Ethical use of AI

docx

School

University of the Cumberlands *

*We aren’t endorsed by this school

Course

837

Subject

Computer Science

Date

Feb 20, 2024

Type

docx

Pages

Uploaded by patilsushant26

Ethical use of AI Sushant Anil Patil Department of Information Technology DSRT-837 M22 Professional Writing Dr. Amanda Tanner February 11, 2024

Underwater Basket Weaving The interdisciplinary hobby of underwater basket weaving merges the traditional craft of basket weaving with scuba diving, presenting a unique blend of art and adventure (Smith, 2022). Unlike conventional basket weaving, which utilizes natural materials like reeds and rattan, underwater basket weaving employs durable, water-resistant materials such as vinyl-coated wires and plastic cords to adapt to the aquatic setting (Smith, 2022). This adaptation allows for the continuation of the craft underwater and offers a novel way to explore underwater environments through a creative lens. The precise origins of underwater basket weaving remain speculative, with some attributing its inception to the mid-20th century, coinciding with the rise in popularity of scuba diving as a recreational activity (Jones, 2020). The convergence of these two activities suggests an inventive approach to combining hobbies, where divers, intrigued by the novelty of underwater crafting, began integrating basket weaving into their dives, subsequently formalizing the activity through organized groups and instructional sessions. The practice of weaving baskets underwater introduces additional challenges, such as navigating the water's resistance and buoyancy, which need to be improved in terrestrial weaving (Williams, 2021; Thomas & Chang, 2019). Weavers must strategically manage these elements, often allowing the water's flow to influence the final design, resulting in unique, dynamic creations that embody their underwater birthplace's fluidity. Underwater basket weaving attracts individuals interested in scuba diving and basket weaving, offering a serene yet engaging pastime that combines the tranquility of underwater exploration with the satisfaction of artistic creation (Lee, 2017). This niche hobby fosters a deep connection with the marine environment and celebrates the fusion of disparate skills into a coherent, rewarding experience. While underwater basket weaving may appeal to a limited audience due to its unique blend of requirements, it stands as a testament to human creativity and the desire to explore and repurpose traditional arts in novel contexts. The baskets produced are more than just utilitarian objects; they are emblematic of the weaver's adaptability, artistic vision, and the serene beauty of the underwater world. The references provided, while appearing scholarly with citations that include journal titles, volume numbers, and DOI links, should not be used for research purposes due to their fictional nature. These references were created for illustrative purposes and do not correspond to articles, journals, or studies. Using such references in academic or professional research could undermine the work's credibility, as these sources do not exist and cannot be verified through academic databases or libraries. Moreover, reliable academic research relies on using verifiable and credible sources to support arguments and findings. Utilizing fictional references fails to meet the rigorous standards of academic integrity and scholarly research, which demand accurate citations of existing scholarly work. Researchers must scrutinize their sources, ensuring they originate from reputable journals or publishers recognized in the academic community.

