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IEEE Computer Society
2024 Technology Predictions Update
Hironori (Hiro) Washizaki
IEEE Computer Society 2025 President
Waseda University, Professor
FM+SE SUMMIT 2024, March 28th 2024
IEEE Computer Society: Empowering Computer Science and Engineering
Professionals to Fuel Continued Advancement
IEEE CS Technology Prediction
Team (Chair: Dejan Milojicic)
IEEE CS Technology Predictions 2023
4
IEEE CS Technology Prediction Team (Chair: Dejan Milojicic) https://www.computer.org/2023-top-technology-predictions
Chance of success higher
than impact on humanity
Impact on humanity higher than
chance of success (worth investing in)
Remote Healthcare
Wearables
Generative AI
Disinformation
detection/correction
AI-assisted
DevOps
Artificial General
Intelligence (AGI)
5
IEEE Computer Society (CS) Global Scientists and Engineers Rank 2023
Technology Trend Predictions
https://www.computer.org/press-room/scientists-and-engineers-rank-2023-
technology-trend-predictions
Remote Healthcare &
Wearables
Generative AI
Disinformation
detection/correction
AI-assisted
DevOps
Artificial General
Intelligence (AGI)
IEEE CS Technology 2023
Prediction vs. Assessment
• How original grades
stood the one-year test,
as reflected in A/B
grading
• High growth of generative
AI, slowdown of COVID-
related technologies
Prediction
Jan 2023
Assessment
Dec 2023
IEEE CS Technology Prediction
Team (Chair: Dejan Milojicic)
7
Megatrends in IEEE Future Direction 2023 and IEEE-CS Technology Predictions 2024
IEEE CS Technology Prediction Team (Chair: Dejan Milojicic) https://www.computer.org/resources/2024-top-technology-predictions
• AGI technologies are
deeply entangled with
socio, economic, and
ecological aspects.
Next Gen AI
Generative AI
applications
Metaverse
Low power AI
accelerator
IEEE CS Technology Predictions 2024
Chance of success higher
than impact on humanity
Impact on humanity
higher than chance of
success (worth investing in)
IEEE CS Technology Prediction Team (Chair: Dejan Milojicic) https://www.computer.org/resources/2024-top-technology-predictions
Generative AI
• Provides flexibility for new challenges and
adaptive responses demand.
• Safety and security: Need to build safeguards
against misuses and generated harmful content,
such as deep fakes.
• Lacking Robustness, Reliability, Control, and
Explainability, necessitating transparent
techniques and consistent AI models. This is a
major issue for agents and trusted apps.
• Bias and data quality issues in large datasets call
for better curation.
• High computational costs limit model training to
an oligarchy of very few players who can afford to
train a foundation model.
• Evolving regulatory landscapes, especially
regarding data privacy and use, demand for
ensuring legal and ethical compliance.
• Enhanced creativity in arts and
design, accelerated design.
• Generative AI-based
revolutionized personalized
medicine, from drug discovery to
tailored treatment plans.
• Personalized education and
marketing boost productivity.
• Improved customer support
through natural interactions-
conversation, problem solving,
detailed product knowledge.
• Accelerated scientific discovery
and 3D modeling.
Problems/demand Opportunities
IEEE CS Technology Prediction Team (Chair: Dejan Milojicic) https://www.computer.org/resources/2024-top-technology-predictions
• Helps content creators and designers to be
more productive.
• Helps businesses improve their digital
channels and marketing.
• Time-To-Market significantly decreased.
• Better accessibility: image-to-text, audio
transcripts, translations (including to sign
language).
• Personalized assistants (coding, editing,
teaching, etc.) increase productivity and
efficiency.
• Displacement of repetitive jobs requires
reskilling/upskilling.
• Spreading of much higher quality
misinformation requires source checking
and critical thinking.
• More environmentally sustainable practices
in various industries through optimization of
resources and reduction of waste.
• Significantly changing traditional
Industries—like manufacturing, agriculture,
and transportation.
• Generative AI may decrease the need for processing-
intensive training.
• Support for no/low-code.
• Generative AI will increase AI adoption and create new
revenue streams.
