The Design of Future Things (4 page)

Example four, the recommendation system, is very different from the other three for it is slower, less graceful, and more intellectual. Nonetheless, it is an excellent example of a positive interaction between people and complex systems, primarily because it suggests without controlling, without annoyance: we are free to accept or ignore its recommendations. These systems work in a variety of ways, but all suggest items or activities that you might like by analyzing your past selections or activities, searching for similarities to other items in their databases, and by examining the likes and dislikes of other people whose interests
appear similar to yours. As long as the recommendations are presented in a noninvasive fashion, eliciting your voluntary examination and participation, they can be helpful. Consider the search for a book on one of the internet websites. Being able to read an excerpt and examine the table of contents, index, and reviews helps us decide whether to make a purchase.

Some sites even explain why they have made their recommendations, offering to let people tune their preference settings. I have seen recommendation systems in research laboratories that watch over your activities, so if you are reading or writing, they suggest articles to read by finding items that are similar in content to what is on your display. These systems work well for several reasons. First, they do offer value, for the suggestions are often relevant and useful. Second, they are presented in a nonintrusive manner, off to the side, without distracting you from the primary task but readily available when you are ready. Not all recommendation systems are so effective, for some are intrusive—some seem to violate one's privacy. When done well, they demonstrate that intelligent systems can add pleasure and value to our interactions with machines.

When I ride a horse, it isn't any fun for me or the horse. Smooth, graceful interaction between horse and rider requires considerable skill, which I lack. I don't know what I am doing, and both I and the horse know this. Similarly, I watch drivers who are neither skilled nor confident struggle with their automobiles, and I, as a passenger, do not feel safe. Symbiosis is a wonderful concept, a cooperative, beneficial relationship. But in some cases, as in my
first three examples, it requires considerable effort, training, and skill. In other cases, such as in my fourth example, although no high-level skill or training is required, the designers of these systems must pay careful attention to appropriate modes of social interaction.

After I had posted a draft version of this chapter on my website, I received a letter from a group of researchers who were exploring the metaphor of horse and rider to the control of automobiles and airplanes. The “H-metaphor,” they called it, where “H” stands for “horse.” Scientists at the American National Aeronautics and Space Administration research facilities at Langley, Virginia, were collaborating with scientists at the German Aerospace Center's Institute for Transportation Systems in Braunschweig, Germany, to understand just how such systems might be built. I visited Braunschweig to learn more about their work (fascinating stuff, to which I return in
chapter 3
). Riders, it seems, delegate the amount of control they give to the horse: when using “loose reins,” the horse has authority, but under “tight reins,” the rider exerts more control. Skilled riders are in continual negotiation with their horses, adjusting the amount of control they maintain to the circumstances. The American and German scientists are trying to replicate this relationship with human-machine interaction—not only with cars but with houses and appliances.

Symbiosis
, in the sense meant by Licklider half a century ago, is a merger of two components, one human, one machine, where the mix is smooth and fruitful, the resulting collaboration exceeding what either is capable of alone. We need to understand how best to accomplish this interaction, how to make it so natural that training and skill are usually not required.

What would it mean for a car and driver to interact much as a skilled rider interacts with a horse? Suppose a car were to balk or act skittish when getting too close to the cars ahead or when driving at a speed it computed to be dangerous? Suppose the car responded smoothly and gracefully to appropriate commands and sluggishly and reluctantly to others? Would it be possible to devise a car whose physical responsiveness communicated the safety status to the driver?

What about your house? What would it mean to have a skittish house? I can see my vacuum cleaner or stove acting up, wanting to do one thing when I wanted it to do another. But my house? Today companies are poised to transform your home into an automated beast, always looking out for your best interests, providing you with everything you need and desire, even before you know you need or desire it. Many companies are anxious to equip, wire, and control these “smart homes”—homes that control the lighting according to their perception of your moods, that choose what music to play or that direct the television images to move from screen to screen as you wander about the house. All these “smart” and “intelligent” devices pose the question of how we will be able to relate to all this smartness. If we want to learn to ride a horse, we have to practice or, better yet, take lessons. So, do we need to practice how to use our home, to take lessons on getting along with our appliances?

What if we could devise natural means of interaction between people and machines? Could we learn from the way that skilled riders interact with horses? Perhaps. We would need to determine the appropriate behavioral mappings between the
behaviors and states of the horse and rider and those of the car and driver. How would a car indicate nervousness? What is the equivalent for a car to a horse's posture or skittishness? If a horse conveys its emotional state by rearing back and tensing its neck, what might the equivalent be for a car? What if suddenly your car reared back, lowering its rear end while raising the front, perhaps moving the front end left and right?

