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This study is part of the preparatory work needed for establishing a foundational comprehension of specific aspects related to the research goal, which is to investigate the multidimensional interplay of individual factors and context in shaping trust towards Artificial Intelligence Expert Systems. This study is primarily a validation study in a representative German sample. It aims to validate a generally satisfying description of how an AIES should be described such that people can make an informed decision on whether they would want to use that system or not. Initially, a set of descriptive elements was introduced and exploratively analyzed in a predecessor study (https://doi.org/10.17605/OSF.IO/YQZGK). The descriptive elements identified as 'most essential' components of a comprehensive yet concise description are presented herein. It further aims to replicate and confirm the factor structure of a translated propensity to trust scale by Frazier et al. 2013. Additionally, it identifies people's risk and trust perceptions in five different contexts (medicine, psychotherapy, law, education, and finance).

Project title Shaping Future Practices: Understanding Medical and Dental Students' Perception of Artificial Intelligence in Austria, Germany and Schwitzerland – an online survey Abstract Artificial intelligence (AI) applications are advancing across healthcare fields. Our study investigates the perceptions and attitudes of medical and dental students towards AI in Germany, Austria and Switzerland. We conducted an online survey with 409 participants and analyzed their AI knowledge, education, attitudes and emotions using correlations, t-tests, and thematic analysis.

To explore the process of projecting real human emotions and characteristics onto non-human objects (also referred to anthropomorphism) and how factors such as personality and the need to have control over an unfamiliar object contribute to the formation of a perceived relationship between a human user and a Generative Artificial Intelligence (G-AI) Model.

Understanding self perception of sentience in Animal, Human and Artificial Intelligence by observational studies of human attitudes and practices towards sentient beings.

Understanding self perception of sentience in Animal, Human and Artificial Intelligence by observational studies of human attitudes and practices towards sentient beings.

We spoke with Christo Wilson, a professor of Computer Science at Northeastern University, about how artificial intelligence works and the advantages and potential drawbacks of the technology. Background image courtesy of rawpixel.com on Freepik.

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Artificial intelligence reporter, Karen Hao, from MIT Technology Review joins us on the Digital Selling Secrets podcast.  In this interview, we discuss how artificial intelligence is evolving. We also discussed different forms of innovation within artificial intelligence.  Artificial intelligence is expected to impact all industries, including sales. If you want to stay ahead of the curve with your knowledge of artificial intelligence, this episode is for you. 

DMF Talks: Understanding Artificial Intelligence

DMF Talks: Understanding Artificial Intelligence

Artificial intelligence AI powered adaptive learning systems ALS offer individualised learning experiences catered to the requirements of each individual student, marking a revolutionary development in the field of education. This study examines the mutually beneficial link between AI and adaptive learning, emphasising how both have the power to completely transform conventional educational approaches. ALS addresses the different learning demands of students by dynamically modifying instructional material, tempo, and resources based on learner responses. This approach departs from the one size fits all methodology of traditional education. Artificial intelligence AI powered computers improve ALS by analysing massive volumes of data, allowing for real time adjustments and student specific feedback. AI also makes scalability and accessibility possible, allowing cloud based and online systems to reach a larger student population. To guarantee the moral and just use of AI driven ALS, issues including algorithmic bias, data protection, and the requirement for teacher professional development must be resolved. The study covers the theoretical underpinnings of AI and adaptive learning, looks at their implementations, and talks about the advantages and difficulties of combining the two. Methodologically, secondary data from research papers, journals, and academic publications were used in a documentary analytic technique. In the future, developments in artificial intelligence AI and machine learning will continue to influence educational methods, calling for support for the dynamics between teachers and students as well as ethical and legal frameworks. All things considered, the incorporation of AI into adaptive learning systems has the potential to produce more successful, welcoming, and student focused learning environments that cater to the individual requirements of every learner. Sudeshna Rana "Understanding the Role of Artificial Intelligence in Adaptive Learning Systems" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-2 , April 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64545.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/education/64545/understanding-the-role-of-artificial-intelligence-in-adaptive-learning-systems/sudeshna-rana

This scoping review aims to systematically map the existing literature on the environmental impact of artificial intelligence (AI) used in healthcare settings. As AI technologies become more prevalent in clinical, public health, and health system applications, it is essential to understand their environmental footprint, including energy consumption and carbon emissions. We will search MEDLINE, CINAHL, and GreenFILE for studies published from January 2015 onward, including peer-reviewed articles, grey literature, and theses. Inclusion criteria focus on studies involving AI methodologies such as machine learning, deep learning, and natural language processing applied within healthcare, with explicit discussion of environmental impacts. Studies outside healthcare or those not addressing environmental outcomes will be excluded. Expected outcomes include a comprehensive overview of the types of evidence available, identification of key themes and knowledge gaps, and recommendations for future research and policy to support more sustainable AI integration in healthcare.

