Designing Agentive Technology. Christopher Noessel

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in knowing when that artist is on tour near me (or near where I might be traveling), or has an interview, or releases a new video online, but that task might befit the Google Alerts agent better. However, interests aren’t just limited to digital goods, either. They can be physical.

      eBay Followed Searches: Interests in Stuff

      Most folks know of eBay as a great place to go and find something to purchase at a good price, but it also has an agentive feature called Followed Searches. Launched back in 1999 as the Personal Shopper, this feature lets users take any search and keep it going. Even if I don’t find one right now in a style, size, and price I want, I can ask the site to keep an eye on all new items that go on sale there for me, and let me know when any match.

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      eBay has search tools for that moment I hope to find something for now, and agentive tools to help me keep track of things I’m interested in.

      What’s interesting for the kind of search embodied in these three agentive examples is that creating too specific of a search term can work against you. Following a search for “green Ted Baker shirts selling for $53 in San Francisco” might find you exactly the shirt you’re looking for right now, but it would not provide a fruitful persistent search in the future. Users need to be able to set up more abstract searches, and agents may need to help them do it.

      These kinds of persistent searches move you from having to go out and find stuff of interest yourself to letting stuff of interest find you—for example, to subscribe to your favorite artists (or authors) or to notify you when cool things are mentioned online. The dark side of this might be opt-out advertising, but in the best cases, these agents turn the tables so that your interests find you. How will marketing and advertising change when this becomes the norm?

      Autopilots are handy because getting from point A to far-away point B can be monotonous in the middle, and people aren’t reliable at those kinds of attention-endurance tasks. Fortunately, for the past century, people have been developing systems to help with that part of the journey in boats, planes, and increasingly, cars.

      Autohelm Steers the Boat

      Boat captains navigating easy seas simply need to keep the boat pointed in the same direction. Early mechanical systems worked by using a wind vane to keep the boat at the same angle against the wind. Today these systems are known by a couple of names, with marine autopilots being the most common and autohelm being a genericized trademark of Raymarine’s product line (which nicely distinguishes it from aviation autopilots). In their simplest mode, the captain presses the AUTO button, demonstrates the angle at which it must be held, and then lets go to attend to other things around the boat, like perhaps a nice hot buttered rum or the next track of yacht rock.

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      More expensive configurations pair with GPS, sonar, and course-plotting devices to make the autohelm aware of the heading, obstacles above and below the water, location (and corresponding maritime law), and planned course. Touching the tiller or ship’s wheel can be the exception and not the rule.

      Understanding this function of the autohelm, it’s easy to see how a captain on a short pleasure ride might get distracted by other things on the boat and need to recover quickly when she finds herself off course or hears the drone of an alarm from the autohelm, or finds her vessel in all sorts of possible trouble. Since the device is an add-on to the normal mechanics of a ship, the pilot can use normal means to assess the problem, quickly disengage the device to take manual control if necessary, or troubleshoot the electronics if the problem is the technology itself.

      Autoflight Pilots the Plane

      Airplane pilots have to manage more complex variables with less margin for error than their maritime counterparts, but long trips can still be fatiguing. The earliest mechanical autopilots worked like the simple autohelm, but with rudder control being augmented by an attitude sensor adjusting the plane’s horizontal tail flaps, or elevators. Nowadays, autopilots are required for most long-range passenger planes over a certain size, and they consist of many subsystem controls for altitude, speed, throttle, heading, and course. While airplane pilots are always busy and can’t just zone out, they do rely on the autoflight systems to manage some of the tedious aspects of flying and to warn them when there is a problem.

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      Don Norman has studied the interaction of pilots with autopilot. Norman estimates that a pilot flying at 25,000 feet up has about five minutes to figure out that there’s something wrong, then decide what’s going wrong, and finally to recover in order to save the plane and the people aboard.

      Autodrive Drives the Car

      Even though driverless cars aren’t yet common on roads, we’re already dealing with autodrive. (Aside: Dear future, forgive us. We’re still in that transitional phase where we have to call them “driverless,” to distinguish them from the “manually driven” variety, but you’ll know them simply as “cars.”) Manufacturers like Tesla, Volvo, and Mercedes-Benz car models have the driver facing forward, ready to take over. Google’s driverless cars are eventually meant to be wholly agentive, so there won’t be any need for passengers to suddenly take control. But in the near term, while the technology is being introduced to roads, riders and even legislators1 are most comfortable with a driver sitting at the helm of the driverless car, ready to take over should the agent fail.

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      But if a, uhhh, “driver” is just sitting there not driving, can they really stay, just sitting there, keeping their attention on their non-task constantly? Ten seconds is all it takes for a user’s attention to drift while using slow software, and I’m pretty sure a car trip won’t be worth taking if it’s under ten seconds long. Perhaps the car will have to introduce some means of keeping the driver actively engaged in the driving, such as a game that drivers play by trying to match the software’s driving. But if not, then the sitrep-and-takeover will present major problems to the driver who’s just about to win a difficult, timed game on their phone and has to drop that to wonder what that alarm is all about.

      ShotSpotter is a civic agent that constantly listens to a large number of microphones that are sprinkled across a neighborhood. When it hears gunshots, it compares the timestamp on each microphone to triangulate the location of the shots to within a meter’s accuracy. Within seconds of the gunfire, officers can be on their way to investigate.

       How Does Auto* Fail Gracefully?

      Agents do things for you while your attention is elsewhere. That’s an awesome way to maximize your time, but it can pose a major challenge if you and others are relying on the agent to do its job, and it runs into a problem big enough that it needs someone to take over quickly to avert a crisis. How does a person get up to speed quickly on the state of things? What is the troublesome thing and what’s troublesome about it? What does the user need

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