Personal Intelligent User Interfaces 2008 - Development of a methodology framework to evaluate technologies in order to define high potential use cases

Table of Contends

Abstract

Kurzfassung

Figures

Tables

Abbreviations

1 Introduction
1.1 Scenario
1.2 Problem Setting and Goals
1.3 Structural Overview of the Thesis

2 Delimitation and Conceptual Definitions
2.1 Strategic Technology Management
2.2 Methods of Strategic Technology Management
2.2.1 Technology Forecasting
2.2.1.1 Expert Panel
2.2.1.2 Scanning and Monitoring
2.2.1.3 Patent and Literature Analysis
2.2.1.4 Trend Impact Analysis
2.2.1.5 Gap Analysis
2.2.1.6 Scenario Analysis
2.2.2 The Gardner Hype Cycle
2.2.3 Technology Assessment
2.3 Personal Intelligent User Interface
2.3.1 Definition Human-Computer Interaction
2.3.2 Definition of User Interface
2.3.3 Definition of Intelligent User Interface
2.3.4 Definition of Personal Intelligent User Interfaces

3 Development of the user requirement framework
3.1 Usability
3.2 Analysis of existing usability standards
3.2.1 The technology user requirements framework
3.2.2 Use case development

4 User interfaces and technologies
4.1 Affective Computing
4.2 Virtual Reality
4.3 Mixed Reality - Augmented Reality
4.3 Chip Implants for Identification
4.4 Brain-Computer Interface
4.5 Displays
4.5.1 Electronic Ink and Digital Paper
4.5.2 Retinal Displays
4.6 Gaze Tracking
4.7 Gesture Recognition
4.8 Handwriting
4.8.1 Handwriting Capture
4.8.2 Natural Handwriting Recognition
4.9 Haptic Interfaces
4.10 Intelligent Agents
4.11 Location Sensing
4.12 Machine Translation
4.13 Natural Language Search
4.14 Speech Recognition
4.15 Speech-to-Speech Translation
4.16 Synthetic Characters
4.17 Telepresence
4.18 Text-to-Speech Synthesis
4.19 Wearable Computers

5. Conclusion
5.1 Summary
5.2 Outlook

Appendix
Attachment 1: Gartner Hype Cycle (1/2)
Attachment 1: Gartner Hype Cycle (2/2)
Attachment 2: International standards for HCI and usability (1/3)
Attachment 2: International standards for HCI and usability (2/3)
Attachment 2: International standards for HCI and usability (3/3)
Attachment 3: The PIUI-Team
Attachment 4: About DETECON
Attachment 5: Usability attributes additional information
Attachment 6: Fulfilment Relevance Matrices for all Technologies
Attachment 7: Use case list - rough draft after the first consolidation
Attachment 8: Final consolidation – high potential PIUI use cases

Bibliography

Index

Abstract

Diploma thesis

Engineering and economics

University of Applied Science Rosenheim

Markus Fischer

Personal Intelligent User Interfaces 2008

Development of a methodology framework to evaluate technologies
in order to define high potential use cases

Germany depends heavily on the only raw material available within its national territory – knowledge. Nevertheless, major management faults due to a lack of management
knowledge have led to closures of prosperous companies and in many cases to layoffs in the thousands in the recent past. This questions the abilities of companies and their decision makers and, once again, the actual quality of our most precious good. Managers cannot talk themselves out of this by stating that Germany is no longer able to produce competitively, as this is not true. The challenge is to make products people both need and enjoy. To achieve this goal, this thesis provides a tailored solution for the information and communication market.

The topic deals with one of the most promising technologies since the internet, namely the next generation of user interfaces – personal intelligent user interfaces (PIUIs). Some call it the Pandora’s Box of the information century, whereas others consider it to be the salvation for the mobile generation. This thesis might not be able to give a final answer to this dispute but provides a toolkit for the strategic technology management to cope with new technologies. Furthermore, a methodology framework is developed and applied to evaluate the usability of intelligent user interfaces. Usability is the key factor for broad user acceptance and success in a highly competitive market environment like the communication sector. Beyond that, the work presents a list of high potential use cases for PIUIs till 2008. First “products” of this list have been presented or even rolled out earlier this year by major ICT companies like Nokia and Microsoft. This proof of validity and the fact that this paper includes a comprehensive list of in-depth analysed next generation user interface technologies make this work a must read for every determined and responsible manager.

