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AI出錯會給企業帶來什么后果?

Anne Fisher 2019年09月11日

這本書很有趣,提供了一些AI體驗出現偏差的例子。

還記得去年的感恩節嗎?喬治叔叔堅持要嘗試炸火雞,然后不得不讓Alexa(亞馬遜人工智能助手)打電話給服務熱線Butterball Turkey Talk-Line求助。如果問題復雜,喬治叔叔聽起來又很驚慌,接電話的就有可能是人工客服,比如經驗豐富的Butterball老員工瑪吉·克林德拉。而如果問題簡單易答,接電話的就可能是一個復雜的算法系統,它可以識別數百個和火雞有關的常見詞語,并使用瑪吉的錄音作答。

喬治叔叔有可能不知道(或者不在乎)誰接的電話,前提是他能夠快速而順利地得到了自己想要的準確答案。消費者也是這么想的。《互聯網時代:用人工智能帶來卓越客戶體驗》(The Age of Intent: Using Artificial Intelligence to Deliver a Superior Customer Experience)是一本極好的新書,作者P·V·康南(與喬希·貝諾夫合著)在書中寫道:“虛擬助手和人類進行合作的最佳商業環節就是幫助客戶。機器人迅速而準確,人則感性而且有判斷力。結合兩者的優勢可以打造出完美的客戶服務。”

康南是圣何塞咨詢與軟件公司[24]7.ai首席執行官。在這本書中,他深入研究了幾十家公司使用AI來取悅新客戶并發展回頭客的情況,其中包括租車公司安飛士和旅游服務公司Xanterra。

讓機器人或其他虛擬客服代表處理常見問題,較難問題則轉給人工客服,這樣可以降低成本。衛星電視公司Dish Network稱,如果人工客服每分鐘能少接一些電話,該公司每年就能節省200萬美元。每年顧客會打進約600萬個電話,而虛擬客服代表每年都能為Dish Network節省“數千萬美元”的客戶關系管理預算。

但康南認為,遠比這重要的是,用AI來提高銷售和服務的速度及精度,并使之更為有趣的公司很快就能建立巨大的競爭優勢,這類似于20多年前率先使用互聯網的公司。

同時,《世界是平的》(The World Is Flat)一書作者托馬斯·弗里德曼在本書前言中寫道,智能機器將“改變非機器,也就是人的工作。人們需要更為感性并掌握更詳盡的知識……[而且]他們的工作將是調整虛擬客服代表,以便它們變得更聰明。”

《互聯網時代》這本書很有趣,其間點綴了一些AI體驗出現偏差的警示性事例。它一字不差地復述了另一位作者喬希·貝諾夫和Expedia聊天機器人的一長串對話,內容非常滑稽而且沒有任何成效。暴跳如雷的貝諾夫最后打出的一句話是:“你可真傻。”機器的回應則是重復了它已經問了兩遍的愚蠢問題。

不過,《互聯網時代》的大多數內容都集中在迄今為止哪些奏效及其奏效的原因上。讓我們再回到Dish Network,該公司的DiVA系統可以回答常規問題,并且把更復雜的問題留下來,從而幫助人工客服更好、更快地工作。康南指出:“就算DiVA將對話轉給客服,它也會在后臺繼續運行,它會告訴客服出現了什么情況,它認為顧客的問題在哪里以及幫助顧客的最佳途徑是什么。”康南還說,這樣的合作會讓客服人員感到高興,因為機器去除了工作中乏味的部分,并讓他們把自身技能用于“更需要一些關心和共情”的任務上。

世界上其他讓AI和人工客服合作的公司都有類似于DiVA的系統。比如,荷蘭皇家航空公司的算法已經可以識別約60萬次客戶電話咨詢中的字眼和詞匯。系統會持續實時地學習這些互動內容,并篩選海量內部數據,然后為人工客服提供建議,后者則能迅速運用相關知識解答客戶疑問。

此類團隊協作“需要一個足夠聰明的系統來連接公司的所有數據庫,包括在周末和假期回答問題的數據庫。然后擴大其規模以滿足需求,并為人工客服提供支持。”《互聯網時代》全面地探討了其中涉及的復雜因素,不光是建立恰當的基礎設施等科技細節,還有讓人類成員投入工作所需要的條件。

比如,考慮到最近的那些自動化取代人工的炒作(大多都是夸張,但這是另一個問題),你如何說服人工客服接受甚至歡迎機器提出的建議?關鍵的一點是要從現在就開始強調智能系統的作用是協助人類,而不是取代人類。

同時,康南建議“謹慎處理內部關系”。很顯然,公司的首席技術官和客服(有時是銷售)部門負責人必須參與進來。但也別忘了產品開發主管、首席營銷官、首席運營官以及人力資源主管,你不可避免地會以這樣或那樣的方式觸及他們的領域。康南寫道,廚房里有了如此之多的廚師之后,“就會有許多可能說不的人”。但“除非他們都支持這個決定,否則就不大可能取得進展”。

準備向前邁進的企業或許得注意連鎖餐廳TGI Fridays的經驗帶來的三點啟示。千禧一代不像他們的父母那么傾向于在休閑餐廳里吃飯,為了吸引他們,這家公司開發了AI輔助系統,把對社交媒體友好的聊天機器人打造成了明星,此舉使其外賣訂單在短短一年時間里增長了一倍,達到1.5億美元左右。

首先,Fridays從自己的一小部分業務著手,具體來說是為了節省時間而預先點菜的顧客,然后在推廣這個系統前糾正了其中的所有錯誤。其次,康南引用該公司負責此項工作的高管謝里夫·米特雅斯的話說:在這個過程中“要徹底衡量所有東西”,以便判斷你的系統是否帶來了你和顧客想要的結果。

