The Chicken Littles of Artificial Intelligence

CNNMoney, citing a PwC report, declared that 38 percent of USA jobs will be lost due to robots and artificial intelligence over the coming 15 years.  Jobs that perform routine, repetitive tasks and are in industries include manufacturing, banking, education, retail and hospitality.  The same warning bells are being rung by The Economist, New York Times, The Guardian and others.   The World Economic Forum cites a “net loss of over 5 million jobs by 2020 in 15 major developed and emerging economies.” The mainstream media headlines around automation related job loss are akin to Chicken Little’s warning that the sky was falling. The sensationalism overstates reality. The impression is that job loss due to automation is a recent phenomenon. It’s not. The ATM was created in 1967 and has taken over 30 years to evolve into what we take for granted today. Did it significantly reduce bank teller jobs?  Yes, over a long period of time. But it did not eliminate the position; it evolved. There are countless examples of how technology has changed economies, professions and industries.  This has been going long before the steam engine and electricity was invented. The pace of technological change today is, however, increasingly faster.  PwC’s 15 years forecast for job loss is challenging to believe when we look at the reality of what it takes to implement artificial intelligence. Spoiler alert - our ability to forecast the timing of future events with a measurable degree of accuracy isn’t particularly good. Rurik Bradbury, Head of Research at LivePerson, a mobile and online messaging company, has a different perspective. “The prospect of replacing entire jobs with just technology is unlikely,” shares Bradbury. “There is a lot of confusion about AI with more talk than actual deployment.” Today’s artificial intelligence technologies are capable of performing tasks at the atomic level. These are very narrowly defined tasks that operate within a clearly defined set of responses. Based on LivePerson’s customer experience, Bradbury strongly believes that AI can perform, on average, 40 percent of the tasks comprising customer care jobs.  In other words, AI driving the level of unemployment forecasted by CNN within the next 15 to 20 years is unlikely. Even if we just focus on customer care jobs across all industries. Here’s why. Jobs are comprised of a multitude of tasks as well as a wide range of problem solving situations that require lateral thinking and complex, emotion-based human interactions. Bringing in AI to a customer support position, for example, requires the job to be broken down into its detailed components. On average approximately 40 to 50 percent of tasks in a call center are good candidates for automation. These are tasks that a call center agent or manager can trigger – updating your address, for example. The dialog between the AI and the customer is controlled by how the AI application is programmed and closely measured with human oversight.  AI does not run without tight controls in place.  The analytics include sentiment analysis that tells management which AI-conducted customer interactions were positive or negative.  Negative interactions can result in shifting that task back to a human or reprogramming the AI software. AI doesn’t replace workers; it augments their ability to be more effective and productive. That doesn’t mean that the nature of work will not change, it will. The operative word is augmented – Bradbury calls it “job sharing.” Routine, data-driven, narrowly defined subtasks will be automated freeing the human worker to engage in higher level, most sophisticated tasks such as creative problem solving, strategic thinking and relationship building.   The latter being things humans are much better suited for. Based on Bradbury’s research and LivePerson customers’ experience, the rate of AI taking over human tasks is slower than popular media would lead you to believe. First, to effectively employ AI to drive a positive, productive customer experience requires a clear plan based on gradual automation over time.  Secondly, the current rate of automating tasks is one percent a year. In the case of the 40 percent of call center agent tasks that could be candidates for automation, companies would be extremely hard pressed to achieve that level of automation within ten to fifteen years. So much for predictions. That doesn’t mean ignore artificial intelligence. Approach it with a solid plan based on best practices.  Here are a few of Bradbury’s suggestions:

  1. Collect a data set of good (read: successful) customer interactions and categorize them, identifying the most frequent interactions.
  2. Pick candidates for automation based on opportunities to improve the interaction. Start with a very small group of interactions to experiment with.
  3. Take a subset of these identified interactions and create a chatbot or AI interface that is specific to the atomic task being automated. The more granular the definition and automation of the task, the higher the success. 70 percent of current AI tasks fail because they are too general.
  4. Put the AI task into production aside a team of call center agents and test. That means collect data, perform A/B testing, and analyze the conversations and their outcomes. Evolve the AI software over time based on the results of the analysis.
  5. As success is realized, automate additional tasks based on the same testing and analysis approach. Set performance thresholds for each AI task. Keep in mind that AI applications work in tandem with employees and need to be orchestrated are part of a company’s ecosystem.
How we look at technology directly influences how we fit it into our lives.  Don’t think of artificial intelligence as a separate project or technology. Think of it as part of a job and measure it accordingly. Ignore the chicken littles. Leverage AI where it enhances the customer experience and delivers measurable value add. Start small, get granular, and go slow.

