Introduction
The statement “AI is helping society” invites a critical examination of artificial intelligence’s role in modern life. As an English undergraduate exploring themes of technology and society in contemporary discourse, I agree with this assertion. This essay argues that AI provides substantial benefits, particularly in healthcare, education, and environmental sustainability, despite some limitations. Drawing on academic sources, I will justify this position with examples, demonstrating AI’s positive societal impact while acknowledging counterarguments for a balanced view. The discussion highlights how AI enhances human capabilities, fostering progress in key areas.
AI’s Contributions to Healthcare
Artificial intelligence has revolutionised healthcare by improving diagnostics and treatment efficiency, arguably saving lives and reducing costs. For instance, machine learning algorithms can analyse medical images with high accuracy, often surpassing human experts in detecting conditions like cancer. A notable example is Google’s DeepMind, which developed an AI system for identifying breast cancer in mammograms, achieving results comparable to radiologists (McKinney et al., 2020). This not only speeds up diagnoses but also addresses shortages in medical professionals, particularly in underserved regions.
Furthermore, AI aids in drug discovery, accelerating processes that traditionally take years. During the COVID-19 pandemic, AI models predicted protein structures, aiding vaccine development. As Topol (2019) explains, these advancements represent a “deep medicine” era where AI integrates data for personalised care. However, critics argue AI could exacerbate inequalities if access is limited, yet its overall help outweighs such concerns, as it democratises high-quality healthcare through scalable tools.
AI’s Role in Education
In education, AI enhances learning experiences by personalising instruction and expanding access, which is particularly relevant in diverse societal contexts. Tools like adaptive learning platforms adjust content to individual student needs, improving outcomes for struggling learners. For example, Duolingo uses AI to tailor language lessons, resulting in faster proficiency gains compared to traditional methods (Settles and Meeder, 2016). This is especially beneficial in English studies, where AI can analyse writing styles and provide feedback, fostering critical thinking skills.
Moreover, AI-driven virtual tutors offer support outside classrooms, bridging gaps in under-resourced areas. Research by Luckin et al. (2016) emphasises how AI promotes inclusive education, enabling lifelong learning. Indeed, while some fear job losses for educators, AI typically augments rather than replaces human roles, allowing teachers to focus on mentorship. Therefore, AI’s integration supports societal advancement by empowering individuals through knowledge.
AI’s Impact on Environmental Sustainability
AI also helps society by addressing environmental challenges, optimising resource use and combating climate change. Predictive models forecast natural disasters, enabling timely evacuations and resource allocation. For instance, AI analyses satellite data to monitor deforestation, aiding conservation efforts in regions like the Amazon (Hansen et al., 2013). This proactive approach mitigates societal risks from environmental degradation.
Additionally, AI optimises energy consumption in smart grids, reducing waste and promoting renewable sources. Rolnick et al. (2019) argue that AI’s potential in climate action is vast, from enhancing agricultural efficiency to modelling carbon footprints. Generally, these applications demonstrate AI’s role in sustainable development, countering narratives of technological harm by providing evidence-based solutions. Typically, such innovations foster a greener society, aligning with global goals like the UN Sustainable Development Agenda.
Conclusion
In summary, I agree that AI is helping society, as evidenced by its transformative effects in healthcare, education, and environmental sustainability. Examples like diagnostic tools and adaptive learning platforms illustrate tangible benefits, supported by scholarly analysis (Topol, 2019; Luckin et al., 2016). While limitations exist, such as ethical concerns, AI’s positive contributions arguably prevail, implying a need for responsible implementation to maximise societal gains. This perspective, from an English studies viewpoint, underscores technology’s narrative in shaping human progress, encouraging further discourse on its evolving role.
References
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- Luckin, R., Holmes, W., Griffiths, M. and Forcier, L.B. (2016) Intelligence unleashed: An argument for AI in education. Pearson.
- McKinney, S.M., Sieniek, M., Godbole, V., Godwin, J., Antropova, N., Ashrafian, H., Back, T., Chesus, M., Corrado, G.S., Darzi, A., Etemadi, M., Garcia, F., Gilbert, F.J., Halling-Brown, M., Hassabis, D., Jansen, S., Karthikesalingam, A., Kelly, C.J., King, D., Ledsam, J.R., Melnick, D., Mostofi, H., Peng, L., Reicher, J.J., Romera-Paredes, B., Sidebottom, R., Suleyman, M., Tse, D., Young, K.C., De Fauw, J. and Shetty, S. (2020) International evaluation of an AI system for breast cancer screening. Nature, 577(7788), pp.89-94.
- Rolnick, D., Donti, P.L., Kaack, L.H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A.S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., Luccioni, A., Sherwin, E., Mukkavilli, S.K., Kording, K.P., Gomes, C.P., Ng, A.Y., Hassabis, D., Platt, J.C., Creutzig, F., Chayes, J. and Bengio, Y. (2019) Tackling climate change with machine learning. arXiv preprint arXiv:1906.05433.
- Settles, B. and Meeder, B. (2016) A trainable spaced repetition model for language learning. Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, pp.1848-1858.
- Topol, E.J. (2019) Deep medicine: How artificial intelligence can make healthcare human again. Basic Books.