Rosenheim, 4th October 2006

Kurzfassung

Diplomarbeit im Fachbereich Wirtschaftsingenieurwesen
Fachhochschule Rosenheim

Markus Fischer

Personal Intelligent User Interfaces 2008

Development of a methodology framework to evaluate technologies
in order to define high potential use cases

Immer wieder wird von Seiten der Wirtschaft und Politik betont, das Deutschland von dem einzigen Rohstoff, der auf Bundesgebiet zu finden ist, abhängig ist – Wissen. Nichtsdestotrotz machen immer wieder schwerwiegende Management-Fehlentscheidungen Schlagzeile, die zum Bankrott von eigentlich gesunden Firmen und somit leider auch oft zu Entlassungen im vier- bis fünfstelligen Bereich geführt haben. Dieser Umstand lässt an den Fähigkeiten der Entscheidungsträger in solchen Unternehmen doch stark zweifeln und somit auch an unserem „wertvollsten Gut“. Manager können sich nicht mehr damit herausreden, das man in Deutschland nicht konkurrenzfähig produzieren kann, da schon viele gezeigt haben wie es geht. Die eigentliche Herausforderung liegt darin, Produkte zu entwickeln, die die Menschen brauchen und an denen sie Gefallen finden. Um dieses Ziel zu erreichen bietet diese Arbeit eine maßgeschneiderte Lösung für den Informations- und Kommunikationsmarkt.

Das Thema gehört zu den interessantesten und erfolgversprechendsten Technologien seit dem Internet; die nächste Generation von Mensch-Maschinen Schnittstellen – die Personal Intelligent User Interfaces (PIUIs). Von einigen werden sie schon als die Büchse der Pandora verteufelt und wiederum andere sehen in ihnen die Erlösung der „Mobile Generation“. Diese Diplomarbeit mag vielleicht keine Antwort auf die Frage „gut oder schlecht“ geben, jedoch hält sie für den Leser gut aufbereitete Methodiken des strategischen Technologie-Managements bereit, um mit diesen Technologien in Zukunft arbeiten zu können. Zudem wird die Entwicklung eines Rahmenwerks beschrieben zur Bewertung von intelligenten Benutzerschnittstellen hinsichtlich ihrer Anwenderfreundlichkeit oder besser Usability. In einem so hart umkämpften Marktsegment wie der Kommunikationsbranche, ist eine hohe Anwenderfreundlichkeit der Garant für eine breite Akzeptanz und somit Erfolg beim Kunden. Darüber hinaus wird im Rahmen dieser Arbeit eine Liste von besonders vielversprechenden PIUI Anwendungsszenarien bis zum Jahr 2008 vorgestellt, welche mit den neuen Schnittstellen umgesetzt werden könnten. Die ersten „Produkte“ aus dieser Liste wurden bereits der Öffentlichkeit präsentiert oder werden sogar schon von führenden Herstellern wie Nokia seit Anfang des Jahrs vertrieben. Diese nachträgliche Bestätigung des hier angewandten Konzepts und der Umstand, dass diese Diplomarbeit eine umfangreiche Analyse von nahezu allen relevanten Schnittstellentechnologien der nächsten Generation beinhaltet, macht sie zu einer überaus lohnenswerten Lektüre für jeden zielstrebigen und verantwortungsbewussten Manager.

Rosenheim, 4. Oktober 2006

Figures

Figure 1-1: Structural overview of the thesis

Figure 2-1: Strategic planning process by Renfro and Morrison (1983) (qtd. in Gorden and Glenn 1994, p. 28)

Figure 2-2: Typical event impact parameters (based on Gordon, p. 2)

Figure 2-3: Working model of the scenario method - the scenario funnel (Cf. Geschka 1995, p. 305)

Figure 2-4: Phases of the Gartner Hype Cycle (Gartner, 2005)

Figure 2-5: The IUI research field and selected topics (Ehlert, p. 4)

Figure 2-6: General IUI Architecture (Maybury, p. 13)

Figure 3-1: The ISO 9241-11 usability framework

Figure 3-2: ISO/IEC 9126-1 – the six categories of software quality.

Figure 3-3: Relevance and fulfilment graph using the example of the brain-computer interface.

Figure 3-4: Fulfilment relevance gap graph using the example of the brain-computer interface.

Figure 4-1: User requirement graphs of affective computing

Figure 4-2: User requirement graphs of virtual reality

Figure 4-3: The Virtuality Continuum (based on Milgram 1994, page 2).

Figure 4-4: User requirement graphs of augmented reality

Figure 4-5: User requirement graphs of chip implants for identification

Figure 4-6: User requirement graphs of brain-computer interface

Figure 4-7: User requirement graphs of electronic ink and digital paper

Figure 4-8: User requirement graphs of retinal displays

Figure 4-9: User requirement graphs of gaze tracking

Figure 4-10: User requirement graphs of gesture recognition

Figure 4-11: User requirement graphs of handwriting capture

Figure 4-12: User requirement graphs of natural handwriting recognition

Figure 4-13: User requirement graphs of haptic interfaces

Figure 4-14: User requirement graphs of intelligent agents

Figure 4-15: LBS applications in categories (Steiniger, et al., p. 8)

Figure 4-16: User requirement graphs of location sensing

Figure 4-17: Methods of machine translation

Figure 4-18: User requirement graphs of machine translation

Figure 4-19: User requirement graphs of natural language search

Figure 4-20: User requirement graphs of speech recognition on mobile devices

Figure 4-21: User requirement graphs of speech-to-speech translation

Figure 4-22: User requirement graphs of synthetic characters

Figure 4-23: User requirement graphs of telepresence

Figure 4-24: User requirement graphs of text-to-speech synthesis

Figure 4-25: User requirement graphs of wearable computers

Figure 0-1: Gartner Hype Cycle for Human-Computer Interaction, 2005

Tables

Table 1: Relevance matrix for the FRG calculation using the example of the brain-computer interface

