Rough Draft Review Process Evaluation
[WLOs: 1, 2, 3, 4, 5] [CLOs: 1, 2, 3, 4, 5]
Purpose
:The primary goal of this weekly assignment is to enable you to understand the revision process and revise your paper with the help of a writing specialist.
Prepare
:
Step 1: Prepare a shortened version of your Final Paper (at least four pages) by including the following:
- Introduction paragraph and thesis statement you developed for your Week 3 Assignment.
- Background information of the global societal issue you have chosen.
- Brief argument supporting at least two solutions to the global societal issue.
- Conclusion paragraph.
- Must document any information used from at least five scholarly sources in APA style as outlined in the University of Arizona Global Campus Writing Center’sCiting Within Your Paper
Knowledge Area Module (KAM) I 5 THE RISE OF ARTIFICIAL INTELLIGENCE Darla Blevins GEN499 General Capstone Prof. David Ward September 10, 2021 1 Introduction There has been a significant advancement in the field of artificial intelligence (AI). Image and speech recognition, robotics, language problems, and game-playing have made considerable strides in recent years. As a result, significant improvement expects in decades to follow. It has many potentials: recent science breakthroughs, cheaper and more efficient commodities, and medical advancements, among others. Artificial intelligence (AI) has been used in our research and collaborations to address various global issues such as climate change mitigation, pandemic preparedness, and food security. Privacy, prejudice, inequality, and safety and security are some of the immediate problems with AI. Consistently modifying present systems to achieve desired outcomes is challenging, resulting in unanticipated adverse effects. More significant damage does a system triggered an accident with more power than it has. Artificial intelligence (AI) will bring novel governance problems and global collaboration and representation to minimize risk while attaining global advantages. Artificial Intelligence (AI) advanced, and robust systems will be created and implemented in the following years. These systems are likely to have revolutionary effects, both positive and harmful. The rise of AI is also causing threats in different fields like education, public health, cybersecurity. Thesis Statement The rise of AI gives us opportunities to explore the negative and positive outcomes of AI on sustainable development, which also causes threats in different fields like education, public health, cybersecurity. Annotation 1 Reference Ouchchy, L., Coin, A., & Dubljević, V. (2020). AI in the headlines: the portrayal of the ethical issues of artificial intelligence in the media. AI & SOCIETY, 35(4), 927-936. Annotation Media coverage of the ethical implications of artificial intelligence (AI) technology is rising as AI technology becomes more prevalent in our daily lives. Ethical issues in AI portray in the media may provide a significantly more extensive overview of the potential implications this public discourse may have in terms of AI development and regulation. Previous research has shown that media coverage of novel technologies can influence public discourse. For the sake of better understanding how media coverage of these concerns may impact public opinion, this article builds on prior studies by thoroughly analyzing and categorizing media depictions of AI's ethical difficulties. As a result of our research, we discovered that while the media covers AI ethics from a realistic and practical standpoint, coverage is still restricted. Increase public access to reliable information in the form of fact sheets and ethical corporate values on trusted internet pages (e.g., government agencies), collaborative effort, and integration of principles. AI experts in both research and public debate and consistent government policy and guidance are all needed to address AI technology's social, ethical, and policy implications. The writers of this study discovered that a wide variety of subjects connected to computer ethics cover a wide range of various technologies. It led them to believe not enough attention paid to methodology, recommendations, and contributions to publications. Annotation 2 Reference Benke, K., & Benke, G. (2018). Artificial intelligence and big data in public health. International journal of environmental research and public health, 15(12), 2796. Annotation AI and automation dominate the conversations about the future of job opportunities, social change, and economic performance. AI and Big Data are basic ideas described in this study and their importance to public health. There are several problems to consider and the possible consequences and obstacles for medical practitioners. According to the current research, enhanced data analytics and machine learning might provide several advantages. Problems recognized and debated in terms of ethics and the future responsibilities of professionals in the era of artificial intelligence. While artificial intelligence (AI) benefits consumers and businesses, it also has unintended and occasionally catastrophic drawbacks. While this Essay focuses on AI, similar consequences (and the techniques to prevent or minimize them) apply to any advanced analytics. Concerns are exercised based on the most glaring examples, such as privacy violations, discrimination and accidents, and political system manipulation. Even more worrying are the undiscovered or unexperienced effects. Suppose a ruined AI medical algorithm or an adversary's misinformation feeds into a military AI system. In that case, organizations might face disastrous consequences, including losing human life and national security breach. Future AI development has a fundamental challenge: