RTIFICIAL INTELLIGENCE - Be Accountable - Hacking Happiness: Why Your Personal Data Counts and How Tracking It Can Change the World (2015)

Hacking Happiness: Why Your Personal Data Counts and How Tracking It Can Change the World (2015)



Be Accountable



Welcome to the next phase of computing . . . Companies ranging from IBM to Google to Microsoft are racing to combine natural language processing with huge Big Data systems in the cloud that we can access from anywhere. These systems will know us better than our best friends, but will also be connected to the entire Web of Things as well as the collective sum of all human knowledge.1


WE ARE ALL creatures of habit. We are steeped in binary behavior, making choices between two options that will lead to a desired outcome. Here’s an example of this from my own life in my morning routine:

· Start coffee, unless dog is barking loud enough to wake my wife.

· If dog is barking, take him outside to pee, and then make coffee.

· If dog is not barking, smile at him and give him peanut butter.

· Pour soy milk in my mug and cream in my wife’s mug while waiting for coffee.

· If there’s no soy milk, curse, then pour a small portion of cream in my mug.

· Savor first sip of coffee after first handing other mug to wife.

· If interrupted by children, unless they’re on fire, finish coffee.

· If children are on fire, curse, then put them out before reheating coffee.

Years ago I read an excellent book called The Weekend Novelist by Robert J. Ray, which provides a fifty-two-step plan to help you write a book in a year. He made an excellent observation about human behavior, which is that we’re “mired in ritual.” We get up every morning and do the exact same things—pee, take a shower, shave. When I’m on the road for work, I organize my rituals in such a way that I can actually look forward to traveling.

We think like machines. We also think like humans, but decision-making based on predetermined outcomes is a part of our lives.

Take dating, for instance. Most people feel they have a type of person they’d like to have as a partner. But are the criteria we think will make us happy in another person always right? Speaking for myself, before I met my wife, my choices in dating sucked. This isn’t a criticism of the women I went out with, mind you. My dating pattern before I met Stacy was to have short relationships with women I knew weren’t ready for commitment. Mutual usury seemed to be working for me until the nadir of my romantic life when, during a first date, a woman told me, “Technically I’m still married,” and I didn’t flee. The familiarity of my dating pattern had brought such comfort, I couldn’t see the damage it was doing.

Here’s how Wikipedia defines an algorithm: “In mathematics and computer science, an algorithm is a step-by-step procedure for calculations. Algorithms are used for calculation, data processing, and automated reasoning.”2 In terms of dating, the use of an algorithm mentality can be found in Amy Webb’s memoir, Data, A Love Story: How I Gamed Online Dating to Meet My Match. The book is funny and real and documents her use of data and algorithmic behavior to accurately assess her perfect man, which she does. I wish I had thought of it back with “still married” lady.

eHarmony is taking the matchmaking algorithm to a new level, according to John Tierney in the New York Times. While presenting research at the Society for Personality and Social Psychology, eHarmony’s senior research scientist, Gian C. Gonzaga, reported, “It is possible to empirically derive a matchmaking algorithm that predicts the relationship of a couple before they ever meet.”3 While the statement drew a great deal of criticism from peers, eHarmony has gathered answers from over forty-four million people on questionnaires featuring over two hundred questions. The data set is substantial enough to warrant credibility.

Predictive algorithms tend to freak people out. We don’t like to think our intentions can be gamed or guessed. We’re also distrustful of how they can shape our perceptions of the world, as Eli Pariser, chief executive of Upworthy and board president of MoveOn.org, wrote about in The Filter Bubble: How the New Personalized Web Is Changing What We Read and How We Think:

Left to their own devices, personalization filters serve up a kind of invisible autopropaganda, indoctrinating us with our own ideas, amplifying our desire for things that are familiar and leaving us oblivious to the dangers lurking in the dark territory of the unknown. In the filter bubble, there’s less room for the chance encounters that bring insight and learning . . . If personalization is too acute, it could prevent us from coming into contact with the mind-blowing, preconception-shattering experiences and ideas that change how we think about the world and ourselves.4

It’s a point we all think about concerning our interactions with machines: Where do we lose intentionality in our actions? Does our Connected World demand the sacrifice of serendipity?

