其可接受性、可取性和可持续性。本文探讨并比较了这两种评估方法:源于技术研究的负责任创新(RI)框架和源于设计研究的共同设计方法。虽然 RI 框架已被引入通过预期、包容、反思和响应来指导早期技术评估,但共同设计是支持脆弱老年人护理的技术开发中常用的方法。然而,对于共同设计如何有助于预期影响,人们的理解有限。
本文通过实证研究探讨了 AI 为基础的痴呆症护理人员决策支持系统(DSS)的共同设计过程如何补充明确的影响预期。
本案例研究调查了一个国际合作项目,该项目专注于共同设计、开发、测试和商业化一个 DSS,旨在为痴呆症患者的正式护理人员提供可操作的信息。与共同设计过程并行的是 RI 探索,其中涉及检查项目成员对使用 DSS 的积极和消极影响的观点,以及解决这些影响的策略。对共同设计过程和 RI 探索的结果进行了分析和比较。此外,还对项目成员进行了回顾性访谈,以反思共同设计过程和 RI 探索。
我们的结果表明,在参与探索 DSS 的需求时,共同设计参与者自然提出了各种关于负责任设计和部署的影响和条件:保护隐私、防止认知过载、提供透明度、赋予护理人员控制权、保护准确性和培训用户。然而,当将共同设计结果与 RI 探索的见解进行比较时,我们发现共同设计结果存在局限性,例如,关于影响和解决影响策略的规范、相互关联性和上下文相关性。
本案例研究表明,关注创新机会而非平衡关注积极和消极影响的共同设计过程可能会导致与社会和伦理影响及其如何解决相关的知识差距。在追求负责任的结果时,共同设计推动者可以扩大其范围,并重新考虑面向过程的 RI 原则中预期和包容的具体实施。