Thanks to Don Norman for sharing the intro to his new book, in which he comments on the pervasive impact of design and suggests that the impact may not always lead to more satisfying, high-quality experiences. He goes on to suggest that there is a need to change how we teach design. While I agree with Don, I believe that the problems are not specific to Design Education. I would argue that the problems are pervasive across the board, when it comes to university education.
Current educational systems are organized around disciplines and techniques. The emphasis on HOW has left little room for consideration and discussion of WHY. The emphasis on technical skills has left little room for consideration and discussion of philosophy, little room for explorations of fundamental questions about the nature of experience. For example, I have been shocked to discover that many students trained in systems engineering are clueless about general systems thinking. And I have long regretted the emphasis in the cognitive sciences on experimental and modeling methods at the expense of considerations of the philosophical roots of the science.
Current educational systems have been designed around selling answers and solutions - rather than around exploring questions. The educational systems have been organized around authority based on POWER and POLITICS, rather than authority based on CURIOSITY and EXPERIENCE. We need new educational systems designed around LEARNING, rather than around TEACHING.
Yes, Don Norman is right, but I hope people don't place the blame exclusively on Design Education and I hope they don't look exclusively to Design Education for the solution. Perhaps, Designers are the people who are best suited to lead the revolution. But the problems Don describes will ultimately require a more pervasive change to universities. It will require us to tear down the walls that separate disciplines and it will require educators, in general, to be more humble with respect to the current answers that they are selling. It will require educators to listen more carefully to the questions their students are asking. It will require re-envisioning education to be a process of co-exploration across generational perspectives - rather than a process of passing answers and techniques from one generation to the next.
With respect to the logic of block diagrams, the four diagrams above are all identical. Thus, the similarities illustrate that the four paradigms all accept that cognition involves a circular coupling among the various component processes. Despite this consensus, there are striking differences about how the four different paradigms view the dynamics of cognition. This is reflected in which components are considered to be 'driving' the forward loop and which components are considered to be consequences in the feedback loop.
Classical Information Processing - tends to start with perception as the stimulus that leads ultimately to a choice (decision) that sets the goal for action. This reflects the residuals of a stimulus-response model. In this model, the function of cognition is to generate a 'plan' that directs action.
Cognitive Science - tends to focus on the internal cognitive processes (e.g., mental models or schema) and the associated intentions as the 'central processor' where all the interesting action happens and tends to treat perception and action as peripherals. In this approach, the mind is a disembodied computational system and focus is on the brain as the central controller of human performance.
Hypothesis/Abduction - reflects the long neglected pragmatic perspective associated with Peirce, James, and Dewey. This perspective starts with action as a 'guess' or 'test of a hypothesis' - that is measured against the practical consequences that follow. If the hypothesis leads to satisfying consequences the 'idea' or 'habit' is strengthened, otherwise an alternative hypothesis is considered. Note that while this has clear similarities with behaviorism - the key difference is that 'ideas' are strengthened - not mindless actions. These ideas reflect an ability to generalize about the world in ways that lead to improved fitness. A key distinction from traditional cognitive science is that cognition makes sense of the relation between action and consequences after the fact. Cognition is part of the feedback loop. Mercier and Speber (2007) have more recently made the case that reasoning is a post hoc phenomenon for making sense of our behavior.
Ecological Psychology - reflects the intuitions of JJ and EJ Gibson. They focused on the coupling of perception and action as the central issue for psychology - and delegate cognition and intention to the periphery. This is the central thesis of JJ's theory of direct perception which posits that there are structures in the perceptual array that directly specify the possibilities and consequences for action (i.e., the affordances) without the need for interpretation or mediation via mental models. This is also reflected in EJ's theory of perceptual learning in which expertise results from perceptually tuning to the relevant perceptual information, rather than in storing memories and constructing mental models.
For me, the key is to recognize the circularity of the coupling among the various components. Once this is recognized, the contradictions and points of contention among the various approaches take on a quite different flavor. Once it is recognized that all of these different approaches are talking about the same circle - then it becomes easier to appreciate the value of each perspective, to discover the common ground, to pull the signals from each of the four perspectives, and to filter out some of the debates and arguments that unproductively circle the same tree over and over.
