Virtual pets: nine-year-old Zhu Ying tries out a Tamagotchi in a Beijing store.
Rest in peace: Tamagotchis even have their own graveyards, the ultimate reflection
of their quasi-human status.
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Website of the month
www.unicef.org
Nearly everyone is familiar with the United
Nations Children’s Fund through its greeting cards. Yet the activities of this 1965
Nobel Peace Prize laureate go far beyond Christmas fund-raising. Its programmes on
child health, nutrition, education and labour operate in 161 countries, a far cry
from its original mandate in 1946 to meet the emergency needs of children in post-war
Europe and China.
Today, the organization continues to provide relief and humanitarian assistance to
every trouble spot in the world. Its website offers a wealth of information–teaching
aids, games, photos, as well as full-text versions of many publications such as its
annual report, The State of the World’s Children.
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 A “cybershrink”
traces relations between children and their electronic pets and computer toys over
three generations
 Children
have always used their toys and playthings to create models for understanding their
world. Fifty years ago, the genius of Swiss psychologist Jean Piaget showed it is
the business of childhood to take objects and use how they “work” to construct theories
of space, time, number, causality, life and mind. At that time, a child’s world was
full of things that could be understood in simple, mechanical ways. A bicycle could
be understood in terms of its pedals and gears, a windup car in terms of its clockwork
springs. Children were able to take electronic devices such as basic radios and (with
some difficulty) bring them into this “mechanical” system of understanding.
Revisiting
Merlin
But in the
early 1980s, a first generation of computer toys changed the traditional story. When
children removed the back of their computer toys to “see” how they worked, they found
a chip, a battery, and some wires. Sensing that trying to understand these objects
“physically” would lead to a dead end, children tried to use a “psychological” kind
of understanding. They asked themselves if the games were conscious, if they had
feelings and even if they knew how to “cheat.” Earlier objects encouraged children
to think in terms of a distinction between the world of psychology and the world
of machines, but the computer did not. Its “opacity” encouraged children to see computational
objects as psychological machines.
Among the first generation of computational objects was Merlin, which challenged
children to games of tic-tac-toe. For children who had only played games with human
opponents, reaction to this object was intense. For example, while Merlin followed
an optimal strategy for winning tic-tac-toe most of the time, it was programmed to
make a slip every once in a while. So when children discovered strategies that allowed
them to win and then tried
these strategies a second time, they usually would not work. The machine gave the
impression of not being “dumb enough” to let down its defences twice. Robert, seven,
playing with his friends on the beach, watched his friend Craig perform the “winning
trick,” but when he tried it, Merlin did not slip up and the game ended in a draw.
Robert, confused and frustrated, threw Merlin into the sand and said, “Cheater. I
hope your brains break.” He was overheard by Craig and Greg, aged six and eight,
who salvaged the by-now very sandy toy and took it upon themselves to set Robert
straight. “Merlin doesn’t know if it cheats,” says Craig. “It doesn’t know if you
break it, Robert. It’s not alive.” Greg adds, “It’s smart enough to make the right
kinds of noises. But it doesn’t really know if it loses. And when it cheats it don’t
even know it’s cheating.” Jenny, six, interrupts with disdain: “Greg, to cheat you
have to know you are cheating. Knowing is part of cheating.”
In the early 1980s such scenes were not unusual. Confronted with objects that spoke,
strategized and “won,” children were led to argue the moral and metaphysical status
of machines on the basis of their psychologies: did the machines know what they were
doing? Despite Jenny’s objections that “knowing is part of cheating,” children did
come to see computational objects as exhibiting a kind of knowing. By doing so, they
recast the Piagetian framework in which a definition of life centred around “moving
of one’s own accord.”
Observing children in the world of the “traditional”–that is non-computional–objects,
Piaget found that at first they considered everything that moved to be alive. Then
only things that moved without an outside push or pull. Gradually, children refined
the notion to mean “life motions,” namely only those things that breathed and grew
were taken to be alive.
Motion
gives way to emotion
Children broke
with this orderly categorization by making distinctions about “machines that think.”
Their discussions about the computer’s aliveness came to centre on what the children
perceived as the computer’s psychological rather than physical properties. To put
it simply, motion gave way to emotion and physics gave way to psychology as criteria
for aliveness.
In the 1980s, the computational objects that evoked “artificial life” (the “Sim”
series, for example, assigns the task of creating a functioning ecosystem or city)
strained that order to the breaking point. Children still tried to impose strategies
and categories, but they did so in the manner of theoretical bricoleurs, or tinkerers,
making do with whatever materials were at hand and with any theory that fit a prevailing
circumstance. When children confronted these new objects and tried to construct a
theory about what is alive, we were able to see them cycling through theories of
“aliveness.”
“Sort
of alive” robots
An eleven-year-old
named Holly watched a group of robots with “onboard” computational intelligence navigate
a maze. As the robots used different strategies to reach their goal, Holly commented
on their “personalities” and “cuteness.” She finally came to speculate on the robots’
“aliveness” and blurted out an unexpected formulation: “It’s like Pinocchio [the
story of a puppet brought to life]. First Pinocchio was just a puppet. He was not
alive at all. Then he was an alive puppet. Then he was an alive boy. A real boy.
But he was alive even before he was a real boy. So I think the robots are like that.
