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The Social Impacts of Intelligent Agents on Internet Use

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Title: The Social Impacts of Intelligent Agents on Internet Use


1
The Social Impacts of Intelligent Agents on
Internet Use
  • Alexander Serenko Mihail Cocosila
  • McMaster University, Canada
  • AoIR, Toronto 2003

2
Agenda
  • 1. The Purpose of the Study
  • 2. What are Intelligent Agents?
  • 3. Why Intelligent Agents?
  • 4. Social Impacts of Intelligent Agents on
    Internet Use
  • a) first-level impacts
  • b) second-level impacts
  • - user privacy
  • - economic impacts
  • - user confidence and trust
  • - online habits and behavior
  • - Web performance
  • - online social interactions
  • - online service providers
  • 5. Conclusions and Directions for Future Research
  • 6. QA

3
Introduction
  • The purpose of the study
  • To present a non-technical overview of
    intelligent agents technologies
  • To identify and classify several possible domains
    of the social impacts of intelligent agents
    Internet use
  • To briefly show the reasons why intelligent
    agents should ? (or should not ?) exist
  • To suggest directions of future research
  • It is the first attempt to discuss social
    implications of intelligent agent technologies on
    Internet use

4
What are Intelligent Agents?
  • Metaphor of intelligent agents
  • non-human electronic assistants
  • a newer form of software
  • possible to implement since the end of the past
    century
  • new dimensions in the Internet era
  • History of the concept
  • introduced by John McCarthy in the 50s
  • coined by Oliver Selfridge at the MIT Lincoln
    Laboratory
  • agent visionaries in the 80s
  • classic works in the 90s
  • human-agent cooperation metaphor after 2000

5
What are Intelligent Agents?
  • Intelligent agents as an ascription
  • characterized in terms of what users ascribe,
    attribute, or assign agents to be
  • agent exists only in the minds of people if
    individuals believe that they are delegating
    tasks to a particular software entity, this
    application is considered an agent
  • This paper follows a description approach
  • An intelligent agent is a software entity which
    is
  • continuous (long-lived)
  • autonomous (independent)
  • reactive (adapts its behavior under the changes
    in the external environment), and
  • collaborative (collaborates with other agents or
    electronic processes)

6
What are Intelligent Agents?
  • General types of intelligent agents
  • user agents
  • assist human users by interacting with them
    directly, knowing their preferences and
    interests, and acting on their behalf
  • Examples personal assistants, news editors,
    electronic shoppers, and Web guides
  • service agents
  • collaborate with different parts of a complicated
    computer system and perform more general tasks in
    the background being invisible for human users
  • Examples Web indexing, information retrieval,
    and phone network load balancing agents

7
Why Intelligent Agents?
  • Intelligent agents allow software users to
    utilize the indirect management approach rather
    than the previous less efficient direct
    manipulation method
  • Direct manipulation approach people explicitly
    indicate all tasks the application should
    perform, monitor the process, observe results,
    and intervene when necessary
  • Indirect management concept users are able to
    indirectly manage agents rather than directly
    manipulate objects agents, in turn, operate
    objects on users behalf and report back only
    final results thereby hiding tasks complexity
  • Important while dealing with complex,
    heterogeneous systems, and unpredictable systems
    such as the Internet

8
Social Impacts of Intelligent Agents
  • Every technological invention has dual effects
    on an individual, society, organization, group,
    or other social entity
  • First level effects
  • presumably positive outcomes
  • always anticipated by technology inventors
  • usually considered justifications of investments
  • Examples dramatic cost reduction, improved
    quality, or the introduction of new products and
    services
  • Second level effects
  • can never be totally envisioned by researchers,
    innovators, and entrepreneurs
  • natural consequence of altering peoples
    behavior, creating new values, expectations, and
    norms

9
Social Impacts of Intelligent Agents
  • Web User Privacy
  • Extremely important for proper functioning of
    modern society characterized by skyrocketing
    information exchange rates and availability of
    information collection tools and techniques
  • Two basic ways intelligent agents obtain
    information about people
  • Individuals may voluntarily express their private
    information when they first start using agents
  • Intelligent agents work in the background by
    monitoring constantly all users activities such
    as surfing pattern, purchasing behavior, and
    search engine results

10
Social Impacts of Intelligent Agents
  • Web User Privacy
  • Your digital Mini Me
  • Example Shopping bots (product assistants,
    shopping guides, intelligent portals, consumer
    oriented price comparison engines, auction
    watchers, book finders, intelligent online
    catalogues, and bargain finders)
  • Improper use of people personal information may
    seriously undermine trust to intelligent agents,
    the Web, and online shopping

11
Social Impacts of Intelligent Agents
  • Economic Impacts on Online Businesses
  • Transform the existing online markets into the
    condition of perfect competition eventually
    predominantly price oriented
  • The economic value of online information becomes
    one of the most valuable intangible assets
  • Example Shopping bots (or shopbots)-price
    comparison shopping agents
  • Increase the bargaining power of customers who
    may efficiently locate the best item price on the
    Web
  • Transform the whole online shopping industry
    markets will move closer to the perfect
    competition model where the long-run cumulative
    profit of all sellers is a zero
  • Drive sellers, in turn, to rely on intelligent
    agent real-time pricing technologies, or
    pricebots
  • In conjunction with pricebots can theoretically
    engage virtual business in lose-lose price wars

12
Social Impacts of Intelligent Agents
  • User Confidence and Trust
  • The degree of user confidence in the quality of
    agents performance
  • Does the agent present relevant information?
  • Can it potentially find the best deal? and,
  • Is the user able to exploit the full capabilities
    of the intelligent agent in order to obtain the
    desired results?

