Determining a job candidate’s potential for success is a difficult task. In the past, hiring managers looked to people’s intelligence quotient (IQ) to gauge whether they would bring value to their organizations. Now, however, emotional intelligence (EQ) is seen as an increasingly relevant predictor for success.

The post Emotional Intelligence is the Key to a Successful Company Culture appeared first on Artificial Intelligence.

Emotional intelligence is an essential skill in the customer service functions with the productivity and efficiency of the role is directly tied to the quality of conversations. The personal dynamics of emotionally cognisant customer service agents play an important role in empathetically resolving any queries or concerns, impacting customer churn and increasing brand loyalty by leaving customers with a positive impression of an organisation.

However, rapid adoption of automation technology within customer-facing roles presents new challenges to organisations that want to harness its benefits, without impacting the service that it delivers to its customers.

A hybrid workforce

Already helping many companies increase customer service availability, reduce wait times and improve resolution rates, Gartner has predicted that a quarter of all customer service operations will use artificial intelligence (AI)-powered virtual assistants by 2020. In many organisations, this has resulted in the creation of a hybrid workforce of human and digital agents.

While some organisations are still using basic chatbots, businesses that prioritise giving high quality customer service are opting for more sophisticated digital colleagues, that can respond to more complex and nuanced requests. In addition to handling simple customer queries directly, they can also act as a whisper agent to human customer service representatives to help them provide faster and more accurate responses. For instance, at insurance firm Allstate, virtual colleague Amelia has collaborated with live agents on more than three million calls. Employees are able to access her knowledge to augment their own.

A common view of emotional intelligence

However, as digital colleagues play a greater role in customer-facing workplaces, a key challenge for businesses is to ensure that both human and digital agents are delivering the same emotionally cognisant service. While the leading digital colleagues can understand and react to customers’ emotional state, how can this be productively combined with human experience and intelligence to deliver a truly superior and consistent service?

To establish a common view between digital and human colleagues on emotional intelligence, we should consider how the symbiotic relationship can support the five components of emotional intelligence, as outlined by psychologist Daniel Goleman.

Self-awareness, self-regulation, motivation, empathy and social skills: these five original components of Goleman’s theory help us create a blueprint for emotional intelligence within the hybrid workforce. While human and digital agents don’t all excel in the same areas, it does show us the opportunity for augmenting human experience and expertise with AI, without losing the “human touch”.

So, how do the five components apply to hybrid customer services?

Self-awareness and self-regulation

When dealing with customers, it’s important to be aware of your own emotional state and how it will impact your actions. This is tough for human agents – especially when dealing with particularly frustrating or aggressive customers.

Working in symbiosis, digital colleagues can assist human agents in these situations by acting as a whisper agent. The intelligent system records and analyses the reactions to all responses previously given by customer service agents, enabling it to consider the emotional aspect of the dialogue when suggesting what the best response is for that customer in the given situation.

For instance, when working on a cancellation line, where the majority of interactions are negative, it can be tough for human agents to keep their cool. However, you’re less likely to get an emotional outburst from AI, because rules dictate how they act when seeing certain behaviour or emotions. This doesn’t make digital colleagues alone the best agent to deal with cancellations, as there is no opportunity for reconciliation and already-frustrated customers may feel fobbed off. However, they can provide the human agents the responses that best serve the customers’ emotional state, while helping them self-regulate their response.

 Motivation

As times have changed, the motivation for customer service roles has shifted from merely churning through calls as quickly as possible, to increasing the value of interactions and making sure that each has a positive outcome. While this is a welcome shift for customers, being engaging and personable for hours on end can be exhausting for customer service representatives, leading to lapses in concentration and less than ideal outcomes for customers.

A digital colleague is also focused on achieving the outcome and a positive emotional state for the customer when directly handling interactions, but, given its digital nature, doesn’t care if it spends five minutes or five hours handling one query and can scale to any number of conversations.

Even when working as a whisper agent, the digital colleague helps balance both the organisation’s need for a high amount of resolved queries and deliver a better service and outcome, as it is able to provide the agent with the best response and most relevant information in real time. This helps the agent provide that superior service at the high rate of resolution often welcomed in customer service roles.

Empathy

Having a customer service agent empathise with our issue and show dedication to resolving it is a key component of delivering emotionally cognisant engagements. Empathy is a key life skill for humans, however, it has been much harder for digital agents to authentically be empathetic, show listening skills and understanding.

