Unterstützung der Wissensarbeit durch Künstliche Intelligenz - Anforderungen an die Gestaltung maschinellen Lernens

Entwicklungen der Informationstechnologie stellen zunehmend Möglichkeiten bereit, den menschlichen „Wissensarbeiter“ durch kognitive Assistenzsysteme auf Basis Künstlicher Intelligenz (KI) in seinen Entscheidungen oder Aktionen zu unterstützen. Im vorliegenden Beitrag wollen wir beleuchten, welche Anforderungen an die zugrundeliegenden maschinellen Lernverfahren zu stellen sind, um die individuelle sowie gesellschaftliche Akzeptanz solcher „Augmented Intelligence“ zu gewährleisten

Methodologies to improve product life cycle decision making in the telecommunications industry

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.As pressure from regulation and customers increases on telecommunications equipment manufacturers and service providers to reduce the hazardous material content of telecommunications products and generally improve environmental performance, new methods for Product Life Cycle Management are required. Supplier and component environmental evaluation are vital and fundamental elements of any Product Life Cycle Management programme, as is the capture of data from the supply base. The information that needs to be captured from the supply base to meet the requirements of customers of telecommunications equipment providers; to meet the requirements of legislation; and to provide data for improving ecodesign and facilitating product-focused continual improvement for ISO 14001 has been identified. A method for capturing data from the supply base has been developed and recommendations made for implementation. A hierarchical supplier and component eco-evaluation methodology has been developed and tested. This methodology incorporates supplier environmental management performance, component inherent human toxicity, ecotoxicity and resource depletion. It provides component qualifiers and purchasers with a method of supplier environmental performance comparison and enables this criterion to be integrated with existing criteria such as quality and cost in the component and supplier selection decision-making process. Recommendations are made regarding the implementation of an industry-wide system to enable the capture of detailed product material composition data from the supply chain and the implementation of the eco-evaluation methodology to identify the supplier that has superior environmental performance. The result will be enhanced decision making in product design and manufacture, improved transparency in communication to customers and more informed decision-making at the end-of-life stage of the product life cycle.Funding was obtained from the Engineering and Physical Sciences Research Council

Analysing the Security Aspects of IoT using Blockchain and Cryptographic Algorithms

Technological advancement is a never-ending field that shows its evolution from time to time. In 1832, with the invention of the electromagnetic telegraph, the era of the Internet of Things (IoT) began. Within the time of 190 years, this technological domain has revolutionized IoT and made it omnipresent. However, with this evolved and omnipresent nature of IoT, many drawbacks, privacy, interoperability, and security issues have also been generated. These different concerns should be tackled with some newer technologies rather than the conventional ones as somehow, they are only the generator of those issues. Outdated Security could be an appropriate issue of IoT along with the centralized point of failure. It also possesses more concerns and challenges to tackle. On the other side, there is a visible solution to address the challenges of IoT in this developing domain of technology. The visible approach is Blockchain which acted as the backbone in securing Bitcoin in 2008, which was created by the pseudo group named Satoshi Nakamoto. Blockchain has evolved from Blockchain 1.0 to Blockchain 4.0 as the latest one depicts its amalgamation with another component of Industry 4.0 i.e., Artificial Intelligence (AI). AI will give the ability to think logically and like humans. In addition to this SMART solution, there is also an advanced cryptographical technique known as the Elliptic Curve Digital Signature Algorithm (ECDSA) which can enhance the security spectrum of IoT if applied appropriately. This paper produces a vision to enhance and optimize the security of IoT using a network peer-to-peer technology Blockchain along with advanced cryptography

Trust in Computational Intelligence Systems: A Case Study in Public Perceptions

The public debate and discussion about trust in Computational Intelligence (CI) systems is not new, but a topic that has seen a recent rise. This is mainly due to the explosion of technological innovations that have been brought to the attention of the public, from lab to reality usually through media reporting. This growth in the public attention was further compounded by the 2018 GDPR legislation and new laws regarding the right to explainable systems, such as the use of “accurate data”, “clear logic” and the “use of appropriate mathematical and statistical procedures for profiling”. Therefore, trust is not just a topic for debate – it must be addressed from the onset, through the selection of fundamental machine learning processes that are used to create models embedded within autonomous decision-making systems, to the selection of training, validation and testing data. This paper presents current work on trust in the field of Computational Intelligence systems and discusses the legal framework we should ascribe to trust in CI systems. A case study examining current public perceptions of recent CI inspired technologies which took part at a national science festival is presented with some surprising results. Finally, we look at current research underway that is aiming to increase trust in Computational Intelligent systems and we identify a clear educational gap