With respect to the logic of block diagrams, the four diagrams above are all identical. Thus, the similarities illustrate that the four paradigms all accept that cognition involves a circular coupling among the various component processes. Despite this consensus, there are striking differences about how the four different paradigms view the dynamics of cognition. This is reflected in which components are considered to be 'driving' the forward loop and which components are considered to be consequences in the feedback loop.
Classical Information Processing - tends to start with perception as the stimulus that leads ultimately to a choice (decision) that sets the goal for action. This reflects the residuals of a stimulus-response model. In this model, the function of cognition is to generate a 'plan' that directs action.
Cognitive Science - tends to focus on the internal cognitive processes (e.g., mental models or schema) and the associated intentions as the 'central processor' where all the interesting action happens and tends to treat perception and action as peripherals. In this approach, the mind is a disembodied computational system and focus is on the brain as the central controller of human performance.
Hypothesis/Abduction - reflects the long neglected pragmatic perspective associated with Peirce, James, and Dewey. This perspective starts with action as a 'guess' or 'test of a hypothesis' - that is measured against the practical consequences that follow. If the hypothesis leads to satisfying consequences the 'idea' or 'habit' is strengthened, otherwise an alternative hypothesis is considered. Note that while this has clear similarities with behaviorism - the key difference is that 'ideas' are strengthened - not mindless actions. These ideas reflect an ability to generalize about the world in ways that lead to improved fitness. A key distinction from traditional cognitive science is that cognition makes sense of the relation between action and consequences after the fact. Cognition is part of the feedback loop. Mercier and Speber (2007) have more recently made the case that reasoning is a post hoc phenomenon for making sense of our behavior.
Ecological Psychology - reflects the intuitions of JJ and EJ Gibson. They focused on the coupling of perception and action as the central issue for psychology - and delegate cognition and intention to the periphery. This is the central thesis of JJ's theory of direct perception which posits that there are structures in the perceptual array that directly specify the possibilities and consequences for action (i.e., the affordances) without the need for interpretation or mediation via mental models. This is also reflected in EJ's theory of perceptual learning in which expertise results from perceptually tuning to the relevant perceptual information, rather than in storing memories and constructing mental models.
For me, the key is to recognize the circularity of the coupling among the various components. Once this is recognized, the contradictions and points of contention among the various approaches take on a quite different flavor. Once it is recognized that all of these different approaches are talking about the same circle - then it becomes easier to appreciate the value of each perspective, to discover the common ground, to pull the signals from each of the four perspectives, and to filter out some of the debates and arguments that unproductively circle the same tree over and over.
Four years ago, I left academia to join a small design startup, Mile Two. Ironically, after more than 30 years in academia teaching about applied cognitive psychology, human factors and cognitive systems engineering, it feels like my education on design has just begun. I discovered that essential people on our design teams were trained very differently than I was and brought skills and talents to the team that I was lacking. I recently collaborated with some of these teammates on a chapter to reflect on some of the different perspectives that contribute to the development of software to support cognitive work. The first figure was our attempt to summarize some of the different disciplinary perspectives and the second figure is a more elegant revision of that figure suggested by my friend and colleague Fred Voorhorst.
Figure 1. Multiple perspectives on design from Flach, Bennett, Butler & Heroux (In press Handbook of Human Factors).
Figure 2. Multiple perspectives on design by Fred Voorhorst.
These diagrams suggest four classes of constraint that must be considered in the design and development process:
Agency Constraints: These are properties of the "agents" in the system. Traditionally, the agents have been humans, but as machines becoming increasingly autonomous - we now have to consider the internal constraints of these autonomous agents.
Implementation Constraints: These reflect properties of the computers that will host the software. They include things such as the types of displays and the control/input devices.
Functional Constraints: These are properties of the work domains or the problem spaces that are the targets for the cognitive work. These include the physical, regulatory, and organizational dynamics that limit the range of possible actions and consequences.
Aesthetic Constraints: These are properties of the psychological and cultural values that determine the degree of satisfaction or frustration associated with using the software products.