using Big Data to build high-level abstractions that may imitate a subjective reaction from human subjectivity. An expert system automatically converts pathology results into written reports or verbal explanations that might develop in a clinical setting. Annotation 3 Reference Purandare, N. (2020). Guiding the Automation and AI Revolution: What the Rise in Automation Means for Shifting Standards of Human Value and Our Societal Structure (Doctoral dissertation). Annotation Although the automation revolution is imminent, we do not have to accept this technology as our fate. Automation has traditionally been linked with replacing human employment, but it may also empower people via strategic application. The impact of automation relies on how individuals accept the technologies, companies' sentient approaches, and legislative reactions to fundamental alterations in social structures and economic systems. First, this Essay aims to aid by pointing up several often-missed problems. After that, it provides executives with frameworks that will help them identify their most significant risks and apply the breadth and depth of nuanced controls necessary to avoid them, according to the book. There's also an early look at real-world initiatives to combat AI dangers by applying these techniques. Also, AI-driven workplace automation might lead to massive job losses, widely debated over the last few years. The importance of AI systems also has second-order impacts, such as the atrophy of skills (such as the diagnostic abilities of medical experts). Because of their apparent relevance, these repercussions will continue to get attention in the future, although they are outside the scope of this article's discussion at this time Annotation 4 Reference Chen, X., Xie, H., Zou, D., & Hwang, G. J. (2020). Application and theory gaps during the rise of Artificial Intelligence in Education. Computers and Education: Artificial Intelligence, 1, 100002. Annotation Artificial Intelligence in Education (AIEd) is becoming increasingly important, but there is no complete evaluation. This research attempts to do just that by conducting a systematic and thorough analysis of vital AIEd studies. In 45 papers, they looked at yearly distribution, influential journals, institutions, and countries/regions, as well as the most used words and theories. To further clarify the link between AIED, Educational Data Mining, Computer-Based Education, & Learning Analytics, we compared definitions of AIED from broad and specific viewpoints. According to the results, the influence and interest in AIEd research have been steadily rising over time. There was a lack of research on the use of deep learning technology in educational settings. The use of conventional AI technologies in education, such as natural language processing, was prevalent, while more sophisticated AI approaches were rare. Because there was little research that both used AI technology and thoroughly engaged with educational ideas, because of findings, academics should consider the possibility of incorporating artificial intelligence into the classroom. AI tutoring systems attempt to recognize the entailment links between learners' replies and the required conceptual knowledge. They should pay greater attention to deploying sophisticated deep learning techniques such as generative adversarial and deep neural networks. NLP uses to improve accuracy or customized instruction. Use of biological detection and imaging technologies like electroencephalograms to address learners' concerns throughout the learning process, et cetera. The use of artificial intelligence technology in education is tightly integrated with educational ideas. Current research on AIEd has not been systematically reviewed. In this study, a systematic review technique gives a comprehensive overview of significant academic works involving AIEd throughout the world. After defining what an AIEd is, this study analyses 45 highly referenced AIEd papers to identify development, trends, and technologies utilized, as well as significant research concerns that affect the AIEd community. This section divides into three subsections—a brief introduction to the use of AI in education in Section 1. The citation-based literature analysis introduces in Section 1.2. In the end, the study questions and objectives are described in section 1.3 Annotation 5 Reference Wu, T. (2019). Will Artificial Intelligence Eat the Law? The Rise of Hybrid Social-Ordering Systems. Columbia law review, 119(7), 2001-2028. Annotation Much of what used to be done by humans were replaced by software. Examples include capturing speeders or piloting airplanes. What are the chances that human courts will be replaced as the center of legal decision-making? Although human courts are unlikely to disappear anytime soon, hybrid machine-human systems represent the future of legal adjudication. There is some promise in a well-executed mix of machine-human systems, according to this Essay. The following are five pain points that can lead to AI problems. These problems connect to what may be called AI enablers, such as data issues, technological issues, and security issues. The AI's core functionality addresses two categories of algorithms and human-machine interactions. People shake their heads when anything goes wrong with AI, and they find out what caused it. A new competitive advantage will emerge when the price of hazards connected with AI grows. Customer experience is about to undergo a paradigm shift for many businesses, as AI-driven results bring both benefits and drawbacks to the table. It is hard to believe that no one saw this coming. In contrast, if you ask senior executives what the next AI danger will be, you're unlikely to come up with a unanimous answer.