In June 2015, the Japanese company SoftBank Robotics Corp. released a product named Pepper, which sold out in a mere 1 minute. What’s so special about Pepper? Pepper is a robot, standing about four feet tall, who can read and process a range of human emotions, in order to understand and communicate with people. Pepper can “feel” relaxed, anxious, happy, scared and much more. Because Pepper is connected to a cloud-based system, and utilizes machine learning, each Pepper robot will gradually become more adept at social engagement, and learn from the collective range of interactions, of all of his counterparts.
At first glance, Pepper might appear to be little more than a charming novelty. Yet, SoftBank’s invention is an early act in a long-heralded technological revolution, which will transform our world forever. In the coming years, an ever-growing array of socially and emotionally intelligent robots will take on a wide range of customer-facing functions, allowing businesses, governments, and nonprofit organizations, to deliver more effective services, to a greater range of people, at a much lower cost.
Developing software which replicates human behavioral patterns and interaction, is hardly a new goal. After all, Alan Turing’s eponymous Turing Test dates back to 1950. In the decades since the publication of his visionary paper “Computing Machinery and Intelligence” we’ve inched closer and closer to meeting his bar for artificial intelligence (AI), that is, a machine which is humanesque enough that, during a normal conversation (written, rather than verbal), the average person can’t tell whether he or she is interacting with a live human being, or a robot.
In just the past 7 years, we’ve witnessed the rise of Siri on the iOS platform, watched Google’s AlphaGo beat the world’ greatest Go player, and been awed as IBM’s Watson defeated some of the most skilled Jeopardy contestants of all time. Deep-learning based image recognition and language translation programs have improved at a remarkable pace, while self-driving cars inch closer and closer to actual market implementation.
The trend is clear. Software-based machines, utilizing the power of artificial intelligence, deep learning, and machine learning, can learn to perform a growing array of tasks, often, better than humans can. This trend will become only more pronounced over time.
Most of the examples offered above, however, don’t require much in the way of social or emotional intelligence. After all, a robot playing Go, or competing in Jeopardy, needn’t form a meaningful personal connection, with either an audience, or users. Yet, for smart robots to realize their full potential, they will need to do just that; that is, understand human communication styles, conversations, and emotional states, and engage accordingly.
At this very moment, teams of determined technologists are working to achieve this goal. Companies such as Affectiva, a spinoff of the M.I.T. Media Lab, have developed software to identify and understand (at a deep level) people’s emotional states, largely by analyzing facial expressions. Affectiva’s tools have applications ranging from empowering individuals with autism, to more intelligent advertising, and smarter videoconferencing. As Affectiva collects and learns from more and more human emotional data, the company’s products will become increasingly effective.
Of course, much of today’s communication isn’t done in person, or by video, but rather, on the phone. This is particularly true in sales and customer service. Cogito, another child of the M.I.T. Media Lab, has developed software to guide phone-based customer support employees in providing more effective customer support. Cogito does this by tracking the speed of conversations, pauses, tone, interruptions and more, and providing feedback, based on comparison to typical conversations within various situations and industries.
Cogito is currently working with cadets at West Point to improve negotiation skills, and with employees at Aetna and BlueCross to reduce customer call time, as well as callbacks. What’s particularly fascinating about Cogito, is that it combines both qualitative and quantitative data, to allow for rapid improvement and feedback.
Firms like Cogito and Affectiva are taking hold at a time when chatbots, basically, messaging tools which communicate with humans through the use of artificial intelligence and natural language processing, are growing in popularity. Chatbots are still in a relatively early stage of implementation, but are being used by major companies like Bank of America ,H&M and Whole Foods, to engage with customers more effectively. At the same time, a variety of independent chatbot platforms have started to take root, ranging from personal assistants to customer support tools. Each of these devices has the potential to both complement, and in some cases supplant, human involvement.
Taken in aggregate, we can sketch out a roadmap of where these technological advancements might lead us. Innovations offered by firms like Affectiva and Cogito, have allowed software to gain a deeper understanding of human emotional states, and communication styles. Right now, many of these insights are utilized to guide humans towards more effective communication; such as the use of Affectiva’s software by advertising executives, or Cogito’s implementation at West Point.
Eventually, however, the knowledge contained in these tools might be integrated directly into various devices. Imagine a digital chatbot, or perhaps a video or voice-enabled robot, which is equipped with the sort of understanding of conversational dynamics offered by Cogito, paired with the emotional intelligence by Affectiva, and other insights from neuroscience, psychology, and other disciplines. What’s more, what if this chatbot can become progressively more intelligent, by engaging in the sort of deep learning that’s increasingly driving so much of today’s most impactful innovations? How might we utilize such an innovation?
