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Sep 15 2020 
Making AI less ‘Human’ and more useful
For 25 years, technology companies have designed user interfaces for our eyes, largely neglecting our other senses.
After heavy investments in screens and visual media, the industry has shifted towards the auditory realm and advancements in natural language processing (NLP) and artificial intelligence (AI) have made Siri, Alexa, and Cortana possible.
These assistants sound human-like, but that’s not why we appreciate them. Technologists who program AI to be more ‘human’ misunderstand how the human mind works.
Setting aside the creepy factor, people don’t need or want AI created in their image. By examining how our attitudes towards visual and auditory media have changed in the last decade, we can identify a less anthropomorphized but more rewarding future for intelligent technology.
The rise of visual communication and asynchronicity
The dilemmas of present-day AI begin with smartphones. The decline of phone calls and the rise of text messaging was somewhat counterintuitive. Speaking with a person is more ‘on-demand’ and ‘instant’ than SMS exchanges that can last days without resolution. Nonetheless, in 2007, monthly text messages surpassed monthly phone calls among Americans for the first time.
Phone calling declined because it is synchronous communication — you must be present and engaged throughout the dialogue. After phones became mobile, anyone could call and hijack your attention. Sometimes, I’m sure you check the caller ID and think, “No, not now.”
In contrast, text messaging is a form of asynchronous communication, meaning the parties engage and respond as their schedules permit. It’s not necessarily more or less social than phone calls. But, it promised freedom. Rather than feeling pressured to answer immediately, asynchronicity gave us time to think about the message, delay commitments, and plan our responses.
Cheryl Casey, an assistant professor of media communication at Champlain College, discusses two sides of asynchronous communication.
On the one hand, it can make exchanges friendlier and less stressful than synchronous communication by facilitating self-censorship (often a good thing), careful message construction, and feelings of safety. On the other hand, it can shield jerks from the reactions to and consequences of their behavior, and it can distract people from face-to-face conversations. We’ve all seen families at restaurants buried in their phones, ignoring each other.
Over the last decade, smartphones funneled countless forms of asynchronous communication — text, email, social networking, advertising, commerce, news, research, video, and more — into mobile screens.
The analytics platform Dscouts recently found that, on average, people now tap, swipe, or click their phones 2,617 times per day and spend 2.42 hours on the phone split across 76 sessions.
The screen demands full attention. Imagine doing creative work, loading a dishwasher, talking with family, or driving a car while watching a movie on a smartphone. People try. But, as neuroscientist Daniel J Levitin explains in The Guardian, our focus, cognitive health, and decision-making ability suffer if we condition ourselves to multitask. Visual asynchronous communication overwhelms our brains.
Sensory design and AI
Screens won’t go away, but they have some limitations. The discipline of sensory design is helping us overcome them. Sensory designers use multiple inputs and outputs to create immersive experiences.
Creative use of sight, hearing, touch, taste, and smell can preserve our focus, reduce emotional stress, and simplify tasks. Sight is our most dominant sense, but sound in combination with AI offers some advantages over screens.
People walk and talk, play sports to music, drive to radio and podcasts, or sing while showering. Siri, Alexa, and Cortana free up vision yet interact asynchronously. While I’m loading the dishwasher, I can ask Alexa about the weather or news. I can’t load a dishwasher and text message with friends simultaneously.
Unlike websites, social networks, and other visual advertising channels, an audio AI assistant responds strictly on our terms.
Anecdotally, people tell me that they love the experience of giving AI orders. There’s no complications or arguments. We feel in command because it’s a one-way exchange. Tell Alexa to order more coffee beans, and she does it. There’s no emotional stress weighing down the ‘conversation,’ if it’s even fair to use that term. We can talk in front of Alexa yet not talk to Alexa.
A better vision for AI
If we want frictionless tech experiences and useful sensory designs, why are so many innovators trying to make AI more human-like? Human beings are not easy to deal with. An AI assistant that is emotionally static and says “yes” to every request is unlike any human I know!
It’s not shocking that human beings would try to create AI in their own image (and miss). Our movies, novels, and religions reinforce that approach to AI.
However, as we expand sensory design to combine AI with vision, hearing, touch, taste, and smell, we need a better target than humanness. A few suggestions:
- Predictability: While we often admire human spontaneity, AI shouldn’t be a robotic improv actor. AI should be optimized to understand what we want and act upon it. Companies like ai.x have created AI assistants that can schedule and reschedule meetings with human email contacts. If we want to trust AI with more complex tasks — like scheduling a business trip — the intelligence must be predictable. When we speak to auditory AI, we want the certainty of tapping without actually tapping.