All of the four disciplines, at least implicitly, recognize the full range of constraints, however, each discipline tends to emphasize a subset of these constraints in training and practice.
Human Factors [HF] tends to emphasize the constraints associated with human agency. That is, the focus is on specifying the physical [e.g., reach envelops], perceptual [e.g., visual acuity] and cognitive [e.g., working memory capacity] limitations of humans, so that these limitations are respected in the final design.
User Interface Design [UI] or Human Computer Interaction [HCI] tends to emphasis the impact of various computer capabilities on performance. For example considerations include types of displays [e.g., table-top, large-screen, hand-helds, or head mounted], types of controls [e.g., keyboard, mouse, game controller, touchscreen], and types of mediation [e.g., co-located or distributed via internet].
Cognitive Systems Engineering [CSE] focuses on the problem or work domain constraints. This involves describing the means-ends relations in terms of affordances and exploring alternative strategies or heuristics that might be used to efficiently navigate the functional space.
User-eXperience Design [UX] tends to consider the larger psychological and cultural context of use that impacts people's self-image and sense of satisfaction when using the design product.
I come from an HF perspective and was involved in the early development of the CSE perspective. Thus, much of my career has been spent arguing for the value of a CSE perspective for filling gaps in the design space that I felt were not adequately addressed by the HF perspective. The point was not that the HF perspective was wrong, but that it was not sufficient.
However, over the last few years spent developing software products I have come to realize that even the combination of HF and CSE leaves many gaps in the design space that require skills and perspectives associated with UI and UX design. I realize that my sense of the full demands of design were still quite naive and inadequate.
I now regret that I did not have and was not able to give my students a broader sense of the full breadth of the design challenge. Yet, I realize that it would be impractical to cover the full breadth of design in any reasonable course of study. Thus, much of the education must continue beyond the formal course work. And ultimately, I have come to the conclusion that design is a team sport that requires a diverse set of perspectives and people who are open to and who welcome alternative perspectives. To function on such a team I have had to dampen my tendencies to be an advocate for a particular perspective and I have had to heighten my ability to listen to and appreciate the value of alternative perspectives.
Four years ago, I left academia to join a small design startup, Mile Two. Ironically, after more than 30 years in academia teaching about applied cognitive psychology, human factors and cognitive systems engineering, it feels like my education on design has just begun. I discovered that essential people on our design teams were trained very differently than I was and brought skills and talents to the team that I was lacking. I recently collaborated with some of these teammates on a chapter to reflect on some of the different perspectives that contribute to the development of software to support cognitive work. The first figure was our attempt to summarize some of the different disciplinary perspectives and the second figure is a more elegant revision of that figure suggested by my friend and colleague Fred Voorhorst.
Figure 1. Multiple perspectives on design from Flach, Bennett, Butler & Heroux (In press Handbook of Human Factors).
Figure 2. Multiple perspectives on design by Fred Voorhorst.
These diagrams suggest four classes of constraint that must be considered in the design and development process:
Agency Constraints: These are properties of the "agents" in the system. Traditionally, the agents have been humans, but as machines becoming increasingly autonomous - we now have to consider the internal constraints of these autonomous agents.
Implementation Constraints: These reflect properties of the computers that will host the software. They include things such as the types of displays and the control/input devices.
Functional Constraints: These are properties of the work domains or the problem spaces that are the targets for the cognitive work. These include the physical, regulatory, and organizational dynamics that limit the range of possible actions and consequences.
Aesthetic Constraints: These are properties of the psychological and cultural values that determine the degree of satisfaction or frustration associated with using the software products.
All of the four disciplines, at least implicitly, recognize the full range of constraints, however, each discipline tends to emphasize a subset of these constraints in training and practice.
Human Factors [HF] tends to emphasize the constraints associated with human agency. That is, the focus is on specifying the physical [e.g., reach envelops], perceptual [e.g., visual acuity] and cognitive [e.g., working memory capacity] limitations of humans, so that these limitations are respected in the final design.
User Interface Design [UI] or Human Computer Interaction [HCI] tends to emphasis the impact of various computer capabilities on performance. For example considerations include types of displays [e.g., table-top, large-screen, hand-helds, or head mounted], types of controls [e.g., keyboard, mouse, game controller, touchscreen], and types of mediation [e.g., co-located or distributed via internet].
