Technology Predictions 2021 | IEEE Computer Society
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Technology Predictions 2021 Mary Baker, Tom Coughlin, Paolo Faraboschi, Eitan Frachtenberg, Kim Keeton, Danny Lange, Phil Laplante, Andrea Matwyshyn, Avi Mendelson, Cecilia Metra, Dejan Milojicic, Roberto Saracco 2 In This Report 3 SECTION 01 Mary Baker Tom Coughlin Paolo Faraboschi Eitan Frachtenberg Kim Keeton Broader HP Inc. Coughlin Associates Hewlett Packard Ent. Reed College Entrepreneur Technology Predictions Danny Lange Phil Laplante Katherine Mansfield Andrea Matwyshyn Avi Mendelson Team Unity Technologies Penn State IEEE Computer Society Penn State Technion and NTU Cecilia Metra Dejan Milojicic Roberto Saracco Jeffrey Voas Bologna University Hewlett Packard Ent. IEEE FDC NIST, IEEE Computer EIC 4 SECTION 02 Introduction Technology Predictions from Hypothetical Exercise to Critical Planning The pandemic data1 • Societal distancing vs depleting individuals’ social credits • 28 Trillion $ loss in 2020, unevenly distributed across • Future of workforce regions and sectors • Forced to trusting AI to assist in transportation, • Recovery time estimated at 2 to 4 years; market and healthcare, elderly, etc. priorities reshaped Acceleration of the Digital Transformation was forced • Up to 10% of GDP in jobs support, good portion is upon work, education, and private life “wasted” money The pandemic had impact on: human lives, supply chains, Technologies increasingly play crucial role in all of this and workforce, unpredictability of operations and markets are becoming essential for our survival Counter-measures: cutting costs; repurposing assets; Predicting technologies helps addressing pandemics, it eliminating the middle-man; shift to “as-a-Service” models goes well beyond hypothetical exercise Pandemics have created STRESS on current humankind existence, values, and daily lives 1 From Roberto Saracco, Industry Advisory Board report to IEEE Future Directions Committee 5 SECTION 03 1. Remote workforce technologies 2. Social distancing technologies 3. Reliability/Safety for Intelligent Autonomous Systems 4. Synthetic Data for training ML systems free of bias 5. Disinformation detection 6. HPC as a Service 7. Election security / social media controls Technology 8. Trustworthy & Explainable AI/ML 9. Low latency virtual musical rehearsal and performance Predictions at the 10. Computational memory 11. AI for additive & subtractive Times of Pandemics manufacturing 12 Predictions Landscape 12. Advanced Cyber Weapons 6 SECTION 03 Relationship Between Predicted Technologies 7 SECTION 03 In Reality ... 8 SECTION 04: INDIVIDUAL 12 PREDICTIONS Problems/demand Impact • The pandemic required social • Customized remote work environments Remote distancing, which in turn created an and Improved accommodation of immediate explosion in remote work, workers with different needs. especially for white-collar industries • A more inclusive work environment, • The vast majority of remote work policy, and culture Workforce uses preexisting technology, such as • Growth in remote-based services such video conferencing and virtual private as tele-health. networks • Adoption of remote collaboration, hiring, Tools, policies, and regulations for remote • But there are many important and training. workplace interactions that don’t work will evolve rapidly, improving currently have a great technological Sustainable solution/business solution and are ripe for innovation existing remote roles and expanding opportunity Opportunities • A permanent transition to a remote to use cases that don’t currently have or hybrid work model in white-collar • Technology to facilitate proximity- industries. ideal solutions, such as education, based or spontaneous collaboration, substituting for the office environment • Increase in worker mobility and geographical diversity. manufacturing, and healthcare. • Technology to facilitate effective teaching and learning with rich • Improvements in diversity, equity, and communication, substituting for the inclusion of the workforce. classroom environment • Enablers: tech & app innovations; AR/ • Technology to facilitate effective large- VR, regulation scale meetings, substituting for the • Inhibitors: company policy, lack of conference environment (short-term) financial support and buy-in 01 More details at https://doi.org/10.36227/techrxiv.13278092 9 SECTION 04: INDIVIDUAL 12 PREDICTIONS Problems/demand Closeness provides a sense of safety in case of perceived danger. • The pandemic required social distancing, which in turn created an • The negative aspects of social distancing immediate explosion in remote work, can be decreased by improving Social especially for white-collar industries technologies to overcome separation (e.g. VR/AR). • The vast majority of remote work