What will be the problem you plan to solve with AI?
Santiago:
The problem I would like to solve with AI is something that it is not really talked about, yet it can have a significant influence in the future: Social dynamics. This refers to the prediction of the different scenarios that the human society can lead to, employing AI models that use huge amounts of data (in this case, socioeconomical data such as demographics, economic statistics, etcetera).
In the past, this was considered pure science fiction, depicted in literature as in the Foundation Trilogy, of Isaac Asimov. However, the exponential advance of information systems and data processing is breaking the limitations of the past and will probably allow this discipline to flourish.
This would for example, know when the next economic crisis would happen, knowing what the chance of wars to happen, predicting resource shortages in the future; This implies knowing which events would or could happen in the near or distant future. In this way, we could have a broad knowledge on our own future, making wiser large-scale socioeconomical decisions, and allowing humanity to develop in a stable environment, avoiding crisis and catastrophes.
Nway:
From my perspectives, AI’s role in education is multifaceted and can significantly enhance both teach and learning experiences. In the educational field, I plan to utilize AI to tackle several pressing issues. My primary focus will be on personalizing learning experiences to accommodate individual student needs and learning styles. By leveraging AI’s data analysis capabilities, I aim to create adaptive learning paths that help students learn more effectively at their own pace.
Additionally, I intend to use AI to reduce the administrative burden on educators. Tasks such as grading and attendance can be automated, allowing teachers to dedicate more time to student interaction and personalized teaching.
I also see AI as a tool to democratize education, providing access to quality learning resources regardless of location. This technology can bridge gaps, making global classrooms a reality and fostering a more inclusive learning environment for students with diverse needs.
Ultimately, my goal is to harness AI to make education more engaging, inclusive, and tailored to prepare students for the future, equipping them with essential skills like critical thinking and problem-solving.
Sara:
When it comes to me, I would like to implement AI into cybersecurity to automate Threat Intelligence in a system. Here are some ways where AI can come in handy:
Detecting vulnerabilities: AI can be used to analyse system configurations and identify potential weaknesses. This can be done through automated penetration testing, where AI algorithms simulate cyber-attacks to identify vulnerabilities in the system. AI can also be used to monitor network traffic and identify unusual patterns or behaviours that may indicate a vulnerability.
Scanning malwares: AI can be used to detect and analyse malware by identifying patterns and behaviours that are indicative of malicious activity. This can be done through machine learning algorithms that are trained to recognize malware signatures, behaviours, and patterns. AI can also be used to detect zero-day attacks, which are attacks that exploit vulnerabilities that are not yet known.
Generating secure user accounts and passwords: AI can be used to generate secure user accounts and passwords by analysing user behaviour and preferences. This can be done through machine learning algorithms that analyse user behaviours, such as typing patterns and browsing history, to generate passwords that are both secure and memorable. AI can also be used to monitor user accounts and detect suspicious activity, such as multiple failed logins attempts or unusual login locations.
Creating honeypots: AI can be used to create honeypots, which are decoy systems that are designed to attract and detect cyber-attacks. Honeypots can be used to detect and analyse advanced persistent threats (APTs), which are sophisticated cyber-attacks that are designed to evade detection. AI can be used to analyse honeypot data and identify patterns and behaviours that are indicative of APTs.
Honoka:
In my opinion, AI has the potential to effectively address various challenges across industries. Specifically in retail, one critical issue that AI can tackle is accurately predicting consumer demand through machine learning and predictive analytics. By analysing past and current sales data, AI can provide more precise forecasts of future demand, which is crucial for inventory planning. This can help merchants prevent lost revenue from product shortages or resource waste from overstocking. With AI's ability to streamline operations, automate repetitive tasks, and deliver personalized shopping experiences through deep learning algorithms, it has the potential to improve profitability and enhance consumer satisfaction in the retail industry.
Ellie:
Artificial Intelligence (AI) has brought great number of benefits to a handful of industries, though one industry that I wish AI can be focused on more is in the healthcare industry. At the moment, taking advantage of AI in the healthcare industry remains underexplored despite its capability of addressing a variety of difficulties. One concurrent problem that AI can potentially solve in the healthcare industry is to be able to diagnose and treat diseases.