Cognitive Systems Engineering [CSE] focuses on the problem or work domain constraints. This involves describing the means-ends relations in terms of affordances and exploring alternative strategies or heuristics that might be used to efficiently navigate the functional space.
User-eXperience Design [UX] tends to consider the larger psychological and cultural context of use that impacts people's self-image and sense of satisfaction when using the design product.
I come from an HF perspective and was involved in the early development of the CSE perspective. Thus, much of my career has been spent arguing for the value of a CSE perspective for filling gaps in the design space that I felt were not adequately addressed by the HF perspective. The point was not that the HF perspective was wrong, but that it was not sufficient.
However, over the last few years spent developing software products I have come to realize that even the combination of HF and CSE leaves many gaps in the design space that require skills and perspectives associated with UI and UX design. I realize that my sense of the full demands of design were still quite naive and inadequate.
I now regret that I did not have and was not able to give my students a broader sense of the full breadth of the design challenge. Yet, I realize that it would be impractical to cover the full breadth of design in any reasonable course of study. Thus, much of the education must continue beyond the formal course work. And ultimately, I have come to the conclusion that design is a team sport that requires a diverse set of perspectives and people who are open to and who welcome alternative perspectives. To function on such a team I have had to dampen my tendencies to be an advocate for a particular perspective and I have had to heighten my ability to listen to and appreciate the value of alternative perspectives.
I've spend much of my career exploring how representations can be designed to help people to manage and control complex systems. The goal has been to use representations to increase perspicacity and to help people to 'see' what matters with respect to the situations that they are managing.
So it makes me sad and angry to see people intentionally use graphics to hide information and to purposely mismanage situations. In this case, in a way that can have severe consequences. Look at these two graphics and note how the graphical images are intentionally manipulated to misrepresent the COVID situation in the state of Georgia. This manipulation is intentionally designed to create the impression that there is no increasing risks of COVID in the state of Georgia. This manipulation is being used to justify policies and decisions that threaten the health of people in Georgia.
The graphic below is a more current version. Note the numbers continue to increase, but the graphic remains much the same - small red spots in a sea of blue. Note that the stated intention of the graph is to "aid understanding whether the outbreak is growing, leveling off, or declining...." But of course, the increases across these graphs will be hidden, as long as the color-to-number-mapping changes to accommodate the increasing number of cases.
In my view, the public officials responsible for these graphics are criminally liable for intentionally misleading the public. I don't understand why every newspaper in Georgia is not calling out this deception and publishing corrected graphics that show the true state of the COVID situation. This is not the first time that state officials have presented misleading data. The image below is from a press conference in May to help make the case that things were getting better. Note that the dates on the x-axis are not chronological.
For those involved in designing technology - this illustrates the powerful impact that representations can have on how people think. And this is an important reminder that we have an ethical responsibility to use that power to enhance and improve human experience.
Last week, in the middle of the pandemic, the highly publicized police killings of black men, and the resulting protests and demonstrations I learned of the death of Professor Anders Ericsson. Professor Ericsson was a preeminent psychologist who studied the development of expertise. He was interested in the development of high levels of skill that allow 'experts' to do things that are beyond the capacity of most humans. In particular, his work was instrumental in illustrating that deliberate practice was critical in developing the heuristics that allow experts to become both faster and more accurate in processing information. In essence, because of these tricks of the trade, experts are able to avoid the information limits that bound the performance of most humans. This is the positive, good aspect of heuristics. These heuristics allow experts to focus onthe patterns (or chunks) that specify significant aspects of situations and to coordinate their action to respond automatically - quickly and accurately.
The term heuristic is also used to describe biases in decision making. As the extensive research of Kahneman and Tversky demonstrates, heuristics can lead people to make choices that violate the conventions of traditional logic. Heuristics are a form of bounded rationality that apply within certain domains of activity. Thus, the automatic responses that work in one set of situations can seem illogical or mindless when they are applied in situations outside that domain. This is the negative, bad side of heuristics - they can lead to performance that Jim Reason referred to as 'strong, but wrong.'