uses preexisting technology, such as • The growing awareness at personal Distancing video conferencing and virtual private & social level can stimulate specific networks behavior and foster proactive healthcare. Social Credits growth was • But there are many important noticed in China. A host of technology is converging, workplace interactions that don’t currently have a great technological Sustainable solution/business solution and are ripe for innovation creating streams of data that will be opportunity processed locally and globally creating Opportunities • We can expect emergence of new and improvement of existing wearable • Societal Distancing Techniques can devices. Existing smartphones improve a framework of massively distributed increase service quality and decrease sustainability (reuse), like the adoption cost by leveraging alternative ways to of GPS/Wireless, Bluetooth intelligence with impact on apps, turn distance into closeness (by creating a feeling of presence) • The leverage of data is also in line wearables, and sensors. of sustainability, opening up biz • On the business side they open up new opportunity, e.g. adoption of existing opportunities, as demonstrated by the data frameworks like Electronic Health number of tools for managing virtual Records (EHR)z meetings and by the rapid evolution of their features. • The need to create personal data space goes hand in hand with the evolution • Social distances techniques, when duly trends of Digital Twins and Personal addressed, provide tools that foster the Digital Twins that in turn is likely to digital transformation foster new biz opportunity Impact • Enablers: VR/AR technologies, social • The impact of Social Distancing is credits substantial. Humans are social animals, • Inhibitors: distancing enforcement, 02 psychologically against “distancing”. poor technology support 10 SECTION 04: INDIVIDUAL 12 PREDICTIONS Problems/demand Impact • Expected market growth for intelligent • Significant reduction of humans’ work risks autonomous systems (e.g. mobile robots, • Improvement of humans’ health Reliability vehicles) with high level of autonomy • More efficient healthcare, surveillance, and • To enable high levels of autonomy, stringent better services requirements in terms of reliability/safety of and Safety their components have to be met • Technological boost • The ability to reach a safe state in a fully Sustainable solution/business opportunity autonomous way (thanks to reliable components) has to be guaranteed in case of • Significant research investment (academia hazardous conditions and industry) in high reliability and safety for Intelligent solutions for highly autonomous intelligent • High reliability and safety should be systems guaranteed with respect to transient faults and aging phenomena occurring in the field • Research needed to investigate interaction among reliability, safety and security and time Autonomous Opportunities determinism constraints • Intelligent, autonomous systems proved very • Applicability to environmental monitoring, helpful in facing the pandemic emergency catastrophes’ prediction and avoidance (e.g., robots to disinfect infected areas, • Enablers: Innovative approaches for Systems autonomous vehicles transporting Covid19- enhanced reliability and safety; new tests, etc). international standards in the field; • Moving towards fully autonomous systems regulations for ethical responsibility will significant help humans by preventing Fueled by the pandemic, • Inhibitors: technical challenges; regulations exposure to health’s risky conditions substantial growth in • Applications are pandemic support, environmental monitoring, post-earthquake autonomous systems will further management, space exploration, etc. improve reliability and safety of such autonomous systems. For more details, please join the IEEE Computer Society Special Technical Community (STC) on Reliable, Safe, Secure and Time Deterministic Intelligent Systems at 03 https://www.computer.org/communities/special-technical-communities/rsstdis 11 SECTION 04: INDIVIDUAL 12 PREDICTIONS Problems/demand Impact • Real-world data often embed strong biases • More and better training data at order of found throughout society thus allowing AI magnitude lower cost algorithms to amplify those undesirable biases • Creating training data reflecting the world as • Real-world data is difficult to gather and very we want to see it rather than the biased world Synthetic Data expensive to manually label hence limiting the we live in use of ML • Eliminate the risk of model overfitting • Real-world data often raise privacy concerns • Disrupting model accuracy through active which may severely limit its application for Training ML learning and dynamic data generation in a • Read-world data can sometimes not be virtuous feedback