1. Agents & Agency What do we mean by agents? Are agents just a metaphor?
Science Fiction?
Physical or Virtual?
Are agents just a metaphor?
By defining agents are we defining intelligence?
Replacing people with agents
Replacing systems with agents
Agents force us to discover & address tacit knowledge (experience) in knowledge work

2. Agents are here
We’ve been using agents and agent like technology for a long time.

3. That’s agents, not robots

4. What kinds of agents are there?
Intelligent Agents
Show “intelligence” in interacting with the environment
Act based on previous facts or rules
Make leaps of intuition
Do things for you
Autonomous Agents
Interact with the environment
Stimulus & response, not always rules
Can perform a wider range of activities over time
Do things we do not or can not do

5. Agents & Angels Agents as help to manage information
Agents also are creating lots of new data
Possible uses
Managing our social life
Replace conventional organizations
Helping us find things (web crawlers)
Performing repetitive information tasks
A human face on information tasks?
Jeeves, Watson, Sherlock, Eliza, the Wizard
Pushes our interaction into something more “natural”

6. Agents or Angels? Who manages the agents? When is a decision made?
Upon arrival of the information
After information is compared
Blink vs. DeepThought
Is it possible to make our information use behavior transparent?
Is it flattering?
What if we find too much information?
Enabling more knowledge work or just more work?
Speed vs. Accuracy

7. Ranks of Agents Information Brokering Product Brokering
Networks & the Web
Search & Overload Management
Product Brokering
Shopping (Buying?)
Recommendations / Collaborative Filtering
Merchant Brokering
Personalization, Customer “service”
Logical, naïve decisions & gaming
Negotiating
Multi-part decisions
Conversation?

8. Autonomy & Agents Delegating
“Do this every time”
“More like this”
“Buy when AUS to LAX = $300”
How subtle is this kind of (tacit) work / decision making?
Agents interacting with each other
Negotiations between systems
APIs, crawlers, auction bots, reminders
Semantic Web
Cancelbots (“Nots”)
Easier to say “no” than “yes”

9. Autonomous Interface Agents
Both showing & doing things for users
A combination of classical Artificial Intelligence & Human Computer Interaction
Interact with the interface & the user
Any program acting as an assistant with learning, inference, adaptibility, independence, creativity, etc. Lieberman p 1
More examples
Contextual help, tutoring systems
Filtering, Highlighting systems
Autonomous agents operate in parallel with the user

10. How agents should work
Observe interface actions & act
Run “in the background” to
Manipulate information (& the interface) for you
Why this personalized view of agent interactions?
Understanding one person is difficult enough
Group interactions require making relationships explicit

11. Letizia - a surfing agent
Watching what you surf
Predicting where you might go
Searching for you as links
Another type of memory about what you do

12. Design principles for agents
Suggest rather than act
Take advantage of information the user gives the agent “for free”
Take advantage of the user’s think time
Problems with agents
The user’s attention may be time shared
Provide context for input
Use the interface to show history & state
Deliberation vs. Action
Sufficient data for a decision
Waiting, watching & doing
Cognitive style differences
Agents may not fit user’s mental models
Distraction (over time?)

13. Social Filtering with Agents
SOaP - a system of agents to mediate between people, groups & the Web
Privacy issues among people & businesses
Smart Groupware?
Collaborative Filtering + Agents?
Coordinating knowledge work?
Matching user interests
Agents specialize in the system
Supports groupwork automatically

14. Social Information Filtering
Can a system replace “word of mouth”?
Quality of information, not frequency
Volume of information, broader perspectives
Is the best information digital?
Digital great for facts
Not to great for intuitions or wisdom
How do you code in organization culture?
A focus on user (interest) profiles
Helping you understand what you’re already doing
Large numbers help reveal quality
Are we already used to recommendations?

15. Reducing Information Overload
Most apt use of agents in the last 10 years
Might be creating more information for us to manage
Increases explicit knowledge,but tacit?
We need agents to help do things in real time, without our intervention
The Web & agents are a good match
Understanding behavior & training agents
Watching, examples, (others) profiles
Not filtering as much as ordering
Might be most interesting to see others’ agents, not your own

16. How might people use agents?
Do we need more complexity to create simplicity?
How long will it take before we don’t worry about agent imperfection?
Ensure control
Meet privacy considerations
Safeguards for actions
Meet (& communicate) expectations
Show actions, but hide complexity
Build confidence slowly
Social acceptance of agents (organizational expectation)

17. Blogs & Social Dimensions
Are blogs taking the place of newsgroups?
RSS Readers
Topic discovery methods
Blog rolls
Search engines
Links
Issues of Awareness
Posting technologies s. Usenet