• Global cooperation in standardization and best practices to
address challenges like intellectual property, cybersecurity,
and ethical norms.
• Public-Private Partnerships: tighter collaborations between
government, academia, and industry.
• Increased significance of Edge Computing in processing data
closer to the source, reducing latency, and improving response
times.
• Enablers: New ML approaches, affordable AI tools, open
models, access to large curated datasets, AI-integrated agents
for automation.
• Inhibitors: Threat to content creators and IP holders, difficulty
in distinguishing human created content versus machine
created, adversarial applications, Ethical questions of GAI
versus human content generation, lack of interoperability,
closed models, low quality and biased datasets, high
compute costs, lack of trust in AI, regulatory burdens and
resistance to change.
Impact Sustainable Solution/Business Opportunity
IEEE CS Technology Prediction Team (Chair: Dejan Milojicic) https://www.computer.org/resources/2024-top-technology-predictions
Knowledge Area
Topic Topic
Reference
Material
Body of Knowledge Skills Competencies Jobs / Roles
SWEBOK
Software Engineering Professional Certifications
SWECOM
EITBOK
Learning courses
11
Guide to the Software Engineering Body of Knowledge (SWEBOK)
https://www.computer.org/education/bodies-of-knowledge/software-engineering
• Guiding researchers and practitioners to identify and have
common understanding on “generally-accepted-knowledge”
in software engineering
• Foundations for certifications and educational curriculum
• ‘01 v1, ‘04 v2, ‘05 ISO adoption, ‘14 v3, ’24 v4 soon!
SWEBOK Guide V4
(Editor: Hironori Washizaki)
Mainframe
70’s –
Early 80’s
Late 80’s -
Early 90’s
Late 90’s -
Early 00’s
Late 00’s -
Early 10’s
PC,
Client &
server
Internet
Ubiquitous
computing
Late 10’s -
Early 20’s
IoT,
Big data,
AI
Structured
programming
Waterfall
Formalization
Design
Program
generation
Maturity
Management
Object-oriented
Req. eng.
Modeling
Verification
Reuse
Model-driven
Product-line
Global & open
Value-based
Systems eng.
Agile
Iterative &
incremental
DevOps
Empirical
Data-driven
Continuous
SE and IoT
SE and AI
SWEBOK V1
SWEBOK V2
SWEBOK V3
SWEBOK V4
SWEBOK Evolution from V3 to V4
• Modern engineering, practice update, BOK grows and recently developed areas
Requirements
Design
Construction
Testing
Maintenance
Configuration Management
Engineering Management
Process
Models and Methods
Quality
Professional Practice
Economics
Computing Foundations
Mathematical Foundations
Engineering Foundations
Requirements
Architecture
Design
Construction
Testing
Operations
Maintenance
Configuration Management
Engineering Management
Process
Models and Methods
Quality
Security
Professional Practice
Economics
Computing Foundations
Mathematical Foundations
Engineering Foundations
V3 V4
Agile,
DevOps
AI for SE,
SE for AI Software
engineering
AI
AI for SE
SE for AI
Mainframe
70’s –
Early 80’s
Late 80’s -
Early 90’s
Late 90’s -
Early 00’s
Late 00’s -
Early 10’s
PC,
Client &
server
Internet
Ubiquitous
computing
Late 10’s -
Early 20’s
IoT,
Big data,
AI
GenAI, FM,
Autonomous,
Quantum,
Continuum
Late 20’s
Structured
programming
Waterfall
Formalization
Design
Program
generation
Maturity
Management
Object-oriented
Req. eng.
Modeling
Verification
Reuse
Model-driven
Product-line
Global & open
Value-based
Systems eng.
Agile
Iterative &
incremental
DevOps
Empirical
Data-driven
Continuous
SE and IoT
SE and AI
SE and GenAI
SE and QC
Sustainability
SE for
autonomous
and continuum
AI-assisted
DevOps/OpsDev
SWEBOK V1
SWEBOK V2
SWEBOK V3
SWEBOK V4
8
Megatrends in IEEE Future Direction 2023 and IEEE-CS Technology Predictions 2024
IEEE CS Technology Prediction Team (Chair: Dejan Milojicic) https://www.computer.org/resources/2024-top-technology-predictions
• We have four core AGI technology
predictions compared to eight
sustainability-related and nine
digital transformation-related
predictions.
