Intelligent Agents - Unit 9: Introduction to Adaptive Algorithms

Overview

As per the course website, "This week’s lecturecast introduces adaptive algorithms, such as Artificial Neural Networks (ANNs) and Deep Learning. These algorithms are at the leading edge of AI research and are responsible for pushing the boundaries of today’s technologies This week will focus on how they work, and how they are being deployed to great effect."

My Reflection

Overall Reflection

This week was a slow one. The unit covered some concepts of ANNs and Deep Learning, and the lecturecast touched on Convolutional Neural Networks (CNNs) as well, which were all already covered in Machine Learning Module. There were no worthy readings as well, as one of them was an article from 2015 on Deep Learning and image recognition, and a video by Andrew Ng on Deep Learning with a temporarily broken link at the time of me trying to access it, in addition to video on YouTube that has been set to be private.

I also wonder what this unit has to do with Intelligent Agents, the topic of the module. Maybe the few upcoming units will answer this question. Probably they won't. We'll see.

Artefacts

Collaborative Discussion 3

This week, we started a new collaborative discussion with the following prompt, "The advent of new technologies supported by Deep Learning models mean that it is now possible to generate ‘new’ content, for example, Dall-E AI to generate images or ChatGPT to create prose. Do you think that these new technologies offer any ethical issues that should be considered, and if not, why not?" I chose to focus on the aspect of GenAI and human creativity. Below is my initial post for the discussion.

My Initial Post

Deep learning models that are capable of generating new content, also known as generative artificial intelligence (GenAI), have been posing ethical questions on all fronts since their significant advancement and popularity over the last four years. Whether generating text or multimedia, GenAI has been raising questions on how to handle a variety of challenges, from misinformation and deepfakes to biases and privacy, and all the way to copyright issues and authenticity (Al-kfairy et al. , 2024).

For me, all of these ethical fronts are concerning, but the one that I’m most interested in is regarding creativity. In addition to the questions above, GenAI has been posing questions regarding what human creativity means in this new era, since the advancing models can generate endless new content - whether prose, literature, paintings, music, etc. - easily in all sorts of styles, artistic schools, ideas, and tones (Sternberg, 2024). Under the light of such artificial capabilities, how can we understand human creativity?

After computers took over the advantage on the front of computational capabilities since the 1970s, creativity has long been considered a capability very specific to human beings. Now, this belief is threatened with founded suspicions. Some researchers argue that ‘artificial creativity’ has its limitations - or rather, in better terms, it is inherently different than humans’. For example, GenAI has been found to be able to come up with incremental discoveries but not groundbreaking new ideas like humans (Ding and Li, 2025). Other researchers do not see the topic from the perspective of a zero-sum game and focus more on human-machine collaboration frameworks and examples (Cai and Gao, 2025).

My interest slides more to the latter scope, as I look forward to pursuing further research in the future to have better approaches to understand creativity in the first place, especially regarding arts and literature, and how we can keep reaping the benefits of human creation with the aid, or side by side, with artificial intelligence. I hope I will have the chance to pursue such a research direction and will be able to produce work that is beneficial in this domain.


Reference List

Al-kfairy, M. et al. (2024) ‘Ethical Challenges and Solutions of Generative AI: An Interdisciplinary Perspective’, Informatics, 11(3), pp. 58–58. Available at: https://doi.org/10.3390/informatics11030058.

Cai, W. and Gao, M. (2025) ‘Beyond Hallucination: Generative AI as a Catalyst for Human Creativity and Cognitive Evolution’, ICCK Transactions on Emerging Topics in Artificial Intelligence, 2(1), pp. 36–42. Available at: https://doi.org/10.62762/tetai.2025.657559.

Ding, A.W. and Li, S. (2025) ‘Generative AI lacks the human creativity to achieve scientific discovery from scratch’, Scientific Reports, 15(1). Available at: https://doi.org/10.1038/s41598-025-93794-9.

Sternberg, R.J. (2024) ‘Do Not Worry That Generative AI May Compromise Human Creativity or Intelligence in the Future: It Already Has’, Journal of Intelligence, 12(7), pp. 69–69. Available at: https://doi.org/10.3390/jintelligence12070069.