As a general purpose technology without a concrete pre-defined purpose, personal chatbots can be used for a whole range of objectives, depending on the personal needs, contexts, and tasks of an individual, and so potentially impact a variety of values, people, and social contexts. Traditional methods of risk assessment are confronted with several challenges: the lack of a clearly defined technology purpose, the lack of clearly defined values to orient on, the heterogeneity of uses, and the difficulty of actively engaging citizens themselves in anticipating impacts from the perspective of their individual lived realities. In this article, we leverage scenario writing at scale as a method for anticipating AI impact that is responsive to these challenges. The advantages of the scenario method are its ability to engage individual users and stimulate them to consider how chatbots are likely to affect their reality and so collect different impact scenarios depending on the cultural and societal embedding of a heterogeneous citizenship. Empirically, we tasked 106 US-based participants to write short fictional stories about the future impact (whether desirable or undesirable) of AI-based personal chatbots on individuals and society and, in addition, ask respondents to explain why these impacts are important and how they relate to their values. In the analysis process, we map those impacts and analyze them in relation to socio-demographic as well as AI-related attitudes of the scenario writers. We show that our method is effective in (1) identifying and mapping desirable and undesirable impacts of AI-based personal chatbots, (2) setting these impacts in relation to values that are important for individuals, and (3) detecting socio-demographic and AI-attitude related differences of impact anticipation.

翻译：作为一种没有明确预定义目标的通用技术，个人聊天机器人可根据个体的个人需求、情境和任务用于各种目标，从而可能影响多种价值观、人群和社会背景。传统的风险评估方法面临若干挑战：缺乏明确的技术目标、缺乏可依循的清晰价值观、使用场景的异质性，以及难以让公民从其个体生活现实角度主动参与影响预判。本文利用大规模场景编写方法作为应对这些挑战的AI影响预判工具。该方法的优势在于能够吸引个体用户参与，促使他们思考聊天机器人可能如何影响其现实生活，从而根据异质性公民群体所处的文化和社会嵌入环境收集不同的影响场景。在实证研究中，我们要求106名美国参与者撰写关于AI个人聊天机器人对个体和社会未来影响（无论是理想还是非理想的）的短篇虚构故事，并进一步要求受访者解释这些影响为何重要以及它们与其价值观的关联。在分析过程中，我们绘制这些影响图谱，并将其与场景编写者的社会人口统计学特征及AI相关态度进行关联分析。研究结果表明，我们的方法能有效：(1)识别并绘制AI个人聊天机器人的理想与非理想影响，(2)将这些影响与个体重视的价值观建立关联，以及(3)发现影响预判中的社会人口统计学及AI态度相关差异。