The ugly side emerges when we put people in domains where the circumstances lead them to develop heuristics or implicit biases that not only violate logic, but that violate our cultural values!
My father entered the Marines when he was 17 at the end of WW II. He only served for two years and never left the country. But in his forties, when someone tried to mug him on the street one night, he automatically responded as he had been trained - slash, kick, gouge! It thwarted the attack and may have saved his life.
There are many parallels in the training of police and soldiers - to prepare people to respond automatically to defend themselves and to survive potentially deadly situations. It is very tempting to attribute these mindless responses to evil intent of individuals, but we might consider that these implicit biases are a product of training and socialization. These biases are the result of years of deliberate practice!
In some cases, the violent acts that we see on the cell phone videos are the result of many years of deliberate practice, that result in mindless responses to situations. The implication is that the problem of police violence is not simply a function of a few bad apples, but the product of a system that deliberately trains mindless responses to threatening situations.
In hindsight, it is easy to attribute the clearly mindless violence to evil intent. But, at least in some cases, consider that these mindless responses are the product of a system of training designed for soldiers, not for peace officers. We want to blame the officer, but this will not ultimately solve the problem of police violence. Ultimately, we must change the system and reconsider what type of skill training is most important for creating expert peace keepers, rather than expert soldiers.
Last week, in the middle of the pandemic, the highly publicized police killings of black men, and the resulting protests and demonstrations I learned of the death of Professor Anders Ericsson. Professor Ericsson was a preeminent psychologist who studied the development of expertise. He was interested in the development of high levels of skill that allow 'experts' to do things that are beyond the capacity of most humans. In particular, his work was instrumental in illustrating that deliberate practice was critical in developing the heuristics that allow experts to become both faster and more accurate in processing information. In essence, because of these tricks of the trade, experts are able to avoid the information limits that bound the performance of most humans. This is the positive, good aspect of heuristics. These heuristics allow experts to focus onthe patterns (or chunks) that specify significant aspects of situations and to coordinate their action to respond automatically - quickly and accurately.
The term heuristic is also used to describe biases in decision making. As the extensive research of Kahneman and Tversky demonstrates, heuristics can lead people to make choices that violate the conventions of traditional logic. Heuristics are a form of bounded rationality that apply within certain domains of activity. Thus, the automatic responses that work in one set of situations can seem illogical or mindless when they are applied in situations outside that domain. This is the negative, bad side of heuristics - they can lead to performance that Jim Reason referred to as 'strong, but wrong.'
The ugly side emerges when we put people in domains where the circumstances lead them to develop heuristics or implicit biases that not only violate logic, but that violate our cultural values!
My father entered the Marines when he was 17 at the end of WW II. He only served for two years and never left the country. But in his forties, when someone tried to mug him on the street one night, he automatically responded as he had been trained - slash, kick, gouge! It thwarted the attack and may have saved his life.
There are many parallels in the training of police and soldiers - to prepare people to respond automatically to defend themselves and to survive potentially deadly situations. It is very tempting to attribute these mindless responses to evil intent of individuals, but we might consider that these implicit biases are a product of training and socialization. These biases are the result of years of deliberate practice!
In some cases, the violent acts that we see on the cell phone videos are the result of many years of deliberate practice, that result in mindless responses to situations. The implication is that the problem of police violence is not simply a function of a few bad apples, but the product of a system that deliberately trains mindless responses to threatening situations.
In hindsight, it is easy to attribute the clearly mindless violence to evil intent. But, at least in some cases, consider that these mindless responses are the product of a system of training designed for soldiers, not for peace officers. We want to blame the officer, but this will not ultimately solve the problem of police violence. Ultimately, we must change the system and reconsider what type of skill training is most important for creating expert peace keepers, rather than expert soldiers.
It's the same temperature, as measured by the thermometer, but one person experiences miserable cold, while another experiences a refreshing chill. Which experience is 'true' or 'real.' Or are both experiences illusions (i.e., purely subjective)?
Most introductory psychology texts describe an experiment in which the participant leaves one hand in a bucket of ice water and another hand in a bucket of hot water for a few minutes, then simultaneously puts both hands into a bucket of water at room temperature. What happens? One hand experiences the water as being warm, while the other hand experiences the bucket as being cold.
