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Tamara Cibenko
Nelson Kunkel

These technologies are engaging you—a human driving a car—in human terms. Myriad technologies that detect physical states such as alertness are increasingly being used to infer emotional states such as happiness or sadness. Unlike their machine forebears that set rigid rules of engagement, these systems will follow rules, reading your mood, intuiting your needs, and responding in contextually and emotionally appropriate ways.

Welcome to the next stage of human-machine interaction, in which a growing class of AI-powered solutions—referred to as “affective computing” or “emotion AI”—is redefining the way we experience technology. These experiences are hardly confined to automobiles. Retailers are integrating AI-powered bots with customer segmentation and CRM systems to personalize customer interactions while at the same time capturing valuable lead-nurturing data.2 Apps are designing custom drinks and fragrances for fashion-show attendees based on emotional quotient (EQ) inputs.3 A global restaurant chain is tailoring its drive-through experiences based on changes in the weather.4 The list goes on.

As part of the emerging human experience platforms trend, during the next 18 to 24 months more companies will ramp up their responses to a growing demand for technology to better understand humans and to respond to us more appropriately. System users increasingly expect the technologies they rely on to provide a greater sense of connection—an expectation that should not be ignored. In a recent Deloitte Digital survey of 800 consumers, 60 percent of long-term customers use emotional language to describe their connection to favored brands; likewise, 62 percent of consumers feel they have a relationship with a brand. Trustworthiness (83 percent), integrity (79 percent), and honesty (77 percent) are the emotional factors that consumers feel most align with their favorite brands.5

Historically, computers have been unable to correlate events with human emotions or emotional factors. But that is changing as innovators add an EQ to technology’s IQ, at scale. Using data and human-centered design (HCD) techniques—and technologies currently being used in neurological research to better understand human needs—affective systems will be able to recognize a system user’s emotional state and the context behind it, and then respond appropriately.

Early trend participants recognize that the stakes are high. The ability to leverage emotionally intelligent platforms to recognize and use emotional data at scale will be one of the biggest, most important opportunities for companies going forward. Deloitte Digital research reveals that companies focusing on the human experience have been twice as likely to outperform their peers in revenue growth over a three-year period, with 17 times faster revenue growth than those who do not.6 Moreover, inaction could lead to more “experience debt”7 and user alienation as AI applications make us all feel a bit less human. Chances are, your competitors are already working toward this goal. Research and Markets projects that the size of the global affective computing market will grow from US$22 billion in 2019 to US$90 billion by 2024; this represents a compound annual growth rate of 32.3 percent.8

Time to get started. How will you create emotionally insightful human experiences for your customers, employees, and business partners?

Knowing me, knowing you

In Tech Trends 2019, we examined how marketing teams—by adopting new approaches to data gathering, decisioning, and delivery—can create personalized, contextualized, dynamic experiences for individual customers. These data-driven experiences, embodying the latest techniques in HCD, can inspire deep emotional connections to products and brands, which in turn drive loyalty and business growth.9 The human experience platforms trend takes that same quest for deeper insights and connections to the next level by broadening its scope to include not only customers but employees, business partners, and suppliers—basically anyone with whom you interact.

In addition to data, human experience platforms leverage affective computing—which uses technologies such as natural language processing, facial expression recognition, eye tracking, and sentiment analysis algorithms—to recognize, understand, and respond to human emotion. Affective computing can help us achieve something truly disruptive: It makes it possible for us to be human at scale. What do we mean by that? Right now, true human connections are limited to the number of people we can fit into a room. Technologies such as phones or webcams connect us to other humans but remain only a conduit, and connections made through technology conduits are useful yet emotionally limited.