Table 2: Hype Cycle Phases. (Gartner Hype Cycle for HCI 2005)

Table 3: International standards for HCI and usability - interface and interaction (cf. Usability Net, 2005)

Table 4: Development of ISO standards

Table 5: Stages of development of international standards and abbreviations

Table 6: Additional definitions / explanations for usability attributes

Table 7: Fulfilment relevance matrix for the FRG calculation of affective computing

Table 8: Fulfilment relevance matrix for the FRG calculation of virtual reality

Table 9: Fulfilment relevance matrix for the FRG calculation of augmented reality

Table 10: Fulfilment relevance matrix for the FRG calculation of chip implants for identification

Table 11: Fulfilment relevance matrix for the FRG calculation of brain-computer interfaces

Table 12: Fulfilment relevance matrix for the FRG calculation of electronic ink and digital paper

Table 13: Fulfilment relevance matrix for the FRG calculation of retinal displays

Table 14: Fulfilment relevance matrix for the FRG calculation of gaze tracking

Table 15: Fulfilment relevance matrix for the FRG calculation of gesture recognition

Table 16: Fulfilment relevance matrix for the FRG calculation of handwriting capture

Table 17: Fulfilment relevance matrix for the FRG calculation of natural handwriting recognition

Table 18: Fulfilment relevance matrix for the FRG calculation of haptic interfaces

Table 19: Fulfilment relevance matrix for the FRG calculation of intelligent agents

Table 20: Fulfilment relevance matrix for the FRG calculation of location sensing

Table 21: Fulfilment relevance matrix for the FRG calculation of machine translation

Table 22: Fulfilment relevance matrix for the FRG calculation of natural language search

Table 23: Fulfilment relevance matrix for the FRG calculation of speech recognition

Table 24: Fulfilment relevance matrix for the FRG calculation of speech-to-speech translation

Table 25: Fulfilment relevance matrix for the FRG calculation of synthetic characters

Table 26: Fulfilment relevance matrix for the FRG calculation of telepresence

Table 27: Fulfilment relevance matrix for the FRG calculation of text to speech synthesis

Table 28: Fulfilment relevance matrix for the FRG calculation of wearable computers

Table 29: Use case list rough draft after the first consolidation, part 1 of 5

Table 30: Use case list rough draft after the first consolidation, part 2 of 5

Table 31: Use case list rough draft after the first consolidation, part 3 of 5

Table 32: Use case list rough draft after the first consolidation, part 4 of 5

Table 33: Use case list rough draft after the first consolidation, part 5 of 5, part 5 of 5

Table 34: List of high potential use cases - draft version

Abbreviations

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1 Introduction

1.1 Scenario

The evolution of computing and communication is on the fast track - its impact on work and life style is immense and carries with it vast social and economical implications for both individuals and enterprises. Advances in wireless and broadband technologies and trends such as pervasive networks, fixed-mobile convergence, seamless communication and sensor networks will have a broader impact and an even more profound influence on the way we live than the personal computer, PDA, cellular phone and Internet had from 1995-2005.

“Always on” and “ubiquity”, the credos of today's ICT market, have already become customer demands. Under constrain to satisfy these demands, generate new service revenues, and retain higher percentages of existing customers worldwide, operating telecommunication companies have to break new ground.

Personalization is considered a key differentiator in the increasingly competitive landscape. With the increasing proliferation of service types and features, a personal intelligent user interface will enable higher customer utility and also make new service scenarios possible.

1.2 Problem Setting and Goals

The main problem areas discussed in this thesis are technology forecast and usability evaluation of a new technology. Two well known quotations as follows will introduce the problem of technology forecasting.

“This 'telephone' has too many shortcomings to be seriously considered as a means of communication. The device is inherently of no value to us.”
(Western Union internal memo from 1876)^[1]

A more contemporary the following statement by William Gates III^[2] from 1981:

“640Kbyte ought to be enough for anybody.”

These statements might cause amazement, especially considering the fact that both companies are still in business. Admittedly, as the telephone replaced the telegraph, money transfer became the Western Union Telegraph Company's primary line of business. However, this begs the question how such companies were even capable of surviving such major misjudgements regarding their strategic technology alignment. Generally speaking, the only possible strategies were changing the focus of their business (as was the case with Western Union), simply “getting lucky” or, alternatively, having enough money to assimilate the missing technology through purchases.

But it can’t be the goal of a global player to miss or loose millions and, in the case of a small firm, to go out of business simply because the chief executive or the person in charge misdiagnosed strategic technology management, especially because it is avoidable. In order to survive in today’s highly competitive environment as a companies a consolidate knowledge about the methodologies and possibilities has become indispensable. Therefore, in the first part of this thesis, the reader will be provided with a kind of “basic toolkit” regarding technology forecasts, the application of which will be shown on the basis of the PIUI research in course of this dissertation.

