AI in Practice | Origin: EC133
This is a general discussion forum for the following learning topic:
Introduction to Artificial Intelligence --> AI in Practice
Post what you've learned about this topic and how you intend to apply it. Feel free to post questions and comments too.
This module focused on providing some background and context to AI in industries. In practice, it can look like a lot of things. In education, and to me, it looks like workshops and tutoring sessions; we could guide students on how/when to use. But also in practice, these look like large-scale programs/cases; still very different from the classroom.
This module highlighted how core AI technologies—specifically Natural Language Processing (NLP), computer vision, and recommendation engines—translate theoretical machine learning into operational business and technical tools. A particularly crucial takeaway is the ethical dimension: recognizing that data bias can easily propagate into algorithmic outputs if fairness and transparency are not actively audited.
In practice, I plan to apply these concepts by designing applied classroom projects where students analyze real-world case studies involving automated decision-making. By exploring both functional deployments (such as sentiment analysis and automated systems) and ethical governance frameworks, students will learn not only how to deploy AI tools effectively, but also how to critically detect bias and ensure responsible implementation in professional settings.
The most facinating aspects so far, are the behind the scenes and everyday aspect of AI. As an instructor, I always pay attention to ethical considerations and I will defintely guide students on how to utilize AI effectively with strict ethical guidelines.
AI can be used in many ways in practice, starting from using it in autonomous driving to selecting the program you want to watch on Netflix, etc., based on customer satisfaction. Similarly, using ChatGPT to respond to my verbal and written responses. I would like to use AI in education, where I can use AI to give me ideas on how to improve my syllabus, reports, and curriculum overall. Also, providing me with input to polish my ideas, where AI can help refine my language and make my case more convincing.
AI in practice means advancing personalized feedback and engagement. It can help with brainstorming activities.
I learned that AI is already used in many areas, including facial recognition, self-driving vehicles, recommendation systems, robotics, and medical imaging. I also learned that AI can create problems involving privacy, bias, and fairness. I plan to use AI as a helpful tool while checking its results carefully and using it responsibly.
This module helped me understand that AI is much more than a futuristic concept; it is already integrated into many everyday tools and professional settings. I learned how AI can improve efficiency, automate routine tasks, and support better decision-making while still requiring human oversight and ethical use. I intend to apply what I learned by using AI to enhance lesson planning, streamline administrative tasks, and create more engaging learning experiences while ensuring that accuracy, critical thinking, and responsible use remain priorities.
This module helped me uniderstand that AI muchmore than automation, it combines technologies and recommendations to support better decisions
Repetitive phrases/concepts that seemed to form a pattern was infrastructure cost, training of instructors, and measured moves to ensure ethics in several areas. Specifically, using ML in my classroom for immediate feedback on activities that have been thoughtfully curated for reaching meaningful standards embedding AI inspired lessons.
AI is a very complex tool. What amazed me is; we can still be non bias when one programs AI. For it is suggested that one includes all demographics when inputting information. How do I find myself using this for my Students? I am able to present the learned material in many different ways for my students.
AI is one of the fastest growing uses of technology. I already use AI to help me in my teaching by having AI help with everyday tasks. It is good to have a understanding the of the basics of AI and several of the ways that AI can be used in everyday life. Explaining this to students is a great way to show students the useful ways AI is helpful. Students also have to learn how bias and ethics can come into play using AI.
I think AI is helpful get more organized and streamline more study guides and lecture for my students.
RPA is something I want to learn more about and see how it can drive what I work on further.
I intend to apply this knowledge to streamline daily workflows by leveraging generative AI tools to accelerate content creation, ideation and brainstorming.
La IA para la educacion es genial se puede citar libros, rapidamente, hacer resumenes sobre lo mas interesante y trnsmitir rapidamente el conocimiento, igualmente preparar casos de trabajos en segundos
I intend to apply this knowledge to streamline daily workflows by using generative tools to accelerate content creation and brainstorming, while using advanced algorithms to optimize image and visual asset quality for a more premium finish. Ultimately, this allows me to automate repetitive tasks and dedicate more energy to high-level strategy and creative execution.
AI Natural Language Processing with the use of Chatbots can detect through sentiment analysis positive, negative, and neutral tones. Computer Vision can detect object and assist in Security ID, Self Driving (UAV)s, and collaborative robots used in manufacturing. Ethics and Bias are concerns with programming algorithms with preconceived perspective and perceptions that could lead to stereotypes of all kinds. AI will help with figuring out or detecting its own bias with counter programming. AI Seems intuitive and ideally common-sense approach to greater good.
I am a big fan of AI and know I will use it as a partner in the development of instructional components
As someone who teaches computer science and robotics, I view algorithmic bias not as a minor technical glitch, but as a critical ethical issue that future engineers must learn to identify and address. Students need to understand that every dataset carries the values of the people who created it. When we build robots or AI systems, we are not just writing code — we are encoding decisions that can affect real human lives.