Not according to Greg Linden, former principal engineer at Amazon who invented the company’s recommendation engine and personalization framework. In response to how personalization algorithms could supplant serendipity, Linden told me during an interview:

For the early work on recommendations at Amazon, it always had the goal of helping people find books they wouldn’t otherwise find. You can only search for something if you know it exists. You have to embrace serendipity to discover new things. It’s more of a process of wandering than of searching. But it would take forever to wander through a five-million-item catalog. Even the earliest recommendation features at Amazon were designed with the idea of helping people wander, helping them discover things they wouldn’t find on their own.5

“Machine learning” refers to systems that can learn from data. Artificial intelligence enlarges this idea to incorporate systems that can learn from their surroundings. Humans learn from data and their surroundings, but at different rates. We also aren’t programmed to constantly monitor our lives to optimize at all times.

At least until now, because we can. Hacking H(app)iness wasn’t possible before passive sensors and mobile phones became widely available, tied together by the Internet of Things. We have more opportunities to quantify our emotions than ever before, testing our perceptions and beliefs in the wake of ordered data. This process doesn’t have to be scary. While I loathe the idea of usurping serendipity for technology, I still use my GPS almost daily. I’ve made a trade-off—I get lost less, knowing I may also never stumble upon a glorious restaurant not registered by TomTom. But I still meet people I didn’t before, and they tell me about cool places they’ve discovered. Serendipity once removed still stimulates. Assisted wandering works for me.

We can call ourselves Luddites and say we’re not on Facebook. We can point to an older relative who doesn’t own a cell phone or talk about emerging countries in the world where technology doesn’t exist. But of the world’s estimated seven billion people, six billion have access to mobile phones,6 and only four and a half billion people have access to working toilets. Rather than decry the use of algorithms for fear of losing serendipity, we should focus on creating technology with positive intent that can help other people in our Connected World.


Robotics technology holds the potential to transform the future of the country and is expected to become as ubiquitous over the next decades as computer technology is today.7


Our future is inexorably tied to robots. Autonomous machines build our cars, perform surgery, travel to inhospitable depths of the sea, and participate in combat operations to keep human lives from being put at risk. Soon, robots will become commonplace in assisted living centers, providing companionship for the teeming number of boomers requiring specialized care. Our homes and cars already feature primitive forms of robots equipped with Wi-Fi that can communicate to manufacturers or other devices around the Connected World.

The notion of The Singularity has been popularized by Ray Kurzweil, renowned author, inventor, and director of engineering at Google. The term refers to a date in time when computer intelligence catches up to and surpasses that of human beings. While opinions vary, The Singularity is predicted to occur within twenty to forty years, probably around 2040. The logic for this assertion is based on Kurzweil’s Law of Accelerating Returns, the idea that technology increases at an exponential versus a steady rate. This means it takes less time for new technological advancement to occur by utilizing tools that didn’t exist before. A simple example: You build a house faster with a hammer than a rock. Once electricity was invented, pneumatic hammers shortened building times even further.

Ethics and identity in the wake of robotic technology need to be considered now. Living an examined life has to include individual decision on how we interact with an intimately connected world.

“Right now, engineers have to be certified to work with elevators. Soon we’ll have emotional ethics certification for people dealing with technology that interfaces with our emotions.”8 Alexander Reben created the project Blabdroid, “the world’s first documentary shot and directed entirely by robots,” that was featured in Amsterdam and at the 2013 Tribeca International Film Festival’s Storyscapes Competition. I interviewed Reben along with filmmaker Brent Hoff, who worked on Blabdroid as well as creating The Love Competition, a documentary featuring people competing in MRI machines to express emotion.

For both projects, Reben and Hoff were investigating the theory of the ELIZA effect, named after an experiment conducted by MIT computer scientist Joseph Weizenbaum in 1966. In the experiment, users would respond to different recordings from a simple boxlike machine (named ELIZA) programmed to play recordings based on people’s verbal responses. Here’s a sample conversation between ELIZA and a young woman as recorded in “Dialogues with Colorful Personalities of Early AI” by Güven Güzeldere and Stefano Franchi:

YOUNG WOMAN: Men are all alike.

ELIZA: In what way?

YOUNG WOMAN: They’re always bugging us about something specific or other.

ELIZA: Can you think of a specific example?

