The document discusses the challenges of achieving successful digital transformation (DX) and presents a new roadmapping method tailored for machine learning applications to foster dialogue among stakeholders. It highlights the importance of addressing perception gaps caused by unclear goals and the need for closer human-machine collaboration. The proposed method was evaluated in a workshop, revealing the effectiveness of roadmapping as a tool for mutual understanding and planning in DX initiatives.

1. Copyright 2021, JAIST Naoshi Uchihira.
AHFE HSSE 2021
Session 243: Creating Value in Teams, Organizations, Communities, and Societies II
Dialogue Tool for Value Creation
in Digital Transformation:
Roadmapping for Machine Learning Applications
1
July 29, 2021 15:00-16:30
Naoshi Uchihira
Japan Advanced Institute of Science
& Technology
uchihira@jaist.ac.jp
12 minutes
presentation

2. 2
Outline
Digital transformation (DX) is
extremely important, but difficult
to achieve successfully
because of various gaps.
Roadmapping is effective for
dialogue among stakeholders
to fill the gaps.
Existing roadmapping methods
are not suitable for DX utilizing
machine learning applications.
Proposal of a new roadmapping
method for DX utilizing machine
learning applications.
Machine
(Technology/Function)
Human/Society
Value
Machine
(Technology/Function)
Human/Society
Value
Machine
(Technology/Function)
Human/Society
Value
Phase
Time
Phase Phase
The proposed method was applied
and evaluated in the roadmapping
workshop.

3. 3
Digital Transformation
Chances
•Digital transformation (DX) is expected to create new value.
•In DX, AI technologies including machine learning are
indispensable for creating new value.
Difficulties
•DX faces many difficulties due to various perception gaps
among the stakeholders.
•Perception gaps are caused by an unclear goal and path.
•Roadmap and Roadmapping are effective for sharing how
business and society should be transformed in the future
and how AI and machine learning will evolve for DX.

4. 4
Technology & Product/Service Roadmap
Technology
Products/
Services
Market
Drivers
Time
A technology roadmap is a flexible planning technique
to support strategic and long-range planning (Wikipedia).

5. 5
Roadmapping as a Dialogue Tool
•Roadmapping is the process of creating, sharing, and
utilizing a roadmap.
•Roadmapping is effective as a "dialogue tool" for clarifying
the values to be realized and filling the perception gaps
among stakeholders.

6. 6
Traditional Roadmapping
•Backcasting type: Leads to what
kind of technological development
is necessary to realize the desired
future. Ex. T-Plan (Phaal et al., 2001)
•Fore-casting type: The future is
drawn as an extension of the
current technology mainly used in
academic societies.
•Middle-up-down type: Uchihira
(2007) proposed a road mapping
method suitable for systems
engineering.
Backcasting Type
Technology
Function
Value(Human/Society)
Time
Forecasting Type
Technology
Function
Value(Human/Society)
Time

7. 7
Roadmapping for Machine Learning Application Systems
• In Machine Learning Application Systems (MLAS) in DX, humans and
machine should collaborate (socio-technical system).
• Roadmapping of MLAS requires collaboration phase design.
• Each phase should be stable for humans and society, and
discontinuous transformation is needed to move between phases .
⇒ Co-evolution Type Roadmapping
Example (Autonomous Driving)
Machine
(Technology/Function)
Human/Society
Value
Driver Assistance
Machine
(Technology/Function)
Human/Society
Value
Partial Automation
Machine
(Technology/Function)
Human/Society
Value
High Automation
Phase Phase Phase

8. 8
Co-evolution Type Roadmapping for MLAS
Co-evolution Type
Machine
(Technology/Function)
Human/Society
Value
Machine
(Technology/Function)
Human/Society
Value
Machine
(Technology/Function)
Human/Society
Value
Phase
Time
Phase Phase
Backcasting Type
Technology
Function
Value(Human/Society)
Time
Forecasting Type
Technology
Function
Value(Human/Society)
Time

9. 9
Proposed Technology Roadmapping Method
Collaboration phase design is introduced
in Step 3 and refined Step 4.
(Step 1) Issues and
Needs Map
(Step 2) Technology
Seeds and Policy Map
(Step 3) Market Trend
Map (by application)
(Step 4) Issues and
Needs Trend Map
(by application)
(Step 7) Strategic Story
(by application)
(Step 6) Technology
Roadmap (by application)
(Step 5) Needs/Seeds
Matching Table
(by application)

10. 10
Two-Day Roadmapping Workshop
Date&Place: September 15 and 16, 2019, Shonan International
Village Center, Kanagawa, Japan.
Participants: 20 experts in machine learning engineering and road
mapping (half university members and half company members).

11. 11
Step1: Issues & Needs Map for MLAS
Source:
■Interviews
• Denso
• Kewpie
• KIOXIA
• NTT Data
• Panasonic
• SUBARU
• Toshiba
etc.
■Literature
• Reports
• Books
• Web Pages
http://www.jaist.ac.jp/ks/labs/uchihira/mlas-pm-map.html
Issues and Needs Explanation
1 Reliability and Safety
Difficulties in quality assurance of MLAS (reliability, safety, and
performance).
2 Efficiency and Productivity
Difficulties related to the efficiency and productivity of MLAS development
(cost and delivery).
3 Process Management
Difficulties in process management of MLAS implementation, operation,
and maintenance.
4
Relationship between
Humans and AI
Difficulties arising from the immaturity of the human-AI relationship.
5 Business and Monetizing Difficulties related to investment and return in MLAS.
6 Standards and Guidelines
Difficulties caused by the lack of safety standards, quality assurance
guidelines, and liability recognized in society and industry.
7 AI Awareness Difficulties caused by stakeholders' misperceptions of AI.
8
AI Human Resource
Development
Difficulties related to the talent shortage capable of leveraging AI
(executives, users, managers and system developers).
9
Data and Model
Distribution
Difficulties related to the distribution and protection of data and models
(ownership of models and data).
10 Policy and Social System Difficulties due to the immaturity of the policy and social system for AI.
11 Security and Privacy Difficulties in ensuring security and protecting privacy.
12
Legal Systems and
Regulations
Difficulties due to the immaturity of the legal and regulatory system for AI.
(Step 1) Issues and
Needs Map
(Step 2) Technology
Seeds and Policy Map
(Step 3) Market Trend
Map (by application)
(Step 4) Issues and
Needs Trend Map
(by application)
(Step 7) Strategic Story
(by application)
(Step 6) Technology
Roadmap (by application)
(Step 5) Needs/Seeds
Matching Table
(by application)

