(Thought I posted this at 9:47am, just saved the draft better late than never)

As with anything that involves using information, Artificial Intelligence , and releasing that online for the world to see there are ethical concerns that arise when thinking about how you’ll execute a project. My project focuses on International Film Distribution. Still in its early stages I plan to use or create a dataset of perhaps 30 or so films from both inside and outside the U.S. that debuted in Theaters . Using variables such as Title, Year, Country of Production, Distributor, Domestic release date, International release date, Genre, Director, Language, Box Office. This not only to create an understanding of Film distribution but also to create a sense of how these markets work with each other and how censorship, politics and other factors influence what gets released and where. So part Data Visualization part Digital Storytelling.

Data Collection: This one is interesting. Much of the data I would collect would be public, However if I only use easily accessible databases, my dataset could unintentionally favor films from certain countries, industries, or time periods. I probably need to clearly say where my data comes from, how films were selected, and what limitations or gaps exist in the dataset.

Privacy: Privacy would probably be a relatively minor concern because the project would primarily examine films, distribution companies, countries, and publicly available information. Avoiding personal details about directors and those involved in the filmmaking and distribution process should relatively simple.

Transparency and Providing Context: Visualizations can make data appear more objective or complete than it actually is. I will clarify what criteria I used to include films and what may be skewed in the visualization. For example, a map showing that one country distributes more films internationally than another does not necessarily mean that its cinema is more culturally influential and so on.

AI Use: Environmental Concerns: If, and that’s a big IF, I use AI tools during the project like to brainstorm, organize information, analyze text, or assist with coding and such there is a potential environmental concern because AI systems require computing resources and energy. Noman Bashir of MIT brings a great point when saying “What is different about generative AI is the power density it requires. Fundamentally, it is just computing, but a generative AI training cluster might consume seven or eight times more energy than a typical computing workload,” Using an LLM model to even help brainstorm a dataset outline would use ridiculous amounts of energy. In the end it would be better to just avoid AI use as much as possible.

Accessibility / Universal Design: Accessibility should be considered when creating the project’s designs. A visualization that depends entirely on color, for example, may be difficult for some users to interpret, while an interactive map may be difficult to navigate with a keyboard or screen reader. I should provide readable labels, good contrast, descriptive captions.

Generative AI usage: No Gen was used in the writing of this module

Sources: https://news.mit.edu/2025/explained-generative-ai-environmental-impact-0117?utm_source=chatgpt.com

https://www.iubenda.com/en/help/181591-inclusive-design/