This scoping review aims to systematically map the existing literature on the environmental impact of artificial intelligence (AI) used in healthcare settings. As AI technologies become more prevalent in clinical, public health, and health system applications, it is essential to understand their environmental footprint, including energy consumption and carbon emissions. We will search MEDLINE, CINAHL, and GreenFILE for studies published from January 2015 onward, including peer-reviewed articles, grey literature, and theses. Inclusion criteria focus on studies involving AI methodologies such as machine learning, deep learning, and natural language processing applied within healthcare, with explicit discussion of environmental impacts. Studies outside healthcare or those not addressing environmental outcomes will be excluded. Expected outcomes include a comprehensive overview of the types of evidence available, identification of key themes and knowledge gaps, and recommendations for future research and policy to support more sustainable AI integration in healthcare.

Many people have seen  The Terminator  and know what happens if you’re busy playing video games instead of preparing for SkyNet.

While AI holds incredible potential, it’s also shrouded in misconceptions that range from the amusingly absurd to the dangerously misinformed. Some of these are shaped by the depiction of AI in movies and entertainment, while others are perpetuated by fear or lack of knowledge. As builders of AI systems for businesses, Quantilus strives to educate businesses on the best utilization of AI. To achieve this, businesses must grasp the realities of AI: how it operates, its capabilities and limitations, and the indispensable role that human oversight plays in crafting effective and ethically responsible AI systems.

Scientists use artificial intelligence for understanding psychokinesis. Psychokinesis, sometimes referred to as "telekinesis" or "mind over matter," is the ability to influence the movement of matter or energy through mental processes. Psychokinesis is an interesting topic that explores the possibility of manipulating physical objects with the power of the mind. This theory has been studied by scientists for decades, and it continues to fascinate many people. Experiments have been conducted to test the accuracy of psychokinetic abilities. Some researchers believe in paranormal phenomena while others are skeptical about its existence. I have shown my ability to various scientific institutions under strictly controlled conditions. So far, they have not been able to find a plausible explanation for the phenomenon, nor a concept that anybody can imitate it. My ability was examined at a leading brain research center MindLab international in The United Kingdom by neuroscientist Dr David Lewis-Hodgson, in Germany by Prof. Dr. Dr. Ruhenstroth-Bauer in Max Planck Institute, in Russia by Prof. dr. Konstantin Korotkov, Professor of Physics at Saint Petersburg University and in the United States I was examined by Dr. Alexander Imich, MPhil D Barbara G. Koopman. I also showed my skill in live television programs. Sir David Frost was a British journalist and Television presenter on ITV live show “Beyond Belief”, Fact or Fiction in UK. He gave me the name Magnetic Man. Stan Lee the inventor of numerous superheroes from the Marvel Comics Cosmos, such as Spider-man, the X-Men, Iron Man, Thor, the Hulk in "Stan Lee's Superhumans" television documentary aired on History and Discovery Channel. He gave me the name Mind Force. Christophe Dechavanne and Patrice Carmouzeon on TF1 live show “La soirée de l'étrange” in France, they gave me the name Magnetic. In Germany on TV Sat.1 program "Clever" hosted by Barbara Eligmann and Wigald Boning, the show that creates knowledge, which is trying to answer scientific questions relating to the experiments conducted by contestants. They gave me the name Magnet Mann. I am convinced that very soon a new generation will show that with more developed technology like Artificial intelligence, which is rapidly becoming an invaluable tool in neuroscience, Quantum physics, the study of matter and energy at the most fundamental level and a more developed state of consciousness of humanity, such things can be seen as nothing out of the ordinary but as something quite natural.

Explainable artificial intelligence (XAI) uses artificial intelligence (AI) tools and techniques to build interpretability in black-box algorithms. XAI methods are classified based on their purpose (pre-model, in-model, and post-model), scope (local or global), and usability (model-agnostic and model-specific). XAI methods and techniques were summarized in this paper with real-life examples of XAI applications. Local interpretable model-agnostic explanations (LIME) and shapley additive explanations (SHAP) methods were applied to the moral dataset to compare the performance outcomes of these two methods. Through this study, it was found that XAI algorithms can be custom-built for enhanced model-specific explanations. There are several limitations to using only one method of XAI and a combination of techniques gives complete insight for all stakeholders.

Explainable artificial intelligence (XAI) uses artificial intelligence (AI) tools and techniques to build interpretability in black-box algorithms. XAI methods are classified based on their purpose (pre-model, in-model, and post-model), scope (local or global), and usability (model-agnostic and model-specific). XAI methods and techniques were summarized in this paper with real-life examples of XAI applications. Local interpretable model-agnostic explanations (LIME) and shapley additive explanations (SHAP) methods were applied to the moral dataset to compare the performance outcomes of these two methods. Through this study, it was found that XAI algorithms can be custom-built for enhanced model-specific explanations. There are several limitations to using only one method of XAI and a combination of techniques gives complete insight for all stakeholders.

