意大利发展人工智能的主要举措及启示

意大利重视人工智能及数字化发展,将其作为疫后经济复苏的优先方向和重要支柱,颁布了相关战略和计划,启动大型超级计算机建设。人工智能在筛选新冠肺炎药物方面取得重要进展。意大利对人工智能赋能未来产业发展和改善社会公共服务寄予厚望,其相关思路值得借鉴。     

Marketing via smart speakers: what should Alexa say?

ABSTRACT

A smart speaker is a wireless device with artificial intelligence that can be activated through voice command. The artificial intelligence interacts in the form of a virtual personal assistant, such as Amazon’s “Alexa”. Companies are currently creating voice applications for smart speakers that allow consumers to use the personal assistant to perform tasks, such as acquiring information and ordering products. This is the dawn of a new type of interaction between brands and consumers, a new touchpoint. Brands need to catch the vision and create content for this new technology, content that is useful in the buying process. The purpose of this study is to determine what types of marketing messages people find acceptable on smart speakers. Based on the findings, a cognitive message strategy is effective with smart speakers. The paper presents three types of executional frameworks that are best suited for the design of a cognitive message: authoritative, testimonial, and slice-of-life. The overriding requirement for marketing on smart speakers is that the message must provide value to the listener.     

Forecasting artificial intelligence on online customer assistance: Evidence from chatbot patents analysis

The main goal of this research is to provide a comprehensive understanding of the actual progresses in artificial intelligence, with emphasis on chatbots as emerging forms of customer assistance in online retailing. Drawing upon an analysis of the chatbot patents in the past 20 years, our findings show the increasing technology push towards the adoption of new conversational agents based on natural language. Findings also highlight the extent to which the research and development efforts are attempting to improve artificial intelligence systems that characterize chatbots. To this end, technology advancements are mainly focusing on: (i) improving chatbot ability to automatically draw inferences on users starting from multiple data sources, and (ii) using consumers’ knowledge adaptively to provide more customized solutions. Finally, results show the tight relationship between the digital assistants’ analytical skills and their ability to automatically interact with the users.     

Using artificial neural network and multivariate analysis techniques to evaluate road operating conditions

Regional paved roads are low volume roads with a prevalence of heavy traffic. In the world, these roads concern about 80% of the total road network; however, the traffic that affects these roads is about 20%. Since regional roads are characterized by weak demand, budget for their management/maintenance is very low. This produces considerable difficulties in the choice of strategies for maintenance planning and scheduling. For this reason, the recurring topics of research in this field deal with typical roads issues and aim to develop low cost tools and methods. The study proposes a decision support system to evaluate regional paved roads operating condition in relation to the hydrogeological situation. In particular, the system allows to evaluate in a quick and easy manner, the operating conditions of the road, through low-cost tools (i.e. using low economic resources). This is very useful in the case of LVRs because administrations for these roads have a limited budget. The procedure is developed on a regional paved roads network based on more than 80 roads located in Southern Italy. Data is collected by direct surveys in the field and is integrated with cartography and information available in road agency records. From data analysis, obtained using two different techniques, an easy and quick use procedure is made. In particular, Model 1 is built through multivariate analysis and Model 2 using the artificial neural network (ANN) technique. The results show the validity of the two models in Regional paved roads operating conditions estimation in relation to hydrogeological situations of sites. Both models show good reliability. In particular, the first model (Model 1) is characterized by a high level of significance (p < 0.01) and by a coefficient of determination equal to 0.82. Comparative tests between the second model (Model 2) on which standard tests cannot be performed for obvious reasons, and the first model (Model 1). The results show that the ANN model (model 2), characterized by lower residual, simulates more accurately than the second (Model 1).     

