Submissions due: 1 December 2020
Publication issue: July 2021
Technology predictions have always been hard to make, yet they attract wide audiences because of their speculative nature and potential impact. Accurate predictions could have substantial impact on business. Degree of speculation as well as potential impact is dramatically amplified with radical changes introduced by pandemics. The ability to correctly predict may differentiate countries that will sustain tragic losses from those that will evade impact. Similarly, technology trends may make a difference in whether industries will entirely go away, undergo complete transformation, or suddenly start blooming.
Technology prediction is hard because it entails both technical and business components, as well as a time dimension. Superior technologies have not always won. And those that did win sometimes took much more time to mature and ultimately reach adoption. Technology success depends on technical, production, market, social, and many other aspects.
Successful technology predictions will provide a basis and justification for the prediction, including research and development results that can quantify and qualify prediction. Ideally, the prediction will have been motivated by novel technological aspects or the use thereof.
Over the past ten years, the IEEE Computer Society has conducted technology predictions at the end of each year. Many other organizations around the world do the same. For examples of papers on technology predictions, see the December 2019 issue of Computer, including a rebuttal by Jeff Voas, at that time the incoming EiC of Computer. For examples of technology predictions, see the IEEE Computer Society Press Room, including scorecards from the past 10 years.
Scope of Interest
All submitted papers to this special issue are to focus on state-of-the-art technology predictions from various academic and industry viewpoints. The topics of interests in this special issue include, but are not limited to:
- AI, machine learning, and deep learning
- Novel computer technologies such as CPUs, accelerators, memories (including non-volatile), storage, and interconnects
- Communication technologies such as the Internet, wireless, and 5G
- Deployment of cloud and edge technologies
- Predictions from the standards perspective
- Predictions from the road-mapping perspective
- Novel technology applications and use cases, including in manufacturing, biotech, healthcare, oil and gas, transportation, finance, smart cities, and education
- Personal and pervasive computing technologies
- Societal, legal, and ethical aspects
- Security and reliability aspects
- Impact on supply chains
- Future workforce support
- Paper submissions due: 1 December 2020
- First-round review due: 22 January 2021
- Revision due: 5 March 2021
- Final decision notification: 9 April 2021
- Camera-ready submission due: 23 April 2021
- Publication: July 2021
Computer is looking for succinct, practical, readable articles that will appeal to experts and nonexperts alike. Feature articles shouldn’t exceed 6,000 words (minimum 4,500 words), including text, bibliography, and author biographies. Columns shouldn’t exceed 2,500 words (minimum 1,500 words), including text, author biographies, and table text. Each figure and table is counted, on average, as 300 words. Any article that exceeds these word counts may be rejected automatically without going through the review process. Article titles shouldn’t exceed nine words. All manuscripts are subject to peer review on both technical merit and relevance to Computer’s international readership–primarily practicing engineers and academics who are looking for material that introduces new technology and broadens familiarity with current topics. We do not accept white papers, and papers that are primarily theoretical or mathematical must clearly relate the mathematical content to a real-life or engineering application. Manuscripts should not be published or currently submitted for publication elsewhere.
Contact the guest editors at email@example.com.
- Phillip A. Laplante, Penn State
- Dejan Milojicic, Hewlett Packard Labs