Natural signals akin to what the horse receives from its rider are actually being explored in research laboratories. Research scientists in the automobile companies are experimenting with measures of emotion and attention, and at least one automobile model sold to the public does have a television camera located on the steering column that watches drivers, deciding whether or not they are paying attention. If the automobile decides that a crash is imminent but the driver is looking elsewhere, it brakes.

Similarly, scientists are hard at work developing smart homes that monitor the inhabitants, assessing their moods and emotions, and adjusting room temperature, lighting, and background music. I've visited several of these experiments and observed the results. At one research facility at a European university, people were asked to play a stressful video game, then allowed to rest afterwards in a special experimental room equipped with comfortable chairs, friendly and aesthetically pleasing furniture, and specially equipped lighting designed to relax the inhabitants. When I tried it, I found it to be a calm and restful environment. The goal of the research was to understand how to develop room environments appropriate to a person's emotional state. Could a home relax its inhabitants automatically when it detected stress? Or perhaps the home could take on a zingy, upbeat mood with
bright lights, lively music, and warm colors when it determined that the inhabitants needed an energy boost.

“Follow me,” says Manfred Macx, the hero/narrator of Charles Stross's science fiction novel
Accelerando,
to his newly purchased luggage. And follow him it does, “his new luggage rolling at his heels” as he turns and walks away.

Many of us grew up with the robots and giant brains of novels, movies, and television, where machines were all-powerful, sometimes clumsy (think of
Star Wars'
C–3PO), sometimes omniscient (think of
2001's
HAL), and sometimes indistinguishable from people (think of Rick Deckard, hero of the movie
Blade Runner
: is he human or replicant?). Reality is rather different from fiction: twenty-first century robots can't conduct any meaningful communication with people; indeed, they are barely capable of walking, and their ability to manipulate real objects in the world is pathetically weak. As a result, most intelligent devices—especially in the home, where costs must be kept down and reliability and ease of use kept up—concentrate on mundane tasks such as making coffee, washing clothes and dishes, controlling lights, heating, and air conditioning, and vacuuming, mopping, and cutting the grass.

If the task is very well specified and the environment under control, then intelligent machines can indeed do a reasonable, informed job. They can sense temperature and moisture, as well as the amount of liquid, clothing, or food, and thus determine
when the laundry is dry or the food is cooked. The latest models of washing machines can even figure out what kind of material is being washed, how large the load is, and how dirty the clothes are, and adjust itself accordingly.

Vacuum cleaners and mops work as long as the pathway is relatively smooth and clear of obstacles, but the luggage that follows its owner in Stross's
Accelerando
is still beyond the capability of affordable machines. Nonetheless, though, this is precisely what a machine might be able to do, for it doesn't require real interaction with people: no communication, no safety-related issues, just follow along. What if someone tried to steal the freewheeling suitcase? It could be programmed to scream loudly at any attempt, and Stross tells us that it has learned the owner's “fingerprints, digital and phenotypic”: thieves might be able to steal it, but they wouldn't be able to open it.

But could the luggage really make its way through crowded streets? People have feet, the better to step over and around obstacles, to go up and down stairs and over curbs. The luggage, with its wheels, would behave like a handicapped object, so it would need to seek out curb cuts at street intersections and ramps and elevators to maneuver within buildings. Human wheelchair users are often stymied: the wheeled luggage would be even more frustrated. And beyond curbs and stairs, navigating through city traffic would likely defeat its visual processing systems. Its ability to track its owner, avoid obstacles, and find paths navigable by a nonlegged device, while avoiding collisions with automobiles, bicycles, and people, would surely be compromised.

There is an interesting disjunction between the things people and machines find easy and hard. Thinking, which once was
held up as the pinnacle of human achievement, is the area in which machines have made the greatest progress, especially any thinking that requires logic and attention to detail. Physical actions, such as standing, walking, jumping, and avoiding obstacles, are relatively easy for people, but difficult if not impossible for machines. Emotions play an essential role in human and animal behavior, helping us judge what is good or bad, safe or unsafe, while also providing a powerful communication system for conveying feelings and beliefs, reactions and intentions among people. Machine emotions are simplistic.

Despite these limitations many scientists are still striving to create the grand dream of intelligent machines that will communicate effectively with human beings. It is in the nature of research scientists to be optimists, to believe that they are doing the most important activity in the world and, moreover, that they are close to significant breakthroughs. The result is a plethora of news articles, such as this one:

Many conferences are held to discuss progress on the development of “smart environments.” Here is the wording of one invitation among the many that I receive:

Do you trust your house to know what is best for you? Do you want the kitchen to talk to your bathroom scale, or perhaps to have your toilet run an automatic urinalysis, sharing the results
with your medical clinic? And how, anyway, would the kitchen really know what you were eating? How would the kitchen know that the butter, eggs, and cream taken out of the refrigerator were for you, rather than for some other member of the household, or for a visitor, or maybe even for a school project?