- Initiative: AI needs some leeway to interrupt us and make exchanges less asynchronous. If I have a meeting across town and there’s bad traffic, I’d like AI to warn me then ask if it should book an Uber at an earlier time than planned. Consider how different that is from the AI of visual media, which is optimized to hook our attention and maximize advertising-based revenue models. We don’t want Alexa to bombard us with marketing offers. Auditory AI should be proactive but not distracting.
- Trainability: Although people talk about their dogs like children, kids are a lot harder to ‘train.’ Dogs will respond diligently to our signals and commands with some Pavlovian conditioning. Unless you’re a modern Captain vonn Trapp from The Sound of Music, you’re not blowing whistles to condition your kids. AI should be more like a dog than a person. It needs to be highly trainable rather than annoyingly independent. Maybe AI should even act excited to greet us when we come home.
Technologists made screens the nexus of communication but created a boundless source of distraction and temptation. Sensory design and AI promise to free up our vision and redefine the concept of a ‘frictionless’ experience. It’s not just about instant, on-demand gratification — it’s that, plus preserving our presence of mind and freedom to focus beyond a screen.
Let’s make AI predictable, proactive, and trainable. As technologists embrace the full spectrum of sensory design, expect less humanness but more utility from artificial intelligence.
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Mar 18 2018 
THE PARADIGM SHIFT OF BUSINESS TRANSFORMATION
Part 1 of 3: Business & Digital Transformation (Read Part 2 and Part 3)
There’s been disruption all around us. Over the past three decades, the rise of high speed internet, exponential growth of computational power, and ever-decreasing costs of storage have drastically changed how we live, what we interact with, and how businesses operate. The democratization of data and technology gave us all easier access to things that we had never imagined before. It helped organizations to push boundaries and disrupt the status quo. However, the creative disruption process is not always easy or straight-forward.
For roughly the last 15 years, thanks to bandwidth ubiquity, we have seen successful new business models emerge and threaten conventional business practices and value propositions. Netflix displacing Blockbuster, Borders succumbing to Amazon, Uber, and Airbnb challenging traditional transportation and travel brands, and countless other examples.
Not only are technology trends shaping business models, but the ever-evolving behaviors and expectations from consumers are also impacting organizations’ current practices.
In some cases, consumers’ unintended use of products may benefit businesses to completely redefine their value proposition. The original intent transforms itself into something that’s not imagined by the company’s leaders. Kleenex is a great example. They started out in 1924 as a disposable towel used to take off make-up. Its unintended use started in 1926 after the manufacturer received tons of customer feedback indicating that most people were using the product to blow their noses. They started advertising it as such and doubled their sales. The rest is history.
Fast forward to 2016 where organizations like Under Armour have shifted their entire business model from a sports clothing company to an innovation and experience company, simply based on how their customers were using their products and interacting as a community. Organizations that are nimble enough to respond to such changing user expectations succeed wildly and make it impossible for the competition to capitalize on that change.
Competition and macro-economic forces also push organizations to reevaluate their business models. The auto and aerospace industries are well known for reacting to such forces. Boeing saw the threat of higher gas/oil prices as well as an adverse impact to the environment with continued climate changes and reacted early on to bring the revolutionary 787 Dreamliner to the market. Not only has this product had a better and different value proposition for airline companies, but it also helped Boeing to take the lead over its competitors. Similarly, Toyota, GM, and other car manufacturers reacted to rising gas prices by introducing hybrid and eventually electric cars to compete with Tesla and to go after a cost-conscious consumer sector.
A PARADIGM SHIFT
The fall of AOL, Circuit City, Kmart, Yahoo and the rise of mobile-only business such as Uber and Venmo have forced many big and small companies to re-think their own models. In industry after industry, scenarios that once appeared improbable are becoming all too real, prompting boards and CEOs of wavering businesses to embrace transformation. Transformation is one of the most overused terms in business, perhaps just behind innovation — and it’s often misunderstood and loosely used by many business leaders. This is because organizations have failed to create a shared definition of what ‘transformation’ means to them. Many times leaders use the term nebulously for incremental changes and proudly wear the badge of being transformative.
Transformation, as I see it, is a paradigm shift for organizations. It significantly alters their pace and rhythm, while improving key business drivers. The shift often results in creating, or significantly modifying, business processes and the value it yields for its customers. However, when enterprises embark on a ‘transformation’ journey, they often fail to communicate ‘why’ to employees. This is a responsibility that starts in the C-suite and must be championed from the top down. Building a compelling vision, aligning key business leaders, and enrolling service line and business unit managers into the concept will help successfully motivate the employee base to adopt and advocate for the change.
All businesses understand that change is inevitable. Eventually, every brand must adapt to market shifts, consumer behaviors, and technology trends in order to survive. The difference between successful organizations and those that fail, however, is the foresight to recognize that change before it’s too late. Transformation is happening now, and the sooner brands treat it with a sense of urgency, the sooner they can spur their business forward.
