ai-pocalypse Recent research details how customer service reps at a Chinese utility's call center often struggled when trying to use an AI assistant, and were forced to make manual fixes.
AI-Pocalypse最近的研究详细介绍了中国公用事业呼叫中心的客户服务代表如何在尝试使用AI助手时经常挣扎，并被迫进行手动修复。
Researchers affiliated with a Chinese power utility and several Chinese universities recently conducted a study of how customer service representatives (CSRs) at the power utility's call center use AI assistance during their interactions with customers. The study is based on 13 semi-structured interviews with service reps, including team leaders and shift supervisors, responsible for handling phone inquiries.
研究人员隶属于中国电力公司和中国几所大学，最近对Power Utilities呼叫中心的客户服务代表（CSR）进行了研究，他们在与客户的互动过程中使用AI援助。该研究基于对服务代表的13次半结构化访谈，包括团队负责人和轮班主管，负责处理电话查询。
The preprint paper, accepted to the 28th ACM SIGCHI Conference on Computer-Supported Cooperative Work & Social Computing (CSCW) in October, attempts to provide an alternative to assessments of AI geared toward management and customer experience, focusing instead on the workers forced to use AI during customer calls.
10月，第28届ACM Sigchi Sigchi会议上接受了预印本论文，该论文于10月份接受了计算机支持的合作工作与社交计算（CSCW），试图提供替代对管理和客户体验的AI评估的替代方法，而是专注于工人在呼叫期间被迫使用AI的工人。
One of the findings is that the AI often inaccurately transcribed customer call audio into text thanks to caller accents, pronunciation, and speech speed. The AI also had trouble rendering sequences of numbers accurately, like phone numbers.
一个发现之一是，由于呼叫者的口音，发音和语音速度，AI通常不准确地转录客户呼叫音频。AI也很难准确地渲染数字序列，例如电话号码。
"The AI assistant isn’t that smart in reality," one survey respondent said."It gives phone numbers in bits and pieces, so I have to manually enter them."
一位受访者说：“实际上，AI助手并不是那么聪明。”“它可以用碎片和零碎的方式提供电话号码，因此我必须手动输入。”
Another said the AI had trouble transcribing homophones – words that sound the same but have different spellings or meanings.
另一个人说，AI很难转录同音字 - 听起来相同但拼写或含义不同。
And the AI's emotion recognition system worked poorly – it would misclassify normal speech as a negative emotion, had too few categories for classification, and would treat volume level as a sign of poor attitude. As a result, reps mostly ignored the emotional tags created by the AI system and said they had no trouble understanding the caller's tone.
AI的情绪识别系统的工作效果很差 - 它将将正常的语音误认为是负面情绪，对分类的类别太少，并且将数量水平视为态度不佳的标志。结果，代表大多忽略了AI系统创建的情感标签，并表示他们毫不费力地了解呼叫者的语气。
While reducing basic typing labor, AI-generated outputs introduced structural inefficiencies in information processing
在减少基本打字人工的同时，AI生成的输出在信息处理中引入了结构性低效率
The customer service staffers also found that AI output created redundancies or required corrections."While reducing basic typing labor, AI-generated outputs introduced structural inefficiencies in information processing because most AI-prefilled content required manual correction or deletion," the report says.
客户服务人员还发现，AI输出创建了冗余或所需的更正。报告说：“在减少基本打字人工的同时，AI生成的输出在信息处理中引入了结构性低效率，因为大多数AI填充的内容都需要手动校正或删除。”
Text summaries of calls could be useful, the report says, but they often require editing or rewording. What's more, these transcriptions didn't necessarily capture key information.
报告说，呼叫的文本摘要可能很有用，但是它们通常需要编辑或重新单词。更重要的是，这些转录不一定捕获关键信息。
"While the AI enhances work efficiency, it simultaneously increases CSRs’ learning burdens due to the need for extra adaptation and correction," the report concludes."The mismatch between technological expectations and actual implementation reflects a common oversight among technology designers, who overestimate efficiency gains while underestimating the implicit learning burdens of adapting to new systems."
报告总结说：“尽管AI提高了工作效率，但由于需要进行额外的适应和更正，它同时增加了CSR的学习负担。”“技术期望与实际实施之间的不匹配反映了技术设计师之间的共同监督，他们高估了效率的提高，同时低估了对适应新系统的隐性学习负担。”
Moreover, there's an emotional factor that has to be considered, the researchers say."The service sector presents unique challenges for AI integration due to its emphasis on direct customer engagement and emotional labor," the study explains, citing potential barriers to AI integration like employee resistance, organizational culture, and the way that AI implementation can increase stress among customer service reps through productivity pressure and concerns about job loss.
此外，研究人员说，必须考虑一个情绪因素。该研究解释说：“由于强调了直接的客户参与和情感劳动，服务部门对AI集成提出了独特的挑战。”该研究解释说，其潜在的AI整合障碍（例如员工抵抗力，组织文化）以及AI实施可以通过生产力压力和对工作损失增加客户服务代表之间的压力。
In other words, don't rush to replace those customer service reps quite yet.
换句话说，不要急于替换这些客户服务代表。
This seems to be a growing consensus among the consultancy class as well. In 2023, IT consultancy Gartner predicted that by 2026, organizations would replace 20-30 percent of their customer support staff with generative AI.
这似乎也是咨询课程中日益增长的共识。2023年，IT咨询公司Gartner预测，到2026年，组织将用生成AI取代20-30％的客户支持人员。
Then last month, Gartner revised its forecast, noting that rehiring human agents to replace AI is the current trend:"By 2027, 50 percent of organizations that expected to significantly reduce their customer service workforce will abandon these plans."
然后，上个月，Gartner修改了其预测，并指出重新培训人类代理人取代AI是当前的趋势：“到2027年，预计将大大降低其客户服务劳动力的组织中有50％将放弃这些计划。”
"The human touch remains irreplaceable in many interactions, and organizations must balance technology with human empathy and understanding,” said Kathy Ross, senior director analyst in the Gartner Customer Service & Support practice, in a statement."A hybrid approach, where AI and human agents work in tandem, is the most effective strategy for delivering exceptional customer experiences."®
Gartner客户服务和支持实践的高级总监凯西·罗斯（Kathy Ross）在一份声明中说：“在许多互动中，人的触觉仍然无法替代，组织必须与人类的同理心和理解之间的平衡。”“ AI和人类代理在同时工作的混合方法是提供卓越客户体验的最有效策略。”®
