Data, technology, and the future of play

Dimensions of Play

According to Montessori, play includes the following dimensions:

Play is voluntary

Whether sports, painting, or making music, play is an activity we enjoy and engage in willingly. How many of us, as children, were told to “go play outside” after annoying our parents for a bit too long? Although we do not always seek play, it is something we pursue with happiness when we find it. This is an important point where technological toys are concerned. For example, a toy like Dash and Dot, which encourages kids to write programming code, turns software development into “play,” where writing software code might be considered work in another context.

Play expands skills

Particularly in young children, play tends to draw the player into situations that require the use of existing skills, or the learning of new skills. This is readily apparent in sporting activities, but can also be observed in creative play like visual or performing arts and role-playing. Large and small motor skills, communication, and memory are a just few of the skills we refine over time through play.

Play expands new ideas

We often perform experiments when we play, inventing contraptions, staging complicated interactions, and exploring new places, both physically and figuratively. Role-playing and competitive games allow children to safely explore their roles in society, personal relationships, and expectations of cause and effect. These are some of the complex ideas that children develop while they’re young.

Play is social

Obviously, you can play by yourself. But unlike sleep, work, or reading a book, play is a social interaction. Solo play creates a feedback loop that provides a social reward. Whether you paint a picture, fly a kite, or spend an hour on a swing singing to yourself, you are interacting with yourself in a social way, which helps you interact with others. Group play has more conspicuous social benefits.

Play is emotional

If it didn’t feel good, we wouldn’t do it. With the exception of professional athletes and artists, very few of us are paid to play. We enjoy playing. It’s also a survival impulse that can be observed in many young animals. The games and adventures we embark on as children lead us past our fear of the unknown into a greater awareness of the world and its pitfalls. In fact, play often summons a combination of emotions—from fear and disappointment to excitement and happiness. Through games, we learn to experience, express, and cope with a wide range of feelings.

Constraints and Rules

Another cornerstone of play is constraint. Some forms of play are competitive, and those constraints become rules—a way to determine the winner and loser. Less structured play, such as “playing house,” may be collaborative, with the only constraints being the setting and roles. Linda El-Fakir, president of The Big Idea Factory and serial toy entrepreneur, compared the fluctuating constraints of smart toys with the somewhat fixed constraints of traditional toys. “Smart toys use electronics and their programming to guide children in how to play or learn, and some allow growth and change over time with mastery; for example, they can move to a next level of play, select more types of play, or play differently,” said Linda. “Traditional toys tend to have set play patterns and can’t change over time, but can be played with as intended or differently, and with other toys—for example, blocks and action figures and vehicles together—depending on the child’s interest and imagination.”

From constraints comes creativity. Constraints provide context, as well as limitations to overcome. In the case of competitive play (e.g., chess or tag), the rules provide the basis for the contest. In creative play, these rules are often emergent, invented as play progresses.

The Nature and Evolution of Toys

“If play is the work of the child, toys are the tools,” said Maria Montessori in an article for the Child Development Institute. “Through toys, children learn about their world, themselves, and others.”

Per Montessori, toys teach children to:

• Figure out how things work

• Pick up new ideas

• Build muscle control and strength

• Use their imagination

• Solve problems

• Learn to cooperate with others

However, the nature of toys (and play) is in flux. In the last half century, toys stopped being tools for play, and became agents of play. All toys offer affordances—a stick might be a weapon, or a mode of transport, or a musical instrument. A stick isn’t designed for any of these things, of course, but a child provides the necessary context. One way to look at toys is to consider them in two dimensions: whether the child is a spectator versus a creator, and whether the toy is being used for its intended purpose versus being repurposed (see Figure 1-1).

Purpose-built toys have more constraints—ball wants to be thrown, a doll wants to be hugged, and a pen wants to draw. The more complex the toy, think today’s smart toys, the more “opinions” it has about how it should be used.

How Toys Became Smart

The brains of today’s toys started with arcade video games. Early computer games were the digital equivalent of board games. For example, Pong (released in 1972), pitted opponents against one another, without agency on the part of the game. These early games merely enforced the policies and constraints of the game. The next wave of games allowed single-player play, but they weren’t adaptive. Breakout (released in 1976) had no intelligence beyond a simulation of physics. The enemy in Space Invaders (released in 1978) didn’t adapt to player behavior, other than speeding up on more advanced levels. As games became more sophisticated, they began to adjust their play in response to the player’s actions. The ghosts in Pac-Man (released in 1980) changed their trajectories according to how the player moved.

While difficult to pinpoint, the emergence of “smart toys” likely started in the early 90s, with VTech and LeapFrog. These were the first big toy manufacturers to focus on the smart toy market, and to spread the message that digital toys offer superior educational experiences. The small handheld arcade games and Tamagotchi toys never claimed to make kids smarter, or to be particularly smart themselves. But LeapPad and other products were packaged with the message that they could actually teach kids with their built-in technology.

The idea that toys could also learn from kids came later, with toys like Robosapien and Furby. The Tamagotchi’s smart companion Furby required care, feeding, and interaction with an owner. This paved the way for even more advanced sidekicks, such as Jimmy the 21st century robot.

In Alone Together (Basic Books), author Sherry Turkle writes, “The first computational objects of the playroom provoked a change in children’s way of sorting out the question of aliveness. … Unlike traditional dolls, the robots wouldn’t thrive without attention, and they let you know how you were doing. But even the most primitive of these objects—Tamagotchis and Furbies—made children’s evaluation of aliveness less about cognition than about an object’s seeming potential for mutual affection.”

While furry dependents and charming robots were hitting the shelves, ubiquitous computing also became a reality. There are now billions of smartphones in the world, as well as microcontroller kits like Raspberry Pi and Arduino on which to build the brains of a toy. Many modern smart toys rely on ubiquitous broadband for everything from software updates to analytics to tie-ins between physical and virtual elements.

