Understanding public perception of artificial intelligence (AI) and the tradeoffs between potential risks and benefits is crucial, as these perceptions might shape policy decisions, influence innovation trajectories for successful market strategies, and determine individual and societal acceptance of AI technologies. Using a representative sample of 1100 participants from Germany, this study examines mental models of AI. Participants quantitatively evaluated 71 statements about AI's future capabilities (e.g., autonomous driving, medical care, art, politics, warfare, and societal divides), assessing the expected likelihood of occurrence, perceived risks, benefits, and overall value. We present rankings of these projections alongside visual mappings illustrating public risk-benefit tradeoffs. While many scenarios were deemed likely, participants often associated them with high risks, limited benefits, and low overall value. Across all scenarios, 96.4% ($r^2=96.4\%$) of the variance in value assessment can be explained by perceived risks ($\beta=-.504$) and perceived benefits ($\beta=+.710$), with no significant relation to expected likelihood. Demographics and personality traits influenced perceptions of risks, benefits, and overall evaluations, underscoring the importance of increasing AI literacy and tailoring public information to diverse user needs. These findings provide actionable insights for researchers, developers, and policymakers by highlighting critical public concerns and individual factors essential to align AI development with individual values.

翻译：理解公众对人工智能（AI）的认知及其潜在风险与收益之间的权衡至关重要，因为这些认知可能影响政策决策、塑造创新轨迹以制定成功的市场策略，并决定个体与社会对AI技术的接受程度。本研究采用德国1100名参与者的代表性样本，考察了公众对AI的心理模型。参与者定量评估了71项关于AI未来能力的陈述（如自动驾驶、医疗护理、艺术、政治、战争及社会分化），评估内容包括预期发生可能性、感知风险、感知收益及总体价值。我们呈现了这些预测的排序结果，并通过可视化图谱展示了公众的风险-收益权衡关系。尽管多数场景被认为可能实现，但参与者常将其与高风险、有限收益及低总体价值相关联。在所有场景中，价值评估方差的96.4%（$r^2=96.4\%$）可由感知风险（$\beta=-.504$）和感知收益（$\beta=+.710$）解释，与预期可能性无显著关联。人口统计学特征与人格特质影响了对风险、收益及总体评估的认知，这凸显了提升AI素养和针对多样化用户需求定制公共信息的重要性。这些发现通过揭示关键公众关切和个体因素，为研究者、开发者和政策制定者提供了可操作的见解，对推动AI发展与个体价值观的协调具有重要意义。