人工智能技术辅助开发“智铸”系统

采用开源免费的深度学习平台,利用python二次开发了“智铸”系统,包括“识铸”“听铸”“盯铸”三个模块,铸造企业员工可以用手机或电脑自主学习,提升员工从业能力。在设备旁安装“听铸”软硬件一体化设备,可以实现对连续运行设备的在线自动监听侦测。“盯铸”模块实现连续生产铸件的自动检测、铸造缺陷分析与重点安全区域的监控。     

人工智能发展对通胀动态的影响及政策挑战——基于动态随机一般均衡模型的分析

人工智能的发展是生产力进步的表现，但广泛使用人工智能技术的经济效应尚待深入研究。基于人工智能对劳动的替代作用，将人工智能投资引入动态随机一般均衡模型，通过比较静态分析和短期动态分析考察人工智能发展对通胀动态的影响。稳态分析表明：人工智能投资效率提高和使用范围扩大均会提升劳动生产率进而提高产出水平，但对长期或趋势通胀没有影响；在人工智能发展初级阶段人工智能的发展会引起实际工资下降，而在相对高级阶段人工智能的发展会引起实际工资上升。短期动态分析显示：人工智能发展水平的提高，无论是投资效率的提高还是使用范围的扩大，都会导致通胀及实际边际成本对偏好冲击和技术冲击等外生冲击的反应变弱。人工智能的发展会使通胀动态与实际经济活动变化间的联系减弱，其原因是人工智能对劳动的替代作用使工资调整不再是应对外生冲击的必然选择，进而改变了外生冲击通过影响工资来影响通胀的传导机制。因此，发展人工智能在促进生产率提升和产出增长的同时，还会改变宏观经济变量间的传导机制，进而对通胀等政策调控目标变量的准确预测以及政策调整和实施的有效性带来新的挑战，也为金融理论研究提出新的课题。     

Designing,developing, and deploying artificial intelligence systems: Lessons from and for the public sector

Artificial intelligence applications in cognitive computing systems can be found in organizations across every market, including chatbots that help customers navigate websites, predictive analytics systems used for fraud detection, and augmented decision-support systems for knowledge workers. In this article, we share reflections and insights from our experience with AI projects in the public sector that can add value to any organization. We organized our findings into four thematic domains—(1) data, (2) technology, (3) organizational, and (4) environmental—and examine them relative to the phases of AI. We conclude with best practices for capturing value with cognitive computing systems.     

A systematic review of AI technology-based service encounters: Implications for hospitality and tourism operations

The hospitality and tourism industry faces serious challenges during public health emergencies such as COVID-19. Managers are concerned not only about how to maintain business and provide humanized services but also about social distancing. This study presented artificial intelligence (AI) technology-based service encounters as a possible solution and examined the antecedents and consequences of the encounter triad including customers, employees, and AI. Based on a systematic literature review, the study identified 4 modes of AI technology-based service encounters: AI-supplemented, AI-generated, AI-mediated, and AI-facilitated encounters. In addition, the study developed an integrated model to specify the factors that influence AI technology-infused service encounters in general and the customer service outcomes that result from the encounters. The findings contribute to service management and AI application theoretically and practically.     

关键核心技术攻关新型举国体制研究

面对新一轮科技革命,传统创新组织和模式已难以适应新形势的要求,美国科技界认为会聚创新模式将成为推动科技发展的重大战略举措。本文深入分析会聚创新兴起的内在机理,以人工智能领域为切入点,广泛借鉴国际创新组织不同模式经验,提出构建社会主义市场经济条件下关键核心技术攻关新型举国体制的若干建议。     

Shifts in consumer behavior towards organic products: Theory-driven data analytics

Consumer behavior is key in shifts towards organic products. A diversity of factors influences consumer preferences, driving planned, impulsive, and unplanned purchasing decisions. We study choices among organic and conventional wine using an extensive survey among Australian consumers (N = 1003). We integrate five behavioral theories in the survey design, and use supervised and unsupervised machine learning algorithms for analysis. We quantify a gap between intention and behavior, and emphasize the importance of cognitive factors. Findings go beyond correlation to the causation of behavior when combining predictive prowess with explanatory power. Results reveal that affective factors and normative cues may prompt unplanned and spontaneous purchasing behavior, causing consumers to act against their beliefs.