1. Human-Machine Reconfigurations
Plans and Situated Actions

2. Preface to 1st Edition European and Trukese navigators Interpretations
Caricatures of plans and situated action
Interpretations
Cultural differences in purposeful action
Nature of activity and level of expertise
However planned, purposeful actions are inevitably situated actions
Talk vs. walk, plans are also explanations of action generated for communication
The caricature of western navigation is
“reified in the design of intelligent machines”

3. Interactive Artifacts

4. Shared Understanding & Mutual Intelligibility
Interpretation of action the field of social studies
Goal is to come up with accounts of the significance of human action
As part of this, so is the study of how individuals understand one another’s actions
Study how members of society accomplish mutual intelligibility of action
Relationship between observable behavior and processes that make it meaningful
Behavior/action can be part of indefinite number of meanings/goals
Goals can be achieved through indefinite number of behaviors

5. Understanding Mutual Intelligibility
Relation between actions and the reasoning processes that make them meaningful
In psychology – cognitive focus on formation of beliefs, desires, intentions, etc.
In social studies – focus on interpersonal (inter-agent) relationships and relations with the environment
Relationship to Simon’s notion of interface

6. Practical vs. Theoretical Goals of AI
Different meanings ascribed to Strong AI
Machines that reason in the same way as humans
Machines with an intelligence that matches or exceeds that of humans
Weak AI
Develop systems whose behavior appears intelligent regardless of how it is achieved
Perhaps deep understanding is required for either

7. Interactive Artifacts
Computer as evocative object (Turkle)
Children’s view of computers as blending of
Physical: things we build, design, use
Social: things we communicate with
Human-computer interaction/communication implies mutual intelligibility
Need to answer how this works for humans before considering machines

8. Cognitive Science and Automata
Automata brought focus on how the structure of an agent generates observable behavior
Mind viewed as neither substantial nor insubstantial but as an abstraction
Introspection-> behaviorism -> cognitive science
Cognitive science combines discussion of
“beliefs, desires, symbols, schemata, planning, problem solving” with scientific method
Testing of cognitive models sufficiency on computers
Often results in a view of intelligence as the manipulation of symbols

9. Human-Computer Interaction
History:
batch processing -> interactive computing -> shared languages
Uses terms from human interaction
Hayes/Reddy say difference is robustness
Ability to respond to unanticipated circumstances
Ability to detect and remedy troubles in communication
Said no graceful systems exist but components are there
Abilities cited are necessary but not sufficient
Work done was in limited domains

10. Should Interaction be Human-like?
Benefits
More natural
More accessible to those that are new to or shy away from technology
Costs
Might conceal miscommunication
May not allow taking advantage of strengths of partners
People have a tendency to assume more capability than shown to exist
Opaqueness of computer also results in reification
Is intentional vocabulary a shortcut?

11. Self-Explanatory Artifacts
Machines should be able to explain goals and relations of actions to goals
Self-explanatory as:
Obvious/discoverable, e.g. a hammer
Able to explain itself, e.g. training applications
Need to know when not to say things
WEST
Watched student and only interrupted when viewed appropriate

12. Understanding Computers
Computer as artifact designed for a purpose
Increasing use of computers means increasingly complex technology should be usable with decreasing training
Purposes are not always obvious (e.g. archeology)

13. Instruction as a Goal
Face-to-face training relies on specifics and context (different each time)
Tailored to current needs
Written instruction relies on generalization
Reusable for large number of people and situations
Interactive systems can be both reusable and individualized
Example of WEST

14. Computers as Purposeful
Artifacts as presenting not just purposes of users or designers but having their own goals
Designer builds system to be accountably rational
History of Turing Test
Does not care about similarity of process
ELIZA as limited success (Weizenbaum denied intelligence)
DOCTOR (Rogerian therapist) – people assumed reasons even if none existed
Eliza conceals lack of understanding where “graceful interaction” requires it to be made explicit