Distributed ledger systems have become more prominent and successful in recent years, with a focus on blockchains and cryptocurrency. This has led to various misunderstandings about both the technology itself and its capabilities, as in many cases blockchain and cryptocurrency is used synonymously and other applications are often overlooked. Therefore, as a whole, the view of distributed ledger technology beyond blockchains and cryptocurrencies is very limited. Existing vocabularies and ontologies often focus on single aspects of the technology, or in some cases even just on one product. This potentially leads to other types of distributed ledgers and their possible use cases being neglected. In this paper, we present a knowledge graph and an ontology for distributed ledger technologies, which includes security considerations to model aspects such as threats and vulnerabilities, application domains, as well as relevant standards and regulations. Such a knowledge graph improves the overall understanding of distributed ledgers, reveals their strengths, and supports the work of security personnel, i.e. analysts and system architects. We discuss potential uses and follow semantic web best practices to evaluate and publish the ontology and knowledge graph.

In a survey of institutional traders conducted by JP Morgan, more than half of the respondents predicted that, over the next three years, machine learning and artificial intelligence will have a greater impact on trading than blockchain and distributed ledger technology. The seventh edition of JP Morgan's e-Trading Edit report was released in January and was based on a survey of 835 institutional traders across 60 worldwide marketplaces. The objective of the annual survey of trader sentiment, which covers a variety of asset classes, is to identify "upcoming trends and the most controversial topics." The turbulent cryptocurrency bear market, along with recent consumer and business enthusiasm over approachable AI technology like ChatGPT, appears to have changed the perspective of financial industry professionals. With 25% of respondents saying they were critical to the future, blockchain and distributed ledger technologies tied for second place with AI and machine learning last year.

More than half of the institutional traders surveyed by global financial services giant JP Morgan said that artificial intelligence and machine learning will be the most influential technology in shaping the future of trading over the next three years--cited four times more often than blockchain and distributed ledger technology. JP Morgan's e-Trading Edit report is now in its seventh year, the latest report drawn from a January survey of 835 institutional traders in 60 global markets. The annual assessment of trader sentiment spans several asset classes and is intended to reveal "upcoming trends and the most hotly debated topics." The tumultuous bear market in crypto--coupled with the recent consumer and commercial hype over accessible AI technology like ChatGPT--seems to have shifted the outlook of financial industry professionals. Last year, blockchain and distributed ledger technology tied for second with AI and machine learning with 25 percent of respondents declaring them key to the future.

The entrepreneurial disruption phase of "move fast and break things" is being replaced with a mantra of "move fast and keep up" when it comes to applying ethical frameworks and leading practices to emerging technologies, according to a new study by Deloitte. The firm's first-ever State of Ethics and Trust in Technology annual report defines emerging technologies, identifies trustworthy and ethical standards, explains different approaches to operationalizing standards, and encourages actions that can be taken in the short term. Many companies want to be on the cutting edge of emerging technologies to stay competitive and gain benefits such as improved customer experience, operational efficiencies and newly-enabled use cases, according to Deloitte. "But these technologies are often being developed at such breakneck speeds that few companies are pausing to consider the ethical implications,'' the report noted. "With great power comes great responsibility.

The Machine Economy offers us a tantalizing future, says Till Wendler, co-founder of peaq. Like when you are driving your electric car, the vehicle will not only find you a free space, but pay with its own wallet, ready for when you roll up. From tiny devices to robots and drones, machines will drive 70% of GDP growth in the global economy between now and 2030, according to PwC. The number of connected devices, known collectively as the Internet of Things (IoT), is quickly growing. Interconnected machines are taking over more functions across industries and in our daily lives.

Web 3.0 is the generation of interest where apps and websites can analyze data like a human with the help of Machine Learning, Big Data, and decentralized ledger technologies. Data here is decentralized and open, unlike Web 2.0 and it is autonomous and intelligent. Cybersecurity is the most important in the technology world. And as Web 3.0 develops, more cybersecurity risks will come to light. At present risks like Information quality, Data Availability, Data Confidentiality, and Data Manipulation are being the major concerns.

After I published my conversation on AI Ethics with GPT-3, my colleague Jorge Lesmes and I thought that it would be fun to try the same kind of conversation on Blockchain. He kindly prepared the questions you will find below, so I want to thank him very much for his contribution! Let's see what GPT-3 replied to his questions. I am sure that you have heard about Blockchain before so, can you elaborate on what the main benefits of this technology are when compared to traditional solutions? A: The main benefit is that the blockchain is decentralized and transparent, which means that there is no central authority that can control the data and perform fraudulent actions.

One of the greatest barriers to adopting and scaling AI applications is the scarcity of varied, high-quality raw data. To overcome it, firms need to share their data. But the many regulatory restrictions and ethical issues surrounding data privacy pose a major obstacle to doing this. A novel solution that my firm is piloting that could solve this problem is a data trust: an independent organization that serves as a fiduciary for the data providers and governs their data's proper use. Research shows that companies are becoming increasingly aware of the value of sharing data and are exploring ways to do so with other players in their industry or across industries.

New technologies have emerged over the last years, creating a need for standardization. Artificial Intelligence, Blockchain and Distributed Ledger technologies are those new sectors, which produces standardization solutions. In this context, CEN and CENELEC support the activities of ISO/IEC JTC 1 SC 42, IEC SEG 10 on Artificial Intelligence and ISO/TC 307 on Blockchain and Distributed Ledger technologies. CEN, together with CENELEC, has created two Focus Groups to mirror the activities of those groups, in order to identify potential specific European requirements, and to act as an interface with the European Commission. Beginning 2019, the Technical Boards of CEN and CENELEC have set up a Focus Group on Artificial Intelligence which held its first meeting in April 2019 in Copenhagen.

From performing simple commands on smartphones using Alexa or Siri to high-end technical operations in big tech firms, one thing is sure: Ease is a necessity in the modern human experience. The 21st century has marked a rapid advancement of technology in every aspect of human life and interactions. Despite being around for many decades, the replication of human intelligence in machines -- artificial intelligence -- has now become popularized. With many tech companies rushing to adopt the technology, the market size is expected to grow to $126 billion in 2025. Similarly, distributed ledger technology and cryptocurrencies have exceeded everyone's expectations and are looking to compete with traditional fiat currencies.