course material

1. (Mt) – SUNYESC Business Benefits of Using Intelligent Techniques
Questions
12 LY 1810518880 450 Part Three Key System Applications for the Digital Age C Sources:
Christian Davenport, “IBM’s Watson Supercomputer May Have Met Its Match: The Federal
Procurement Mess,” Los Angeles Times, March 26, 2016; International Business Machines
Corpora- tion, “Form 10-K Annual Report,” February 23, 2016; Greg Bens- inger, “IBM CEO:
Too Soon to Break Out Watson Revenue,” Wall Street Journal, June 1, 2016; Virginia Lau,
“How Watson for Oncol- ogy Is Advancing Cancer Care,” Medical Marketing & Media, April
19, 2016; John Markman, “IBM Makes Its Big Data Play,” Forbes, July 11, 2016; Greg
Slabodkin, “CVS Taps IBM Watson for Predic- tive Analytics,” Information Management,
August 3, 2015; Steve Lohr, “IBM Creates Watson Health to Analyze Medical Data,” New
York Times, April 13, 2015; Mohana Ravindranath, “How IBM IS Trying to Commercialize
Watson,” Washington Post, May 11, 2014; Spencer E. Ante, “IBM Struggles to Turn Watson
Computer into Big Business,” Wall Street Journal, January 7, 2014; Michael Goldberg, “Five
Things to Know About IBM Watson, Where It Is, and Where It’s Going,” DataInformed,
January 14, 2014; and Larry Dignan, “IBM Forms Watson Business Group: Will
Commercialization Fol- low?” ZDNet, January 9, 2014. CASE STUDY QUESTIONS 11-13 How
powerful is Watson? Describe its technol- ogy. Why does it require so much powerful
hardware? 11-14 How “intelligent” is Watson? What can it do? What can’t it do? 11-15 What
kinds of problems is Watson able to solve? How useful a tool is it for knowledge
management and decision making? 11-16 Do you think Watson will be as useful in other
industries and disciplines as IBM hopes? Will it be beneficial to everyone? Explain your
answer. 1yMISLab Chapter 11 Managing knowledge 449 rises send to Watson. id service
that will er’s information, Sharing of data-driven ud-based service that e companies to ana-
mo ns for Watson medical informa- 1 in 2020 will be won’t be able formation, but able to
read in context and ssionals. the largest U.S. members, Reviewer ysicians es of the y. The c
patient Dital, the and treat- ks and ce presi- k too vas able train- Care is able to present an
analysis in about 15 min- utes that would typically take humans months to develop. Using
Watson for Oncology turned out to be re complex than originally envisioned. For instance,
Sloan Kettering oncologist Dr. Mark Kris displayed a screen from Watson that listed three
potential treatments, but Watson was less than 32 percent confident that any of them were
correct. But progress is genuine, and Watson for Oncology is now used at a number of
hospitals worldwide, including Bumrungrad International Hospital in Bangkok and Manipal

2. Hospitals in seven cities in India as well as Memorial Sloan Kettering in New York.
Additional Watson oncology-related solutions are being used at MD Anderson Cancer
Center and the Cleveland Clinic. In November 2013, IBM announced it would make Watson
technology available via the Internet as a cloud service that could be used by many dif-
ferent industries. IBM opened parts of the system to outside developers to create
businesses and mobile applications based on cognitive comput- ing. A Watson Developer
Cloud provides tools and methodologies for developers to work with a Wat- son system, a
content store supplying both free and fee-based data for new applications, and about 500
subject matter experts from IBM and third parties. IBM has also made Watson easier and
less expen- sive to use. The Watson Health Cloud launched in 2015 is a secure platform
where corporations and researchers can build systems and exchange data. Initial indus- try
partners are Johnson & Johnson, Medtronic, and Apple. Johnson & Johnson will use Watson
to personalize patient care before and after knee and hip replacements. Medical equipment
maker Medtronic wants to use Watson to spot diabetes patients trending toward trouble,
automatically adjust insulin doses from its devices, and send alerts to care providers and
the patients. Apple and Under Armour are using Watson analytics to deci- pher the deluge
of data from connected watches and fitness bands. to bid on or to determine the
requirements for competing for a contract. Genesys, which provides customer experience
and call center technology solu- tions, is building a platform that allows clients to call into a
bank and interact with Watson. The software understands and uses natural language to
offer assis- tance and even recommends products based on the conversation. IBM has
aggressively been moving away from hardware and focusing on cloud-based analytic and
artificially intelligent software. Although Watson is one key to IBM’s future, analysts believe
it’s not growing fast enough to offset the weakness in its legacy computer and consulting
businesses. CEO Virginia Rometty is hoping Watson will bring in $1 billion in revenue
annually by 2018 but states that it is too early to break out financial results for the Watson
unit because the company is still growing the product. In order to effectively commercialize
the technol- ogy, IBM will need to expand Watson’s knowledge domains, and this is its
greatest challenge. Turning Watson into a useful business tool requires an enor- mous
amount of work. Watson has to learn the termi- nology and master the domains of expertise
in many different areas, including health care and scientific research, understand the
context of how that lan- guage is used, and learn how to correlate questions with the correct
answers. Watson can’t come up yet with its own ideas. re IBM will have to be careful not to
oversell what Watson can do so that Watson does not end up like other artificial intelligence
systems where expec- tations were way overblown. Making machines that beat humans at
chess or a TV game is much easier than solving problems in the real world. According to
Curt Monash, president of Monash Research, Watson hasn’t yet overcome the hurdle that
derailed Al in the 1980s, when it was only able to capture very small pieces of a limited
knowledge domain for a single-purpose use. Watson is having more trouble solving real-life
problems than Jeop- ardy! questions. Watson’s basic learning process requiring IBM
engineers to master the technicali- ties of a customer’s business and translate those
requirements into usable software has been very arduous. It remains to be seen whether
the com- plexity of establishing a body of knowledge and training an intelligent system is