In recent years, games have become even more sophisticated, with storylines that adjust to the player’s choices and behaviors, and deeply branched conversations. Games like Guitar Hero, which introduced a physical toy linked to a digital game, have blurred this physical/virtual line. And kid-friendly communities such as Disney’s Club Penguin and shared servers for sandbox games like Arc and Minecraft provide creative interaction.

Powered by software, collecting data, and personalizing their actions based on the user, smart toys not only change how children learn, but also act as surrogates for intimacy and companionship. Play is largely about narrative, and when the toy comes with its own narrator, will it drown out the narrative of the child?

From Opponent to Companion

One of the many ways smart toys differ from traditional toys is that they can control the narrative of play. Their programming is hardly sentient—today it’s at the level of a non-player character (NPC) in a video game—but context will soon enable them to react algorithmically, rather than programmatically. This interactivity is compelling. It’s why virtual toys are flourishing.

Looking at automated chat programs like Cleverbot, it’s clear that this future isn’t far off. Figure 1-2 shows an example chat with Cleverbot.

Chat agents like Cleverbot learn from every user, often parroting back what others have said. In this example, nearly 30,000 people are talking with Cleverbot. Its interactivity is a product of a constant feedback loop, just as Google Now learns from the searches its users conduct. And as we’ll see, that feedback loop holds both promise and risk for toys.

Apps and the Soul of the Toy

We spend a tremendous amount of time in front of screens. Late 2014 was a tipping point, when, according to Flurry Analytics, the average American spent 168 minutes a day watching TV, but 177 minutes a day on their smartphone.

Behind each of those screens are applications. Much of the time, they’re affordable, educational, and better able to teach the new norms of interaction than any other experience. They incorporate increasingly sophisticated software, allowing the apps to learn and adapt over time. The biggest disadvantage to these apps is that many of them serve up sedentary activities, and are generally not social.

Parents worry about the sedentary behavior that toy apps encourage. But, parents are concerned for the wrong reasons. These toys are in fact becoming less passive, and more interactive. And they’re always on.

While toys can’t relate to a child as well as humans can, their immediacy is limitless. Children mistake the undivided attention of a toy for intimacy, and as toys get smarter and more contextual, we risk entering an era of “drone parenting,” abdicating the raising of our children to a digital nanny. However, we aren’t building nannies yet, and we’re still very far from artificial intelligence that can do more than one or two things really well. Self-driving cars and delivery drones, for example, require a very specific context (a set of human behaviors and information) to operate well. A great deal more context is required to successfully teach and raise a child to become a responsible adult. If parents lean on technology to satisfy their children’s emotional and physical needs, they may be depriving their children of that context.

This is happening before our eyes. Check out MIT’s the Huggable, a robotic teddy bear that helps kids cope with the stress of major illnesses. The teddy’s brain is a phone. He’s an app, with an adorable little body. So is the pre-programmed playmate Ubooly, dubbed “the learning toy that listens.” So is the robot Jibo, a family-friendly personal assistant. So is the robotic ball Sphero, and so are the coding robots Dash and Dot.

Is this bad? It’s not the first time we’ve worried about toys. According to London Knowledge Lab’s report on Children’s Playground Games and Songs in the New Media Age, “Ever since children’s games, songs, rhymes, rituals and objects of play were first documented in the mid-19th century, there have been concerns over their vulnerability to a succession of perceived threats. They have regularly featured as symptoms of what adults imagine as the innocence of childhood, and its supposed fragility.”

The next generation’s imaginary friends will be software-generated, and will change how we learn and think—and maybe that’s a good thing.

Three Feedback Loops

Smart toys have three distinct feedback loops: real-time adjustment of toy behavior based on child’s reaction, pooled behavior and automated learning, and product roadmaps established by analytics (see Figure 1-3).

Together, these three loops guide a toy’s behavior over its lifetime. Let’s look at each loop a bit more closely:

• Real-time adjustment of toy behavior based on child’s reaction has been around since the Tamagotchi—toys like Furby can change their behavior and personality based on feedback. Some of the newer toys even try to simulate interactivity, and in many cases are programmable.

• Pooled behavior and automated learning is the real promise for smart, connected toys. When the sum of all play leads to feedback and adaptation, toys get smarter. Consider Tesla’s recent self-driving car: when it was first launched, drivers complained that it was taking corners too quickly, or edging toward exits when it shouldn’t. But within a week, the cars were learning, as each time a problem occurred the driver took the wheel and taught the collective intelligence what to do. When toys benefit from similar automated learning, they’ll wise up faster than we expect.

• Product roadmaps are informed by customer feedback, but obtaining this feedback was traditionally done in focus groups and by observing sales or product usage. Building analytics into toys gives product teams faster feedback, and it comes from real-world use rather than staged environments. When the toys are smart, new functionality can be pushed out to them quickly, too. Wonder Workshop lets children use their Dash and Dot robots to compete in a robotics league. This league enabled the Workshop to release a new application for visual coding, Wonder, nearly a year after Dash and Dot was launched. With the new app came a variety of new functions and sounds for the robots themselves.

Interactive products like smart toys inherently collect data, but that data can be repurposed and misappropriated. How do we control what’s stored, for how long, and how it’s used?

Usage of smart toys may even have permanent, long-lasting biological consequences. In a piece she wrote for the UK’s Daily Mail, Professor Susan Greenfield observes that “electronic devices and pharmaceutical drugs all have an impact on the micro-cellular structure and complex biochemistry of our brains. And that, in turn, affects our personality, our behavior, and our characteristics. In short, the modern world could well be altering our human identity.”