Even when tracking and responding to a person’s emotional state, digital agents could still sound cold and robotic when using empathetic language. So, digital colleagues need an additional aspect of self-awareness, which recognises conversations that require empathy and sympathy, so they can pass them on to a human agent.

Social skills

That said, in their role as whisper agent, digital colleagues can help human customer service representatives build better relationships. Using their analysis of the emotional state and previous interactions, they can advise agents on how to best engage with any customer.

Augment the potential of customer services

The post 5 components of emotional intelligence in a human-AI customer service appeared first on Artificial Intelligence.

MIT has launched a new project, the MIT Intelligence Quest, whose aim is to “advance the science and engineering of both human and machine intelligence.”

The goal of this project is to discover the foundations of human intelligence, and how this knowledge can be applied to the burgeoning science and technology of Artificial Intelligence.

The idea of Artificial Intelligence as “the simulation of human intelligence as processed by machines,” is an idea that has been stored in the collective consciousness of humanity since time immemorial. One needs to look no further than mythology to see how Artificial Intelligence can run the ethical gamut from sinister to benign.

Thus, Artificial Intelligence, the ability to give mind to matter, is ingrained in the human psyche.  The problem arises when asking: how can humans stay relevant in an automated world?

According to Andrew Coleman’s A Dictionary of Psychology (2008), emotional intelligence is defined as, “the capability of individuals to recognize their own emotions and those of others, discern between different feelings and label them appropriately, use emotional information to guide thinking and behavior, and manage and/or adjust emotions to adapt to environments or achieve one’s goal(s).”  It is measured most often using the EQ-i 2.0 test, which measures trait emotional intelligence.

Currently, emotional intelligence separates us from the machines.  Customer service is an example of the type of job that AI might not be able to perform as well as humans. There are three types of situations in customer service where emotional intelligence is a requirement for a successful outcome: dealing with anger and impatience, dealing with disappointment and frustration, or dealing with surprise, happiness, and gratitude.

The rise of AI makes emotional intelligence that much more important in humans. In the future, AI already fills roles that require traditional intelligence.  In the future, many of these jobs could become obsolete for humans. Humankind will have to adapt its skills to stay relevant in a changing society.

In the future, for example, robots and computers could potentially replace all the tasks that a doctor performs. Machines could perform data collecting and analyses of diseases, as well as actual operations.

Among the things that a robot will not be able to replace in the near or distant future, however, is bedside manner. Skills such as persuasion, empathy, and understanding that will become highly valued over all other skills in the future.  These skills are highly undertrained and undervalued in today’s world, but with the rise of AI, they will become the most prized.

What humans can offer to the world that machines cannot is the ability to relate to the people around us. Machines will have to learn how to develop their capacity to understand others as well as grow their ability for compassion and empathy in order to be on the level of humans.

This may be the only way humans can stay relevant in the workforce, as computational skills and number crunching could be completely automated down the line.

Perhaps somewhere in the future, we will develop an AI that can relate to humans emotionally. Until then, we will have to nurture and train humans to highly value emotional intelligence, where previously, it has been underestimated as a trait in the workforce.

The post Artificial vs Emotional Intelligence in Machine Learning appeared first on Artificial Intelligence.

Call centers have been around since the 1960s, gaining mainstream attention when employees were seen wearing telephone headsets on televised NASA Mission Control Center events. Since then, customer service centers have been typically regarded as a necessary evil, where customers have encountered their fair share of unhelpful calls.

Despite many companies’ attempts to nudge customers toward unassisted channels, consumers still pick up the phone when they need service—especially in the finance and insurance industries, where people are dealing with complex issues such as loan refinancing, health requests and insurance claims. Forrester confirms that the phone is still the most widely used customer-service channel, with 73 percent of consumers phoning in for live interactions.

Call center interactions influence brand perception and loyalty. They serve as a critical moment of truth in a customer relationship with a lasting impact on the decision to purchase or abandon ship.

New technologies such as artificial intelligence, machine learning, and voice analytics are paving the way for brands to increase employee engagement and improve the customer experience. They can improve rapport between customers and agents and provide supervisors with reliable, comprehensive and real-time insight into the voice of the customer.

The Power of AI

AI powered voice technology is being deployed today in call centers to augment the intelligence of agents and improve their performance. The latest voice capabilities have enabled organizations to provide in-call guidance for agents, helping them adjust their communication style to be more confident, empathetic and responsive. AI within voice applications is disrupting sales and service operations and improving the interaction between brands and customers.

