What will be the problem you plan to solve with AI?

Education

One of the significant problems that can be found in the education sector is the traditional education that usually follows a class of students' approaches rather than one-to-one lessons, therefore this approach does not cater to the individual needs of the students. Each student has their own learning pace and requirements, and it is impossible to fulfil all the requirements in one class. 

Firstly, AI-powered platforms can analyze students’ data such as their performance and learning pace which can be used to provide a personalized learning pathway for each student individually based on their specific needs and learning behavior (AI, 2023). These platforms can also provide recommendations of resources, videos, and other learning materials that will help the specific needs of each student. 

Students can also use AI-driven tutoring systems to instantly resolve any questions. For example, using a virtual chatbot to respond to each student’s questions instantly without having to wait for their teachers to respond (Neendoor, 2024). These systems can adapt to the student’s progress and provide targeted explanations, solutions, and feedback to help the students to understand the areas of difficulty in the specific subject.

Transportation

Injuries and fatalities from road accidents remain a critical issue. The World Health Organization identifies road crashes as the leading cause of death for individuals aged five to 29 (Chia, 2024). In Malaysia, traffic accidents rose significantly every year, most of the accident is trigger by human behavior such as drunk drinking, speeding, using mobile phone while driving, and fatigue (Kurnia, 2024). However, with today's technology, I believe AI presents a viable solution to address this issue effectively. Autonomous vehicles (AVs), also known as self-driving cars, represent one of the most exciting and transformative applications of artificial intelligence (AI) and related technologies. These vehicles use a combination of sensors, cameras, radar, lidar, and sophisticated AI algorithms to navigate and operate without human intervention (Cole, 2024). 

With the help of AI, drivers no longer need to worry about their condition while driving. For instance, if someone is drunk, they can summon their car and let it drive them home autonomously. Even during the drive, drivers can watch movies or use their phones without worrying about traffic. Overall, I believe AI can be implemented to effectively solve the problem of traffic accidents. By leveraging AI technology, we can enhance road safety, reduce human error, and enable autonomous driving, making it possible for individuals to travel without constantly focusing on the road.

Public Safety

One of the primary duties of governments and law enforcement organizations is to ensure public safety. Traditional methods of managing disasters and preventing crime can have certain drawbacks, though. We now have the chance to improve public safety protocols by utilizing data, algorithms, and machine learning thanks to the development of artificial intelligence. (Turing, 2024)

In military and public safety contexts alike, disruptive technologies are heralded as "force multipliers," significantly enhancing the chances of success. Particularly in densely populated metropolitan areas where multiple overworked teams operate within overlapping jurisdictions, the demand for such advancements is pressing. These departments often contend with understaffing and an overwhelming influx of data.

In scenarios such as cross-jurisdictional criminal activities or emergencies like hazardous material incidents, AI can swiftly analyze data, identify patterns, and disseminate insights to all relevant agencies in real-time. By efficiently processing vast amounts of information, embedded AI technology lightens the load for dispatchers and responders, freeing them to focus on taking swift and effective action. (Kalyn Sims, 2023)

In conclusion, by analyzing data and identifying trends to stop crime and respond to emergencies, artificial intelligence (AI) is a potent instrument for enhancing public safety (Chris Chiancone, 2023).

Healthcare

Artificial intelligence (AI) is an indispensable tool in healthcare, providing innovative solutions to complex problems. This is evident in diagnostic processes where AI algorithms have the capability to analyze medical imaging rapidly and with greater accuracy than humans (Sermesant et al., 2021). For example, AI-powered systems in radiology can detect anomalies such as tumors and fractures from X-rays and MRIs, leading to earlier and more precise diagnoses (Mouridsen & Borra, 2020).

Beyond diagnostics, the potential of AI extends to personalized medicine, where it can analyze vast amounts of genetic data to tailor treatments for individual patients. This approach enhances treatment efficacy and minimizes adverse side effects by adapting to each patient’s unique genetic profile. (Miller & Brown, 2017)

AI also plays a crucial role in predictive healthcare. By continuously monitoring vital signs, AI systems can predict and alert healthcare providers about potential medical events, such as strokes or heart attacks, before they occur. This capability allows for preemptive medical intervention, potentially saving lives. (Coppola et al., 2021)

Finally, AI simplifies administrative tasks in healthcare settings by automating routine duties such as scheduling and billing. This automation enables healthcare professionals to devote more time to patient care, thereby improving service efficiency and accessibility. Through these multifaceted applications, AI is poised to transform healthcare delivery, making it more effective and patient-centric. 

Environment

One of the critical challenges of our time is monitoring and mitigating the impacts of climate change. Traditional methods of environmental monitoring rely heavily on manual data collection and analysis, which can be time-consuming, costly, and prone to errors. Artificial intelligence (AI) presents a powerful solution to enhance environmental monitoring and combat climate change. AI can automate data collection from various sources such as satellites, drones, sensors, and IoT devices, and then process and analyze this vast amount of data in real-time. This provides accurate and timely insights into environmental changes, improving the accuracy of weather forecasting, detecting deforestation, and tracking wildlife populations (Rolnick et al., 2019).