Does this demonstrate that perception is illusionary? Or does it suggest that the experience of temperature is dynamic. That it reflects change, or relations over time (as opposed to isolated events in time).
Imagine two intersecting lines on a graph one sloping down and the other sloping up. At the intersection, both point values are identical - but the slopes are different. Classically, we have tended to treat human experience as if it were a collection of isolated points in time. Thus, we have failed to consider that the slopes may be different.
If experience is dynamic, then it is essential that we consider the points as integrated components of the line. Rather than isolating behavior in time, we need to examine behavior over time (we need to consider the lines).
From the perspective of dynamics, the experiences of both people can be real. Both experiences are partial functions of the current physical temperature (as measured by a thermometer), but they are also functions of different past histories and different potential futures (e.g., intentions). Though the temperature 'points' may be the same for both, the slopes may be very different. The experiences may be situated on different trajectories.
When the different experiences are dismissed as 'subjective,' there is an implication that all experience is illusionary. That experiences are groundless with respect to the objective physical situations (e.g., the objective temperature). That experiences are 'in the head.' However, if you view experience as a dynamic property over time (e.g., with both a position and a velocity or slope), then you can see that the differences may be due to the fact that both are grounded, but in different ways. In this context, both experiences can be considered to be 'real' (in the sense that they are grounded, but with respect to objectively different situations).
Note that (as with constructs such as affordance) the 'situation' is not purely physical (objective) or purely mental (subjective). Both the situation and the experience are dynamical phenomenon reflecting both where agents are coming from and where agents are going. And that trajectory is shaped by both objective physical properties (e.g., the temperature) and by mental properties (e.g., an intention).
Cognitive Science will resolve many mysteries and contradictions, if it will only connect the dots and begin to consider trajectories as the fundamental units of analysis.
It's the same temperature, as measured by the thermometer, but one person experiences miserable cold, while another experiences a refreshing chill. Which experience is 'true' or 'real.' Or are both experiences illusions (i.e., purely subjective)?
Most introductory psychology texts describe an experiment in which the participant leaves one hand in a bucket of ice water and another hand in a bucket of hot water for a few minutes, then simultaneously puts both hands into a bucket of water at room temperature. What happens? One hand experiences the water as being warm, while the other hand experiences the bucket as being cold.
Does this demonstrate that perception is illusionary? Or does it suggest that the experience of temperature is dynamic. That it reflects change, or relations over time (as opposed to isolated events in time).
Imagine two intersecting lines on a graph one sloping down and the other sloping up. At the intersection, both point values are identical - but the slopes are different. Classically, we have tended to treat human experience as if it were a collection of isolated points in time. Thus, we have failed to consider that the slopes may be different.
If experience is dynamic, then it is essential that we consider the points as integrated components of the line. Rather than isolating behavior in time, we need to examine behavior over time (we need to consider the lines).
From the perspective of dynamics, the experiences of both people can be real. Both experiences are partial functions of the current physical temperature (as measured by a thermometer), but they are also functions of different past histories and different potential futures (e.g., intentions). Though the temperature 'points' may be the same for both, the slopes may be very different. The experiences may be situated on different trajectories.
When the different experiences are dismissed as 'subjective,' there is an implication that all experience is illusionary. That experiences are groundless with respect to the objective physical situations (e.g., the objective temperature). That experiences are 'in the head.' However, if you view experience as a dynamic property over time (e.g., with both a position and a velocity or slope), then you can see that the differences may be due to the fact that both are grounded, but in different ways. In this context, both experiences can be considered to be 'real' (in the sense that they are grounded, but with respect to objectively different situations).
Note that (as with constructs such as affordance) the 'situation' is not purely physical (objective) or purely mental (subjective). Both the situation and the experience are dynamical phenomenon reflecting both where agents are coming from and where agents are going. And that trajectory is shaped by both objective physical properties (e.g., the temperature) and by mental properties (e.g., an intention).
Cognitive Science will resolve many mysteries and contradictions, if it will only connect the dots and begin to consider trajectories as the fundamental units of analysis.