Similar questions were posed by Dr. Stuckenschneider, head of strategic marketing within Siemens corporate technology. During an information luncheon in Lucerne in 2005, he confronted his audience consisting of managers with the following crucial questions:

“1. What are attractive new technologies for the enterprise?
2. Which technologies should be fostered and which should be reduced?”
(2005, p.2)

The shortcomings of a determined attempt to successfully integrate desktop UI technology like WIMP (Windows, Icons, Mouse, Pull-Down Menu) into next generation communication devices (like smart phones, PDAs, etc.) are conspicuous. As Professor John Canny from the UC Berkeley puts it:

“If you've tried interacting with a non-trivial smart-phone application, you'll know what an ordeal it can be. There has been a brave effort to evolve it from its WIMP interface roots, but it just feels wrong - like a shark in a shopping mall.” (2006, p.3)

Furthermore, a whole range of highly sophisticated gadgets whose purpose is to make our lives more convenient and enjoyable has invaded our living rooms in recent years. One example would be a state-of-the-art HD-TV set. It has internet connectivity, a hard drive capable of storing seemingly endless hours of TV programming, and all the necessary hardware to connect to any conceivable media device. It does not yet include the software, but it is only a matter of time before this will change. The time has clearly come for a new breed of user interfaces. In response to Dr. Stuckenschneider’s first question, this thesis will give the reader the opportunity to obtain comprehensive knowledge of one of the

most attractive and promising new technologies for the information and communication technology (ICT) market – intelligent user interfaces (IUIs) and, in the next phase, personal intelligent user interfaces (PIUIs).

In addition, in order to assist those struggling to come up with an answer to the second question, a framework is presented to evaluate the usability of IUIs.

1.3 Structural Overview of the Thesis

The discussion of the goals starts with a brief overview of the area of strategic technology management in order to facilitate the understanding of the focus of the thesis and the importance of technology forecasting. This is followed by an individual introduction of the strategic technology management methods applied in this thesis and of the field of personal intelligent user interfaces. Both fields of interest are defined and examined in detail to provide a comprehensive theoretical base for the subsequent chapters.

illustration not visible in this excerpt

Figure 1-1: Structural overview of the thesis

Tying in with chapter two, chapter three uses previously presented definitions and theories in order to develop a user requirements framework, and, in the end, to define high potential use cases. First, the importance of usability for overall user acceptance is examined. Therefore, existing international standards for usability in the area of human computer interaction will be analyzed. Following that, these findings together with external and internal expert assessments are processed to determine significant attributes for the evaluation of intelligent user interface technologies. Thereafter, the relevance matrix, which determines the fulfilment relevance gap for intelligent user interfaces, will be presented. This is again the key to determine the time until broad market user acceptance for a certain technology. Defining usage scenarios and elucidating their importance in order to find the most promising personal intelligent user interfaces till 2008 completes chapter three.

In chapter four, an in-depth analysis of all the selected interface technologies provided. After a brief description of each technology, its main user requirements are discussed using the findings from the gap analysis. This is followed by an assessment of the time to the previously mentioned user acceptance and a list of possible use cases.

The concluding chapter five gives an outlook on further research needs, raises questions which could not be answered within the scope of this thesis and provides a critical review of the thesis. It closes with a proof of concept by showing that one of the developed high potential use cases of 2005 has been realized by major ICT companies just recently.

Figure 1-1 shows a structural overview of the thesis.

2 Delimitation and Conceptual Definitions

This chapter will provide the necessary theoretical base for the subsequent chapters. Combined through the focus of this thesis, each of the four fields, i.e. strategic technology management, technology forecasting, scenario analyses, and intelligent user interfaces, will be introduced, described, and important terms defined.

2.1 Strategic Technology Management

The future is unknowable and, the more distant the future, the more varied its possibilities. Future survival and prosperity, however, demand current planning and preparation for those unknown possibilities. Specific forecasts, whether they are projections of established trends or inspired hypotheses, can provide planners with but one point estimate of these innumerable possibilities. The challenge is not miraculously to pick the winning forecast but, rather, to develop plans that are viable over the wide range of possible futures—with both plans and a process that manage uncertainty. The technology management is the discipline which meets this strategic challenge.

When approaching this terminology, it is useful to take a closer look at the relevant contextual setting. Therefore, the first step is to clarify the general meaning of the term “management”. The Oxford English Dictionary defines it as follows:

“Organization, supervision, or direction; the application of skill or care in the manipulation, use, treatment, or control (of a thing or person), or in the conduct of something” (qtd.in Henselewski, p. 14)

In business, environment management is usually subdivided into operational, strategic, and technology management. During a lecture at Northwestern University in 2000, Probert encapsulated the main tasks of the three subdivisions in a very simplified but therefore tangible way:

Operational Management = Doing the business

Strategic Management = Keeping the business on track

Technology Management = Managing the know-how

David's more detailed definition of strategic management also states the activities it includes.

