scholarly journals Digitale Wissensorganisation

2021 ◽  
Author(s):  
Christian Linke
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
21St Century ◽  
Information Acquisition ◽  
Autonomous Systems ◽  
Knowledge Attribution ◽  
Contractual Relationships ◽  
Evaluation Decision ◽  
Environmentally Sensitive ◽  
Open Concept

The thesis investigates the attribution of knowledge in the use of autonomous systems in enterprises. It analyzes the challenges posed by digitization and artificial intelligence to the practical topic in contractual and non-contractual relationships, when information is increasingly processed by algorithms instead of humans. Using an environmentally sensitive legal approach, it develops an innovation-open concept of knowledge attribution for the 21st century. In doing so, the work is practice-oriented and focuses on the areas of application of autonomous systems in enterprises: information acquisition and evaluation, decision making, and decision and decision implementation.

scholarly journals Towards Trust, Transparency and Liability in AI / AS systems

2017 ◽  
Author(s):  
Eva Thelisson
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Autonomous Systems ◽  
Research Problem ◽  
Collective Decision ◽  
Collective Decision Making ◽  
Global Level ◽  
Governance Mechanisms ◽  
Decision Making Processes ◽  
Artificial Intelligence Systems

The research problem being investigated in this article is how to develop governance mechanisms and collective decision-making processes at a global level for Artificial Intelligence systems (AI) and Autonomous systems (AS), which would enhance confidence in AI and AS.

scholarly journals Global technological trends in the field of weapons and military equipment

2020 ◽  
Author(s):  
T. V. Pysarenko ◽  
◽  
T. K. Kvasha
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
New Technologies ◽  
Autonomous Systems ◽  
Space Technology ◽  
Negative Consequences ◽  
Seamless Integration ◽  
The Future ◽  
Military Innovations ◽  
The Military

Technology is the fundamental factor of social change, offering new opportunities for the production, storage and dissemination of knowledge. This is especially true in the military sphere, because progress in military technology can have both positive and negative consequences: improved capabilities for measures to mobilize and use force, or more powerful capabilities for cause harm and destruction. Current innovations in artificial intelligence, robotics, autonomous systems, space technology, 3D printing, biotechnology, materials science and quantum computing will bring unprecedented transformations. Artificial intelligence (AI) is becoming the "defining technology of the future", both in everyday life and in the military sphere. For developing a military potential suitable for the geostrategic challenges of the present and the future, it is important to navigate military innovations and new technologies, which is what this work is devoted to. Based on the analysis of publications of the international analytical and consulting organizations, foreign governments, NATO, SIPRI, the Munich Security Conference, the EU the latest forecasts for the introduction and adaptation of new technologies and methods originating from the civilian sector into military programs were presented. In particular, this applies to technologies of the fourth industrial revolution - artificial intelligence, robotics, autonomy, cybersecurity, etc., as well as space, nuclear technologies, technologies of new materials, biotechnologies - for military transformation. The future of military success will now belong to those who design, build and use combinations of information technology with existing technology and military capabilities to form a new combat force - smart, interconnected, distributed and digital. This change manifests itself in new forms of war - hyper war, memetic war, cyberspace war. The future scientific and technological landscape in the military sphere will be characterized (and at the same time guided) by the following: - Intelligence: built-in artificial intelligence, advanced analytics and decision-making capabilities across the entire technology spectrum. - Autonomy: autonomous systems with artificial intelligence that are capable of up to a certain level of autonomous decision-making. Such autonomous systems can be robotic, platform-based, or (digital) agents. - Humanistic intelligence: seamless integration of psycho-socio-technological systems supporting human and machine connectivity, as well as synergistic behaviour. - Interconnection: overlay of real and virtual domains, including sensors, organizations, institutions, individuals, autonomous agents and processes.

Perceived Effectiveness of Artificial Intelligence based Decision Support System in a Clinical Setting: A Systematic Literature Review (Preprint)

2020 ◽  
Author(s):  
Avishek Choudhury
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Decision Support ◽  
Literature Review ◽  
Decision Support System ◽  
Support System ◽  
Clinical Setting ◽  
Clinical Decision Making ◽  
Theoretical Perspective ◽  
Care Providers

UNSTRUCTURED Objective: The potential benefits of artificial intelligence based decision support system (AI-DSS) from a theoretical perspective are well documented and perceived by researchers but there is a lack of evidence showing its influence on routine clinical practice and how its perceived by care providers. Since the effectiveness of AI systems depends on data quality, implementation, and interpretation. The purpose of this literature review is to analyze the effectiveness of AI-DSS in clinical setting and understand its influence on clinician’s decision making outcome. Materials and Methods: This review protocol follows the Preferred Reporting Items for Systematic Reviews and Meta- Analyses reporting guidelines. Literature will be identified using a multi-database search strategy developed in consultation with a librarian. The proposed screening process consists of a title and abstract scan, followed by a full-text review by two reviewers to determine the eligibility of articles. Studies outlining application of AI based decision support system in a clinical setting and its impact on clinician’s decision making, will be included. A tabular synthesis of the general study details will be provided, as well as a narrative synthesis of the extracted data, organised into themes. Studies solely reporting AI accuracy an but not implemented in a clinical setting to measure its influence on clinical decision making were excluded from further review. Results: We identified 8 eligible studies that implemented AI-DSS in a clinical setting to facilitate decisions concerning prostate cancer, post traumatic stress disorder, cardiac ailment, back pain, and others. Five (62.50%) out of 8 studies reported positive outcome of AI-DSS. Conclusion: The systematic review indicated that AI-enabled decision support systems, when implemented in a clinical setting and used by clinicians might not ensure enhanced decision making. However, there are very limited studies to confirm the claim that AI based decision support system can uplift clinicians decision making abilities.

scholarly journals BattleNet: Capturing Advantageous Battlefield in RTS Games (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13849-13850
Author(s):  
Donghyeon Lee ◽  
Man-Je Kim ◽  
Chang Wook Ahn
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Real Time ◽  
Large Scale ◽  
Outcome Predictor ◽  
Short Term ◽  
Rts Game

In a real-time strategy (RTS) game, StarCraft II, players need to know the consequences before making a decision in combat. We propose a combat outcome predictor which utilizes terrain information as well as squad information. For training the model, we generated a StarCraft II combat dataset by simulating diverse and large-scale combat situations. The overall accuracy of our model was 89.7%. Our predictor can be integrated into the artificial intelligence agent for RTS games as a short-term decision-making module.

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