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Chapter 2 • Foundations and Technologies for Decision Making 101

Questions for Discussion impacting the decision-making process radically by
1. What is a cognitive system? How can it assist in shifting them from an opinion-based process to a
real-time decision making? more real-time, evidence-based process, thereby turn-
ing available information intelligence into actionable
2. What is evidence-based decision making?
wisdom that can be readily employed across many
3. What is the role played by Watson in the industrial sectors.
discussion?
4. Does Watson eliminate the need for human deci- Sources: Ibm.com, “IBM Watson: Ushering In a New Era of
sion making? Computing,” www-03.ibm.com/innovation/us/watson (accessed
February 2013); Ibm.com, “IBM Watson Helps Fight Cancer with
Evidence-Based Diagnosis and Treatment Suggestions,” www-
What We can Learn from this application 03.ibm.com/innovation/us/watson/pdf/msK_case_study_
case imc14794.pdf (accessed February 2013); Ibm.com, “IBM Watson
Enables More Effective Healthcare Preapproval Decisions Using
Advancements in technology now enable the build- Evidence-Based Learning,” www-03.ibm.com/innovation/us/
ing of powerful, cognitive computing platforms com- watson/pdf/Wellpoint_case_study_imc14792.pdf (accessed
bined with complex analytics. These systems are February 2013).

technOLOgy insights 2.2

Next Generation of Input Devices
The last few years have seen exciting developments in user interfaces. Perhaps the most com-
mon example of the new user interfaces is the iPhone’s multi-touch interface that allows a user
to zoom, pan, and scroll through a screen just with the use of a finger. The success of iPhone has
spawned developments of similar user interfaces from many other providers including Blackberry,
HTC, LG, Motorola (a part of Google), Microsoft, Nokia, Samsung, and others. Mobile platform
has become the major access mechanism for all decision support applications.
In the last few years, gaming devices have evolved significantly to be able to receive and
process gesture-based inputs. In 2007, Nintendo introduced the Wii game platform, which is
able to process motions and gestures. Microsoft’s Kinect is able to recognize image movements
and use that to discern inputs. The next generation of these technologies is in the form of
mind-reading platforms. A company called Emotiv (en.wikipedia.org/wiki/emotiv) made
big news in early 2008 with a promise to deliver a game controller that a user would be able
to control by thinking about it. These technologies are to be based on electroencephalogra-
phy (EEG), the technique of reading and processing the electrical activity at the scalp level
as a result of specific thoughts in the brain. The technical details are available on Wikipedia
(en.wikipedia.org/wiki/electroencephalography) and the Web. Although EEG has not
yet been known to be used as a DSS user interface (at least to the authors), its potential is
significant for many other DSS-type applications. Many other companies are developing similar
technologies.
It is also possible to speculate on other developments on the horizon. One major growth
area is likely to be in wearable devices. Google’s wearable glasses that are labeled “augmented
reality” glasses will likely emerge as a new user interface for decision support in both consumer
and corporate decision settings. Similarly, Apple is supposed to be working on iOS-based wrist-
watch-type computers. These devices will significantly impact how we interact with a system and
use the system for decision support. So it is a safe bet that user interfaces are going to change
significantly in the next few years. Their first use will probably be in gaming and consumer
applications, but the business and DSS applications won’t be far behind.
Sources: Various Wikipedia sites and the company Web sites provided in the feature.

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