第三,著手這些工作時對上述結果要有清晰的預期。康南寫道,TGI Fridays在推廣AI方面取得成果的一大原因是它“沒有脫離自己的目標。只要選對了要解決的問題,你就開始走向成功了”。(財富中文網)

譯者:Charlie

審校:夏林

Remember last Thanksgiving, when your Uncle George insisted on deep-frying the turkey—and then had to ask Alexa to call the Butterball Turkey Talk-Line for help? If the trouble was complicated, and especially if George sounded panicky, he probably reached a real person, like knowledgeable longtime Butterball employee Marge Klindera. On the other hand, with a quick and easy problem, a complex system of algorithms might have connected him instead to a recording of Marge's voice, programmed to recognize and respond to hundreds of common turkey-related phrases.

Chances are, George didn't know (or care) which was speaking to him, as long as he got exactly what he was after, fast and hassle-free. That's what customers want, too. "There's no part of business where virtual agents and humans can work together better than in helping customers," writes P.V. Kannan in a fascinating new book, The Age of Intent: Using Artificial Intelligence to Deliver a Superior Customer Experience (with Josh Bernoff). "Bots are fast and accurate. People are empathetic and have judgment. Together they've got what it takes to deliver the best customer service possible," he writes.

In these pages, Kannan, who is CEO of San Jose-based consulting and software firm [24]7.ai, delves into how dozens of companies, from Avis to Xantera, are using artificial intelligence to delight new customers and keep old ones coming back.

Letting bots or other virtual customer service representatives (CSRs) handle routine queries, while directing trickier challenges to humans, can cut costs. Dish Network says that for every minute, on average, it can shave off customer phone calls with humans, the company can save $2 million per year. Customers initiate about 6 million chats per year, and the virtual CSRs slash "tens of millions of dollars" annually from Dish's CRM budget.

But the far larger point is that companies that deploy A.I. to make sales and service quicker, more accurate, and more fun will soon lay claim to the same kind of huge competitive advantage that early adopters of the Internet enjoyed 20-odd years ago, according to Kannan.

At the same time, smart machines will "change the work of non-machines—also known as 'human beings,'" writes The World Is Flat author Thomas Friedman in this book's foreword. "They will need more empathy and more granular knowledge... [and] their job will be to tweak the virtual agents to make them smarter."

The Age of Intent is fun to read, sprinkled with cautionary tales of A.I. experiments gone awry. A hilarious verbatim transcript of a long, fruitless online dialogue between co-author Josh Bernoff and a chatbot on Expedia ends with an exasperated Bernoff typing, "You're pretty stupid." The bot responds by repeating the same inane question it had already asked twice.

Most of the The Age of Intent, though, focuses on what's working well so far, and why. To go back to Dish Network for a moment, consider how the company's DiVA system, which culls routine queries from thornier ones, helps human customer service agents do their jobs better and faster. "Even after DiVA kicks a chat out to an agent, it continues running in the background," Kannan writes, "where it shares with the agent what already happened, what it believes the customer's problem is, and what might be the best way to help her." The collaboration makes the human reps happier, he adds, because it takes the drudgery out of the job and lets them put their skills to work on the tasks that "require a bit more care and empathy."

DiVA is similar to systems at other companies around the world where A.I. is collaborating with human CSRs. At KLM Royal Dutch Airlines, for instance, algorithms have been programmed to recognize words and phrases from about 60,000 customer chats. Constantly learning from those interactions in real time, while also sifting through oceans of internal data, the system then offers suggestions to the human agent, who can quickly apply the relevant knowledge to the customer's question.

That kind of teamwork "demands a system smart enough to connect to all the company's databases, one that answers questions on weekends and holidays, scales up to meet demand, and supports human agents," Kannan notes. As you'd expect, building that capability is no day at the beach. The Age of Intent takes a thoughtful look at the complexities involved — not only the technical nuts and bolts, like putting the right digital infrastructure in place, but doing what it takes to get the human side humming along too.

How, for example, do you persuade your human CSRs to start taking, and even welcoming, advice from machines? Thanks to all the recent hype about automation taking people's jobs (mostly exaggerated, but that's another story), it's essential to stress from the outset that smart systems are intended to assist human agents, not replace them.

Meanwhile, Kannan suggests, "Navigate politics carefully." It's pretty obvious that a company's CIO and customer-service (and sometimes sales) leaders will have to be on board. But don't overlook the head of product development, the CMO, the COO, and the chief of human resources, all of whose turfs will be trod upon in one way or another. With so many cooks in the kitchen, "there are many potential people who can say no," Kannan writes. But "unless they're all allied behind the decision, it's unlikely to get off the ground."

Businesses ready to forge ahead might bear in mind three insights from restaurant chain TGI Fridays' experience. Aiming to appeal to millennials, who are less inclined to linger in casual-dining eateries than their parents were, the company developed an A.I.-assisted system, starring social-media-friendly chatbots, that doubled its off-premises orders in a single year, to about $150 million annually.

Fridays did this by, first, starting with a relatively small part of its business—people looking to save time by ordering in advance—and working out any bugs before expanding the system. Second, Kannan quotes Sherif Mityas, the Fridays executive who spearheaded the effort: "Measure the hell out of everything" along the way, to see whether your system is producing the results you and your customers want.

And third, go in with a clear idea of what those results would look like. A big reason why TGI Fridays' A.I. push has paid off is that the company "didn't lose track of what they were trying to accomplish," Kannan writes. "Once you've chosen the right problem to solve, you'll be in a position to start succeeding."

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