Simply put, we would see a transformation in service-focused operations, whether at multibillion dollar public corporations, startups, nonprofits, and everything in between.
Let’s consider large firms with a substantial customer service component, such as banks, credit card companies, and wireless service providers. If they were able to shift over to a robot-based approach, the need for a large (human) support staff will be eliminated. A robot could perform much of the work of humans, at a mere fraction of the cost. What’s more, thanks to techniques like machine learning, over a certain period of time, these robots will become increasingly effective at serving customers. Soon enough, customer service will become less of a cost center, as companies use humans for only the most complex cases. As noted earlier, these developments are already taking place at financial institutions, and will surely be adopted elsewhere, in the near future.
For startups and nonprofits, focused on solving big problems, the potential impact is even greater. Picture a small educational technology company, seeking to solve a complex problem, say, helping students become more skilled at math. What if such a company were to create a robot, similar in functionality to those we considered earlier, which provides students with individualized instruction and feedback? A student might work through a math problem at home, displaying his or her work for review by a robot, which could then offer a range of valuable guidance, tailored to her or his specific learning style, and curricular needs. Just as with customer service robots, these robots would grow smarter, and more effective, over time.
Utilizing this approach, an intrepid educational technology company, made up of a relatively small staff, could eventually reach millions of students, and at least partially alleviate gaps in educational outcomes, due to parental income and education levels, as well as teacher quality, all factors which hold back so many students. This certainly isn’t a replacement for effective, engaged public education, or parental involvement, but it can serve as a highly useful, necessary supplement.
For nonprofits and government, robots can help make some rather scarce services, considerably more accessible. Legal aid is a good example. Today, the vast majority of defendants in certain types of civil court matters, such as debt collection and housing rights, are not represented by an attorney. This is largely due to a combination of defendants having lower incomes, while legal services organizations face a lack of funding.
With a chat robot, an unrepresented litigant could ask questions, and analyze and understand documents, as well as the broader legal process, surrounding his or her case. This robot would respond with individualized guidance, helping to simplify and level the legal playing field, at a relatively low cost. Such tools are already being utilized to assist criminal defendants in the UK. It is worth noting, however, rules around unauthorized practice of law would have to be reconciled with robot-based legal assistance.
It’s easy to imagine similar applications, across a variety of other governmental and nonprofit arenas. Everything from tax preparation and construction permits, to social services and healthcare, could be made more transparent and accessible, with the rise of chatbots and similar interfaces.
We can’t overlook the reality that robots have not yet surpassed raw human intelligence (though some experts do expect them to do so within the next 100 years). Neither have robots achieved human levels of emotional intelligence (though experts in the field, most notably Google’s resident futurist, Ray Kurzweil, believe this will happen before 2030). The best robot-focused service models, particularly today, as we await further advancements, will also require humans, to step in where robots fall short. Therefore, the robot revolution will be a fast-moving, yet evolutionary process.
Some might raise another objection: user adoption. That is, will those being asked to interact with robots (say, a customer of a bank, or a client of a legal aid organization), be comfortable with and open to working with some sort of robot? After all, this is a novel means of interaction. Yet, the history of technology shows us that humans will eventually alter a range of behaviors, when presented with a better option. People once used to travel by buggy and ship, but eventually chose the convenience of cars and airplanes. More recently, we shifted from using typewriters to personal computers, while searching for information and communicating online, sharing a range of information on Facebook and Twitter, and messaging each other on our mobile phones. For comfort, convenience, and savings, people are willing to alter their conduct.
Ultimately, for those young businesses with a substantial service component, smart robots will allow them to grow and scale more quickly, which would be more challenging if forced to hire lots of human representatives. For larger companies, whose profits are often under pressure, and in a time when corporate lifespans are decreasing, a notable cost center is reduced. Of course, for firms of all sizes, in the era of the social media and online reviews, where reputations are increasingly transparent, effective efficient robot-based service will only bolster goodwill for the purchasing public.
Nonprofits and governmental organizations, who must often grapple with uncertain funding, along with an ever-present demand for their services, robots will help them to serve more of those who are most in need, also at a lower cost. The societal effects of this increased access to vital services, can only be positive.
A range of smart robots are going to change our lives immeasurably. Get in, buckle up, and really, enjoy the ride.
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