Annotation The article proposes a method for forming a dedicated operational context in course of development and implementation of autonomous corporate management systems based on example of autonomous systems for a board of directors. The significant part of the operational context for autonomous company management systems is the regulatory and legal environment within which corporations operate. In order to create a special operational context for autonomous artificial intelligence systems, the wording of local regulatory documents can be simultaneously presented in two versions: for use by people and for use by autonomous systems. In this case, the artificial intelligence system will get a well-defined operational context that allows such a system to perform functions within the required standards. Local regulations that provide for the specifics of the joint work of individuals and autonomous artificial intelligence systems can create the basis of the relevant legislation governing the development and implementation of autonomous systems.

High AI training costs have been a significant barrier to AI adoption, preventing many companies from implementing AI technology. According to a 2017 Forrester Consulting Report, 48% of companies highlighted high technology costs as one of the primary reasons for not implementing AI-driven solutions. However, recent developments have shown that AI training costs are rapidly declining, and this trend is expected to continue in the future. According to the ARK Invest Big Ideas 2023 report, training costs of a large language model similar to GPT-3 level performance have plummeted from $4.6 million in 2020 to $450,000 in 2022, a decline of 70% per year. Let's explore this trend of declining AI training costs further and discuss the factors contributing to this decline.

Through the pervasive use of massive amounts of data to automate decisions and processes, artificial intelligence (AI) constitutes one of the most impactful developments for businesses and organisations in general. However, this fast-paced and unstoppable trend raises ethical issues. How can we ensure that AI development is fair, when the algorithms at its core are designed with (often unconscious) racist, sexist, or other biases? Lorena Blasco-Arcas and Hsin-Hsuan Meg Lee propose a human-centred view for the design of specific frameworks and regulatory systems. "Okay, Google, what's the weather today?" "Sorry, I don't understand."

How to develop an ethical and non-biased AI application in an undoubtedly biased and unbalanced society? Can AI be the holy grail by developing more balanced societies that overcome traditional inequality and exclusion? It is too early to say, and it seems apparent that we will witness many trial-and-error phases before achieving a consensus on what and how AI might be used ethically in our societies. Much like institutional racism, which requires fundamental shifts in the overall ecosystem, the problems in AI development also call for a similar change to create better output. Behind the development and implementation of algorithms, there are developers and specific people in power positions.

"Okay, Google, what's the weather today?" "Sorry, I don't understand." Does the experience--interacting with smart machines that don't respond to orders--sound familiar? This failure may leave people feeling dumbfounded, as if their intelligence were not on the same wavelength as the machines'. While this is not the intention of AI development (to interact selectively), such incidents are likely more frequent for "minorities" in the tech world. The global artificial intelligence (AI) software market is forecast to boom in the coming years, reaching around 126 billion US dollars by 2025.

Joining a geology team, the Geoscience Data Specialist will play a vital role in the continual development of our digital transformation tools and our geoscience analytic techniques. You will be working alongside our geoscience experts to analyse geological data workflows and develop the database and dynamic data-driven improvements. You will be responsible for maintaining consistency and integrity of the corporate database and for the development of shared resources for workflows. The successful candidate will be responsible for supporting the development and implementation of technologies and efficient workflows to extract, transform, load, manipulate, explore, analyse, report, and visualise data for operational and legacy projects. You will work on projects to assist with data identification, inventory, extraction, transformation and database loading and will also develop, manage and apply ETL tools, scripts and database systems for geoscience data.

August 2020 – On 19 August 19 2020, the Bulgarian Ministry of Transport, Information Technology and Communications released a new draft strategy entitled Concept for the Development of Artificial Intelligence in Bulgaria until 2030. It aims to define focal areas for building scientific and expert capacity for the development and implementation of AI systems and to build on the measures and activities set as a priority in other relevant national strategic documents, including in particular "Vision, Objectives and Priorities for the National Development Program: Bulgaria 2030." Based on the EU-wide principles for the development and implementation of AI technologies, the national AI strategy takes a broad-spectrum approach to encouraging the introduction of next-generation digital technologies in Bulgaria and offers a timely and reliable assessment of possible risks. This framework strategy is expected to play an important role during the next decade in the development of important national policies in the areas of science and scientific infrastructure; education and skills; intelligent industry; electronic public administration; sustainable agriculture; and e-health. All interested parties, including companies active on digital and digitally-enabled markets such as yours, are invited to provide feedback on the concept until 18 September 2020. For your convenience, please refer to the original document (in Bulgarian only) here.

From the President: November 2019 President's Messages November 2019 Español Français 中文 Our Executive and many of our members are involved in numerous ways in the development and use of Artificial Intelligence (AI) in relation to their practice. As an organization we emphasise that nothing can replace the face to face and continuous contact between family doctor and patient. At the same time, we acknowledge that AI is around, available and in increasing use both by our patients and by us. I am pleased that the WONCA Working Party on eHealth, chaired by Pramendra Prasad, is taking the lead on this issue on behalf of family medicine. WONCA is now engaged in a pilot project with Ping An Good Doctors of China (PAGD) to assess an AI assisted primary care system.

Artificial intelligence (AI) is one of the biggest topics in healthcare today, and the authors of a recent analysis published in the Journal of the American College of Radiology wrote at length about radiology's role in the development and implementation of these state-of-the-art technologies. "The radiology community has played a leading role in propelling medicine into its digital age and now has the opportunity to become a leader in exploring medical applications of AI," wrote lead author James H. Thrall, MD, department of radiology at Massachusetts General Hospital in Boston, and colleagues. "The tens of millions of radiology reports and billions of images now archived in digital form exemplify the concept of'big data' and constitute the required substrate for AI research." Thrall and colleagues covered considerable ground, including the various challenges specialists face as they work to use AI to their advantage. "None of the challenges alone will be a showstopper but all may slow progress and need to be addressed," the authors wrote.