“Strategic management can be defined as the formulation, implementation, and evaluation of actions that will enable an organization to achieve its objectives.” (1986, p. 4)

In the context of the above definition, the process of formulation involves identifying internal strengths and weaknesses, determining external opportunities and threats, establishing the company’s mission, setting objectives, developing alternative strategies, analyzing these alternatives, and deciding which ones to execute. Consequently, the process of implementation requires establishing the formulated goals, devising policies, motivating employees, and allocating resources in a manner that will allow pre-conceived strategies to be pursued successfully. Evaluation, in the end, includes all activities necessary for monitoring the results of strategy formulation and implementation.^[3]

The other relevant subdivision of management is technology management. The basic term “technology” describes the application of scientific advances to benefit humanity. Considering the setting of this thesis, the term technology is limited to information and communication technologies. These technologies cover the knowledge and understanding of scientific-technical-socio-economic connections with the products of computers, information, and communication technology. To bring this together with management and to provide a more abstract view, the following definition by Whipp (1991) is helpful:

“Technology may be classified in three ways: as products, processes and people. Here, people is a shorthand way of referring to the management methods, knowledge bases and modes of thought and action which underpin given products and processes.” (qtd. in Probert, p. 11)

Now remembering the definition of management in general, technology management is consequently concerned with ensuring that all the necessary technology is available to the business. In addition, it addresses the processes of understanding and applying technology within the business for profit.

Keeping David’s definition in mind, it is now possible to derive the following definition for strategic technology management (STM): the identification and evaluation of business relevant technologies in a timely manner, as well as the coordination of the know-how, and their application with all vital business units within the company in order to generate potential for economical success.

To seize Probert’s suggestion and put it in a more simple form:

Strategic technology management = Keeping the companies know-how on track

2.2 Methods of Strategic Technology Management

Over the last decades, a number of tools and methods have been developed in order to assist researchers and managers with a key task of STM, namely the identification and evaluation of business relevant technologies in a timely manner.

2.2.1 Technology Forecasting

To a great extent, STM implies technology forecasting (TF). A comprehensive collection of significant attributes regarding TF was developed by Henselewski in 2005. He incorporated the essences of definitions provided by DeLurgio (1998, p.8) and Granger (1989, p. 210) into Bright’s (1979, p. 235), thereby creating the following assessment:

“Technology forecasting is a probabilistic, long-term estimate of the timing, the character or the degree of change in technical parameters and attributes in the design, production and application of devices, materials, and processes, arrived at through a system of reasoning consciously applied by the forecaster and exposed to the recipient.” (Henselewski, p. 19)

Apparently, it is quite essential to base any forecasting activities on an appropriate reasoning system or methodology. Without such a reasoning system or methodology, a forecast is less convincing and loses both its objectivity and capability to decrease uncertainty, especially when it comes to making business decisions (see chapter 1.2; Microsoft, Western Union showcases). Because of the multiplicity of TF-methods (in fact, there are more than 50), only methods applied in this thesis will be discussed.^[4]

2.2.1.1 Expert Panel

This method of technology scouting is based on the assumption that the pooling of knowledge from a certain expert group leads to an early identification of a new technology.^[5] Unlike the related Delphi method, the expert enquiry (or expert panel) is a quantitative technique because findings from the enquiry depend strongly on the statements of every person.^[6] Experts have prolonged or intense experience through practice and education in a particular field. In addition, they possess - for the most part - the most information with the highest actuality and quality regarding the focus area of the enquiry.

There are also some recommended steps that need to be taken to make an expert panel work. First of all, in order to identify eligible panel participants, a systematic literature search has to be performed, nominations must be made by two or more peers in "daisy chain" fashion, and recommendations be submitted by professional organizations. Furthermore, the panellists should be compensated for their time. Regarding communication media, all forms should be included to give panellists maximal freedom of action. During the discussion, questions of fact should be directed to panellists who are relevant experts in that field. A point that is often not taken into consideration is that panellist responses should be anonymous when fed back to the group as a whole.

For this project, DETECON Inc. assembled a permanent team (in the following also referred to as the team) consisting of seven people, including myself, and another group of nine experts which were at our disposal for special topic hearings. The team was not only assembled by DETECON experts but also by two experts from Deutsche Telecom Inhouse Consulting and Capgemini.

A closer look into the biographies of the PIUI experts unveils that even the last consideration of Hungenberg was satisfied, namely that the participants should come from different backgrounds in order to cover a wider spectrum.^[7]

The team generated the relevance matrix for each technology using the input from the ISO framework, researchers and experts from each technology, the basis information research (see also chapter 3.2.2), and added their professional assessment with the entire PIUI team's input. Based on this method, spider graphs for relevance were computed for each PIUI technology. (Meet the team at attachment 3)

2.2.1.2 Scanning and Monitoring

Scanning, in terms of the context of this thesis, is concerned with the search for new technologies while monitoring deals with existing ones. Both are needed for technology forecasting and therefore also for evaluating and analyzing IUIs. Scanning and monitoring (also referred to as environment scanning) should come into operation periodically to ensure it being up to date. Both are also interconnected with each other as Figure 1 shows. It also illustrates the relationship between environmental scanning (ES) and long-range planning, that which defines the strategic technology planning process to a great extent.