But what if technology itself could become more human? What if a bot appearing on the screen in front of our faces could engage us with the kind of emotional acuity and perceptive nuance that we expect from human-human interaction? Today, you may walk into a clothing store and barely notice the screens mounted on shop walls, displaying items currently on sale; the ads aren’t particularly relevant, so you don’t give them a second thought. But imagine if you could walk into that same space and a bot appearing on the screen recognizes you and addresses you by name.10 This bot has been observing you walk around the store and has identified jackets you might love based on your mood today and your purchasing history. In this moment, technology engages you as an individual, and as a result, you experience this store in a very different, more human way. AI and affective technologies have scaled an experience with very human-like qualities to encompass an entire business environment.

Designing for humans

The human experience platforms trend reverses traditional design approaches by starting with the human and emotion-led experience we want to achieve, and then determining which combination of affective and AI technologies can deliver them. The big challenge that companies will face is identifying the specific responses and behaviors that will resonate with—and elicit an emotional response from—a diverse group of customers, employees, and other stakeholders, and then developing the emotional technologies that can recognize and replicate those traits in an experience.

Think about the abilities comprising empathy—among them, the ability to relate to others, the ability to recognize ourselves in a storyline, and the ability to trust and feel complex emotions. As humans, we see these abilities in ourselves and, by using our senses, we can recognize them in others. Today a growing number of companies are exploring ways to develop a deeper understanding of the humans who will be using new technologies, and to incorporate these insights into technology designs. They include:

  • Neuroscientific research. This method moves beyond traditional “soft science” market research approaches (surveys, questionnaires, data analysis, etc.) by deploying a variety of sensory recognition technologies to measure brain activity, eye movement, and other physical responses to stimuli. Analysis of this data can give companies a deeper understanding of individual’s unconscious and implicit decision-making processes. (See sidebar, “Neuroscientific methods for measuring thought processes.”)
  • Human-centered design. HCD brings the human being into focus. It starts with the premise that individuals’ beliefs, values, feelings, and ambitions are important because they form the foundation for who those individuals are and what they want from the organizations with which they engage. HCD involves using ethnographic research11 and neuroscience to better understand individuals’ unmet needs and using these insights to improve service design and delivery. Importantly, a design-led approach brings end users into the room with stakeholders to engage in rapid prototyping, testing, and iteration of solutions with the people for whom they are created.12
  • Removing bias and emphasizing values and ethics. For experiences to resonate, they must reflect human values, such as trustworthiness, integrity and honesty—all emotional factors that humans feel about their favorite brands. But in the absence of ethical consensus on so many aspects of cognitive and affective technologies, individual companies on human experience journeys should factor ethical considerations—as well as their organization’s values—into the development of their own AI solutions. As you build human experiences for your customers, employees, and business partners, ask yourself: What does ethical technology mean? How do governance and ethics overlap? Do the algorithms we are creating align with our values and those of society in general? How can you build transparency into AI decision-making?13 And how can you reduce cognitive bias in the development process by having more diverse teams be part of the design?14 (Note: For a deeper dive into the ethical dimensions of technology development, check out the ethical technology and trust chapter of Tech Trends 2020.)

Learn more

  1. Emotion-driven engagement: Learn why the ability to use emotional data at scale represents one of today’s biggest business opportunities.
  2. AI & cognitive technologies: Explore how cognitive technologies can help leaders make wise strategy and technology choices.
  3. Paying down the experience debt: Read how leading brands use their values to elevate the human experience.

  1.  

    Kavitha Prabhakar, Kristi Lamar, and Anjali Shaikh, Innovating for all: How CIOs can leverage diverse teams to foster innovation and ethical tech, Deloitte Insights, November 18, 2019.

     

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  2.  

    Nitin Mittal, Dave Kuder, and Samir Hans, AI-fueled organizations, Deloitte Insights, January 16, 2019.

     

    View in Article
  3.  

    Angel Vaccaro et al., Beyond marketing: Experience reimagined, Deloitte Insights, January 16, 2019.

     

    View in Article
  4.  

    Tiffany Fishman et al., Elevating the human experience, Deloitte Insights, October 30, 2019.

     

    View in Article

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