• AGI technologies are deeply
entangled with socio, economic,
and ecological aspects.
IEEE CS Technology Predictions 2024
Chance of success
higher than impact
on humanity
Impact on humanity higher
than chance of success
(worth investing in)
IEEE CS Technology Prediction Team (Chair: Dejan Milojicic) https://www.computer.org/resources/2024-top-technology-predictions
Generative AI
• Provides flexibility for new challenges and adaptive
responses demand.
• Safety and security: Need to build safeguards
against misuses and generated harmful content,
such as deep fakes.
• Lacking Robustness, Reliability, Control, and
Explainability, necessitating transparent techniques
and consistent AI models.
• This is a major issue for agents and trusted apps.
• Bias and data quality issues in large datasets call
for better curation.
• High computational costs limit model training to an
oligarchy of very few players who can afford to
train a foundation model.
• Evolving regulatory landscapes, especially
regarding data privacy and use, demand for
ensuring legal and ethical compliance.
• Enhanced creativity in arts and
design, accelerated design.
• Generative AI-based
revolutionized personalized
medicine, from drug discovery to
tailored treatment plans.
• Personalized education and
marketing boost productivity.
• Improved customer support
through natural interactions-
conversation, problem solving,
detailed product knowledge.
• Accelerated scientific discovery
and 3D modeling.
Problems/demand Opportunities
Mainframe
70’s –
Early 80’s
Late 80’s -
Early 90’s
Late 90’s -
Early 00’s
Late 00’s -
Early 10’s
PC,
Client &
server
Internet
Ubiquitous
computing
Late 10’s -
Early 20’s
IoT,
Big data,
AI
GenAI, FM,
Autonomous,
Quantum,
Continuum
Late 20’s
Structured
programming
Waterfall
Formalization
Design
Program
generation
Maturity
Management
Object-oriented
Req. eng.
Modeling
Verification
Reuse
Model-driven
Product-line
Global & open
Value-based
Systems eng.
Agile
Iterative &
incremental
DevOps
Empirical
Data-driven
Continuous
SE and IoT
SE and AI
SE and GenAI
SE and QC
Sustainability
SE for
autonomous
and continuum
AI-assisted
DevOps
SWEBOK V1
SWEBOK V2
SWEBOK V3
SWEBOK V4

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IEEE Computer Society 2024 Technology Predictions Update

  • 1. IEEE Computer Society 2024 Technology Predictions Update Hironori (Hiro) Washizaki IEEE Computer Society 2025 President Waseda University, Professor FM+SE SUMMIT 2024, March 28th 2024
  • 2. IEEE Computer Society: Empowering Computer Science and Engineering Professionals to Fuel Continued Advancement
  • 3. IEEE CS Technology Prediction Team (Chair: Dejan Milojicic)
  • 4. IEEE CS Technology Predictions 2023 4 IEEE CS Technology Prediction Team (Chair: Dejan Milojicic) https://www.computer.org/2023-top-technology-predictions Chance of success higher than impact on humanity Impact on humanity higher than chance of success (worth investing in)
  • 5. Remote Healthcare Wearables Generative AI Disinformation detection/correction AI-assisted DevOps Artificial General Intelligence (AGI) 5 IEEE Computer Society (CS) Global Scientists and Engineers Rank 2023 Technology Trend Predictions https://www.computer.org/press-room/scientists-and-engineers-rank-2023- technology-trend-predictions Remote Healthcare & Wearables Generative AI Disinformation detection/correction AI-assisted DevOps Artificial General Intelligence (AGI) IEEE CS Technology 2023 Prediction vs. Assessment • How original grades stood the one-year test, as reflected in A/B grading • High growth of generative AI, slowdown of COVID- related technologies Prediction Jan 2023 Assessment Dec 2023
  • 6. IEEE CS Technology Prediction Team (Chair: Dejan Milojicic)
  • 7. 7 Megatrends in IEEE Future Direction 2023 and IEEE-CS Technology Predictions 2024 IEEE CS Technology Prediction Team (Chair: Dejan Milojicic) https://www.computer.org/resources/2024-top-technology-predictions • AGI technologies are deeply entangled with socio, economic, and ecological aspects. Next Gen AI Generative AI applications Metaverse Low power AI accelerator
  • 8. IEEE CS Technology Predictions 2024 Chance of success higher than impact on humanity Impact on humanity higher than chance of success (worth investing in) IEEE CS Technology Prediction Team (Chair: Dejan Milojicic) https://www.computer.org/resources/2024-top-technology-predictions
