Sensors, Vol. 23, Pages 4852: Secure and Reliable Big-Data-Based Decision Making Using Quantum Approach in IIoT Systems
Silicon vs. Carbon
Neurosymbolic AI and its Taxonomy: a survey
Neurosymbolic AI deals with models that combine symbolic processing, like
classic AI, and neural networks, as it's a very established area. These models
are emerging as an effort toward Artificial General Intelligence (AGI) by both
exploring an alternative to just increasing datasets' and models' sizes and
combining Learning over the data distribution, Reasoning on prior and learned
knowledge, and by symbiotically using them. This survey investigates research
papers in this area during recent years and brings classification and
comparison between the presented models as well as applications.
Generative AI: Implications and Applications for Education
The launch of ChatGPT in November 2022 precipitated a panic among some
educators while prompting qualified enthusiasm from others. Under the umbrella
term Generative AI, ChatGPT is an example of a range of technologies for the
delivery of computer-generated text, image, and other digitized media. This
paper examines the implications for education of one generative AI technology,
chatbots responding from large language models, or C-LLM. It reports on an
application of a C-LLM to AI review and assessment of complex student work. In
a concluding discussion, the paper explores the intrinsic limits of generative
AI, bound as it is to language corpora and their textual representation through
binary notation. Within these limits, we suggest the range of emerging and
potential applications of Generative AI in education.
The Ethics of AI in Games
Video games are one of the richest and most popular forms of human-computer
interaction and, hence, their role is critical for our understanding of human
behaviour and affect at a large scale. As artificial intelligence (AI) tools
are gradually adopted by the game industry a series of ethical concerns arise.
Such concerns, however, have so far not been extensively discussed in a video
game context. Motivated by the lack of a comprehensive review of the ethics of
AI as applied to games, we survey the current state of the art in this area and
discuss ethical considerations of these systems from the holistic perspective
of the affective loop. Through the components of this loop, we study the
ethical challenges that AI faces in video game development. Elicitation
highlights the ethical boundaries of artificially induced emotions; sensing
showcases the trade-off between privacy and safe gaming spaces; and detection,
as utilised during in-game adaptation, poses challenges to transparency and
ownership. This paper calls for an open dialogue and action for the games of
today and the virtual spaces of the future. By setting an appropriate framework
we aim to protect users and to guide developers towards safer and better
experiences for their customers.