Grand Challenge Problems and Opportunities for … · Grand Challenge Problems and Opportunities ... ethnography) Gerhard Fischer 16 University of Vienna, January ... multimodal presentation

Gerhard Fischer 1 University of Vienna, January 2011

Wisdom is not the product of schooling but the lifelong attempt to acquire it.

- Albert Einstein

Grand Challenge Problems and Opportunities for

Cognitive Informatics

Gerhard Fischer

Center for LifeLong Learning & Design (L3D), Department of Computer Science and Institute of Cognitive Science, University of Colorado, Boulder

Symposium „Defining Cognitive Informatics“, University of Vienna, January 11, 2011


Overview cognitive informatics: defining a context my background and experience grand challenges doing basic research on real problems (models and examples) basic message


Cognitive Informatics definition: the multidisciplinary study of cognition and information sciences,

investigating human and computational information processing mechanisms and processes

objective: explore foundations and develop technologies

o facilitate and extend the cognitive capabilities of individuals and groups through the development and application of novel concepts in human-system integration

o address cognitive bottlenecks (e.g., limitations in attention, memory, learning, comprehension, visualization abilities, and decision making)

multidisciplinary field focused on

o understanding natural systems (people) o designing artificial systems (information and communication technologies) o creating hybrids of the two: symbiotic systems, socio-technical environments


Related Disciplines Neuroscience Psychology (cognitive, social) Linguistics (natural language processing) Learning Sciences Cognitive Science Computer Science (Human-centered computing, Artificial Intelligence,

Distributed Cognition, Design)


Natural Science Sciences of the Artificial <<Herbert Simon: “Sciences of the Artificial”>>

natural science sciences of the artificial (= design)

- natural science: how things are; primary interest: analysis; examples: physics, chemistry

- design: how things ought to be - primary interest: synthesis - examples: engineering, medicine, business, architecture, painting,

universities, cognitive artifacts, notations Cognitive Informatics = part of the Sciences of the Artificial (Design)

taking findings from the natural sciences (e.g. neuroscience) into account - design problems are complex, ill-defined, have no (single) answer, unique (“a

universe of one”) - design leads to changes: “Philosophers interpret the world in various

ways; what matters is to change it!” — Karl Marx


Analyzing the Brain from a “Natural Science” Perspective


Time Frames in Human Computer Interaction source: Newell, A. & Card, S. K. (1985) "The Prospects for Psychological Science in Human-

Computer Interaction," Human-Computer Interaction, 1(3), pp. 209-242

Time Action Memory Theory (sec) (common units) 109 (decades) Technology Culture 108 (years) System Development 107 (months) Design Education 106 (weeks) Task Education

Social and Organizational

105 (days) Task Skill 104 (hours) Task Skill 103 (ten mins) Task LTM 102 (minutes) Task LTM

Bounded Rationality

10 (ten secs) Unit task LTM 1 (secs) Operator STM 10-1 (tenths) Cycle time Buffers

Psychological

10-2 (centisecs) Signal Integration

10-3 (millisecs) Pulse Summation

Neural And Biochemical


My Background and Involvement CU Boulder

o ICS: Institute of Cognitive Science (since 1982) o L3D: Center for LifeLong Learning and Design (since (1993) o DLC: Discovery Learning Center (since 2000) o ATLAS: Alliance for Technology, Learning and Society (since 2002)

Externally

o LIFE: Learning in Informal and Formal Environments (Stanford, Uni of Washington)

o MCLS: Munich Center for the Learning Sciences (LUM, TU) o STELLAR: European Network of Excellence for Technology Enhanced

Learning


MCLS: Munich Center for the Learning Sciences


A Sample of our Recent Research Projects design “A Meta-Design Framework for Participative Software Systems”

(funded by the NSF program “Science of Design”) distributed intelligence / design for all “CLEVER: Cognitive Levers —

Helping People Help Themselves” (funded by Coleman Institute for Cognitive Disabilities)

social creativity “A New Generation Wiki for Supporting a Research

Community in Creativity and IT” (funded by the NSF Program “Creativity and Information Technologies”)

lifelong learning “Transformative Models of Learning and Discovery in

Cultures of Participation” (funded by the NSF program “Cyber-enabled Discovery and Innovation”)


Beyond the Unaided, Individual Human Mind


Grand Challenges a Grand Challenge = a commitment by a scientific community to work

together towards a common goal — valuable and achievable within a predicted timescale

purpose and impact of a Grand Challenge: to change the discourse that

drives research and practice examples of Grand Challenges

o getting a human on the moon (1961; John F. Kennedy: declaring a national goal of “landing a man on the Moon” by the end of the decade)

o Grand Challenges in Environmental Sciences (a book published by National Academy Press in 2001)


Grand Challenges in Technical Computer Science versus Cognitive Informatics

High Performance Computing and Communications program (HPCC,

started 1991): o major problems of science and society whose solutions require 1000-fold or

greater increases in the power and speed of supercomputers o research and education relative to HPCC must link a broad range of sciences o multidisciplinary settings offer the best chance for success

HPCC: an “easy” (?) Grand Challenge Problem because:

o objectives are not controversial (increase speed of computation, increase storage capacity, increase bandwidth

o simple measurement of progress exist

Cognitive Informatics: a “difficult” (?) Grand Challenge Problem


Grand Challenges: Where Do They Come From? Marshall McLuhan: “I donʼt know who discovered water, but it probably wasnʼt a

fish” o beyond group-think o interaction with other disciplines

George Bernard Shaw: "The reasonable man adapts himself to the world.