  • 9. Generative AI • Provides flexibility for new challenges and adaptive responses demand. • Safety and security: Need to build safeguards against misuses and generated harmful content, such as deep fakes. • Lacking Robustness, Reliability, Control, and Explainability, necessitating transparent techniques and consistent AI models. This is a major issue for agents and trusted apps. • Bias and data quality issues in large datasets call for better curation. • High computational costs limit model training to an oligarchy of very few players who can afford to train a foundation model. • Evolving regulatory landscapes, especially regarding data privacy and use, demand for ensuring legal and ethical compliance. • Enhanced creativity in arts and design, accelerated design. • Generative AI-based revolutionized personalized medicine, from drug discovery to tailored treatment plans. • Personalized education and marketing boost productivity. • Improved customer support through natural interactions- conversation, problem solving, detailed product knowledge. • Accelerated scientific discovery and 3D modeling. Problems/demand Opportunities IEEE CS Technology Prediction Team (Chair: Dejan Milojicic) https://www.computer.org/resources/2024-top-technology-predictions
  • 10. • Helps content creators and designers to be more productive. • Helps businesses improve their digital channels and marketing. • Time-To-Market significantly decreased. • Better accessibility: image-to-text, audio transcripts, translations (including to sign language). • Personalized assistants (coding, editing, teaching, etc.) increase productivity and efficiency. • Displacement of repetitive jobs requires reskilling/upskilling. • Spreading of much higher quality misinformation requires source checking and critical thinking. • More environmentally sustainable practices in various industries through optimization of resources and reduction of waste. • Significantly changing traditional Industries—like manufacturing, agriculture, and transportation. • Generative AI may decrease the need for processing- intensive training. • Support for no/low-code. • Generative AI will increase AI adoption and create new revenue streams. • Global cooperation in standardization and best practices to address challenges like intellectual property, cybersecurity, and ethical norms. • Public-Private Partnerships: tighter collaborations between government, academia, and industry. • Increased significance of Edge Computing in processing data closer to the source, reducing latency, and improving response times. • Enablers: New ML approaches, affordable AI tools, open models, access to large curated datasets, AI-integrated agents for automation. • Inhibitors: Threat to content creators and IP holders, difficulty in distinguishing human created content versus machine created, adversarial applications, Ethical questions of GAI versus human content generation, lack of interoperability, closed models, low quality and biased datasets, high compute costs, lack of trust in AI, regulatory burdens and resistance to change. Impact Sustainable Solution/Business Opportunity IEEE CS Technology Prediction Team (Chair: Dejan Milojicic) https://www.computer.org/resources/2024-top-technology-predictions
  • 11. Knowledge Area Topic Topic Reference Material Body of Knowledge Skills Competencies Jobs / Roles SWEBOK Software Engineering Professional Certifications SWECOM EITBOK Learning courses 11 Guide to the Software Engineering Body of Knowledge (SWEBOK) https://www.computer.org/education/bodies-of-knowledge/software-engineering • Guiding researchers and practitioners to identify and have common understanding on “generally-accepted-knowledge” in software engineering • Foundations for certifications and educational curriculum • ‘01 v1, ‘04 v2, ‘05 ISO adoption, ‘14 v3, ’24 v4 soon! SWEBOK Guide V4 (Editor: Hironori Washizaki)
