Computing Leaders Release Dashboard for IEEE Computer Society's 2022 Technology Predictions

Computing Leaders Release Dashboard for IEEE Computer Society’s 2022 Technology Predictions

LOS ALAMITOS, Calif., December 8, 2022 – The IEEE Computer Society (IEEE CS), known for reporting on major technology trends in computing, today reveals the official report dashboard for its 2022 technology forecast. The 2022 Forecast Dashboard shows the level of performance and impacts achieved for currently trending technologies compared to projections made in January 2022. The IEEE CS Technology Forecast for 2022 earned a collective rating of B/C.

IEEE CS Technology Predictions for 2023 to be unveiled in January 2023 – register today for exclusive free access:

The IEEE CS team rated its overall prediction of technological advancement with a score of B/C, and its impact on humanity a B-.

The highest success was attributed to predictions for the convergence of HPC, AI and data analytics (technology advancement: B+; impact: B-); Data-centric AI (B+; B+); Medicine at a distance (B+; A-); and Digital Twins in Manufacturing (B;B).

  • Convergence of HPC, AI and Data Analytics was led by the three technologies and also by governments, industry and academia.
  • Data-centric AI was a success due to the critical importance of data for training AI models.
  • Distance medicine spread during COVID and extended its importance in the post-COVID days.
  • Digital twins has made the most progress in manufacturing where constrained environments have taken full advantage of the benefits of the digital twin.

“On average, we rated the impact of the planned technologies on humanity as B- with overall confidence in all scorecard elements (success, impact, maturity) also a B-. This is very similar to our previous years, maybe slightly down. Not surprising given last year’s very high volatility due to COVID,” said Dejan Milojicic, Past Chair of IEEE CS (2014) and current Distinguished Technologist at Hewlett Packard Labs.

The team’s continued success in prediction was primarily reduced by NFTs (D+ technology advancement; D/E impact), followed by unsuccessful predictions for misinformation detection/correction (C), weak code/no code (C+) and the commoditization of Space Technologies (C+).

In terms of maturity, two additional classes were introduced for the first time – unsuccessful and wide adoption. NFTs and the commoditization of space technologies were classified as failure, and the convergence of HPC, AI, and data analytics was classified as broad adoption.

The following list compares the top 16 technology trends for 2022 and is ranked by rating for, impact on humanity, measured impact of technology, technological maturity and confidence in prediction>:

Top 16 Tech Trends Hit, Impact, maturity, confidence

Convergence HPC, AI, HPDA:B+B-, Wide adoption, B+ >

Data-centric AI:B+B+, Mature, A/B >

Remote medicine:B+A-, Emerging, B >

Digital twins in manufacturing:B, B, Mature, B+ >

Health, safety, wearable biomedical technology:B, B+, Mature, B- >

Security for stand-alone systems:B-B+, Mature, B >

3D printing in healthcare:B-, A/B, Emerging, B/C >

[email protected]Federated learning:B-B-, Emerging, B>

Trustworthy AI:B-, A/B, Emerging, B+ >

Confidential IT:BCB/C, Incubation, B/C>

Metavers:BCC+, Prototyping, B>

Cybersecurity of Critical Infrastructures:C+, A/B, Emerging, B->

Commercialization of space technology:C+B/C, Fail, B/C>

Low-Code/No-Code:C+C+, Incubating, B/C>

Misinformation Detection/Correction:VSB/C, Prototype, B->

Non-fungible tokens (NFT):D+D/E, Fail, B/C>

Following the established process of previous years, the authors who originally made the predictions in January 2022 assessed their predictions individually. The means and standard deviations served as the basis for the discussion that ultimately led to the final grade.

The IEEE CS team of leading technology experts includes Rosa M. Badia, Barcelona Supercomputing Center; Mary Baker, HP Inc.; Tom Coughlin, Coughlin Associates; Paolo Faraboschi, vice president and member of Hewlett Packard Enterprise; Eitan Frachtenberg, Data Scientist, Hewlett Packard Labs; Vincent Kaabunga, AKEM Consulting; Hironori Kasahara, Waseda University; Kim Keeton, Google; Danny Lange, vice president of AI at Unity Technologies; Phil Laplante, Professor, Penn State University; Avi Mendelson, Professor, Technion and NTU Singapore; Cecilia Metra, Professor, University of Bologna and former President of IEEE CS; Dejan Milojicic, Distinguished Hewlett Packard Enterprise Technologist and former IEEE CS Chair; Nita Patel, L3 Technologies, IEEE CS President-elect; Roberto Saracco, Chair of the IEEE-FDC Symbiotic Autonomous Systems Initiative; Michelle Tubb, IEEE CS Marketing and Sales Manager; and Irene Pazos Viana, IT consultant.

Note: The statements expressed in this report do not represent the views of the employers of the authors.

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About the IEEE Computing Society

Through conferences, publications, and programs, the IEEE Computer Society (IEEE CS) sets the standard for education and engagement that fuels global technological advancement. By bringing together engineers, scientists, researchers, and practitioners from all areas of computer science and at every stage of their careers, IEEE CS unlocks new opportunities and empowers not only its members, but the entire the industry. Visit for more information.

Source: IEEE Computing Society

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