Increasing Emotional Intelligence

In the call center, there is no replacement for human compassion, empathy and understanding. Traditional call center technology, best practices and training techniques have helped agents become proficient in following policies and capturing data, but the current tools and techniques are not enough to keep pace with customers demanding a high touch and personalized experience. Call centers are still not keeping pace with customer expectations and employees continue to churn despite massive corporate investment.

This is because companies have not found a way to measure and improve empathy and rapport at scale, or to train agents how to deal more effectively with challenging emotional situations. Existing investments have yet to deliver a real-time and actionable view into the customer’s perception, resulting in delayed insight and generic treatments.

Emotional intelligence is defined as the capacity to be aware of, control, and express one’s emotions and to handle interpersonal relationships judiciously and empathetically. Now, technology can sense behavioral signals and emotions, provide live guidance, measure impact and provide feedback into the system to fuel continuous machine learning. If a customer is nervous, tense or in need of empathy, the system nudges the agent with simple informative notifications. If an agent speaks too quickly, responds slowly, appears as if they have low energy, talks over the customer or introduces awkward pauses into a conversation, the software guides the agent to adjust their behavior.

Improving Performance with Analytics

Analyzing behavioral signals through voice offers a real-time way to improve agent soft skills and instantly measure the impact of their behavior on customers. Prior to these analytics, it was nearly impossible to improve how an agent engaged a customer, and it was unclear how to link the agent’s behavior to the impact it had on the customer’s perception of a business.

The Net Promoter Score is an example of a traditional measurement that provides a broad view of the performance of a company and customer service as a whole. The Humana health care company has implemented AI to better understand and improve their customer service delivery. By deploying technology, they have seen a 14 percent improvement in NPS, a 5 percent improvement in issue resolution and a significant reduction in call handling time. Comprehensive and timely metrics on interaction success and customer experience directly lead to increased customer loyalty and a healthier bottom line.

Conversations between customers and call center agents are at the heart of every customer-brand relationship. Good conversations forge a bond, establish trust, and result in increased loyalty, while bad conversations tarnish brand perception and lead to customer churn.

Leveraging AI to understand and improve phone calls can result in enhanced customer loyalty, increased employee engagement and improved operational effectiveness.

The post When Artificial Intelligence Disrupts the Call Center appeared first on Artificial Intelligence.

Emotional intelligence (EQ) — the ability to pick up on what other people are feeling or thinking, primarily using body language and tone of voice — is a difficult endeavor, even for some humans. When a human misreads their fellow human, they could lose a friendship, a relationship, a job. Stakes are even higher for bots — if their makers can’t teach them empathy, they could cease to exist.

Naveen Joshi, the founder and CEO of enterprise development company Allerin, recently wrote about how EQ will make all the difference in whether AI becomes more widely used by society. “Even the most sophisticated AI technologies lack essential factors like emotional intelligence and the ability to contextualize information like human beings,” he wrote, nailing the basic stumbling block.

Bots like Alexa don’t actually know us. They don’t know how we’re feeling, or what we are thinking. They can’t pick up on the unspoken gestures and frowns. They lack even basic empathy, essentially communicating only in trivia and small talk.

The curious thing about this is that it’s not obvious. When we talk to Alexa, we tend to see the bot as another human, someone who lives inside a small speaker. The bot talks, it tells jokes. Part of the reason we don’t want to think too hard about EQ with bots is that there’s a bit of an “uncanny valley” for AI, that awkward gap where our minds essentially make up the difference between what is obviously a set of algorithms and something that seems more human. We bridge that gap mentally, but as bots evolve and get smarter and show more emotion, we’ll actually start questioning them more — we’ll start realizing they are not human.

The “uncanny valley” is a term used to describe what happens when we see a human avatar. It’s hard to bridge that divide — the more the avatar looks human, the more we start filling in gaps, until at some point we realize it is not human at all. That’s when things start falling apart.

Think of the most recent Final Fantasy movie, called Kingsglaive: Final Fantasy XV. At first, it’s astounding how much the digital actors look like humans. Then there’s a slight misalignment, or a facial twitch, or a squint that doesn’t look quite right. I never finished the movie because eventually I stopped believing it was real and I stopped caring about these digital actors.