  • 12. Mainframe 70’s – Early 80’s Late 80’s - Early 90’s Late 90’s - Early 00’s Late 00’s - Early 10’s PC, Client & server Internet Ubiquitous computing Late 10’s - Early 20’s IoT, Big data, AI Structured programming Waterfall Formalization Design Program generation Maturity Management Object-oriented Req. eng. Modeling Verification Reuse Model-driven Product-line Global & open Value-based Systems eng. Agile Iterative & incremental DevOps Empirical Data-driven Continuous SE and IoT SE and AI SWEBOK V1 SWEBOK V2 SWEBOK V3 SWEBOK V4
  • 13. SWEBOK Evolution from V3 to V4 • Modern engineering, practice update, BOK grows and recently developed areas Requirements Design Construction Testing Maintenance Configuration Management Engineering Management Process Models and Methods Quality Professional Practice Economics Computing Foundations Mathematical Foundations Engineering Foundations Requirements Architecture Design Construction Testing Operations Maintenance Configuration Management Engineering Management Process Models and Methods Quality Security Professional Practice Economics Computing Foundations Mathematical Foundations Engineering Foundations V3 V4 Agile, DevOps AI for SE, SE for AI Software engineering AI AI for SE SE for AI
  • 14. Mainframe 70’s – Early 80’s Late 80’s - Early 90’s Late 90’s - Early 00’s Late 00’s - Early 10’s PC, Client & server Internet Ubiquitous computing Late 10’s - Early 20’s IoT, Big data, AI GenAI, FM, Autonomous, Quantum, Continuum Late 20’s Structured programming Waterfall Formalization Design Program generation Maturity Management Object-oriented Req. eng. Modeling Verification Reuse Model-driven Product-line Global & open Value-based Systems eng. Agile Iterative & incremental DevOps Empirical Data-driven Continuous SE and IoT SE and AI SE and GenAI SE and QC Sustainability SE for autonomous and continuum AI-assisted DevOps/OpsDev SWEBOK V1 SWEBOK V2 SWEBOK V3 SWEBOK V4
  • 15. 8 Megatrends in IEEE Future Direction 2023 and IEEE-CS Technology Predictions 2024 IEEE CS Technology Prediction Team (Chair: Dejan Milojicic) https://www.computer.org/resources/2024-top-technology-predictions • We have four core AGI technology predictions compared to eight sustainability-related and nine digital transformation-related predictions. • AGI technologies are deeply entangled with socio, economic, and ecological aspects. IEEE CS Technology Predictions 2024 Chance of success higher than impact on humanity Impact on humanity higher than chance of success (worth investing in) IEEE CS Technology Prediction Team (Chair: Dejan Milojicic) https://www.computer.org/resources/2024-top-technology-predictions Generative AI • Provides flexibility for new challenges and adaptive responses demand. • Safety and security: Need to build safeguards against misuses and generated harmful content, such as deep fakes. • Lacking Robustness, Reliability, Control, and Explainability, necessitating transparent techniques and consistent AI models. • This is a major issue for agents and trusted apps. • Bias and data quality issues in large datasets call for better curation. • High computational costs limit model training to an oligarchy of very few players who can afford to train a foundation model. • Evolving regulatory landscapes, especially regarding data privacy and use, demand for ensuring legal and ethical compliance. • Enhanced creativity in arts and design, accelerated design. • Generative AI-based revolutionized personalized medicine, from drug discovery to tailored treatment plans. • Personalized education and marketing boost productivity. • Improved customer support through natural interactions- conversation, problem solving, detailed product knowledge. • Accelerated scientific discovery and 3D modeling. Problems/demand Opportunities Mainframe 70’s – Early 80’s Late 80’s - Early 90’s Late 90’s - Early 00’s Late 00’s - Early 10’s PC, Client & server Internet Ubiquitous computing Late 10’s - Early 20’s IoT, Big data, AI GenAI, FM, Autonomous, Quantum, Continuum Late 20’s Structured programming Waterfall Formalization Design Program generation Maturity Management Object-oriented Req. eng. Modeling Verification Reuse Model-driven Product-line Global & open Value-based Systems eng. Agile Iterative & incremental DevOps Empirical Data-driven Continuous SE and IoT SE and AI SE and GenAI SE and QC Sustainability SE for autonomous and continuum AI-assisted DevOps SWEBOK V1 SWEBOK V2 SWEBOK V3 SWEBOK V4