Course Learning Journal
This week, I was introduced to the field of Digital Media. I learned that it combines creativity with technology and communication. Understanding how digital content is produced and shared helped me build a basic foundation for the course. I became more aware of how digital media influences everyday life and culture.
This week, I learned how to create a basic website using HTML and CSS. I practiced building page structure, adding text, and designing simple layouts. Although it was challenging at first, I enjoyed seeing my work directly displayed on the screen. This experience helped me appreciate the creative possibilities of web design.
This week, I explored web scraping and learned how data can be collected from websites. I understood how structured web content can be extracted and transformed into useful information. This skill is powerful for research, but it also raised questions about data ethics and responsibility. I realized the importance of careful and respectful data use.
This week focused on data analysis and understanding how data provides meaning. I learned that data is not just numbers, but information shaped by context and interpretation. Analyzing data helped me see patterns and draw conclusions. I also became more aware of how data influences decisions in society and everyday life.
This week introduced data visualization. I learned how to present complex data in clear and engaging ways using charts and infographics. Visual storytelling made data more understandable and persuasive. It helped me appreciate how design choices can influence interpretation and communication.
I learned how these algorithmic profiles simplified the complete me into individual data points, which in turn increasingly impacted opportunities in my real life—like job hunting and making friends. I also saw the gaps between the real me, the labels algorithms had put on me, and how I was represented in society. For example, biased algorithms might have distorted the images of minority groups. Additionally, it made me reflect on how much agency I had: how I should respond to, resist, or adapt to algorithmic categorization, while advocating for more accurate and inclusive representation of all identities.
Critical Reflections on AI Conversation Drift
Structural Limitations:
AI understanding is built on historical datasets, and its cognitive structure inevitably carries embedded social biases. Non-typical intentions are easily filtered out or misinterpreted, making conversational drift a form of technological and cultural filtering.
Driven by Commercial Logic:
AI platforms rely on continuous user interaction to refine their systems. As a result, “sustained conversation” may be prioritized over “accurate responses,” turning users into unnoticed data laborers contributing to model training.
Misleading Emotional Design:
Human-like interfaces create a false sense of emotional reciprocity, hiding the probabilistic nature of the model. The mismatch between user expectation and system capability exposes the limits of simulated emotions.
Ambiguity in Accountability:
Responsibility for conversational drift becomes difficult to assign—user expression, system design, and dataset bias intertwine, forming a complex accountability dilemma.
Key Insight:
The drift phenomenon reveals that power is deeply embedded in technological structures. Maintaining critical awareness and distinguishing between tool utility and systemic agendas is essential cognitive literacy in the digital age.
This week’s practical session took place in a local market. Through multisensory documentation and speculative listening exercises, we engaged in cross-media observation and recording of material flows, social relations, and digital traces within the food ecosystem.
Multisensory Documentation Expands Ecological Perception:
1. Using audio recorders to capture the soundscape—vendor calls, negotiation conversations, food-processing noises—combined with olfactory, tactile, and visual notes, we created a thicker description of the food ecology. Integrating digital tools such as mapping software with traditional observation revealed hidden relationships, such as price fluctuations and spatial arrangements.
2. Interviewing market vendors and interpreting the recordings together helped reduce researcher-centered bias and offered a more collaborative perspective.
Reflective Insight:
This exercise transformed the abstract concept of “digital ecology” into a concrete, observable, and multisensory system. The market became a “living laboratory,” demonstrating how technology, organisms, and cultural practices intertwine in the Anthropocene—where every payment notification and every piece of wrapped produce becomes a researchable digital-ecological trace.
During the initial stage of sensory exploration, I realized that my perception was largely shaped by vision and hearing. Vision allowed me to observe the spatial layout of market stalls, the textures of goods, and the design of digital payment interfaces. Hearing captured the market’s soundscape—the overlapping conversations, payment alerts, and surrounding noises.
This sensory prioritization was not accidental. Digital tools like smartphones and audio recorders inherently emphasize visual and auditory data, subtly pushing tactile and olfactory sensations into secondary importance. This made me reflect on how technology not only assists sensory documentation but also guides—and limits—the way we sense and interpret environments.