15
Jan

Cybernetics of Human Computer Interaction

   Posted by: dhcsoul   in cybernetics

Cybernetics of Human Computer Interaction

The Cybernetics of HCI: A Pragmatic Approach

This
video clip (approx 1 1/2 hours) gives a good introduction to the
circular causality studied by cybernetics and why it is more than just
control theory.  Lecture b
y Paul Pangaro, Sun Microsystems  

Seminar on People, Computers, and Design
Stanford University February 15, 2001

A discussion of cybernetics for HCI is pragmatic by nature because
cybernetics is a “science of interactions” for which human-computer
interaction is a subset. The ability of cybernetics to model the
progression and limitations of human communications holds insight for
difficult problems such as HCI design.

As we all know, semantic information processing by machine hasn't
yet been achieved and today's technology is incapable of conversing with
humans. Human-computer interaction is a means to the end of
human-to-human exchange (messaging), human-to-team (collaborative
work), or human-to-self (learning). One could paraphrase the goal of
HCI therefore as supporting effective human-through-computer
interaction. Interactions of hands and eyes to input and screen are
necessary but unfortunate intermediations. What we want are our wants
to be manifest. With its practical tools for modeling purpose,
feedback, and autonomy, cybernetics has something to offer.

Early cybernetics was responsible for the now-common but once
startling and revolutionary word “feedback”, along with the first
electronic “turtles”, and the first “learning machines.” From the 1940s
it held an even-handed consideration for either organic or machine
embodiments of intelligence. Neural nets arose here. In the 1950s, with
the ascendancy of the programmable computer and its theoretical
equivalencies to the nervous system, the fathers of cybernetics begat
the fathers of artificial intelligence. Then cybernetics turned inward
to consider the purpose, feedback functions, and limitations of
cybernetics itself — that is, to observe human observing. With the
1960s it grew into an applied epistemology, a discipline whose modeling
tools would crack the conundrum of subjectivity in a scientific frame.

With a sketch of theory and a smattering of screenshots, this talk
will position cybernetics as a means to sharpen understanding of
human-through-computer interactions in terms of:

  • conversation, defined as the rise and evolution of distinctions in a semantic space; and its dual,
  • intelligence, defined as a property of a system that can assert, achieve, and modify its goals.

Today's technology isn't doing much talking, but there is no a priori reason why conversations with
an artifact cannot be achieved. The key is a prescriptive model for
innovation, which is possible in today's cybernetics at least at an
architectural level. At the implementation level, it is a matter of
when, not if.

Paul Pangaro is a software
designer and performer. At MIT he programmed computer-graphics on
vector displays and one of the earliest color raster-scan machines, the
latter at Negroponte's research lab in the mid-70s. The disconnect
between symbolic programming and human expression forced an inquiry
that led to a Ph.D. in cybernetics from Brunel University (UK). He
founded a bi-continent software development company to build hypertext
browsers with fine-grained adaptation to user goals and learning
styles, under contract to US and UK agencies in the mid-80s. Pangaro
was engaged by clients such as Du Pont and Lotus Development Corp to
consider wider questions about the role of information technology in
what is now called “the new economy.” In dot-com startups he worked as
CTO and prototyped desktop knowledge navigators. He is currently Senior
Director at Sun Microsystems where he manages the group that delivers
content and services to developers.- goto

originally Posted to cep.weblogger.com by David Soul on 1/7/05; 8:23:55 PM
in the CEP section.

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Tags: CEP, cybernetics, design, discipline, feedback, goals, HCI, insight, intelligence, knowledge, learning, model, science, semantics, software, Systems

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