Friday, July 24, 2009
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  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  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.)
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
Saturday, July 18, 2009
Smart systems are based on models of their environments. Even a bacterium, as it swims towards its food, has an implicit model of its environment – its model says that a certain chemical gradient implies that food is probably available in that direction. The smart energy grid is based on a model of generation, transmission, distribution, and consumption of electricity.
MODELS AND REALITY
Smart systems must use models because no human-designed system can have a complete representation of its environment; the model may be implicit or explicit, but every smart system is based on a model. Designers of smart systems must acknowledge that their models may misrepresent or ignore critical features of reality. Whether smart systems deal with options trading, baggage handling, medical alerts or earthquake response, smart system vendors and their customers should be aware of the premises upon which a smart system is based.
IMPACT OF MODELS
The model determines what sensors are used and where they are placed, how measured data is analyzed to determine appropriate responses, and the types and locations of responders. When an organization implements a smart system or acquires one from a vendor, the organization uses (possibly implicit) cost-benefit analyses based on models of the system and its environment. Models, implicit or explicit, have a deep impact because they influence whether a smart system is implemented or not. But, most people are not aware of the pervasive role of models in smart systems.
PROBABILISTIC MODELS AND RARE EVENTS
In many cases, models of the environment are probabilistic. Smart systems help organizations exploit opportunities and protect against threats; they are most useful when they help exploit unusually good opportunities and protect against unusually severe threats. But, unusual events are rare and generally don’t occur in a predetermined way. So, most models of smart systems and their environments are fundamentally probabilistic, and some models deal with probabilities of rare events. Decision-making under uncertainty, when the uncertainty is about rare events, is difficult; perforce, analyses and models of smart systems that respond to rare, but very critical events, are complex.
Designers may change models on which their systems are predicated, and so smart systems may be changed as well. Some systems may use machine learning to adapt to changes in their environments automatically; but even so, the process of machine learning is itself based on a model. As in all human endeavors based on models of reality, users of smart systems should check whether the assumptions upon which smart-system models are predicated are likely to remain valid in the future.
MODELS ARE GOOD; SMART SYSTEMS ARE GOOD
None of the ideas on this page are new – they have been propounded for decades by control theorists, and operations researchers studying decision making under uncertainty. What is new, however, is the variety of applications of smart systems ranging from smart roads to ensuring sustainable fish habitats. Smart systems amplify our human ability to sense and respond effectively and intelligently to our world. The use of models is necessary and good. The homo sapiens species is the modeling species – to be sapient is to build abstractions, i.e., models. Vendors and users of smart systems should remain aware of the differences between models and reality, and should continue to verify that their models retain fidelity.
Thursday, July 9, 2009
Organizations sense and respond to their environments
Living things thrive if they sense what is going on in their environments and respond effectively. A bacterium that doesn't sense the presence of food in its vicinity will perish. A zebra that runs away frequently from non-threats will die of exhaustion, and one that doesn't run away from a real threat will die too. Effective sense and response are characteristic of successful organisms and organizations. Smart systems, for the purposes of these notes, are systems integrated with information technologies that help us sense and respond better.
Collective sense and response
Organizations sense and respond collectively. Lions in a pride signal each other and respond collaboratively when they hunt. People in companies collaborate to deal with unexpected events such as sudden changes in revenue. Countries deal with crises such as hurricanes by harnessing capabilities of local governments, corporations, charities and individuals. Smart systems help groups to sense and respond cooperatively.
Roles of Sympathetic and Parasympathetic Nervous Systems in Sense and Response
Mammals, including humans, sense and respond by using the sympathetic and parasympathetic nervous systems. The sympathetic nervous system mediates the "fight or flight" response. When an animal senses prey or aggressors, its sympathetic nervous system triggers intense responses. By contrast, the parasympathetic nervous system helps manage ongoing functions such as digestion - for example, it senses food in the mouth and controls secretion of salivary glands. The sympathetic and parasympathetic nervous systems are complementary; animals need all their resources to fight or fly as the need arises, and they must also control routine activity. Smart systems improve an organization's sympathetic and parasympathetic nervous systems; they are used to sense and respond to both unusual situations and routine activities. For example, RFID (radio frequency ID) tags on bags helps routine transfer of bags to and from planes in airports, but baggage-handling systems also help isolate dangerous cargo.
Sense and respond anywhere, anytime, with anybody, in fractions of a second
When our ancestors hunted millennia ago their hunting parties sensed and responded to threats and opportunities. They saw as far as the eye can see. Today systems allow us to sense activity deep in the oceans and far out into space. Our ancestors threw spears as far as their muscles would let them. Today our responses reach across the globe: traders in London respond to conditions in Shanghai to buy stock on the New York stock exchange. Our ancestors hunted during the day while they could see. Today we work or play around the clock. We sense and respond to our environments just as our prehistoric ancestors did; however, information systems have amplified our sense and response capability many thousand fold - we sense and respond anywhere on the planet, at any time, with anybody, with greater accuracy, and in seconds.
The next two decades will see development of technologies that continue amplify our abilities to sense and respond dramatically.