Sharevski Filipo, Slowinski Anna, Jachim Peter, Pieroni Emma
College of Computing and Digital Media, DePaul University, 243 S Wabash Avenue, 60604, Chicago, IL, United States of America.
Internet Things (Amst). 2022 Aug;19:100566. doi: 10.1016/j.iot.2022.100566. Epub 2022 Jul 8.
In this paper, we analyzed the perceived accuracy of COVID-19 vaccine information spoken back by Amazon Alexa. Unlike social media, Amazon Alexa does not apply soft moderation to unverified content, allowing for use of third-party malicious skills to arbitrarily phrase COVID-19 vaccine information. The results from a 210-participant study suggest that a third-party malicious skill could successful reduce the perceived accuracy among the users of information as to who gets the vaccine first, vaccine testing, and the side effects of the vaccine. We also found that the vaccine-hesitant participants are drawn to pessimistically rephrased Alexa responses focused on the downsides of the mass immunization. We discuss solutions for soft moderation against misperception-inducing or other malicious third-party skills.
在本文中，我们分析了亚马逊Alexa复述的新冠疫苗信息的感知准确性。与社交媒体不同，亚马逊Alexa不对未经证实的内容进行软性审核，这使得第三方恶意技能能够随意表述新冠疫苗信息。一项有210名参与者的研究结果表明，第三方恶意技能能够成功降低用户对谁优先接种疫苗、疫苗测试以及疫苗副作用等信息的感知准确性。我们还发现，对疫苗持犹豫态度的参与者会被Alexa那些侧重于大规模免疫负面影响的消极表述所吸引。我们讨论了针对诱导误解或其他恶意第三方技能进行软性审核的解决方案。