3. repeatable and scalable for other types of work and whether it creates opportunities for
differentiation and com- petitive advantage. Watson is very much a work in progress. Other
industries are starting to use Watson as well. The U.S. Air Force is developing an intelligent
sys- tem to help government procurement officials man- age the Federal Acquisition
Regulation, consisting of 1,897 pages of documents. The number and complex- ity of the
documents make it virtually impossible for an individual to understand in order to answer a
specific question. Businesses will be able to query the system to find programs they might
be eligible EN 2017 448 Part Three Key System Applications for the Digital Age based on
raw big data enterprises send to Watson. IBM Watson Explorer is a cloud service that will
provide a unified view of a user’s information, facilitating the revelation and sharing of data-
driven insights. Watson Health is a cloud-based service that will make it easier for
healthcare companies to ana- lyze large stores of patient data. Some of the earliest
applications for Watson have been in health care, where medical informa- tion doubles
every three years and in 2020 will be doubling every 73 days. Physicians won’t be able to
keep abreast of that volume of information, but IBM believes Watson can. Watson is able to
read and understand all this information in context and become an assistant to medical
professionals. In September 2011, WellPoint Inc., the largest U.S. healthcare provider, with
34.2 million members, enlisted Watson for an Interactive Care Reviewer application
designed to determine if physicians’ requested treatment meets the guidelines of the
company and a patient’s insurance policy. The application combines data from electronic
patient records maintained by a physician or hospital, the insurance company’s history of
medicines and treat- ments, and Watson’s huge library of textbooks and medical journals.
According to WellPoint vice presi- dent Elizabeth Bingham, Watson initially took too long to
“learn” WellPoint’s policies, but IBM was able to improve the system by revising the Watson
train- ing routine for WellPoint, and the Interactive Care Reviewer has been rolled out to
1,600 healthcare is able to present utes that would t develop Using Watson more complex t
instance, Sloan displayed a ser potential treat 32 percent co But progress is now used
including B Bangkok an India as we York. Addi are being the Cleve In Nov make Wa as a clou
ferent i to outs mobile ing. A meth sons fee- subj IBM siv drive, so that Watson could find the
data it needed within three seconds. Watson is able to learn from its mistakes as well as its
successes. To solve a typical problem, Watson tries many of the thousands of algorithms
that the team has programmed it to use. The algorithms evaluate the language used in each
clue, gather information about the important people and places mentioned in the clue, and
generate hundreds of solutions. Human beings don’t need to take such a formal approach to
generate the solutions that fit a question best, but Watson compensates for this with
superior computing power and speed. If a certain algorithm works to solve a problem,
Watson remembers what type of question it was and the algorithm it used to get the right
answer. In this way, Watson improves at answering questions over time. Watson also learns
another way-the team gave Watson thousands of old Jeopardy! ques- tions to process.
Watson analyzed both questions and answers to determine patterns or similarities between
clues, and using these patterns, it assigns varying degrees of confidence to the answers it
gives. Although Watson was only able to correctly answer a small fraction of the questions it
was ini- tially given, machine learning allowed the system to continue to improve until it