Explainable artificial intelligence (XAI) uses artificial intelligence (AI) tools and techniques to build interpretability in black-box algorithms. XAI methods are classified based on their purpose (pre-model, in-model, and post-model), scope (local or global), and usability (model-agnostic and model-specific). XAI methods and techniques were summarized in this paper with real-life examples of XAI applications. Local interpretable model-agnostic explanations (LIME) and shapley additive explanations (SHAP) methods were applied to the moral dataset to compare the performance outcomes of these two methods. Through this study, it was found that XAI algorithms can be custom-built for enhanced model-specific explanations. There are several limitations to using only one method of XAI and a combination of techniques gives complete insight for all stakeholders.

Artificial intelligence has produced new teaching and learning solutions that are now undergoing testing in different contexts. In addition to its impact on the education sector, AI is substantially altering labour markets, industrial services, agriculture processes, value chains and the organization of workplaces in particular. Technical and vocational education and training (TVET) contributes to sustainable development by fostering employment, decent work and lifelong learning. However, the effectiveness of a TVET system depends on its links and relevance to the labour market. As one of the major drivers of change, there is a need to better understand the impact of AI on labour markets, and consequently on TVET systems. In certain middle- and higher-income societies, artificial intelligence is already deeply immersed in legislation and governance, policy, state expenditure, the private sector and national economies. In these cases, TVET institutions are presiding over the 'hollowing out' of intermediate level skills and the direct integration of AI into education and training. Contrastingly, many TVET institutions have yet to form meaningful or robust responses to technological shifts. Regardless of context, all TVET institutions should develop an understanding of the current and future importance of AI and begin to incorporate its use into their planning. Forward thinking and, where possible, pre-emptive action, will put TVET institutions and their graduates in a position to thrive in the era of AI and contribute positively to economic, social, and individual development.

James Poulos, author, founder of “Return,” and editor of “The American Mind,” gives his insight into artificial intelligence and the dangers it presents. While AI will undoubtedly revolutionize the way we do many things, that does not mean it comes without risks. With our society already staring at screens for hours a day, we’re quickly turning into a world of cyborgs. Artificial intelligence will only speed that process up. Just what are we dealing with? Why is it important to have a spiritual backstop in a digital world? James sheds some light on these questions. ► Click HERE to subscribe to BlazeTV! https://get.blazetv.com/chad-prather/ Connect with Chad on Social Media: https://twitter.com/WatchChad https://www.instagram.com/watchchad/ http://facebook.com/watchchadprather About Chad Prather: Chad Prather is known for his way with words. He is a comedian, armchair philosopher, musician, and observational humorist. Often called “the modern day Will Rogers” and “the voice of the everyman,” Chad brings you his armchair philosophy and observational humor four times a week. Politics, inspiration, comedy, and fun — nothing is off limits on The Chad Prather Show! Some of Prather’s most popular videos are shot in the front seat of his truck as he delivers his fast talking, rabid fire rants. CNN has labeled him the “Pick-up Pundit” and Fox News’ Tucker Carlson has called Prather, “supernaturally articulate.” Prather has mad numerous appearances on Fox News, CNN, A&E, MSN. He is the host of BlazeTV’s “The Chad Prather Show” and “Humor Me with Chad Prather.” His wildly successful 2016 “Kings of Cowtown Comedy: was a hit and his current “Star Spangled Banter Comedy Tour” is selling out theaters all over America. Chad’s guests include: Phil Robertson, Glenn Beck, Jon Miller, Elizabeth Johnston, Jeff Kyle, Jason Piccolo, Matt Kibbe, Sara Gonzales, Mark Maxwell, Mike Stewart, Jennifer Nickerson, David Harris Jr., Mike Ritland, Heath Oakes, Kendall Jones, Rob Redwine, Trey Chapman, Katie Thulin, and many more! #chadprather #ai #artificialintelligence #machinelearning #vr #virtualreality #augmentedreality #theology #christianity #christian #bible #biblical #podcast #blazetv #blaze #theblaze