They are alive like Pinocchio but not like real boys.” She cleared her throat and
summed up: “They are sort of alive.”
Robbie, a ten-year-old who has been given a modem for her birthday, put the emphasis
on mobility when she considered whether the creatures she has evolved while creating
a vir-
tual ecosystem through the game SimLife were alive. “I think they are a little alive
in the game, but you cannot save your game [when you turn it off], so that all the
creatures you have evolved go away. But if they could figure out how to get rid of
that part of the programme so that you would have to save the game and if your modem
were on, then they [the creatures] could get out of your computer and go to America
Online [an Internet Service Provider].”
The resurfacing of motion (Piaget’s classical criterion for how a child decides whether
a “traditional” object is alive) is now bound up with notions of a presumed psychology:
children are most likely to assume that the creatures in Sim games have a desire
to “get out” of the system and evolve in a wider computational world.
Through the 1990s, children still spoke easily about factors which encouraged them
to see the “stuff” of computers as the same “stuff” of which life is made. I observed
a group of seven-year-olds playing with a set of plastic transformer toys that can
take the shape of armoured tanks, robots, or people. The transformers can also be
put into intermediate states so that a “robot” arm can protrude from a human form
or a human leg from a mechanical tank. Two of the children are playing with the toys,
mixing human and machine parts. A third child insists that this is not right. The
toys, he says, should not be placed in hybrid states. “You should play them as all
tank or all people.” An eight-year-old girl comforts the now upset third child. “It’s
okay to play them when they are in-between. It’s all the same stuff,” she said, “just
yucky computer ‘cy-dough-plasm.’”
This comment reflects a cyborg consciousness among today’s children: a tendency to
see computer systems as “sort of” alive, to fluidly cycle through various explanatory
concepts, and to willingly transgress boundaries.
Feelings
for Furby
Most recently,
the transgressions have involved relationships with “virtual pets” and digital dolls
(the first and most popular of these were Tamagotchis and Furbies) which raise new
questions about the boundaries of what children consider as life. What these objects
have that earlier computational objects did not is that they ask the child for nurturance.
They ask the child to assess the object’s “state of mind” in order to develop a successful
relationship with the object. For example, in order to grow and be healthy, Tamagotchis
(imaginary creatures “housed” in small screened devices) need to be fed, cleaned
and amused. Going a step further, the furry electronic pets called Furbies simulate
learning and loving. They are cuddly, they speak and play games with the child. Furbies
add the dimensions of human-like conversation and tender companionship to the mix
of what children can anticipate from computational objects. In my research on children
and Furbies, I have found that when children play with these new objects they want
to know their “state,” not to get something “right,” but to make the Furbies happy.
Children want to understand Furby language, not to “win” in a game over the Furbies,
but to have a feeling of mutual recognition. They do not ask how the objects “work,”
they take the affectively charged toys “at interface value.”
In my previous research on children and computer toys, children described the life-like
status of machines in terms of their cognitive capacities (the toys could “know”
things, “solve” puzzles). In my more recent studies, children describe the new toys,
Furbies, as “sort of alive,” which reflects their emotional attachments to the toys
and their fantasies that the Furby might be emotionally attached to them. When asked
whether the Furbies are alive, children tend not to speak about what the toy can
do and focus instead on their feelings for the “pet” and how it might feel about
them.
Emotional
vulnerability
“Well, the
Furby is alive for a Furby,” says Ron, six. “And you know, something this smart should
have arms. It might want to pick up something or hug me.” Katherine, age five, asks:
“Is it alive? Well, I love it. It’s more alive than a Tamagotchi because it sleeps
with me. It likes to sleep with me.” Jen, age nine, focuses not on what the object
offers her, but what she can do for it. “I really like to take care of it. So, I
guess it is alive, but it doesn’t need to really eat, so it is as alive as you can
be if you don’t eat. A Furby is like an owl. But it is more alive than an owl because
it knows more and you can talk to it. But it needs batteries so it is not an animal.
It’s not like an animal kind of alive.”
Today’s children are learning to distinguish between an “animal kind of alive” and
a “Furby kind of alive.” The category of “sort of alive” becomes increasingly used.
Perceived intelligence or “knowing” is another key distinction.
Over the past five decades, research in artificial intelligence has not even come
close to creating a machine as intelligent as a person. But it has succeeded in contributing
to a certain deflation of our language in terms of how we use the word intelligence.
It is now commonplace to talk about intelligent machines when we really are talking
about machines that play chess or assess mortgage applications. These feats are wondrous,
but intelligence used to mean a great deal more than that. We now face the prospect
of a similar deflation of language in talking about affect and emotion. Children
talk about an “animal kind of alive” and a “Furby kind of alive.” Will they also
talk about a “people kind of love” and a “computer kind of love”?
These questions bring us to a different world from the old “AI [artificial intelligence]
debates” of the 1960s to 1980s in which researchers argued about whether machines
could be “really” intelligent. The old debate was essentialist. The new objects sidestep
such arguments about what is inherent in them and play instead on what they evoke
in us: when we are asked to care for an object, when this cared-for object thrives
and offers us its attention and concern, we experience it as intelligent, but more
important, we feel a connection to it. The old AI debates were about the technical
abilities of machines. The new ones will be about the emotional vulnerabilities of
people.
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