Friday, July 24, 2009

The Impact of Smart Systems on Attention - the World’s Scarcest Resource

Well-designed smart systems will allow humankind to manage the world’s scarce resources.

What is the World’s Scarcest Resource? Clean water, food, energy? Surely, a scarce– if not the scarcest – resource in the 21st century is attention. We don’t have uninterrupted time to give undivided attention to things that truly matter. Technology offers us opportunities for distraction. Mobile phones, instant messaging, email, Twitter, social networks, and alert engines give us excuses for getting sidetracked. Of course, we don’t have to give in, but too often we do. Well-designed smart systems amplify attention; poorly designed ones degrade it.

A Well-Designed Smart System is an Attention Amplifier
Habit 3 in “The Seven Habits of Highly Effective People,” by Stephen Covey [1] emphasizes the importance of prioritizing work aimed at long-term goals, at the expense of tasks that appear to be urgent, but are less important. A well-designed smart system is an attention amplifier. It helps you do important tasks first: it acquires data from varied sources, analyzes the data, identifies the information that deserves your attention at the current time based on what you are doing, aggregates information that helps you execute responses, and helps you focus.

A Poorly-Designed Smart System is an Attention Distracter
William James, the psychologist, writing in 1890 [2] said “[Attention] implies withdrawal from some things in order to deal effectively with others, and is a condition which has a real opposite in the confused, dazed, scatterbrained state which in French is called distraction, and Zerstreutheit in German.” A poorly designed smart system is an attention distracter – it doesn’t allow you to withdraw from some things to deal effectively with others because it continues to distract you with information that is irrelevant to your current task. Distracters are best turned off.

Attention in IT Systems
Attention is a characteristic of IT systems as well as human beings: the resources of an IT system – computers, sensors, communication channels and responders – can be optimized to deal with the problems that matter or the resources can be frittered away acquiring and analyzing torrents of irrelevant data. A critical part of designs of sense and respond systems is determining what data should be filtered out at the periphery of the system and what data should be aggregated and forwarded for further analysis. Sending all sensor data for further analysis is a waste of resources; it is akin to attention distraction due to a dissipation of analytic power. Sending too little sensor data for downstream analysis can result in critical events remaining undetected.

An earthquake warning system has hundreds (and possibly thousands of sensors) distributed over a region. Sensors acquire data several times per second. Sending each measurement from each accelerometer and seismometer to central sites for analysis and storage is expensive and adds little value. Such systems are designed so that sensors only send on data about unusual events identified by atypical patterns of measurements. The detection of important events – earthquakes, onset of recessions, power demand exceeding supply capability – often requires deep analysis; the determination of what measurements merit deep analysis is a key aspect of smart-system design.

Relevance depends on Context
Whether a piece of information is relevant to you depends on your context. While you are exploring options for financing or refinancing a home you will find phone calls about cruises to be distracting. While you are thinking about holiday travel plans, you will find phone calls about mortgage rates to be distracting. The same information is an attention distracter in one case, but not the other. (This issue of context applies to IT systems as well as human beings.)

Here’s the challenge: How is a smart system to know what you are doing? How can it know your context? How can it know whether interrupting you with information about a rare low mortgage rate is attention distraction or attention amplification for you at this time?

Online Services can estimate your Context
Search engines can estimate your context based on the items for which you are searching. Email and instant-messaging servers can estimate context based on the messages sent and received. Location-based systems guess context based on location and time of day. Calendar servers figure contexts based on appointments and tasks. When you work on a shared online document you are telling the service provider something about your current context. And the more the service provider knows about what you are doing now, the better it can help you husband that most valuable of your resources – your attention.

(Privacy is a different matter which is discussed in a later note.)

Proactive Computing
An alerts engine can interrupt you with an audible, visual or tactile signal; and an alerts engine can interrupt software processes. If, however, the engine cannot estimate your context accurately, it can save the data and ancillary information for you to look at later – the engine carries out proactive computation on your behalf, and has results and tools ready should you need it. When you are ready to be interrupted, you look at results of the proactive computations and discard them or use them. The advantage of this approach is that you aren’t interrupted; the disadvantage is that the data may be relevant to your context and you may have wanted to be interrupted. The same approach can be used for software processes and hardware.

The costs of executing proactive computations continue to drop as the costs of processors, storage and communication bandwidth fall; so, even if results of proactive computation are often discarded, having results ready when you need it is cost effective.

Peripheral and Tunnel Vision
There are times at which you (and IT processes) need tunnel vision, focusing your attention and resources on a few critical tasks. There are other times at which you need peripheral vision, sensing and integrating data from multiple sources that may not be directly connected to the task at hand. Well-designed smart systems give you peripheral vision by sensing data from multiple sources and analyzing the data – this proactive computing may be carried out all the time. Well-designed smart systems also let you (and IT processes) use tunnel vision during periods when more of your attention and resources need to be dedicated to a few tasks. Poorly designed systems have only one type of vision – they don’t allow organizations and processes to switch back and forth between tunnel and peripheral vision.

Husbanding your limited Scarce Resource
Good smart systems are attention amplifiers. Bad smart systems (no, it’s not an oxymoron) are attention distracters. Attention is a limited resource and it’s increasingly scarce. Smart systems can help you manage this resource – perhaps the most important resource of this century – when the systems are designed well and used wisely.

1. Stephen R. Covey(1990). The Seven Habits of Highly Effective People. Free Press.

2. James, W. (1890). The Principles of Psychology. New York: Henry Holt, Vol. 1


  1. The focus on attention context as a function of time is exactly the right approach. What makes google successful is not only matching the query well, but presenting the results at the time you're making it. In the 90s we thought the model was 'register an interest and wait to be notified when a match happens' Today my blackberry starts blinking every 30 seconds - I had to turn most notifications off. Can we make the notifications smarter -- only if we figure out how to program domain/application-specific intelligence. Once we build a few smart apps maybe we'll learn enough to generalize. Let's start with the phone -- how about propagating calls only from people I designate depending on time of day. How about an algorithm that helps me do that dynamically by analyzing my call patterns and presenting me with a prepared profile (so that I don't have to classify my contacts by hand).

  2. Excellent points!

    Michael Olson, a PhD student in CS at Caltech, has been working on an idea that he calls the Personal Information Broker that does some of the things you mention.