4-2 Activity- Critical Analysis

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Dec 6, 2023

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4-2 Activity: Critical Analysis Natasha Hicks IDS 403 Professor Richard Queeney Southern New Hampshire University

Title: AI Technology in the Covid-19 Pandemic: A Natural Science Perspective Introduction: The COVID-19 pandemic has not only tested the resilience of global healthcare systems but has also spurred the integration of artificial intelligence (AI) technology in various aspects of pandemic response. This paper explores the role of AI in the Covid-19 pandemic through the lens of natural science, utilizing evidence from diverse sources such as "The SAGE Handbook of Social Media," Liu et al.'s study on monitoring the pandemic through social media, reports from the American Psychological Association, and Shin et al.'s examination of AI in media. Reliable Evidence from Varied Sources: "The SAGE Handbook of Social Media" offers insights into the intersection of technology and society. Bury (2018) discusses television viewing and fan practices, providing context for the cultural implications of technology. Miltner's (2018) exploration of internet memes adds a layer to our understanding of digital culture and its role in shaping societal attitudes. Liu et al.'s (2021) study on monitoring the pandemic through social media demonstrates how natural language processing and machine learning can extract valuable insights from vast datasets. This research emphasizes the importance of social media as a real-time source of information during a global crisis. The American Psychological Association's report on the rapid growth of intelligent automation amid the pandemic highlights the increased reliance on AI for optimizing costs and productivity (2021). Shin et al.'s (2022) examination of algorithmic bias and disinformation underscores the need for ethical AI practices in media. Recommend Strategies to Address Limitations:

The limitations of AI technology in the Covid-19 pandemic include potential biases in algorithms and ethical concerns. To address these limitations, developers can implement rigorous testing protocols, involve diverse teams in AI development, and establish clear ethical guidelines. Regular updates to machine learning models and transparency in decision-making processes are essential for mitigating limitations. Assess Significant Factors Impacting Understanding: Two significant factors influencing public understanding of AI technology in the pandemic are biases and pre-existing beliefs. Public perception can be shaped by media portrayals, cultural influences, and individual attitudes towards technology. Recognizing and addressing these factors are essential for fostering accurate and informed public discourse on the benefits and risks of AI technology in crisis situations. Assess Benefits and Challenges of Critically Analyzing Technology: Critical analysis of technology in society has a positive impact by identifying potential risks, ensuring ethical practices, and promoting transparency. However, challenges arise in addressing the rapid pace of technological evolution, potential biases in analysis, and public skepticism towards technological solutions. Recommend Strategies for Personal Goals: Aspiring to become a Pen Tester, critical analysis of AI technology can be applied by staying informed about AI security vulnerabilities, engaging in ethical hacking practices, and advocating for secure AI implementations. In everyday life, this involves evaluating the security implications of technology used in personal and professional settings and actively contributing to the enhancement of cybersecurity measures.

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Conclusion: In conclusion, the integration of AI technology in the Covid-19 pandemic is a multifaceted phenomenon, as analyzed through the natural science lens. Drawing from diverse sources, this paper highlights the importance of reliable evidence, strategies to address limitations, factors influencing public understanding, and the benefits and challenges of critically analyzing AI in society. Recommending strategies for personal goals underscores the practical applications of this critical analysis in everyday life, especially for individuals aspiring to specialize in cybersecurity. References Bury, R. (2018). Television viewing and fan practice in an era of multiple screens. In The SAGE Handbook of Social Media (pp. 372-389). SAGE Publications Ltd, https://doi.org/10.4135/9781473984066 Miltner, K. (2018). Internet memes. In The SAGE Handbook of Social Media (pp. 412-428). SAGE Publications Ltd, https://doi.org/10.4135/9781473984066 Liu, Y., Whitfield, C., Zhang, T., Hauser, A., Reynolds, T., & Anwar, M. (2021). Monitoring COVID-19 pandemic through the lens of social media using natural language processing and machine learning. Health Information Science and Systems, 9(1), 25. https://doi- org.ezproxy.snhu.edu/10.1007/s13755-021-00158-4 (American Psychological Assoc.) U.S. Leads Rapid Growth of Intelligent Automation Amid Pandemic-Related Drive to Optimize Costs, Productivity. (2021, March 4). Business Wire. Shin, D., Hameleers, M., Park, Y. J., Kim, J. N., Trielli, D., Diakopoulos, N., Helberger, N., Lewis, S. C., Westlund, O., & Baumann, S. (2022). Countering Algorithmic Bias and Disinformation and Effectively Harnessing the Power of AI in Media. Journalism & Mass

Communication Quarterly, 99(4), 887–907. https://doi- org.ezproxy.snhu.edu/10.1177/1077699022112924

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