The unreasonable man persists in trying to adapt the world to himself. Therefore all progress depends on the unreasonable man."

o think outside the box Winston Churchill: "This is not the end. It is not even the beginning of the end.

But it is, perhaps, the end of the beginning." o do not assume that we are done (e.g. the true potential of the Internet? it is

only 15–20 years old) o in which way can we look 15-20 years into the future??


Driving Forces behind Research in Cognitive Informatics

“New and deeper understanding does not start with perceptions, observations, or collections of data but it starts with problems.” — Karl Popper

fundamental problems (e.g.: aging populations, energy sustainability,

learning and education in the 21st century, creativity, ………….) visions (e.g.: Memex (Vannevar Bush, 1945); Dynabook (Alan Kay, 1972)) theories (e.g: about distributed cognition, design, learning, collaboration,

motivation, …..) systems / technologies (e.g.: personal computer, WIMP interfaces,

ubiquitous computing, table-top computing, socio-technical environments ) empirical approaches (e.g.: human factors research, ethnography)


Objective: Doing Basic Research on Real Problems —

Models and Examples real problems are systemic problems (transcending individual human minds

and individual disciplines) examples of real problems:

o from the “Renaissance scholar” to the “Renaissance Team” (or: from the “reflective practitioner” to the “reflective community”) collaboration

o from ”automate” to “informate” distributed cognition

o rethinking learning and education co-evolution of learning, new media, and

new learning organizations


The Fish-Scale Model for Collaboration “collective comprehensiveness through overlapping patterns of unique

narrowness” Campbell, D. T. (1969) "Ethnocentrism of Disciplines and the Fish-Scale Model of Omniscience."


Desired but Unrealistic — The Renaissance Scholar as “Superhuman” (being an expert in multiple domains)

Tools/Media Knowledge

Domain

Knowledge

high

low

low high


Realistic: Learning “something” about the Other Domain


Domain

Knowledge

high

low

low high


Objective: Reflective Communities


DomainKnowledge

high

low

low high

reflective community


Human Attention and Information scarce resource is not information but human attention — claim: “a design

representation suitable to a world in which the scarce factor is information may be exactly the wrong one for a world in which the scarce factor is attention”

attention from a neuroscience perspective information processing in the

brain attention from a Cognitive Informatics perspective

From “Anywhere, Anytime, Anyone”

“The Right Information at the Right Time, in the Right Place, in the Right Way to the Right Person”


The Right Information at the Right Time, in the Right Place, in the Right Way to the Right Person

right information: relevant to the task at hand task modeling right time: intrusiveness (pull versus push) right place: location-aware systems (e.g.: smart tour guides) right way: multimodal presentation (textual, visual, auditory, tactile) right person: taking background knowledge and interests of specific users into

account user modeling (“who do I ask and who do I tell”)


The Cognitive Science Department, Univ of California, San Diego —

a homogenous Community of Practice

Psychology Linguistic Cognitive Education Computer Science Science


The Cognitive Science Institute at the University Colorado: a heterogeneous Community of Interest

Psychology Linguistic

Education Computer Science


Cultures of Participation

consumer cultures focus: produce finished goods to be consumed passively

⇓ cultures of participation

focus: provide all people are with the means to participate actively in personally meaningful problems

impact: democratizing innovation, creativity, giving all people a voice, end-user development


L3D’s Research Supporting and Fostering Cultures of Participation table-top computing systems for framing and solving complex urban

planning problems theoretical frameworks

o meta-design = design for designers (supporting users in becoming active contributors)

o SER Model for open systems: seeding, evolutionary growth, reseeding examples:

o modeling all the buildings of the world in 3D (in collaboration with Google-Boulder: SketchUp +3D Warehouse)

o using Smart Grids to support energy sustainability o courses-as-seeds


The Envisionment and Discovery Collaboratory: A Socio-Technical Environment


Basic Message — Cognitive Informatics: An Important and Exciting Discipline for the Future

transcending the individual human mind collaboration (“Renaissance

Team”), cultures of participation identifying the most productive mix of distributed cognition (i.e., what tasks

or components of tasks are or should be reserved for educated human minds, and which can and should be taken over or aided by cognitive artifacts) socio-technical environments, symbiotic environments

shifting from a concern about who has access to new information technologies

to who will have the knowledge that will position them to design, create, invent, and use the technologies to enhance their personal lives and social worlds lifelong learning and education

challenge: create a branding and identity for a specific program (such as Cognitive Informatics at the University of Vienna)

with the objective of “Being a Leader versus a Follower”

Grand Challenge Problems and Opportunities for … · Grand Challenge Problems and Opportunities ... ethnography) Gerhard Fischer 16 University of Vienna, January ... multimodal presentation

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