illustration not visible in this excerpt

Figure 2-1: Strategic planning process by Renfro and Morrison (1983) (qtd. in Gorden and Glenn 1994, p. 28)

The process of environmental scanning can be defined as:

“the collection and evaluation of data and information from the marketing environment that can influence the organisation's marketing strategies.” (Pearson, 1995)

Environmental scanning is based on the thesis developed by Ansoff, claiming that events which are difficult to predict and force a company to adapt are in fact heralded in advance by other events (e.g. global steel shortage). The goal of the scanning process is to detect these precursor events in order to observe their further development – the monitoring process.^[8] ES usually refers solely to the macro-environment, but it can also include industry and competitor analysis, consumer analysis, product innovations, and the company's internal environment.

Additionally, the PIUI-team used means of product, media, and online scanning, psycho-exploration, semantic analysis und ethnographic studies in order to obtain a wide set of information.^[9]

2.2.1.3 Patent and Literature Analysis

Patents and literature (in this case e.g. technical journals, research papers, etc.) analysis are still important when configuring the business strategy of technological companies. This quantitative method is based on the fact that scientific knowledge and information about new technologies is published as soon as possible in order to document scientific authorship. Information about really innovative techniques and products is often published only in form of patents to protect economic interests. It is important to know that findings from patent analysis are in general more convincing than from mere literature analysis due to the fact that patents have to be filed before publication. Thus, this procedure is usually not done for tactical reasons. (Average lead time of caveat before publication is five to seven years.^[10] (Application in this thesis see 3.2.2 Use case development)

2.2.1.4 Trend Impact Analysis

According to Gordon, trend impact analysis is

“a forecasting method that permits extrapolation of historical trends to be modified in view of expectation about future events.” (1994, p. 4)

Trend analysis is used not only for strategic planning at a corporate and a national level, but also for marketing and business planning.^[11] It has a number of sub-methodologies, namely historical trend analysis, content analysis, cyclical pattern analysis, and the use of expert opinions (see 2.2.1.1 Expert Panel). As applies to most strategic management tools, the trend impact analysis should not be used as a stand-alone method. When balanced with other methods, it proves to be efficient. Figure 2-2 shows the typical design of a trend impact graph and its usual parameters.

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Figure 2-2: Typical event impact parameters (based on Gordon, p. 2)

2.2.1.5 Gap Analysis

In this thesis the generated user requirements matrix resulted in a relevance assessment for each technology as well as a fulfilment assessment, finally leading to a gap analysis (see 3.2.1 The technology user requirements framework). The method can be defined as

“the process of determining, documenting, and approving the variance between business requirements and system capabilities in terms of packaged application features and technical architecture.” (UIS U. Georgetown, 2003)

In the case of technology forecasting were the target state is a more or less a fictional state, thus it is necessary to develop at first a vision for the future state. In this instance it is a gap analysis between the current state of the art of intelligent user interface technology regarding usability and the desired future state (critical capabilities needed to realize each vision statement).

Full user acceptance based on high usability is in the case under consideration the desired state. The gap analysis provides first of all information about which attribute lags most behind and secondly it gives a criterion how long it will take before the gap is closed by showing how big the actual gap is. The application of the method for this thesis is described in 3.2.1 The technology user requirements framework.)

2.2.1.6 Scenario Analysis

According to von Reibnitz, a scenario is the description of a future situation and the development or description of the way leading from today into the future.^[12] She makes the case that the ability to create different future situations allows planners to deal with scenarios that fall between two extremes. In her book Scenario Techniques (1988), von Reibnitz describes the process of scenario techniques as follows.

The first step entails an analysis of an organization’s structure, strengths and weaknesses, goals and strategies. Step two involves an examination of areas and factors of external influences with attention to their interrelationship and dynamics in the system. Step three is an analysis of the development of the future of influence factors. Step four clusters different alternatives to form logical and plausible structures for future scenarios. Step five incorporates these structures into scenarios that describe system dynamics and changes. Step six concludes the process with an analysis of opportunities and risks.

Even though von Reibnitz provides a suitable definition and methodology, a clear overall definition of scenarios within economy and social science research is very difficult to find. The reason for that is the fact that in practice and science literature a multitude of ideas and methods exists. The main difference lies in the steps that are necessary to take in order to develop a scenario.

Basis for this thesis is the following definition by Gausemeier, Fink, and Schalke (translated from German):

“A scenario is the description of a complex, future situation. Its occurrence can’t be forecasted with certainty. Furthermore it’s the portrait of a development which could lead from the present to this situation.” (1996, p. 108)

The goal of generating scenarios is to understand the mix of strategic decisions that are of maximum benefit in the face of various uncertainties and challenges posed by the external environment. Scenario building, in conjunction with a careful analysis of the driving forces, fosters systematic study of potential future possibilities—both good and bad. This forecasting approach enables decision makers and planners to grasp the long-term requirements for sustained advantage, growth, and avoidance of problems.^[13]

Figure 2-3 shows the working model of the scenario method. It starts in the present with the target point on the future horizon. The scenario funnel symbolizes the increasing complexity and uncertainty with the progressive time horizon.^[14] The possible target state lies in the future, symbolized in Figure 2-3 by the section of the funnel. The development which will lead to the future state is symbolized by the development paths.