YOUNG WOMAN: Well, my boyfriend made me come here.

ELIZA: Your boyfriend made you come here?

YOUNG WOMAN: He says I’m depressed much of the time.

ELIZA: I am sorry to hear you are depressed.

YOUNG WOMAN: It’s true. I’m unhappy.

ELIZA: Do you think coming here will help you not to be unhappy?

YOUNG WOMAN: I need some help, that much seems certain.9

What began to occur with the machine was both remarkable and disturbing to Weizenbaum: People began to unconsciously assume ELIZA’s questions implied emotional interest in their problems, even when they consciously knew ELIZA was only a machine. They were anthropomorphizing ELIZA and experiencing a therapeutic release, revealing problems that ostensibly weren’t being listened to by their human companions.

What’s so fascinating about this effect is the balance between conscious and subconscious response elicited by users. Not only did they forget they were speaking to a machine, they didn’t care. A number of studies10 continued to document this behavior in the decades that followed, programming robots to mimic eye or voice patterns in humans to garner sympathy and emotional response.

To study the ELIZA effect in action, Reben and Hoff created Cubie, a small cardboard robot outfitted with a camera, wheels, and a set of prerecorded questions voiced by a seven-year-old boy, including, “What’s the worst thing you’ve done to someone?” and “Tell me something that you’ve never told a stranger before.” Footage taken at the International Documentary Film Festival in Am-sterdam revealed a number of candid responses, including one young woman’s response to the worst thing she’d done to someone: “I didn’t tell my father I loved him before he died.”

Blabdroid isn’t intended to be manipulative, however. As Hoff pointed out in our interview, the experiment is designed to provide an emotional outlet for people based on deeper questions than are addressed with modern entertainment:

Instead of watching a reality TV show, we’re interested in what kind of emotional reaction people will have with a little robot. Despite a relatively low level of artificial intelligence, people are having phenomenally emotional experiences. And isn’t that the point? Do robots have to be incredibly smart to make our lives better? No, they just have to be designed right and fit.11

Hoff’s documentary The Love Competition also explores the intersection of emotions and machines. Seven volunteers met with Stanford University neuroscientists who measured their brain patterns in an MRI machine. Volunteers were asked to vividly imagine their experiences with a current or past love, where a winner would be determined based on output of brain activity focused on emotion. The results are described by Angela Watercutter in the Wired article “Neuroscientists Measure Brain Activity in Love Competition,” where she points out that, based on physiological results (levels of dopamine and serotonin activity), people can show they love someone more deeply than someone else can.12 Having watched the video myself, what was more powerful than the empirical evidence was the effect the experience had on competitors, who expressed deep emotion after leaving the MRI, many of whom were almost in tears. And in this case, the ELIZA effect of the MRI machine is less overt than with Blabdroid, but still just as poignant: People willingly, or inadvertently, will express emotions with the presence of robots or technology that would have stayed hidden without them. Fueled by a sense of freedom to express sentiment that may be construed as inappropriate or questionable by humans, people open up to machines. Even though they know they’re doing it.

In a final insight about the nature of people’s responses to artifacts engineered by humans in our interview, Reben brought up a powerful point about the nature of some of our oldest companions:

A lot of people have fears about artificial intelligence and social robotics. They think, if I get a robotic animal as a pet, won’t that be bad? I’ll be replacing social connections with technology. Newsflash—we’ve had this precedent for eons. It’s called a dog. Dogs have been technologically bred for generations through genetic selection to be our companions. Carbon or silicon, sometimes we need to vent our emotions on something that’s nonjudgmental.13


Mirrors aren’t always fun. In light of how we’re looking at ourselves, we may smile and love what we see. Or we may view ourselves through a lens of criticism, noting every blemish. Quantified self and the Internet of Things provide multiple ways to reflect on our humanity. They also let others peek from behind our shoulders and see us in ways we didn’t recognize before.

Being accountable in the Connected World with its multifaceted mirrors doesn’t need to be scary, just informed. The tools involved, like ELIZA, can provide catharsis versus criticism on your journey to optimization. But as the rate of technology is increasing exponentially, you can’t afford to linger at the glass without embracing your digital identity. Privacy isn’t dead, but requires being proactive—be accountable so the identity you broadcast is the one you mean to project.