This will happen with bots. First, we’ll stop seeing them as digital creations and start connecting to them emotionally. But they will always be subroutines on top of subroutines. At some point, we’ll stop bridging the gap between ourselves and Alexa or Cortana. This is where things will become the most interesting, because bot developers will have to figure out how to solve the massive problem of understanding you, the user. Are you sick? In a bad mood? Recently broken up with a boyfriend? Tired? If the bot doesn’t know how to read you, we won’t think of the bot as valuable. “Alexa, how is the weather?” works fine for now, but soon we will want a lot more.

This valley — the rising programmatic accomplishments mirrored by our eventual mistrust as bots seem more and more human — is the single greatest challenge AI developers face. That’s because humans can’t trust things that do not show empathy. It’s not possible. It goes against our nature. We don’t last long in a job, a friendship, or any relationship that is not built on trust and empathy. And we won’t rely more and more on a bot unless it seeks to understand us and demonstates that it “knows” us.

The worst part? We don’t know when this split will occur. For now, bots are mindless minions that do our bidding. Google Home is a sidekick that tells us NFL scores. But when we want to send a bot on an errand to pick up the kids in an autonomous car? When the bot will fill in for us in an interview? When we want a bot that cares for an elderly person? The AI of the not-so-distant future had better be ready to tackle more complex challenges than simply looking up the weather.

The post Why AI will need more emotional intelligence appeared first on Artificial Intelligence.

• 44% of contact centres have no intentions to introduce AI.
• 40% of contact centres agree that emotional intelligence is an area they need to explore.
• Emotional intelligence has been eagerly embraced by the contact centre industry.

You’ve no doubt heard about artificial intelligence making inroads into the contact centre, initially in the form of chatbots: AI-powered software applications that can take customer queries, either textual or verbal, and produce useful, relevant answers with consistency and accuracy that can match a human operator.

Depending on whose views you read, AI is either going to enhance the role of human operators, freeing them to handle the more challenging and rewarding queries, or it’s going to relegate them to the ranks of the unemployed.

SMAART Recruitment surveyed over 150 contact centre leaders and decision makers around Australia for its 2017 Contact Centre Leaders Survey. It reported: “Around seven percent of Australian contact centres currently use AI in their interactions with customers, with an additional 11 percent planning to introduce it in the coming 12 months. A high percentage of remaining contact centres are currently exploring the idea, however 44 percent of contact centres have no intentions to introduce AI.”

“Around seven percent of Australian contact centres currently use AI in their interactions with customers.”

You would not expect a recruitment company to be telegraphing mass reduction in employee numbers and a blog discussing the survey’s findings concluded: “Australian contact centres are taking a steady and careful approach to introducing artificial intelligence (AI) into their contact centres … AI presents contact centres with great opportunities and challenges in the coming years.

Those that learn from it and understand it quickly will be the first to benefit.”

However, SMAART Recruitment also focused on another kind of intelligence that will likely be much more challenging for technology to emulate and/or replace: emotional intelligence.

“Increasing staff emotional intelligence (EQ) is one of the key areas of focus for Australian contact centres.”

In another blog reporting additional results from the survey, it said: “Increasing staff emotional intelligence (EI) is one of the key areas of focus for Australian contact centres. In a recent study of contact centre managers and leaders, over 40 percent of respondents indicated that this was an area they needed to explore more and improve in the next 12 months.”

If you look at the definition of EI on Wikipedia, you will see why computer emulation of EI is challenging. It is defined as “the capability of individuals to recognise their own and other people’s emotions, discern between different feelings and label them appropriately, use emotional information to guide thinking and behaviour, and manage and/or adjust emotions to adapt to environments or achieve one’s goal(s).”

Wikipedia says the term first appeared in a 1964 paper by Michael Beldoch and gained popularity in the 1995 book by that title, written by author, psychologist, and science journalist Daniel Goleman.

It goes on to note that the concept has not been universally accepted. “Goleman’s 1995 analysis of EI has been criticised within the scientific community, despite prolific reports of its usefulness in the popular press.”

However there is no doubt EI has been eagerly embraced by the contact centre industry. A Google search will yield many results such as “Does Your Contact Center Lack Emotional Intelligence?”; “Is Your Contact Center Emotionally Intelligent?”,“Emotional Intelligence and Its Importance in the Call Center” and, intriguingly one that seems to be having a bet each way: “AI Can Help Boost Agents’ Emotional Intelligence.”

In our next post we’ll explore some of these ideas in more detail.

The post Contact centre intelligence: emotional or artificial? appeared first on Artificial Intelligence.