13
Social Impacts of Intelligent Agents
  • User Confidence and Trust (continued)
  • The level of user trust to an agent, which some
    people may associate with trust to many online
    services
  • Does the agent search for the best deals on the
    whole Internet or only visits the sites of those
    online vendors who paid a subscription fee to a
    respective shopping bot designer?
  • Can the agent avoid traps of the vendors trying
    to attract such type of intelligent agents?
  • Would the intelligent agent be able to
    discriminate between serious online vendors and
    fake vendors or fake best offers?
  • Would the intelligent agent be able to find the
    best deal from a more complex view rather than a
    pure price-only perspective?
  • Website owners concern over various intelligent
    agent activities

14
Social Impacts of Intelligent Agents
  • Online Habits and Behavior
  • In an effort to save time, people will tend to
    reduce their efforts
  • for information searching
  • people will risk missing important information
    otherwise acquired by do-it yourself experience
  • software entities can not always make the
    necessary associations to follow other branches
    of information retrieval because intelligent
    agents lack common sense
  • Having intelligent agents perform an Internet
    search and selection on behalf of a human user
    may encourage substitutes of culture
  • people will tend to have the intelligent agents
    do the entire job and receive ready to be
    digested and consumed information
  • this may result in losing rather than acquiring
    knowledge if agents become too excessively
    exploited on the Web

15
Social Impacts of Intelligent Agents
  • Peoples Web Performance
  • The presence of intelligent agents in the form of
    personal assistants will make websites more
    accessible and even friendlier for those people
    who may be very good specialists but, on the
    other hand, have lower computer and Internet
    skills
  • Intelligent agents may expand the usage of
    various capabilities offered by many Web sites
  • Example Intelligent agents would be able to
    educate users on portal resources usage and offer
    real-time navigational help

16
Social Impacts of Intelligent Agents
  • Online Social Interaction
  • Modern work environment is becoming associated
    with the idea of knowledge portals embedding
    intelligent agents
  • Present tendency of creating virtual and
    networking organizations where individuals work
    remotely from home and communicate with each
    other electronically
  • Immediate consequences extra costs savings
    (commuting expenses and office space), more
    convenient work pattern
  • Unpredictable consequence people may replace
    direct social interaction with mediated
    interaction which contradicts social work habits
    people have been developing for millennia
  • Massive and indiscriminate use of software agents
    to facilitate work processes through the Internet
    may have significant social drawbacks in the long
    run

17
Social Impacts of Intelligent Agents
  • Online Service Providers Activities
  • The use of intelligent agents will change some
    peoples job tasks and activities, which will
    affect their job and life patterns
  • People will have to comply with new job
    requirements
  • Example Intelligent agents, in context of a
    library portal would perform most of the
    repetitive and tedious tasks of librarians
    librarians will be able to do more qualitative
    work requiring human innovative thinking
  • Intelligent agents may potentially restructure
    the current online IT labor market and facilitate
    the creation of new jobs
  • Example The boom in agent technologies will
    increase demand on information technology (IT)
    personnel, agent researchers, and agent oriented
    programmers (AOP)

18
Conclusions and Directions for Future Research
  • The authors view
  • Two extremist views on the usefulness of
    agent-based computing
  • intelligent agents should not be included into
    Web-enabled applications
  • agent potential should be fully realized, and
    people should be totally eliminated and replaced
    by machines and software
  • The authors, however, suggest the third approach
    where intelligent agents should be included into
    online systems only under appropriate business
    and technical conditions and after thorough
    considerations of both the projected benefits and
    the unexpected social impacts of agent on
    Internet usage

19
Conclusions and Directions for Future Research
  • Future research
  • present investigation touches upon only a few
    unforeseen social effects
  • each identified social effect provides a fruitful
    research field which may be further explored in
    the form of empirical investigations and
    conceptual discussions
  • the existing social theories may be used to build
    a framework of social impacts of agents on Web
    usage

20
Conclusions and Directions for Future Research
  • Final thoughts
  • The intrusion of innovation into all aspects of
    peoples lives is especially difficult to predict
    in the early stages of technology development
  • It is impossible to say whether intelligent
    agents will be able to fully perform the tasks
    that visionary researchers have predicted
  • Future researchers should be ready to recognize
    those unanticipated effects

21
Questions?
  • Contact
  • Alexander Serenko
  • Ph.D. candidate (MS/S) at the Michael G. DeGroote
    School of Business, McMaster University,
    Hamilton, CANADA
  • serenkav_at_mcmaster.ca
  • Mihail Cocosila
  • Ph.D. candidate (MS/S) at the Michael G. DeGroote
    School of Business, McMaster University,
    Hamilton, CANADA
  • cocosim_at_mcmaster.ca
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