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This research paper examines the potential consequences of AI technology on democratic systems. The study focuses on two main areas: the weakening of the media and the emergence of "smart dictatorship." The paper examines the ways in which AI can be used to supervise, manipulate, and frustrate the media, thereby weakening its role as a check on government and corporate power. The study also explores how AI technology can be used to create an "omnidirectional monitoring" society, where individuals are constantly monitored and controlled through the use of "panopticon" techniques and "social bots". This can lead to the emergence of a "postdemocratic" society, characterized by growing inequality, dehumanization, and the
manipulation of information on online media platforms. The research methodology adopted in the study is qualitative, using expert interviews with three experts who
discussed the overall use of AI and its disruptive effects on democracy, such as the creation of fake news, filter bubbles, and algorithm bias. In conclusion, this research highlights the need for increased awareness and regulation of AI technology to ensure its responsible use and to protect democratic values.
This study analyzes approaches to decarbonize the energy supply of the secondary steel processing industry. Therefore, real data from a secondary steel production company is used in combination with state-of-the art low carbon energy supply technologies. Also, the use of waste heat from a pusher furnace for process integration is considered. The developed temporal process model allows holistic optimizing and expanding the steel making process system regarding techno-economic criteria. As we show, implementing the annual heat demand of a municipality shows that a nearly 100 % self-sufficient heat supply is possible.
Measuring IT security, compliance and data governance within small and medium-sized IT enterprises
(2020)
Biomass gasification is recognized as a viable avenue to accelerate the sustainable production of hydrogen. In this work, a numerical simulation model of air gasification of rice husks is developed using the Aspen Plus to investigate the feasibility of producing hydrogen-rich syngas. The model is experimentally validated with rice husk gasification results and other published studies. The influence of temperature and equivalence ratio on the syngas composition, H2 yield, LHVSyngas, H2/CO ratio, CGE, and PCG was studied. Furthermore, the synchronized effects of temperature and ER are studied using RSM to determine the operational point of maximizing H2 yield and PCG. The RSM analysis results show optimum performance at temperatures between 820 °C and 1090 °C and ER in the range of 0.06–0.10. The findings show that optimal operating conditions of the gasification system can be achieved at a more refined precision through simulations coupled with advanced optimization techniques.