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Figure 2-3: Working model of the scenario method - the scenario funnel (Cf. Geschka 1995, p. 305)

The Future Group points out that a scenario is a rich and detailed portrait of a plausible future world, one sufficiently vivid that a planner can clearly see and comprehend the problems, challenges, and opportunities that such an environment would present. They also make quite clear that a scenario is not a prediction of specific forecast per se; rather, it is a plausible description of what might occur, which brings them in a line with Gausmeier, Fink, and Schalke. Because of the multiplicity of forces that shape the future, their complexity and their interactions, the future itself can never be accurately or completely known. Although most planners and futurists today reject the idea that planning should be conducted against a single “most likely” image of the future, the approach taken in this thesis to develop PIUI usage scenarios aims in this direction. The reasons for this approach are multiple. One is that in order to develop a product scenario usually the most likely user group and use case have to be defined. This reduces the complexity. But, as a matter of fact, due to their special ability to adapt, IUIs and consequently PIUIs have the potential and also demand to be applicable in every possible use case and for every user. Another reason is that the purpose of the thesis is to develop high potential use cases till 2008. In order to do so, it is assumed that such a use case involves IUIs which are highly developed regarding usability; this is to say the best case (compare extreme scenario B t in Figure 2-3). Therefore, the use cases to develop require a “most likely” development of the involved technologies in the future and as described later (see chapter 3.2.2) it is possible to assess when a technology will reach a certain state of maturity.

In summary, though not being scenarios developed in a classic way, the following use cases and scenarios (see chapter four for use cases and attachment seven and eight for usage scenarios) are still scenarios according to the definition given by Gausemeier, Fink, and Schalke.

To conclude this technology forecasting chapter, it’s crucial to remember that no scenario is ever probable. On the contrary, the probability of any scenario ever being realized is minute. Accuracy is not the measure of a good scenario; rather, it is:

To conclude the technology forecasting chapter there is to say that no scenario is ever probable; the probability of any scenario ever being realized is minute. Accuracy is not the measure of a good scenario; rather, it is:

- Plausibility (a rational route from here to there),
- Internal consistency,
- Description of causal processes, and
- Usefulness in decision making.^[15]

Scenarios are designed to expand a planner’s vision. A certain amount of creative thinking and imagination is essential to the process.

2.2.2 The Gardner Hype Cycle

The 2005 Gartner Hype Cycle for Human-Computer Interaction (see Attachment 1: Gartner Hype Cycle) is not only used in the context of this thesis as an additional justification for the selected technologies (see chapter 4) but it is also an example for one of many aids for the strategic management which can be acquired by purchase.

Gartner defines its product as followed:

“A Hype Cycle is a graphic representation of the maturity, adoption and business application of specific technologies.”(Gartner, 2005)

It also includes an estimation of how and in what time a technology will develop in the market environment therefore it is to some extend a trend impact analyses (see 2.2.1.4 Trend Impact Analysis).

Jeckie Fenn the creator of the first Hype Cycle (HC) stated hortative:

„Don't invest in a technology just because it is being hyped or ignore a technology just because it is not living up to early over expectations.“(qtd. in Petty & Goasduff, 2005)

Fenns basic message is that even this easy to read, compact report does not exempt the manager of today from using his knowledge and experience if it comes to strategic decisions within a company.

Since 1995, Gartner has used the HC to characterize the over-enthusiasm or "hype" and subsequent disappointment that typically happens with the introduction of new technologies. The phases a technology typically passes trough afterwards regarding to Gartner are shown in Figure 2-4.

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Figure 2-4: Phases of the Gartner Hype Cycle (Gartner, 2005)

2.2.3 Technology Assessment

Technology assessment (TA) is the study and evaluation of new technologies. It is based on the conviction that new developments within, and discoveries by, the scientific community are relevant for the world at large rather than just for the scientific experts themselves, and that technological progress can never be free of ethical implications. Also, technology assessment recognizes the fact that scientists normally are not trained ethicists themselves and accordingly ought to be very careful when passing ethical judgment on their own, or their colleagues’, new findings, projects, or work in progress.

Technology assessment assumes a global perspective and is future-oriented rather than backward-looking or anti-technological. Being an interdisciplinary approach, TA considers it to be its task to solve already existing problems and to prevent potential damage caused by uncritical application and commercialization of new technologies. Therefore, any results of technology assessment studies must be published, and particular consideration must be given to communication with political decision-makers.^[16]

According to “The Technology Assessment Act” enacted by the Congress of the United States of America, the main goals of TA are (1972, p. 3):

1. to identify existing or probable impacts of technology or technological programs,
2. where possible, to ascertain cause-and-effect relationships,
3. to identify alternative technological methods of implementing specific programs,
4. to identify alternative programs for achieving requisite goals,
5. to make estimates and comparisons of the impacts of alternative methods and programs,
6. to present findings of completed analyses to the appropriate legislative authorities,
7. to identify areas where additional research or data collection is required to provide adequate support for the further assessments and estimates, and
8. to undertake such additional associated activities as the appropriate authorities may direct.

