Page 44 - DCAP310_INTRODUCTION_TO_ARTIFICIAL_INTELLIGENCE_AND_EXPERT_SYSTEMS

Introduction to Artificial Intelligence & Expert Systems

Notes The belief that knowledge management is destined to become the key to future economic
success is based on the following logic:
(i) Many prominent scholars note that a new economic era, referred to as the knowledge-
based economy, is already underway. In this new economy, knowledge is the source of
wealth. It is assumed, therefore, that knowledge management will be the new work of
organizations.
(ii) Knowledge management represents a logical progression beyond information
management. Information technologies, at long last, have demonstrated a notable impact
on organizational performance. Many believe that the next generation of information
technology/artificial intelligence products will increasingly enable knowledge
management, in contrast to information management, and, as such, will have a far bigger
impact on organizational performance.
(iii) Knowledge management can also be seen as representing a culmination and integration
of many earlier organization development ideas, e.g. total quality, re-engineering,
organizational learning, benchmarking, competitive intelligence, innovation,
organizational agility, asset management, supply chain management, change management,
etc.). It encapsulates these concepts into a larger, more holistic perspective that focuses on
effectively creating and applying knowledge.

3.2.1 Factors

MYCIN was an early expert system that used artificial intelligence to identify bacteria causing
severe infections, such as bacteremia and meningitis, and to recommend antibiotics, with the
dosage adjusted for patient’s body weight—the name derived from the antibiotics themselves,
as many antibiotics have the suffix “-mycin”. The Mycin system was also used for the diagnosis
of blood clotting diseases.
MYCIN was developed over five or six years in the early 1970s at Stanford University. It was
written in Lisp as the doctoral dissertation of Edward Shortliffe under the direction of Bruce
Buchanan, Stanley N. Cohen and others. It arose in the laboratory that had created the earlier
Dendral expert system.
MYCIN was never actually used in practice but research indicated that it proposed an acceptable
therapy in about 69% of cases, which was better than the performance of infectious disease
experts who were judged using the same criteria.
MYCIN was never actually used in practice. This wasn’t because of any weakness in its
performance. As mentioned, in tests it outperformed members of the Stanford medical school
faculty. Some observers raised ethical and legal issues related to the use of computers in
medicine—if a program gives the wrong diagnosis or recommends the wrong therapy, who
should be held responsible? However, the greatest problem, and the reason that MYCIN was
not used in routine practice, was the state of technologies for system integration, especially at
the time it was developed. MYCIN was a stand-alone system that required a user to enter all
relevant information about a patient by typing in response to questions that MYCIN would
pose. The program ran on a large time-shared system, available over the early Internet (ARPANet),
before personal computers were developed. In the modern era, such a system would be integrated
with medical record systems, would extract answers to questions from patient databases, and
would be much less dependent on physician entry of information. In the 1970s, a session with
MYCIN could easily consume 30 minutes or more—an unrealistic time commitment for a busy
clinician.

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