In urban environments, AI can optimize energy usage in buildings, reduce emissions, and improve waste management. Smart grids powered by AI can balance energy supply and demand more efficiently, integrating renewable energy sources and reducing reliance on fossil fuels. Additionally, AI-driven systems can provide farmers with real-time recommendations on irrigation, fertilization, and pest control, leading to more sustainable farming practices and reduced environmental impact. By automating data collection, improving predictive capabilities, and optimizing resource usage, AI can play a pivotal role in protecting our planet and ensuring a sustainable future (Vincent & Henson, 2021).

Risk Assessment

Risk assessment involves the systematic identification of hazards and their associated risks within a workplace (British Safety Council, 2023). AI tools could be used to augment this process, allowing risk assessments to be completed within a much shorter amount of time, as well as more accurately.

  

AI systems can process large volumes of data with speed and accuracy vastly above their human counterparts. This greatly improves their capability to precisely diagnose risks and opportunities. New means of data analysis like machine learning and data mining can be used in juxtaposition with traditional methods to predict likely risks.  (Yazdi et al., 2024).

These systems excel in processing unstructured data and identifying complex patterns which may signify certain hazards that an organization might face. Additionally, machine learning could be applied to group unstructured data into a more meaningful format, further improving the efficiency of existing methods while saving time and critical resources that can be better applied elsewhere (Team, 2023).

References

1. Ai, T. (2023, June 5). How AI is personalizing education for every student. eLearning Industry. https://elearningindustry.com/how-ai-is-personalizing-education-for-every-student 

2. Neendoor, S. (2024, April 22). How AI is personalizing education for every student? - Hurix Digital. Digital Engineering & Technology | Elearning Solutions | Digital Content Solutions. https://www.hurix.com/how-ai-is-personalizing-education-for-every-student/ 

3. Chia, C, H. (2024). Reducing traffic accidents and deaths. The Sun. https://thesun.my/opinion_news/reducing-traffic-accidents-and-deaths-JF12171338

4. Kurnia. (2024). The 10 Most Common Causes of Accidents in Malaysia & How to Prevent Them. Kurnia. https://www.kurnia.com/blog/road-accidents-causes 

5. Cole, R. (2024). Autonomous vehicle. Britannica. https://www.britannica.com/technology/autonomous-vehicle 

6. Turing. (2024). Artificial Intelligence in Public Safety. https://medium.com/@a.turing/artificial-intelligence-in-public-safety-88037e40d5a1

7. Kalyn, S. (2023). How Assistive AI Can Be A Force Multiplier In Public Safety. https://www.forbes.com/sites/forbestechcouncil/2023/06/06/can-assistive-ai-can-be-a-force-multiplier-in-public-safety/?sh=381e85134f9c

8. Chiancone, C. (2023). Enhancing Public Safety with AI: A New Dawn for Local Communities. https://www.linkedin.com/pulse/enhancing-public-safety-ai-new-dawn-local-communities-chris-chiancone

9. Coppola, F., Faggioni, L., Gabelloni, M., Vietro, F. D., Mendola, V., Cattabriga, A., Cocozza, M. A., Vara, G., Piccinino, A., Monaco, S. L., Pastore, L. V., Mottola, M., Malavasi, S., Bevilacqua, A., Neri, E., & Golfieri, R. (2021). Human, All Too Human? An All-Around Appraisal of the “Artificial Intelligence Revolution” in Medical Imaging. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.710982 

10. Miller, D., & Brown, E. (2017). Artificial Intelligence in Medical Practice: The Question to the Answer? The American Journal of Medicine, 131 2, 129–133. https://doi.org/10.1016/j.amjmed.2017.10.035 

11. Mouridsen, K., & Borra, R. (2020). Artificial Intelligence in the Analysis of PET Scans of the Human Brain. 105–117. https://doi.org/10.1007/978-3-030-53168-3_5 

12. Sermesant, M., Delingette, H., Cochet, H., Jaïs, P., & Ayache, N. (2021). Applications of artificial intelligence in cardiovascular imaging. Nature Reviews Cardiology, 18, 600–609. https://doi.org/10.1038/s41569-021-00527-2 

13. Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., ... & Bengio, Y. (2019). Tackling Climate Change with Machine Learning. arXiv preprint arXiv:1906.05433.

14. Vincent, J., & Henson, R. (2021). The Role of Artificial Intelligence in Weather Forecasting. AI Magazine, 42(2), 48-57.

15. British Safety Council. (2023). Risk Assessment and Management: a Complete Guide | British Safety Council. British Safety Council. https://www.britsafe.org/training-and-learning/informational-resources/risk-assessments-what-they-are-why-they-re-important-and-how-to-complete-them

16. Team, V. E. G. A. (2023, February 9). AI in Risk Management is Shaping a Safer Tomorrow: Here’s How. Blog.engineering.vanderbilt.edu. https://blog.engineering.vanderbilt.edu/ai-in-risk-management-is-shaping-a-safer-tomorrow-heres-how

17. Yazdi, M., Zarei, E., Adumene, S., & Beheshti, A. (2024). Navigating the Power of Artificial Intelligence in Risk Management: A Comparative Analysis. Safety, 10(2), 42. https://doi.org/10.3390/safety10020042