AI algorithms can analyse from vast amounts of data from a patient’s history to predict health risks and even create preventive personalized measures for the individual. By identifying the patterns in health data, AI can create proper lifestyle choices for the patient to take, detect any early signs of health issues, and even prevent potential diseases. Other than that, AI can boost the healthcare industry to reach certain goals, such as, equalizing healthcare for all individuals, reducing mortality rates, eliminating human errors, lowering medical costs, and much more (Lee & Yoon, 2021).
However, one reason why AI is not implemented enough in the healthcare industry is the fear of machine error and concerns of data privacy especially when healthcare data is highly sensitive. Despite the challenges and doubts from numerous sources regarding implementing AI in healthcare, AI has the potential to provide solutions to problems faced by the healthcare industry around the world (Lena Petersson, 2022). By handling challenges and maximizing on the benefits of AI, the healthcare industry could make significant advancements in providing effective, cost-effective, and high-quality care to patients (Saeed, Bin Saeed, & AlAhmri, 2023).
References:
Cliodynamics: History as Science. (2023, May 17). Peter Turchin. https://peterturchin.com/cliodynamics-history-as-science/
Artificial intelligence in education. (2023, November 29). UNESCO.
https://www.unesco.org/en/digital-education/artificial-intelligence
Matlali, L. (2023, June 5). Cybersecurity and AI: The challenges and opportunities. World Economic Forum. https://www.weforum.org/agenda/2023/06/cybersecurity-and-ai-challenges-opportunities/
Lee, D. H., & Yoon, S. N. (2021). Application of Artificial Intelligence-Based Technologies in the Healthcare Industry: Opportunities and Challenges. International Journal of Environmental Research and Public Health, 18(1), 271. doi:10.3390/ijerph18010271
Lena Petersson, I. L. (2022). Challenges to implementing artificial intelligence in healthcare: a qualitative interview study with healthcare leaders in Sweden. BMC Health Services Research, 22(1). doi:10.1186/s12913-022-08215-8
Saeed, A., Bin Saeed, A., & AlAhmri, F. A. (2023). Saudi Arabia Health Systems: Challenging and Future Transformations With Artificial Intelligence. Cureus, 15(4). doi:10.7759/cureus.37826
Santiago:
The problem I would like to solve with AI is something that it is not really talked about, yet it can have a significant influence in the future: Social dynamics. This refers to the prediction of the different scenarios that the human society can lead to, employing AI models that use huge amounts of data (in this case, socioeconomical data such as demographics, economic statistics, etcetera).
In the past, this was considered pure science fiction, depicted in literature as in the Foundation Trilogy, of Isaac Asimov. However, the exponential advance of information systems and data processing is breaking the limitations of the past and will probably allow this discipline to flourish.
This would for example, know when the next economic crisis would happen, knowing what the chance of wars to happen, predicting resource shortages in the future; This implies knowing which events would or could happen in the near or distant future. In this way, we could have a broad knowledge on our own future, making wiser large-scale socioeconomical decisions, and allowing humanity to develop in a stable environment, avoiding crisis and catastrophes.
Nway:
From my perspectives, AI’s role in education is multifaceted and can significantly enhance both teach and learning experiences. In the educational field, I plan to utilize AI to tackle several pressing issues. My primary focus will be on personalizing learning experiences to accommodate individual student needs and learning styles. By leveraging AI’s data analysis capabilities, I aim to create adaptive learning paths that help students learn more effectively at their own pace.
Additionally, I intend to use AI to reduce the administrative burden on educators. Tasks such as grading and attendance can be automated, allowing teachers to dedicate more time to student interaction and personalized teaching.
I also see AI as a tool to democratize education, providing access to quality learning resources regardless of location. This technology can bridge gaps, making global classrooms a reality and fostering a more inclusive learning environment for students with diverse needs.
Ultimately, my goal is to harness AI to make education more engaging, inclusive, and tailored to prepare students for the future, equipping them with essential skills like critical thinking and problem-solving.
Sara:
When it comes to me, I would like to implement AI into cybersecurity to automate Threat Intelligence in a system. Here are some ways where AI can come in handy:
Detecting vulnerabilities: AI can be used to analyse system configurations and identify potential weaknesses. This can be done through automated penetration testing, where AI algorithms simulate cyber-attacks to identify vulnerabilities in the system. AI can also be used to monitor network traffic and identify unusual patterns or behaviours that may indicate a vulnerability.