12. 12
Step2: Technology Seeds & Policy Map for MLAS
Technology Seeds and
Policy
Examples
1 Quality assurance
Testing, debug, and verification
methods for MLAS
2 Explainable AI
Transformation from black box model to
white box model
3 Development process
Development pattern and process
mining for MLAS
4 Project management Machine learning project canvas
5
Development support
environment
Interactive modeling tool
6 System-wide safety STAMP/STPA, FRAM
7 AI-human cooperation Human-in-the-loop machine learning
8 Security and privacy Adversarial example
9 AI and ethics AI ethics guidelines
10
Human resource
development
AI education curriculum
Source:
• Hearing with
experts
• Academic
papers
(Step 1) Issues and
Needs Map
(Step 2) Technology
Seeds and Policy Map
(Step 3) Market Trend
Map (by application)
(Step 4) Issues and
Needs Trend Map
(by application)
(Step 7) Strategic Story
(by application)
(Step 6) Technology
Roadmap (by application)
(Step 5) Needs/Seeds
Matching Table
(by application)

13. 13
Step3,4: Phases are defined for each sector
•Initial phases are prepared as a rough guide.
•Additions and corrections were made by the
participating members during the workshop.
Autonomous Driving
0. No Automation
1. Driver Assistance
2. Partial Automation
3. Conditional
Automation
4. High Automation
5. Full Automation
Smart Factory
1. Data collection
and visualization
2. Realization of the
data-driven
PDCA cycle
3. Automatic factory
improvement
Robotic Process
Automation (RPA)
1. Expansion of the
automated processes
2. Business optimization
3. Human satisfaction
improvement
(Step 1) Issues and
Needs Map
(Step 2) Technology
Seeds and Policy Map
(Step 3) Market Trend
Map (by application)
(Step 4) Issues and
Needs Trend Map
(by application)
(Step 7) Strategic Story
(by application)
(Step 6) Technology
Roadmap (by application)
(Step 5) Needs/Seeds
Matching Table
(by application)

14. 14
Step 5,6: Creating Roadmap
•A seeds/needs matching
table and a roadmap are
created.
•This was done by trial and error using sticky notes
in front of a white board.
(Step 1) Issues and
Needs Map
(Step 2) Technology
Seeds and Policy Map
(Step 3) Market Trend
Map (by application)
(Step 4) Issues and
Needs Trend Map
(by application)
(Step 7) Strategic Story
(by application)
(Step 6) Technology
Roadmap (by application)
(Step 5) Needs/Seeds
Matching Table
(by application)

15. 15
Example of a completed roadmap
Market Trend
(Phases and
Values)
Technology
Seeds & Policy
Features
(Issues and
Needs)
Phase Phase Phase
Time

16. 16
Step 7: Presentations by Three Sectors
Smart Factory Group
Autonomous Driving Group
RPA Group
(Step 1) Issues and
Needs Map
(Step 2) Technology
Seeds and Policy Map
(Step 3) Market Trend
Map (by application)
(Step 4) Issues and
Needs Trend Map
(by application)
(Step 7) Strategic Story
(by application)
(Step 6) Technology
Roadmap (by application)
(Step 5) Needs/Seeds
Matching Table
(by application)

17. 17
Evaluation and Discussion (1)
Roadmapping as Dialogue Tool
The workshop functioned to promote the mutual
understanding and constructive discussions between
university researchers and company engineers, as
well as between engineers from different companies.
(Questionnaire Survey after Workshop)
“Roadmapping seems to be widely used in business,” “I
want to use it for my company's business planning,” “it was
helpful to understand how to grasp uncertainty,” and “the
three-layer structure of market trend, feature, and
technology is easy to understand.”

18. 18
Evaluation and Discussion (2)
Human-Machine Collaboration Phase Design
•It was difficult in the limited time (two-day
workshop) to design phases clearly.
•RPA group continued to discuss after the
workshop, and were finally able to derive four
phases different from the original one.
•An additional tool is effective to design these
phases more systematically by using typical
design patterns.

19. 19
Summary
Digital transformation (DX) is
extremely important, but difficult
to achieve successfully
because of various gaps.
Roadmapping is effective for
dialogue among stakeholders
to fill the gaps.
Existing roadmapping methods
are not suitable for DX utilizing
machine learning applications.
Proposal of a new roadmapping
method for DX utilizing machine
learning applications.
Machine
(Technology/Function)
Human/Society
Value
Machine
(Technology/Function)
Human/Society
Value
Machine
(Technology/Function)
Human/Society
Value
Phase
Time
Phase Phase
The proposed method was applied
and evaluated in the roadmapping
workshop.
Co-evolution Type Roadmapping
Human-Machine Collaboration Phase Design
Dialog Tool

20. 20
Thank you for your attention.
Japan Advanced Institute of
Science & Technology