presentation shows the use of artificial intelligence in HRM.

1. Self study
paper presentation
Paper Title: Artificial Intelligence in HRM: An Experimental
Study of an Expert System
Author : John J. Lawler (University of Illinois ) & Robin Elliot
(San Francisco)
Published in: Journal of Management , Vol. 22,
No. I, 85-111 Presented by:
Neetika Tiwari
P.Hd Scholar
Course: Pre- P.Hd
Roll no:1906676

2. Research Problem
• This study investigates the impact of an expert
system used as a decision aid in a job evaluation
system.

3. Research Highlights
• Performance outcomes and psychological outcomes are
analyzed in an experiment in which the intended users of
the expert system served as subjects.
• The study draws largely from behavioral decision theory
for its theoretical support.
• The study examines an expert system within an HRM
context, the results are useful as one test of expert system
within the more general area of managerial decision
making.

4. An Expert System
• Expert systems are artificial intelligence (AI) applications
that have shown great promise as decision aids across
several functional areas of management (Feigenbaum,
McCorduck & Nii, 1988; Ernst, 1988).
• An expert system is “a computer program which attempts
to embody the knowledge and decision- making facilities
of a human expert in order to carry out a task.
• Example: MYCIN

5. ACC… TO THIS PAPER
• Expert systems, designed to replicate certain abstract reasoning and problem-
solving capabilities of humans (Simon & Kaplan, 1989), are most appropriate in
helping users cope with semi-structured problems (Simon, 1977).
• Semi-structured problems are those for which a considerable body of knowledge
exists as to the ways in which a given problem ought to be tackled.
• However, the knowledge base is highly complex and not readily accessible to those
without specialized training.
• Consequently, organizations must rely on problem solvers who have accumulated a
track record of generating solutions that, while not necessarily optimal, seem to
work well.
• Expert problem solvers utilize heuristic, rather than algorithmic, methods. In
developing an expert system, the heuristic methods of acknowledged experts in a
specialized problem domain are incorporated into the program (Buchanan & Smith,
1989

6. Objectives of Research
• To discern the impact of expert system utilization on
problem-solving outcomes within an HRM context.
• To find out effects of expert systems in both limited
and often uninformed by behavioral decision theory.
• Examining the impact of both problem-solving
method (with or without the aid of an expert system)
and information-processing difficulty.

7. Research Methodology
• This study involves the assessment of an expert system
designed to facilitate decision making in a classification-based
job evaluation program.
• Data collected from: People in clerical positions in a large
public sector organization operating under a state civil service
system.
• Data collection: during training sessions for users.
• Tools used for the analysis :Problem-Solving Method,
Problem Complexity methodology.
• Statistical tool: ANOVA

8. Hypothesis
• Hl: Expert system use will increase the accuracy of HRM decisions made by non-experts.
• H2: Expert system use will decrease the time required by non-experts to make HRM
decisions.
• H3: As the complexity of a problem increases, the problem-solving performance (both
accuracy and efficiency measures> of subjects when utilizing the expert system should
improve relative to performance without the expert system. At very high complexity levels,
performance with the expert system may deteriorate and the performance levels under the two
approaches may again converge.
• H4: The accuracy of HRM decisions will decrease as the complexity of the problem increases.
• HS: The time required to reach HRM decisions will increase as the complexity of the problem
increases.
• H6: A subject perception of the ease-of-use of a problem-solving method will decrease as the
complexity of the problem increases.
• H7: A subjects perception of the usefulness of a problem-solving method will decrease as the
complexity of the problem increases.

9. Research Design
• To test hypotheses, an experimental study was conducted
in connection with a training program for the intended
users of the expert system.
• All subjects were departmental classifiers who were
required to attend the training sessions. None had been
exposed to the expert system prior to training.
• This study utilized a 2x3 within-subjects factorial design
(two levels for problem-solving method (expert system-
aided versus paper-and-pencil) and three levels for
complexity (low, medium, and high)).

10. Cont….
• No of Observations:288 observations.
• Subjects were randomly assigned to one of twelve
training groups.
• A Latin square approach :served to counterbalance
the order in which the problem-solving methods and
complexity levels were presented to the subjects.

11. RESULTS
• Study results that perceived complexity was higher for problems solved using the expert
system rather than the pencil-and-paper method.
• The results for the three principal psychological outcomes considered in this study
(confidence, perceived ease-of-use, and task attitude) are somewhat similar. All three
decrease in value as complexity increases
• Expert system utilization exerted neither a significant nor positive effect on the accuracy
of skill level decisions.
• Task completion time increased with complexity . Completion time was greater when the
expert system was used, which runs counter to the anticipated relationship
• Subjects did not seem to find the expert system more difficult to use than the paper-and-
pencil approach, even though expert system use did increase perceived complexity. And
their attitude toward the problem-solving task tended to be more favorable in the expert
system condition though the relationship is not significant.

12. Discussions
• Study anticipate that the human resource management field
will increasingly depend upon sophisticated information
technology applications.
• Expert systems and other artificial intelligence programs, still
relatively rare in HRM, are apt to become more
commonplace.
• The work examines the interaction of expert system use and
complexity, which is an important feature of the problem
context.

13. Limitations
• Expert system developed for this study is defective, thus
raising questions regarding the study’s internal validity.
Yet the program clearly generated consistent results when
used by expert personnel analysts.
• The departmental classifiers, who served as experimental
subjects are second limitation of the study.
• Results may be the consequence of the confounding
impact of their prior training and experience with the
paper-and-pencil approach.

14. CONCLUSION
• This study does indicate that is feasible to develop expert systems
that replicate some nontrivial problem-solving competencies in the
HRM field.
• More research is needed in HRM, both on the impact of expert
system use on outcomes and on the efficacy of various features of
expert system applications (e.g., graphical versus textual displays).
• Future research should explore other dimensions of the problem
context and the interaction of context and expert system use.
• Another significant area of inquiry is the impact of the personal
characteristics of users on performance and psychological outcomes.
The technology of expert system development also is a potentially
fruitful area.

15. ANY QUESTION
?