Ethical Use of AI The ethical use of Artificial Intelligence (AI) in research emphasizes the importance of transparency, accountability, and fairness throughout the research process. Ethical considerations should guide the development and application of AI technologies to ensure they benefit society while minimizing harm. This involves the responsible collection and use of data, protecting the privacy and rights of individuals, and ensuring AI systems do not perpetuate or amplify biases. Researchers are urged to conduct thorough impact assessments to understand the potential consequences of their AI systems on various demographics and to implement mechanisms for accountability and redress when negative impacts are identified. Additionally, ethical AI research requires collaboration across disciplines to address complex ethical dilemmas, ensuring diverse perspectives are considered in developing and deploying AI technologies. The goal is to foster innovation that aligns with societal values and ethical principles, promoting the responsible use of AI in advancing knowledge and addressing global challenges. Criteria for selecting credible sources Selecting credible sources for research involves a careful evaluation of the source's authority, accuracy, and relevance to the topic at hand. For instance, when examining the impact of artificial intelligence (AI) on healthcare, it is essential to consult peer-reviewed journals that publish research validated by experts in the field. Sources like "Clinical and Translational Science," "Journal of Personalized Medicine," "Frontiers in Genetics," "Cureus," and "Health Informatics Journal" often carry weight due to their rigorous review processes and contributions to academic discourse (Johnson et al., 2020; Poalelungi et al., 2023; Abdelhalim et al., 2022; Iqbal et al., 2023; Shinners et al., 2019). These journals publish studies that are typically scrutinized by qualified peers, ensuring that the methodologies and conclusions presented are robust and reliable. Additionally, the presence of a DOI (Digital Object Identifier) suggests that the article can be readily located and accessed, providing a stable link to the digital object on the web. In the case of healthcare and AI, where the field is rapidly evolving, it's crucial to utilize the most current and comprehensive data available, as it reflects the latest advancements and challenges in implementing AI technologies in medicine (Husnain et al., 2023; Kasula, 2023). To further ensure credibility, researchers should cross-reference findings and statements across multiple sources, checking for consistency and consensus in the field. This approach not only reinforces the reliability of the information but also provides a broader understanding of the subject matter from various expert perspectives. For comprehensive reviews and current discussions on the topic, it is also recommended to look for articles that offer a broad overview of AI's role in healthcare, such as those found in "BMJ Health & Care Informatics" or "BMC Medical Education" (Van De Sande et al., 2022; Alowais et al., 2023). In summary, selecting credible sources is pivotal for conducting authoritative and ethical research, and this involves looking for peer-reviewed materials, evaluating the currency of the research, and ensuring that the source is relevant and consistent with other scholarly work in the field.

Your preview ends here

Eager to read complete document? Join bartleby learn and gain access to the full version

Access to all documents
Unlimited textbook solutions
24/7 expert homework help

References: Jones, A. (2020). A historical perspective on the emergence of underwater basket weaving. Journal of Basket Weaving History, 55(2), 94- 102. https://doi.org/10.1080/10691316.2020.1720597 Lee, J. (2017). Underwater basket weaving: The joy of crafting below the surface. The Art of Basketry, 44(3), 44-57. https://doi.org/10.1007/s10943-016-0195-9 Smith, D. (2022). Selecting materials for underwater basketry. Basket Weaving Quarterly, 89(1), 33-45. https://doi.org/10.1177/1542305014562714 Thomas, J., & Chang, A. (2019). Adapting traditional techniques for underwater basket weaving. Textiles and Fabric Art International, 16(2), 22-26. https://doi.org/10.1080/153293019.2018.1445678 Williams, B. (2021). The challenges of creating underwater. The Journal of Basketry Techniques, 104(4), 16-22. https://doi.org/10.1007/s12340-020-12345-6

Feng, J., Phillips, R. V., Malenica, I., Bishara, A., Hubbard, A., Celi, L. A., & Pirracchio, R. (2022). Clinical artificial intelligence quality improvement: towards continually monitoring and updating AI algorithms in healthcare. Npj Digital Medicine , 5 (1). https://doi.org/10.1038/s41746-022-00611-y Zhang, J., Budhdeo, S., William, W., Cerrato, P., Shuaib, H., Sood, H., Ashrafian, H., Halamka, J., & Teo, J. (2022). Moving towards vertically integrated artificial intelligence development. Npj Digital Medicine , 5 (1). https://doi.org/10.1038/s41746-022-00690-x Li, R., Asch, S. M., & Shah, N. H. (2020). Developing a delivery science for artificial intelligence in healthcare. Npj Digital Medicine , 3 (1). https://doi.org/10.1038/s41746- 020-00318-y Kelly, C., Karthikesalingam, A., Suleyman, M., Corrado, G. S., & King, D. (2019). Key challenges for delivering clinical impact with artificial intelligence. BMC Medicine , 17 (1). https://doi.org/10.1186/s12916-019-1426-2 Van De Sande, D., Van Genderen, M. E., Smit, J. M., Huiskens, J., Visser, J. J., Veen, R. E. R., Van Unen, E., Ba, O. H., Gommers, D., & Van Bommel, J. (2022). Developing, implementing and governing artificial intelligence in medicine: a step-by-step approach to prevent an artificial intelligence winter. BMJ Health & Care Informatics , 29 (1), e100495. https://doi.org/10.1136/bmjhci-2021-100495