The act was enacted in order to establish the Office of Technology Assessment.

Nowadays, TA is more important than ever. In a time where governments chase after fast technology development, it is more than ever time for scientists, managers and everybody involved in the process of the development of a technology to take responsibility for what they do and, consequently, for the society they live in. As the reader will realize, the technologies described in the following already have or will have a major impact on everybody’s life (especially regarding privacy issues).

The method of TA can be considered to be not only a tool to help the company prevent an investment in a dangerous technology (e.g. CFC, in German called FCKW), but also a reminder for the people in charge to think about the consequences of their work. Due to the limited scope of this paper, a full assessment of the selected technologies cannot be provided. However, this thesis will hopefully encourage the reader to critically question the use of technologies.

2.3 Personal Intelligent User Interface

Before answering the question of what is a high potential use case could be for a PIUI’s (chapter 3.2.2), a definition of personal intelligent user interfaces is needed. To acquire this, the basics of HCI, UI, and IUI have to be described before.

2.3.1 Definition Human-Computer Interaction

In “The future of HCI”, just recently published by the Association for Computing Machinery (ACM), Canny reports that

“at a recent industry advisory board meeting for U.C. Berkeley's computer science division, HCI was unanimously cited as the most important priority for future research and teaching by our industry experts.” (2005, p.1)

But what is HCI? Currently, there is no definition universally agreed upon concerning the range of topics which form the field of human-computer interaction (HCI). However, ACM's Special Interest Group on Computer-Human Interaction offers a working definition:

“Human-computer interaction is a discipline concerned with the design, evaluation and implementation of interactive computing systems for human use and with the study of major phenomena surrounding them.” (Hewett, et al. 2004)

They go one step further by characterizing HCI as a field by listing some of its particular areas of focus:

“Human-computer interaction is concerned with the joint performance of tasks by humans and machines; the structure of communication between human and machine; human capabilities to use machines (including the learnability of interfaces); algorithms and programming of the interface itself; engineering concerns that arise in designing and building interfaces; the process of specification, design, and implementation of interfaces; and design trade-offs. Human-computer interaction thus has science, engineering, and design aspects.” (Hewett, et al. 2004)

Taking all this into account, the key element in human-computer interaction is, first and foremost, humans.

2.3.2 Definition of User Interface

A main element of HCI is the user interface (UI). An interface, in general, is a boundary across which systems communicate with each other.

Adding the user narrows the possibilities of communicating participants to a human on one side, and to (computer) systems on the other. A user interface is one of three main types of interfaces in computer technology, the other two being software and hardware interfaces. A pertinent definition for user interface is offered by Clarke:

“The physical means of communication between a person and a software program or operating system.” (2003)

Fortier, et al. complements the definition by stating that an UI is

“the system of computer screen images, devices, and software components that allow the user to interact with and control the computer’s operating system.” (1988, p. 54)

The quality of HCI depends largely on the effectiveness of the UI. A good indicator therefore is the consumer market, where a product’s success depends on each user’s experience with the interface. In fact, a good UI can carry a product in spite of inherent weaknesses, and a great feat of engineering on the back end will be undone by a poor interface.^[17]

2.3.3 Definition of Intelligent User Interface

“Intelligent user interfaces are human-machine interfaces that aim to improve the efficiency, effectiveness, and naturalness of human-machine interaction by representing, reasoning, and acting on models of the user, domain, task, discourse, and media (e.g., graphics, natural language, gesture). Intelligent user interfaces are multifaceted, in purpose and nature, and include capabilities for multimedia input analysis, multimedia presentation generation, model-based interfaces, agent-based interfaces, and the use of user, discourse, and task models to personalize and enhance interaction.” (Maybury, 2001)

[...]

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^[1] Western Union is a financial services and communications company based in the United States and owned by First Data Corporation. Cf. http://www.westernunion.com

^[2] Cf. http://www.forbes.com/billionaires

^[3] Cf. David, p. 4.

^[4] Cf. Geschka, p. 624.

^[5] Cf. Geschka, p. 631.

^[6] Cf. Gordon and Glenn, p. 1.

^[7] Cf. Hungenberg, p. 119.

^[8] Cf. Ansoff, p. 129 et spp.

^[9] For further reading see Klaas, 2003.

^[10] Cf. Klaas, p. 36 f.

^[11] For further reading see Gordon, 1994.

^[12] Cf. Reibnitz 1992, p. 14.

^[13] For further reading see Ratcliffe, 2000.

^[14] Cf. Reibnitz 1992, p. 26.

^[15] Cf. The Futures Group, p. 4.

^[16] Cf. Bugl, p. 245 et spp..

^[17] Cf. Canny, p. 1.