Scanning malwares: AI can be used to detect and analyse malware by identifying patterns and behaviours that are indicative of malicious activity. This can be done through machine learning algorithms that are trained to recognize malware signatures, behaviours, and patterns. AI can also be used to detect zero-day attacks, which are attacks that exploit vulnerabilities that are not yet known.
Generating secure user accounts and passwords: AI can be used to generate secure user accounts and passwords by analysing user behaviour and preferences. This can be done through machine learning algorithms that analyse user behaviours, such as typing patterns and browsing history, to generate passwords that are both secure and memorable. AI can also be used to monitor user accounts and detect suspicious activity, such as multiple failed logins attempts or unusual login locations.
Creating honeypots: AI can be used to create honeypots, which are decoy systems that are designed to attract and detect cyber-attacks. Honeypots can be used to detect and analyse advanced persistent threats (APTs), which are sophisticated cyber-attacks that are designed to evade detection. AI can be used to analyse honeypot data and identify patterns and behaviours that are indicative of APTs.
Honoka:
In my opinion, AI has the potential to effectively address various challenges across industries. Specifically in retail, one critical issue that AI can tackle is accurately predicting consumer demand through machine learning and predictive analytics. By analysing past and current sales data, AI can provide more precise forecasts of future demand, which is crucial for inventory planning. This can help merchants prevent lost revenue from product shortages or resource waste from overstocking. With AI's ability to streamline operations, automate repetitive tasks, and deliver personalized shopping experiences through deep learning algorithms, it has the potential to improve profitability and enhance consumer satisfaction in the retail industry.
Ellie:
Artificial Intelligence (AI) has brought great number of benefits to a handful of industries, though one industry that I wish AI can be focused on more is in the healthcare industry. At the moment, taking advantage of AI in the healthcare industry remains underexplored despite its capability of addressing a variety of difficulties. One concurrent problem that AI can potentially solve in the healthcare industry is to be able to diagnose and treat diseases.
AI algorithms can analyse from vast amounts of data from a patient’s history to predict health risks and even create preventive personalized measures for the individual. By identifying the patterns in health data, AI can create proper lifestyle choices for the patient to take, detect any early signs of health issues, and even prevent potential diseases. Other than that, AI can boost the healthcare industry to reach certain goals, such as, equalizing healthcare for all individuals, reducing mortality rates, eliminating human errors, lowering medical costs, and much more (Lee & Yoon, 2021).
However, one reason why AI is not implemented enough in the healthcare industry is the fear of machine error and concerns of data privacy especially when healthcare data is highly sensitive. Despite the challenges and doubts from numerous sources regarding implementing AI in healthcare, AI has the potential to provide solutions to problems faced by the healthcare industry around the world (Lena Petersson, 2022). By handling challenges and maximizing on the benefits of AI, the healthcare industry could make significant advancements in providing effective, cost-effective, and high-quality care to patients (Saeed, Bin Saeed, & AlAhmri, 2023).
References:
Cliodynamics: History as Science. (2023, May 17). Peter Turchin. https://peterturchin.com/cliodynamics-history-as-science/
Artificial intelligence in education. (2023, November 29). UNESCO.
https://www.unesco.org/en/digital-education/artificial-intelligence
Matlali, L. (2023, June 5). Cybersecurity and AI: The challenges and opportunities. World Economic Forum. https://www.weforum.org/agenda/2023/06/cybersecurity-and-ai-challenges-opportunities/
Lee, D. H., & Yoon, S. N. (2021). Application of Artificial Intelligence-Based Technologies in the Healthcare Industry: Opportunities and Challenges. International Journal of Environmental Research and Public Health, 18(1), 271. doi:10.3390/ijerph18010271
Lena Petersson, I. L. (2022). Challenges to implementing artificial intelligence in healthcare: a qualitative interview study with healthcare leaders in Sweden. BMC Health Services Research, 22(1). doi:10.1186/s12913-022-08215-8
Saeed, A., Bin Saeed, A., & AlAhmri, F. A. (2023). Saudi Arabia Health Systems: Challenging and Future Transformations With Artificial Intelligence. Cureus, 15(4). doi:10.7759/cureus.37826
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