Ethical Challenges within Artificial Intelligence – From Principles to Practice

June 5, 11:15am
Location: Santa Clara I

Organized by Jim Tørresen, Professor, Research Group for Robotics and Intelligent Systems, University of Oslo, Norway, and Keeley Crockett, Professor in Computational Intelligence, Manchester Metropolitan University, UK

Artificial intelligence (AI) has entered an increasing number of different domains. A growing number of people – in the general public as well as in research and development – have started to consider a number of potential ethical challenges and other issues related to the development and use of AI technologies. The aim of this workshop is to briefly overview the global AI legislation landscape and introduce a range of ethical issues that need to be considered by data scientists, software development teams, industry professionals and academics and practically apply the consequence scanning toolkit to evaluate the impact of AI research ideas / new products and services on individuals and society. There is no specific prerequisite knowledge required.

Trustworthy Artificial Intelligence for High-Risk Applications

June 5, 2:15pm
Location: Santa Clara I

Organized by Truong Tran, Assistant Professor of Computer Science, School of Science, Engineering, and Technology at Pennsylvania State University, and Ramazan S. Aygun, Director of Research Computing, Kennesaw State University

Recent advances in Artificial Intelligence (AI) and Machine Learning (ML) have been enticing for crucial applications such as medical diagnosis, drug discovery, weather forecasting, autonomous robotics, and fraud detection to leverage from historical data and experience. Indeed, the blooming of big data with massive volumes of information has changed how we manage and analyze data and how we feed data to learning models to obtain accurate results. It is necessary to ensure those models perform correctly with a high level of confidence and robustness. While traditional Artificial Intelligence and Machine Learning focus on high achievements, errors caused by trained models could be costly or even fatal in some scenarios, especially for high-risk applications. Therefore, trustworthy AI approaches are significant in creating reliable outcomes. On the other hand, transparency and explainability of complex models may help gain trust and confidence in the prediction results. However, there is a need to develop metrics for measuring the accuracy of the explanation. The workshop’s objective is to promote the need for high confidence, robustness, and explanation accuracy in AI/ML systems and their applications. The workshop consists of presentations followed by discussion and Q&A. The attendees will get to know and discuss the following topics:

– Challenges for AI in high-risk applications

– Characteristics of trustworthy AI and ML systems

– Metrics and methods for evaluating explainable and trustworthy AI (e.g., quantifying reliability of explanation) and risk measurement

– Design of AI/ML model for high-risk applications, including example of trustable neural networks and other classification models.

Digital Twins – The Next Frontier in Data Science for Deep Insights and Prescriptive Analytics

June 5, 3:15pm
Location: Magnolia

Organized by Rajkumar Bondugula, Luminary Scientist & Data Science Fellow, Verizon

Prescriptive analytics has been promised as the next evolutionary step in analytics practice. However, the mechanisms to deliver prescriptive analytics have not been fully realized yet. Digital twin is one powerful way we can deliver prescriptive analytics. It can be used in operations, sales, marketing and strategic decision making. In addition, since real-life experiments are often too expensive or even impossible, decision makers, researchers, and engineers can create and test models of various system designs and answer hundreds of “what-if” questions, all by virtually experimenting in a risk-free environment. This workshop provides an overview on Digital Twins. It covers the definition, a simple example of a digital twin that we all use, and the various uses of Digital Twin. In addition, technical aspects such as why Digital Twins work, how they are different from existing analytical practices will be covered. The practical challenges of building digital twins will be discussed next. Finally, the simulation part of a grocery store Digital Twin will be demonstrated.

Advances in the Assessment and Certification of AI Ethics

June 5, 3:15pm
Location: Santa Clara I

Organized by A.G. Hessami, Chair & Technical Editor, IEEE 7000 Standard; Vice Chair and Process Architect, IEEE Ethics Certification Program for Autonomous and Intelligent Systems; Director of R&D and Innovation, Vega Systems, UK

This workshop will cover the latest advances on technology ethics and two IEEE initiatives namely IEEE 7000 standard and the Ethics Certification Programme for Autonomous and Intelligent Systems (ECPAIS). These provide a basis for raising awareness and providing a systematic framework for the innovators, researchers and technologists as well as small and large, public and private enterprises involved in AI and technology innovation, development and deployment. The main focus is on Autonomous Decision Making and Algorithmic Learning Systems, the emerging regulatory landscape and two complementary approaches to the risk reduction in societal harms and ethical assurance of these technologies.