Data Surveillance and Digital Humanism: An Educational Perspective Through the Medium of Documentary Filmmaking
Translated title
Data Surveillance and Digital Humanism
Author
Fabbro, Arturo
Term
4. term
Education
Publication year
2023
Submitted on
2023-05-25
Pages
70
Abstract
This thesis explains the ideas behind and the production of an educational documentary designed to spark a broader public conversation about digital surveillance and technology. Digital surveillance refers to the ongoing collection and analysis of people’s data by apps, platforms, and connected devices. Some scholars argue that this data extraction can be used for behavior modification, potentially challenging human agency, that is, our ability to make independent choices. At the same time, research highlights digital resignation: many users feel that privacy loss is inevitable and therefore do not act. Because algorithms and automated decision-making are mostly invisible and can feel non-human, they are hard to show and explain in everyday terms. To address this, the thesis proposes a 'digital humanism' approach that shifts attention to the human user and the lived experience of interacting with algorithms. Guided by this approach, the documentary explores the close interplay between user behavior, algorithmic knowledge (what systems learn about us), and the folk theories people develop to explain algorithms. It presents diverse characters, their daily routines, and their beliefs about technology, and it introduces 'personal data obfuscation'—deliberately making one’s data less clear to confuse algorithms—as a possible tactic to protect privacy and autonomy. The film was qualitatively tested with eight participants to assess whether it raised viewers’ awareness of algorithms, especially regarding obfuscation tactics. The results indicate that the film helped audiences engage with digital surveillance as a relatable part of everyday life. However, some communication goals were not achieved: viewers asked for more technical information and offered constructive critiques of obfuscation. The thesis suggests that future work combine this educational framework with more traditional approaches to computer science literacy.
Denne afhandling beskriver ideerne bag og tilblivelsen af en undervisningsdokumentar, som skal åbne en bredere offentlig samtale om digital overvågning og teknologi. Digital overvågning betyder, at apps, platforme og forbundne enheder løbende indsamler og analyserer menneskers data. Nogle forskere mener, at denne dataindsamling kan bruges til adfærdsmodifikation og dermed udfordre menneskelig handleevne, altså vores evne til at træffe selvstændige valg. Samtidig peger forskning på digital resignation: mange brugere føler, at tab af privatliv er uundgåeligt, og derfor gør de ikke noget. Fordi algoritmer og automatiske beslutninger er usynlige og kan virke ikke-menneskelige, er de svære at vise og forklare i hverdagsnære termer. For at imødekomme dette introducerer afhandlingen en tilgang kaldet 'digital humanisme', der flytter fokus til den menneskelige bruger og til oplevelsen af at interagere med algoritmer. Med denne ramme følger dokumentaren det tætte samspil mellem brugeradfærd, algoritmisk viden (hvad systemer lærer om os) og de hverdagsteorier, som mennesker udvikler for at forklare algoritmer. Filmen præsenterer forskellige personer, deres dagligdag og deres syn på teknologi, og den introducerer 'obfuskering af persondata'—bevidst at gøre sine data mindre tydelige for at forvirre algoritmer—som en mulig taktik til at beskytte privatliv og autonomi. Filmen blev kvalitativt testet med otte deltagere for at undersøge, om den øgede seernes bevidsthed om algoritmer, især i forhold til obfuskeringstaktikker. Resultaterne tyder på, at filmen engagerede publikum i digital overvågning som noget, der er relevant i hverdagen. Dog blev alle kommunikative mål ikke nået: nogle efterlyste mere teknisk information og kom med konstruktiv kritik af obfuskering. Afhandlingen foreslår, at fremtidigt arbejde kombinerer denne undervisningsramme med mere traditionelle tilgange til datalogisk dannelse.
[This apstract has been rewritten with the help of AI based on the project's original abstract]
Keywords