Personal reflections on architecture and human-centered design/data viz and data driven design.
Sheelagh Capendale, an expert in data
visualization, whose work has been revolutionary in exploring how researchers
investigate human behaviors in computer science, refers to her work as
“observation”. She claims that she works in science, but she learned to observe
in her background as an artist. She describes her experience as a young art
student, in her first photography course where the instructor gave the
excruciating assignment of asking students to photograph a blank wall; due in
three hours. She refers to the process as a painful lesson in observation, that
it wasn’t until after 2.5 hours of studying that wall, that the photos started
to emerge. That after hours of looking, she finally began to “see”.
Interestingly, she claims that she takes this same skill, the ability to “see”,
into her work as a researcher. That this skill is as useful in her career as an
internationally recognized scientist. Here, instead of photographing a wall,
she observes human behavior. She observes how domain experts, and (at times)
non-experts use visualizations of data. She uses multiple methodologies to
assist her in her observation: quantitative qualitative methods, established
and new. Even though this work is considered science, she uses the same skills
developed as an artist. Here I argue that this act of “observation” is a
learnable skill that and that adopting the posture of observation is admirable
across disciplines, and in particular, I focus its application in the practice
and theory of architecture.
Architecture is undergoing a paradigm
shift. This shift is likely propelled by post-modernism, a data revolution, new
modernism and a mass cultural shift towards pluralism, all of which is further
bolstered by the ubiquity of social media and the communication age. This shift
parallels the conceptual leap required of scientists in the centuries following
Galileo’s declaration that the earth is not the center of the universe. The
term “human-centered design” is not coincidental. For centuries, architects
have not questioned the assumption that their perception of the universe (no
matter how altruistic, or well-meaning) is the center of their inspiration. And
here it is folks: it is not.
In my experience, the mainstream of
architectural approaches do well at observing inanimate objects. Architecture
theory focuses on materiality, the generation of form and expression the poetic
as a spiritual marriage of idea and expression that will somehow inspire and
elevate civilization through a universal experience of the architecture as
expression. Louis Khan asked “what does the brick want to be?” Architects
ponder the nature of materials as a contemplative, expressive, exploration of
the emotive experience of texture, shape, and form. The power of form to
express the poetic is a well explored topic in architecture schools. I feel this has resulted in many architects
who have an uncanny level of skill and ingenuity with materials and an ability
to consciously manipulate the emotive, experiential effects of space, form and
visual information. As researchers, this same approach is manifested in the
philosophical approach of phenomenology. An approach that highlights and
emphasizes the bias of the observer. The personal, self-reflective experience
of space is the source of artistic inspiration, and the center (or starting
place) of knowledge. This is where, as I see it, the trajectory of
architectural theory has taken us. The architect at the center. A
self-reflective expert, who then projects his inspiration on the world through
his expression of experience through form.
While acknowledging bias is part of
the process of becoming a great observer, it is not the end point. True
observation is deeply concerned with understanding and learning the reality of
what lies beyond our own bias. Confirmation bias is a knowledge killer. The
reproducibility crisis in psychology research attests to the challenge of
assuming we know without double (or even better, triple checking). The dangers
of this can lead to mistakes. Mistakes made by people who are making decisions
about cities, hospitals, medicines, health, life and death. It’s not good.
In data visualization there is a
concept called “change blindness”. It is a well-researched phenomenon where
people will often not see something if they don’t expect it. In studies where
researchers replace actors without any hint of the replacement, or where there
is a visual change in an image or scene, participants who are focused on
something else, or not expecting the change - will not actually see it. The type
of observation Sheelagh Carpendale is referring to is one which uses all
available tools to overcome the natural tendency of change blindness. It is
being a good observer, acknowledging bias, grappling with one’s own ego to get
beyond what we think is in front of us - and ACTUALLY SEE WHAT IS THERE. It is
a personal practice as well as adopting iterative, painstaking, rigorous,
research methodologies to ensure our observations are as close a model of
reality as we can hope for. Interestingly, while artists might be excellent at
the former processes of self-reflection and emotive expression, scientists have
well established methods for the latter. Although, as one moves further into
the understanding observation, these divisions between disciplines is less
useful. Artist, researcher, designer or scientist, the act of well-honed
observation is critical to acquiring knowledge, understanding and innovation.
You may assume that true and great
inspiration comes from the ethos of the artist, designer or great scientist.
One may think this, because it is the narrative we have been told. The master
(male) artist, the great (male) architect, the genius (male) scientist, who
ponders existence, and finds inspiration through some magical moment of
inspiration. But this narrative, is, of course not true. Inspiration and
innovation is arrived at through a well-honed practice; that includes
self-reflection, observation, craft, time, pain and struggle. This is inspired
by a sincere and profound sense of curiosity. And though methods and objects
may differ, this process is the same whether a person is a scientist,
researcher, artist or designer.
All this said, architecture is a
deeply inquisitive practice and architects themselves are altruistic and
humble...or at least the ones I know are. Contrary to what I have just said,
architectural practice also has a long history of using data and methods of
inquiry in their practice, although this process has become periphery. While
the discipline has focused on the generation of form, one might wonder where
the “humans” are. Vitruvius in this seminal work about the philosophy or
architecture talks about the three pillars of architecture: beauty, function
and structure. While much of architecture research has highlighted the expressive
nature of structure and beauty, the practice of human observation responds to
the pillar of function. And while architecture research has yet to evolve into
the established academic institution familiar to the sciences, the discipline
has persisted by often disseminating new knowledge in neighboring disciplines
such as urban planning, geography, philosophy and design theory. While this
makes it difficult to define what architecture research is, it points to a
large amount of relevant, data-driven research that has impacted architectural
design culture and practice for generations... (this all leads to a discussion that I plan to continue to write about...stay tuned :) on
using spatial data in design, the love/hate relationship with environmental
psychology, the somewhat irrational fear of science on behalf of architects,
and awesome new relevant work that is generating new technologies and
methods for understanding complex behavior patterns using hierarchical
regression modeling and spatial data)
Architecture research needs to
incorporate rigorous empirical methods using quantitative data. Sheelagh
Carpendale is celebrated for her work in advocating for using multiple
mixed-methods in data visualization. This is not an argument for which method
is better. The nature of the inquiry and the research question dictates the
best method to adopt. I argue that architects and architecture researchers
should follow a similar trajectory as human computer interaction, and data
visualization - while bringing a unique-to-architecture layer of design
expertise. And while architectural research has primarily focused on
qualitative processes of inquiry, it is time for architectural design researchers to balance out
their practices and learn how to use (or at least benefit from) the tools of quantitative research. This
balance of methodology will help tip the balance of architecture research
towards the objectives of “human centered” design.