James Poulos, author, founder of “Return,” and editor of “The American Mind,” gives his insight into artificial intelligence and the dangers it presents. While AI will undoubtedly revolutionize the way we do many things, that does not mean it comes without risks. With our society already staring at screens for hours a day, we’re quickly turning into a world of cyborgs. Artificial intelligence will only speed that process up. Just what are we dealing with? Why is it important to have a spiritual backstop in a digital world? James sheds some light on these questions. ► Click HERE to subscribe to BlazeTV! https://get.blazetv.com/chad-prather/ Connect with Chad on Social Media: https://twitter.com/WatchChad https://www.instagram.com/watchchad/ http://facebook.com/watchchadprather About Chad Prather: Chad Prather is known for his way with words. He is a comedian, armchair philosopher, musician, and observational humorist. Often called “the modern day Will Rogers” and “the voice of the everyman,” Chad brings you his armchair philosophy and observational humor four times a week. Politics, inspiration, comedy, and fun — nothing is off limits on The Chad Prather Show! Some of Prather’s most popular videos are shot in the front seat of his truck as he delivers his fast talking, rabid fire rants. CNN has labeled him the “Pick-up Pundit” and Fox News’ Tucker Carlson has called Prather, “supernaturally articulate.” Prather has mad numerous appearances on Fox News, CNN, A&E, MSN. He is the host of BlazeTV’s “The Chad Prather Show” and “Humor Me with Chad Prather.” His wildly successful 2016 “Kings of Cowtown Comedy: was a hit and his current “Star Spangled Banter Comedy Tour” is selling out theaters all over America. Chad’s guests include: Phil Robertson, Glenn Beck, Jon Miller, Elizabeth Johnston, Jeff Kyle, Jason Piccolo, Matt Kibbe, Sara Gonzales, Mark Maxwell, Mike Stewart, Jennifer Nickerson, David Harris Jr., Mike Ritland, Heath Oakes, Kendall Jones, Rob Redwine, Trey Chapman, Katie Thulin, and many more! #chadprather #ai #artificialintelligence #machinelearning #vr #virtualreality #augmentedreality #theology #christianity #christian #bible #biblical #podcast #blazetv #blaze #theblaze

The Northeast Artificial Intelligence Consortium (NAIC) was created by the Air Force Systems Command, Rome Air Development Center, and the Office of Scientific Research. Its purpose was to conduct pertinent research in artificial intelligence and to perform activities ancillary to this research. This report describes progress during the existence of the NAIC on the technical research tasks undertaken at the member universities. The topics covered in general are: versatile expert system for equipment maintenance, distributed AI for communications system control, automatic photointerpretation, time-oriented problem solving, speech understanding systems, knowledge base maintenance, hardware architectures for very large systems, knowledge-based reasoning and planning, and a knowledge acquisition, assistance, and explanation system. The specific topics for this volume are various aspects of parallel, structural and optimal techniques in computer vision.

This report describes applied research into the application of artificial intelligence (AI) techniques to the problems associated with the extraction of terrain features from synthetic aperture radar (SAR) images. Specific AI techniques have been implemented and analyzed. They have given positive results. A conceptual model for an image-understanding system is described. The model provides the framework for a flexible experimental image-understanding research tool as well as potential for growth to an operational system. Originator-supplied keywords include: Radar Image Understanding, Image Processing, and Artificial Intelligence.

This document is concerned with the important extra-logical knowledge that is often outside of traditional discussions in mathematics, and looks at some of the ingredients and processes involved in the understanding of mathematics. The goal is to develop a conceptual framework in which to talk about mathematical knowledge and to understand the understanding of mathematics, in order to improve how to learn, teach, and how to do it. The framework is developed and used to describe the acquisition of understanding. A classroom experience using the ideas developed in a seminar with six Massachusetts Institute of Technology freshmen is reviewed. The document concludes with a review of five ingredients seen as part of the process of understanding mathematics. (MP)

This report describes the operation of a computer monitor called MYCROFT, a system which can debug elementary programs for drawing pictures. The basic skills which are fundamental to debugging skill (description, plan, linearity, insertions, global knowledge, and imperative semantics) are examined. These programs are written for LOGO turtles. (Author/CP)

The world of work is being impacted by a fourth industrial revolution, transformed by artificial intelligence and other emerging technologies. With forecasts suggesting large shares of workers, displaced by automation, in need of upskilling/reskilling, the design of active skills policies is necessary. Conventional methods used to anticipate technological change and changing skill needs, such as skill surveys and forecasting, have limited scope to provide insights into emerging trends. With the increasing use of big data and AI methods, analysts have new 'real-time' tools at their disposal. Skill foresight techniques are also increasingly used to gauge in-depth stakeholder information about future technologies and skill needs. A series of Cedefop guides aims to inform analysts and policy-makers about available skills anticipation methods used to navigate through the uncertainty of changing technologies and skill demands. This second practical guide focuses on automated skills intelligence methods: big data and AI-driven analyses. [Cedefop wishes to acknowledge the research and services of its contracted institution, the Fondazione Giacomo Brodolini (FGB) (lead partner) in consortium with Economix Research and Consulting, Cambridge Econometrics Ltd, and Panteia B.V. For Cedefop Practical Guide 1, see ED613871. For Cedefop Practical Guide 3, see ED613874.]