Note: Originally, this article was published in Spring of 2017 on R2i website.
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Apr 14 2016 
The Myth of Persona
This year, companies will spend billions trying to reach people who don’t exist. We call them “personas.” Like photos and maps, personas are not reality — they are representations of it. We put personas on a pedestal because, supposedly, they answer the question “Who?” They paste colorful identities on the people we presume will buy our products and services.
What if the better question was “Where?” or better yet, “Why?” What if personas have distorted our buyer, and we risk marketing to a myth?
The trouble is recognizing when it happens. It’s not easy to distinguish a messaging problem from a persona problem. To overcome the myth of persona, we have to reconsider what a persona is and how we create it.
Persona to Personalization
Personas are getting deeper by the day. The proliferation of consumer data has made us confident in our understanding of whom we are targeting — perhaps to our own detriment.
Once, marketers would target males who are 18–34, make at least $60,000 per year, and live in urban areas. The marketer might label them “Millennial Male Professionals.”
Now, companies, products, and services start with a value proposition, the description of a problem and their solution for it. The persona answers the question, “Who has this issue?”
Sure, Millennial men in the 18–34 range might have the problem, but why and when? What do these men believe? How do they live? What are their personalities like? What causes do they care about? How would they describe their affinities and interests? In how many different ways can your brand connect to their lives?
Between market research and social analytics, we can answer these questions. The data adds ‘soul’ to the personas, but it can also lead us to a dead end.
The Scale Problem
Content personalization doesn’t scale well. You could carve your audience into 1,000 segments if you wanted. But, creating writing, photos, and videos for each one would be an onerous task with diminishing ROI. Thus, “Where?” is becoming a better question than “Who?” With smartphones, wearables, Amazon Alexa, and virtual reality headsets stretching the notion of a “channel,” it pays to personalize by experience rather than solely relying on demographic or psychographic data.
Let’s use Uber as an example because most people are familiar with it. When Uber began in 2009, the founders had one user channel: a mobile app. Now, Uber’s touch-points go well beyond that. You might have noticed that in January 2017, Uber (and Lyft) showed up in Google Maps, complete with real-time pricing, vehicle options, and a “Request” button. Uber appeared in Facebook Messenger, too, back in December 2015. There, users can share an address, and their friends can click it to request an Uber. People can also share their Uber trip via Messenger so that coworkers know where they are, or so that friends can walk outside to hop in the car.
Uber for Google Maps and Uber for Messenger each added more dimensions to the existing personas, and in some cases created new personas. The Google Maps users are checking for directions, drive times, and transportation options. They’re deciding among multiple options. The channel and marketing experience (often one in the same) has to convince these users that Uber is the best choice.
Uber for Messenger, on the other hand, has to win the buyers amidst a conversation. If you’re the friend who receives an address, you have choices. You could memorize the address or copy-paste it in another app (perhaps Google Maps). Or, you could just click the darn address and get your ride. You’re more likely to hit request when time is short — maybe you made last-minute plans, or maybe you’re rushing over from another social event. Your friend who sent the address is wondering when or if you’re going to show up. Tapping the address and typing, “I got an Uber. See you in 10,” is easy.
Google Maps is for the unrushed, contemplative Uber user. Messenger is better suited for the impulse requestor. Maybe they both are 18–34 male, urban professionals, but they’re in different situations and therefore behave differently. The personas are dynamic.
Context Shapes Persona
If we link each persona to a channel, then personalization is about capturing a moment. That doesn’t mean the demographic and psychographic data is irrelevant. Surely Uber’s marketers could use that information at the top of the funnel, where would-be customers find deals, advertisements, social posts, news articles, and so forth.
At the top of the funnel though, the message can be universal. Recall that Dos Equis made the “The Most Interesting Man in World” appealing to as broad an audience as possible. If, instead, they had made one most interesting man for each of their 20 core segments, we wouldn’t be talking about him years later. Too much personalization kills the art.
So rather than personalizing every message, personalize distribution and the channel. Blend the boundaries between marketing and user experience by making the experience market itself. The design and function of the app have a message. In Uber for Messenger, perhaps that message is: “This is the easy way to go. Just tap the address and get on with your night.”
The real myth of persona is to believe that your customers think and behave the same way all day. In reality, they change minute to minute. People move in and out of the persona you’re targeting.
If you define your persona as an age range, gender, income bracket, and geographical location, you’ll suffer from the myth of persona. If you start with a value proposition, follow it to a channel (i.e. the context), and then build the persona — and your marketing efforts still fail — you probably have a messaging problem.