4. reached Jeopardy! cham- pion level. IBM terms Watson’s ability to interpret speech and text,
rapidly mine large volumes of data, answer questions, draw conclusions, and learn from its
mistakes cognitive computing. providers. IBM sees its investment in Watson as a stepping In
2012, Memorial Sloan Kettering Cancer stone to broader commercial uses of its AI technol-
Center began work on a Watson for Oncology ogy, including applications for health care,
financial application to recommend personalized cancer services, or any industry where
sifting through large treatments, using data from Sloan Kettering’s amounts of data
(including unstructured data) to clinical database of more than a million patients, answer
questions is important. Watson is expected to 500 medical journals and textbooks, and 12
mil- become more useful and powerful by learning from lion pages of medical literature.
Currently, the new sets of experts in new fields of knowledge. In system offers
recommendations for lung, breast, January 2014, the company created a new division, and
colorectal cancers and is expanding to gastric- the Watson Business Group, with 2,000
employees. related cancers. Once Watson for Oncology has IBM has invested more than $1
billion in this group a patient’s information, it can instantly search and has allocated one-
third of its overall research efforts to Watson. through medical literature from all over the
world to identify the literature that is most relevant IBM is developing new cloud-based
products based to that patient’s specific cancer and prioritize on Watson’s cognitive
intelligence and capabilities. potential treatment options (color-coded for risk IBM Watson
Discovery Advisor is aimed at the phar- maceutical, publishing, and education industries
and confidence) based on the evidence and the and will wade through search results to
deliver data patient’s health record. The system understands faster and help researchers
formulate conclusions. context. If Watson reads in notes that a breast can- IBM Watson
Analytics is a cloud-based service that cer patient’s sister had a mastectomy, the system se
ca t provides insights, including visual representations, knows that’s an indication of family
history even though the word family may not appear. Watson Systems and collabora- es and
gas bars rvices as well erated. Cana- 20 new prod- ooking for a be the prob- lp Collaboration
and Teamwork Project Rating Enterprise Content Management Systems 11-12 With a group
of classmates, select two enterprise content management (ECM) products, such as those
from Oracle, Open Text, IBM, or EMC Documentum. Compare their features and capabilities.
To prepare your analysis, use articles from computer magazines and the websites of the
ECM software vendors. Ii pos- sible, use Google Docs and Google Drive or Google Sites to
brainstorm, organize, and develop a presenta- tion of your findings for the class. Does IBM’s
Watson Have a Future in Business? e num- CASE STUDY s are “east izes In February 2011,
an IBM computer named Watson made history by handily defeating the two most dec-
orated champions of the game show Jeopardy!, Ken Jennings and Brad Rutter. Watson was
named after IBM’s founder, Thomas J. Watson, and its achieve- ment marked a milestone in
the ability of computers to process and interpret human language. The Watson version used
in Jeopardy took 20 IBM engineers three years to build at an $18 million labor cost and an
estimated $1 million in equipment. The project’s goal was to develop a more effective set of
techniques that computers can use to process natural language-language that human beings
instinctively use, not language specially formatted to be under- stood by computers. Watson
had to be able to register the intent of a question, search through millions of lines of text

5. and data, pick up nuances of meaning and context, and rank potential responses for a user
to select, all in less than three seconds. The hardware for Watson used in Jeopardy! con-
sisted of 10 racks of IBM POWER 750 servers running Linux with 15 terabytes of RAM and
2,880 processor cores (equivalent to 6,000 top-end home computers) and operated at 80
teraflops. Watson needed this amount of power to quickly scan its enormous data- base of
information, including information from the Internet. To prepare for Jeopardy!, the IBM
research- ers downloaded more than 10 million documents, including encyclopedias and
Wikipedia, the Internet Movie Database (IMDB), and the entire archive of The New York
Times. All of the data sat in Watson’s primary memory, as opposed to a much slower hard
SYSTEMS, 443 Wisdom, 420 d its integration powerful com- ument manage- er-aided design
h create inter- -ful modeling MyMISLab To complete the problems with the MyMislab, go to
the EOC Discussion Questions in MyMISLab. gence, but it Fapture tacit the form of sed
reason- expanded that use es and is mprove nic the 7 with- ey are nts of Review Questions
11-1 What is the role of knowledge management sys- tems in business? Define knowledge
management and explain its value to businesses. Describe the important dimensions of
knowledge. Distinguish between data, knowledge, and wisdom and between tacit
knowledge and explicit knowledge. Describe the stages in the knowledge man- agement
value chain. 11-2 What types of systems are used for enterprise- wide knowledge
management, and how do they provide value for businesses? Define and describe the
various types of enterprise-wide knowledge management systems and explain how they
provide value for businesses. Describe the role of the following in facilitat- ing knowledge
management: taxonomies, MOOCs, and learning management systems. 11-3 What are the
major types of knowledge work sys- tems, and how do they provide value for firms? Define
knowledge work systems and describe the generic requirements of knowl- edge work
systems. Describe how the following systems support knowledge work: CAD, virtual reality,
and augmented reality. 11-4 What are the business benefits of using intelli- gent techniques
for knowledge management? Define an expert system, describe how it works, and explain
its value to business. Define case-based reasoning and explain how it differs from an expert
system. Define machine learning and give some examples. Define a neural network and
describe how it works and how it benefits businesses. Define and describe fuzzy logic,
genetic algorithms, and intelligent agents. Explain how each works and the kinds of
problems for which each is suited. . . esses rob- ter- . . ut