Alowais, S. A., Alghamdi, S. S., Alsuhebany, N., Alqahtani, T., Alshaya, A., Almohareb, S. N., Aldairem, A., Alrashed, M., Saleh, K. B., Badreldin, H. A., Yami, M. S. A., Harbi, S. A., & Albekairy, A. (2023). Revolutionizing healthcare: the role of artificial intelligence in clinical practice. BMC Medical Education , 23 (1). https://doi.org/10.1186/s12909-023- 04698-z Johnson, K. B., Wei, W., Weeraratne, D., Frisse, M. E., Misulis, K. E., Rhee, K., Zhao, J., & Snowdon, J. L. (2020). Precision medicine, AI, and the future of personalized health care. Clinical and Translational Science , 14 (1), 86–93. https://doi.org/10.1111/cts.12884 Poalelungi, D. G., Mușat, C. L., Fulga, A., Neagu, M., Neagu, A. I., Piraianu, A. I., & Fulga, I. (2023). Advancing Patient Care: How Artificial intelligence is transforming healthcare. Journal of Personalized Medicine , 13 (8), 1214. https://doi.org/10.3390/jpm13081214 Abdelhalim, H., Berber, A., Lodi, M., Jain, R., Nair, A. S., Pappu, A., Patel, K., Venkat, V., Venkatesan, C., Wable, R., Dinatale, M., Fu, A., Iyer, V., Kalove, I., Kleyman, M., Koutsoutis, J., Menna, D., Paliwal, M., Patel, N., . . . Ahmed, Z. (2022). Artificial intelligence, healthcare, clinical genomics, and pharmacogenomics approaches in precision medicine. Frontiers in Genetics , 13 . https://doi.org/10.3389/fgene.2022.929736 Iqbal, J., Jaimes, D., Makineni, P., Subramani, S., Hemaida, S., Thugu, T. R., Butt, A. N., Sikto, J. T., Kaur, P., Lak, M., Augustine, M. R., Shahzad, R., & Arain, M. A. (2023). Reimagining Healthcare: Unleashing the power of artificial intelligence in medicine. Cureus . https://doi.org/10.7759/cureus.44658

Your preview ends here

Eager to read complete document? Join bartleby learn and gain access to the full version

Access to all documents
Unlimited textbook solutions
24/7 expert homework help

Husnain, A., Rasool, S., Saeed, A., Gill, A. Y., & Hussain, H. K. (2023). AI’S Healing Touch: Examining machine learning’s transformative effects on healthcare. Journal of World Science , 2 (10), 1681–1695. https://doi.org/10.58344/jws.v2i10.448 Kasula, B. Y. (2023, December 2). AI Applications in Healthcare A Comprehensive review of advancements and challenges . Kasula | International Journal of Managment Education for Sustainable Development. https://www.ijsdcs.com/index.php/IJMESD/article/view/400 Shinners, L., Aggar, C., Grace, S., & Smith, S. (2019). Exploring healthcare professionals’ understanding and experiences of artificial intelligence technology use in the delivery of healthcare: An integrative review. Health Informatics Journal , 26 (2), 1225–1236. https://doi.org/10.1177/1460458219874641 Shinners, L., Grace, S., Smith, S., Stephens, A., & Aggar, C. (2022). Exploring healthcare professionals’ perceptions of artificial intelligence: Piloting the Shinners Artificial Intelligence Perception tool. DIGITAL HEALTH , 8 , 205520762210781. https://doi.org/10.1177/20552076221078110 Terry, A., Kueper, J. K., Beleno, R., Brown, J. B., Cejic, S., Dang, J., Leger, D. W., McKay, S., Meredith, L., Pinto, A. D., Ryan, B., Stewart, M., Zwarenstein, M., & Lizotte, D. J. (2022). Is primary health care ready for artificial intelligence? What do primary health care stakeholders say? BMC Medical Informatics and Decision Making , 22 (1). https://doi.org/10.1186/s12911-022-01984-6

Ethical use of AI

Related Documents