The next generation of run-time risk models will act as Digital Twins to anticipate threats and enable novel paradigms, like proactive dependability and collaborative security, as support to prognostics and preventive maintenance in Industry 4.0 and other Smart-X applications (e.g.,smart-houses, smart-cities, smart-transportation, etc.).
The concept of risk is a combination of threat probabilities, vulnerabilities, and expected consequences. In traditional risk modeling and evaluation, during the design phase, analyses are performed and may be repeated periodically or at relevant system changes. With such an approach, there is no possibility to evaluate how the risk evolves over time as a condition of the actual system state and detected threats. One challenging objective, in the field of connected cyber-physical systems (CPS) and the Internet of Things (IoT), is to improve resilience by providing non-trivial mechanisms for run-time threat-detection, risk estimation, and system reconfiguration following Self-Xprinciples like self-diagnostics and self-healing. Threats include faults, errors, and failures, and can be either intentional (e.g. security attacks) or unintentional (e.g. random faults).
Developing model-based approaches, allowing for run-time risk evaluation accounting for uncertainties in a system itself and in the surrounding environment, is extremely important. Those models should account for the growing complexity (size, distribution, heterogeneity), and criticality of modern cyber-physical systems. Multi-paradigm modeling can combine probabilistic modeling languages, borrowed from Artificial Intelligence (e.g.Bayesian Networks), with formalisms like high-level Petri Nets, in order to find the optimal balance and trade-off between ease of use, expressive power, and solving efficiency.
Models used in static risk assessment during the design phase can be reused and integrated into appropriate frameworks. This will allow online monitoring of relevant system parameters, threat detection, and dynamic adaptation to respond to threats. In critical applications, the reuse of suitable models already employed for system certification together with run-time model-checking supports explainable Artificial Intelligence (XAI) that is required in order to build a trustworthy autonomous CPS, such as a self-driving vehicle.
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Featured Speaker: Francesco Flammini
Department of Computer Science, Mälardalen University (Sweden)
Francesco Flammini got with honors his master's (2003) and doctoral (2006) degrees in Computer Engineering from the University of Naples Federico II, Italy. He is currently a Professor of Computer Science with a focus on Cyber-Physical Systems at Mälardalen University (Sweden). He has been a Senior Lecturer and the chair of the Cyber-Physical Systems group at Linnaeus University (Sweden). He has worked for 15 years in private and public companies, including Ansaldo STS (now Hitachi Rail) and IPZS (Italian State Mint and Polygraphic Institute), on large international projects addressing intelligent transportation systems, critical infrastructure protection and cybersecurity, as a technical leader and unit head.
Professor Flammini is an IEEE Senior Member and the Chair of the IEEE SMC Technical Committee on Homeland Security. He is also a member of the ERCIM Working Group on Formal Methods for Industrial Critical Systems (FMICS), He has (co)authored 100+ scientific publications and he has served as a chair, invited speaker, steering/program committee member, and editor for several international conferences and journals. He has been an adjunct professor and guest lecturer of computer science, software engineering and cybersecurity at several universities, including University of Maryland University College (UMUC) Europe, Second University of Naples (Italy), University of Naples Federico II (Italy), University Campus Biomedico of Rome (Italy) and University of Girona (Spain).
Digital Twins were defined approximately 15 years ago, and it took them about 7 years to become adopted by the manufacturing industry, first by General Electric and then several others. However, in the last five years, they have been applied in an increasing number of sectors, from building construction to healthcare, and they have evolved significantly from the original idea of being a digital mirror of an object.
Now, their evolution is accelerating both in terms of application and capabilities, extending their coverage to mirror people (from deep twins to cognitive twins). In addition, they are continuously acquiring an increasing amount of intelligence, all aspects of which are being addressed by the IEEE Digital Reality Initiative.
In this decade, we are expecting to reach a point where everything, including each of us, will be flanked by its own digital twin. The European Union has recently committed funding to create a digital twin of our planet: Destination Earth.
As they evolve, and particularly as they enter into our lives, new challenges are created by technology. Challenges that are rooted in our social lives and in our culture are coming to the forefront.
This webinar aims to share views on the ongoing Digital Twin evolution, as well as to address the societal and personal issues that are emerging.
Derrick and Roberto will dialogue on this evolving landscape that will involve everybody, so the real goal of this webinar is to stimulate a much broader discussion on a future that is knocking at our door.
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Featured Speakers: Derrick DeKerchove and Roberto Saracco
Derrick de Kerckhove is former Director of the McLuhan Program in Culture & Technology at the University of Toronto, where he is professor emeritus at the Department of French. He subsequently joined the Faculty of Sociology of the University Federico II in Naples. Presently, scientific director of the Rome-based monthly Media Duemila, he is the author of a dozen books edited in over ten languages. He is also Research Director at the Interdisciplinary Internet Institute (IN3) at l’Universitat Oberta de Catalunya in Barcelona.
