Fait Accompli: Agentive Tech Is Here
Putting Physical and Information Work Together to Become Agentive
Getting to a Working Definition of “Agentive”
Drawing a Boundary Around Agentive Technology
Recap: Agents Are Persistent, Background Assistants
In the prior chapter, we followed temperature control technology from its evolutionary origins through several stages—from the moment our distant forebears developed the need to control their temperature by behavior to using handheld fans and windows, and from the invention of the automated thermostat to the Nest Thermostat.
Tracing this journey is important because it is not unique to thermostats. These increasingly sophisticated technological solutions to the broad general problem of human temperature management illustrate two points. The first is that the evolution of tools can be viewed as iterated solutions to some core human need. The second is that agents are a natural solution to a great many computable human problems, as designers attempt to reduce effort and maximize results.
In this chapter, I’ll define what an agent is and is not, use the thermostat as an example of one, look at some other technologies through a similar lens, and then make the case that far from being a sci-fi future, agents are beginning to appear in the world around us. They’re not yet ubiquitous, but it’s easy to see how they will be.
To start, let’s go back and look at the temperature management tools. But this time, let’s ask what work they are doing on behalf of the user.
Reducing Physical Work
The first and most obvious work that tools can do is to simplify and abstract the physical work involved in a task.
Early tools, like the handheld fan, are tools that simply shape the physical forces that the user is applying to them. The fan spreads out force over a plane, moving air more effectively than we could with our hand alone. These kinds of tools help save us work by letting us use materials and forms better suited to the task than our body parts. A fan is much better at moving air than our outspread hand is. Most technologies start their lives as these manual tools.
Tools can begin to take on the physical effort for us as well, by harnessing forces other than human muscles. Mills let us harness wind- and waterpower. Yokes let us harness animal power. The damper-flapper mechanism that Albert Butz invented saved us from having to get up and cross the room to open a furnace door, by harnessing electricity. These powered tools turn us from laborers to task-managers, steering and guiding the forces to do useful work.
Reducing Information Work
In addition to labor, technology can also help us with the information work involved in a task.
Of course, thermometers give a user some facts to work with in managing the heat of a space.
What’s the actual temperature here? Is it just me who’s feeling cold? What temperature is the thermostat set to? Is it currently putting out heat or not? Is it even on?
These metrical tools give us facts to help us make decisions while performing a task.
More sophisticated technologies can begin to understand the rules of how a task should be performed, and let the user know when good form is being violated or thresholds crossed. These corrective tools help them understand what’s going on and correct course if they’re off track. If a user sets a thermometer to a temperature higher than it could actually attain, for instance, it could immediately provide this feedback and suggest additional measures that could be taken. This would be corrective.
Putting Physical and Information Work Together to Become Agentive
It’s when someone takes these two things—information awareness and machines doing physical work—and connects the two that you begin to see some magic happen. That’s when the tools become agentive.
Drebbel’s incubator was the first tool to do this. It took in information about the temperature to open and close the damper. As brilliant as it was for its time, it was still something of a dumb temperature monitor. It only paid attention to a single variable, and only acted when that variable went above an amount. It couldn’t help if the eggs were getting close to freezing. It didn’t help the alchemist know when fuel was running low. You can consider this an agent, but just barely.
The Nest Thermostat is a much more complicated actor, able to track and manage many variables at once. It even learns over time, refining its model of what good behavior means in its particular household, on this particular day, and for the people it knows are currently present. It is a very powerful tool for managing temperature, and much more exemplary of what you can think of as an agent today.
The thing is, you can examine the history of technology solutions around a human need and find similar patterns. Tools will start out manual. Some evolve to reduce physical effort and become powered. Others evolve to help with the information work and become metrical for measuring or assistive for staying within known rules. And of late, you can see a few dozen examples of systems combining the information and the physical work to do work on behalf of its users, becoming agentive. That these patterns repeat across history is a big claim, but let’s use three examples to illustrate: writing, music, and search.
The Problem of Writing
The Paleolithic cave paintings at Lascaux illustrate an ancient human need of mark-making. This evolution splits in two directions. One is toward expression, like paint brushes, but let’s follow the other direction that veers toward writing. Around this human need, manual tools include burnt sticks, graphite pencils, and pens. There’s not much physical effort involved in writing, but typewriters, both manual and electric, are powered tools that let people output many more letters per minute with less muscle fatigue and much more precision to the letterforms.
In addition, the advent of background spelling and grammar checkers on computers provide both metrical and assistive tools to keep you within the many conventions for clear writing. They’ve now evolved from simple rule-checkers like Sector Software’s Spellbound to more sophisticated ones like Microsoft Word’s grammar checker and iOS AutoCorrect, which not only notes misspellings, but immediately corrects the ones in which it has a high degree of confidence. Recently, Google Inbox released its Smart Reply, which parses incoming emails and provides several short, likely responses from which the user can simply select.
It all becomes agentive with the introduction of x.ai. Subscribers to this meeting scheduler only need to CC “Amy Ingram” (we see what you did there, x.) in an email asking her to “find us a time to meet” and “she” handles the rest. If you prefer a dude, the agent is happy to go by Alex as well. X.ai finds good times in your calendar,