What’s an Airbnb Host’s Worst Nightmare?

A bad review.
Here is a story that outlines some common mishaps that can occur when communication breaks down between a host and a guest, and a simple solution that can change the outcome for the better.

A Common Scenario

Gary, a recently retired professor, is excited about his upcoming travel and his first Airbnb! After booking his reservation, Gary isn’t sure the reservation is confirmed since Huey, the Host, never sent him a confirmation email or thanked him for the booking. Nonetheless, Gary isn’t too bothered and looks forward to his travels.

The Arrival
Travel day is here and Gary finally arrives to his Airbnb destination. He seems a bit confused seeing many parking spaces and tries to remember if Huey ever provided parking details. Gary sees a few empty spots in the parking lot and decides to park in one of them. As Gary begins to remove the luggage from his car, a neighbor approaches him. The neighbor explains that Gary has parked in his parking space. Slightly irritated, but trying not to let it spoil his trip, Gary puts the luggage back in his car and drives to a different parking spot.

The Keys
Standing in front of the home, Gary rings the doorbell. After waiting a few minutes, he looks around to see if Huey may have left the keys in a lockbox or maybe inside the planter. No lockbox, no keys. Gary decides to call Huey, but there is no answer. Gary is now beginning to get anxious and kicks the front doormat in frustration, when he happens upon the door key which had been hidden beneath it. Gary uses the key to enter the home.

The Internet

Gary is a tired from his travel thus far and hopes the remainder of his stay goes more smoothly. The home looks nice and Gary is excited to email his friends back home to tell them about his Airbnb adventure thus far. Gary turns on his computer but can’t seem to connect to the internet. There are multiple Wifi signals available, but all require a password to gain access. He looks around the room for instructions but can’t find anything. It occurs to him that maybe the passcode is on the bottom side of the internet router. No such luck! Gary gives up and goes to the kitchen for a glass of water. There on the refrigerator door, on a small sticky, he sees the words “Wifi Passcode”.

The Departure

During the morning of Gary’s departure, he sips his coffee while reading the newspaper, when the front door opens. A group of people enter with a mop, a broom, and a vacuum cleaner in hand. The cleaning crew has arrived and wants to clean the home and prepare it for the next guest. Annoyed and embarrassed, Gary makes his way to the bedroom to change out of his pajamas.

You can’t help but feel bad for Gary and can only imagine the type of review he will be leaving for Huey.

A Better Way
Now, let’s rewind and imagine an entirely different scenario. One where Gary receives a Confirmation message from Huey minutes after booking his reservation. Then, 24 hours before his scheduled arrival, Gary receives a Check-In message with very specific instructions about parking, where to find the house keys, the Wifi passcode and other pertinent details he will need to make his stay a more enjoyable one.

In this scenario, things go so well for Gary and he truly enjoys the start to his retirement, that he actually wishes he could stay longer. Coincidentally, Gary hears the Airbnb app chime from his phone. Gary pulls out his phone to see a message waiting for him from Huey. The message informs Gary of a vacancy after his scheduled departure, and Huey provided an offer should Gary choose to extend his stay. Gary is pleasantly surprised and decides to extend his trip for two additional days.

The day before his updated departure date, Gary receives a very nice email from Huey reminding him of the Check-Out time and informing him of the Check-Out instructions. Gary has truly enjoyed his first Airbnb experience and looks forward to writing an excellent 5-star review for Huey.

Automate and Simplify
In the latter scenario, Huey has added message automation software to his arsenal of tools. Message automation software allows Huey to create personalized messages that include all of the important details that his guests may need. The messages are delivered into the Airbnb message thread on a pre-set schedule for Gary and all of Huey’s future guests so he will never have guest communication issues again. Riding this wave of the short-term rental market, the host who is most prepared will be the one who delivers the happiest guests. And a happy guest translates into a 5-star review, which means a higher listing ranking and more bookings.

I was inspired to write this story after recently renting an Airbnb from a super host that used a new piece of software to communicate with me. That software was Aviva IQ, a Silicon Valley startup. Necessity remains the mother of invention, the founders developed the SaaS based application out of their frustration in delivering a streamlined communication process that didn’t require immense levels of manual work. Aviva IQ allows Hosts to automate their Airbnb messages so important details about the reservation can trickle out over time, at the optimal time. For the guest, it means having a consistent and enjoyable experience. Their focus is on their trip and less on the details and concerns about rental logistics.

Everyone gets a good night sleep.

First published in HuffingtonPost

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