Roberto Saracco fell in love with technology and its implications long time ago. His background is in math and computer science. Until April 2017 he led the EIT Digital Italian Node and then was head of the Industrial Doctoral School of EIT Digital up to September 2018. Previously, up to December 2011 he was the Director of the Telecom Italia Future Centre in Venice, looking at the interplay of technology evolution, economics and society. At the turn of the century he led a World Bank-Infodev project to stimulate entrepreneurship in Latin America. He is a senior member of IEEE where he leads the Industry Advisory Board within the Future Directions Committee and co-chairs the Digital Reality Initiative. He teaches a Master course on Technology Forecasting and Market impact at the University of Trento. He has published over 100 papers in journals and magazines and 14 books.
Former Chief Justice of the United States Earl Warren once said that “In civilized life, law floats in a sea of ethics.” Nevertheless, regarding new technologies, legal regulations often lag. Firstly, court officials agree that similarly to animals, Artificial Intelligence is not responsible for its’ own decisions and actions.
In contrast to humans, all decisions made by algorithms are systematic and based on user data, sensors, and algorithms. The question is, who is responsible for errors: the provider, the integrator, or the end-user? In most scenarios, responsibility is distributed amongst all stakeholders. Full autonomic systems (including self-driving technology) are not accepted by lawmakers, and a human supervisor is demanded as a backup.
Thanks to behavioral science, research knows that humans can be influenced and manipulated by Artificial Intelligence. This is comparable to the animal kingdom in which an alpha rules the pack, but the beta is able to manipulate the alpha.
Accountability from all sides (including creators, integrators, and users) is required to reduce systematic errors and the related effects on humans, such as falling to biases (like the over-trust of Artificial Intelligence and status pressure), leading to mission and commission error.
System-thinking, as described by W. Edwards Deming in his “System of Profound Knowledge,” can exemplify the direction – AI decision making must be transparent, audited, and understood by humans. Even more, humans need to be aware that responsibility stays with them. This means they not only have to accept accountability for decisions but must also directly create AI-based on Deming’s philosophy. For everything else, Deming concluded that “a bad system will beat a good person every time.” An increasing number of government officials are demanding the inclusion of behavioral science into acceptable corporate behavior. This can result in a greater moral responsibility amongst creators and providers of AI for their technology, in addition to a legal and sanctionable influence.
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Featured Speaker: Patrick Henz
Head of Governance, Risk & Compliance US
Regional Compliance Officer Americas
Patrick Henz started his career in the Corporate Information Office and Compliance at the end of 2007 when he was responsible for the implementation of the Siemens Anti-Corruption program in Mexico and several Central American & Caribbean countries. Together with these tasks, he gained valuable insights into global Compliance programs, with a focus on Latin America. Since 2009 in his role as Compliance Officer he is responsible for an effective Compliance program; based on identification, protection, detection, response & recovery and combined with integrity, respect, passion & sustainability. With these means, he defines Governance, Risk & Compliance as pro-active function, being perceived as guardian, expert, and facilitator. The focus is on information to ensure adequate behavior, not only of the human employee, but Artificial Intelligence included.
Furthermore, he is a member of the IEEE Digital Reality Initiative, and author of the books “Business Philosophy according to Enzo Ferrari” and “Tomorrow’s Business Ethics – Philip K. Dick vs. W. Edwards Deming”.
- 15 April 2021 — Digital Twins for Trustworthy Autonomy — Featured Speaker: Francesco Flammini
- 18 May 2021 — The Future of Digital Twins — Featured Speakers: Roberto Saracco and Derrick DeKerchove
- 8 July 2021 — AI Systematic Errors — Who is Responsible? — Featured Speaker: Patrick Henz
Creating greater immersion in VR/AR/MR applications requires more life-like content. This content should be high resolution, high dynamic range and ideally high frame rate and include volumetric video content. Storing and rendering this content requires large amounts of digital storage and memory as well as specialized processing power. Enabling this content for use at endpoints and the edge will require new memory technologies that provide high capacity, high performance and are persistent. This talk will discuss requirements for capturing, storing and using this content as well as developments in data centers, at the network edge and in endpoints that will be needed to make alternative realities, part of our reality.
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Featured Speaker: Tom Coughlin
President, Coughlin Associates
Tom Coughlin, President, Coughlin Associates is a digital storage analyst and business and technology consultant. He has over 40 years in the data storage industry with engineering and senior management positions at several companies. Coughlin Associates consults, publishes books and market and technology reports (including The Media and Entertainment Storage Report and an Emerging Memory Report), and puts on digital storage-oriented events. He is a regular storage and memory contributor for forbes.com and M&E organization websites. He is an IEEE Fellow, Past-President of IEEE-USA, Past Director of IEEE Region 6 and Past Chair of the Santa Clara Valley IEEE Section and is also active with SNIA and SMPTE. For more information on Tom Coughlin and his publications and activities go to www.tomcoughlin.com.
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