Film Screening - Humans in the Loop
Film Screening - Humans in the Loop
PRE-VIEWING TASK :
1. AI Bias & Indigenous Knowledge Systems
Artificial Intelligence (AI) bias refers to the unfair or unequal outcomes produced by AI systems due to biased training data, limited representation, or embedded social prejudices. Since AI systems learn from human-generated data, they often reflect the dominant social, cultural, or economic perspectives present in that data. As a result, marginalized communities may be misrepresented or excluded within technological systems.
Indigenous knowledge systems, particularly those of Adivasi communities, are based on lived experience, ecological balance, oral traditions, and a relational understanding of land and nature. These systems are holistic and contextual rather than rigid and categorized. AI, however, operates through fixed classifications and algorithmic logic, which may fail to recognize cultural nuance and experiential knowledge.
The film likely explores how indigenous ecological wisdom challenges technological frameworks that prioritize efficiency and categorization over context. This tension raises important questions: Who defines knowledge in the digital age? Can AI truly understand diverse cultural realities? Thus, AI bias becomes not only a technical issue but also a political and cultural concern.
2. Labour & Digital Economies
In digital economies, “invisible labour” refers to the hidden human work that supports automated systems such as AI, search engines, and social media platforms. Although AI is often presented as autonomous and intelligent, it depends heavily on human workers who label data, moderate content, and correct errors. These workers are frequently underpaid, unrecognized, and located in marginalized regions.
In Humans in the Loop, the protagonist Nehma, an Adivasi woman from Jharkhand, engages in AI data-labelling work. Her role highlights the human presence behind so-called intelligent machines. This labour remains invisible because users only see the final technological output, not the human effort that makes it possible.
The film likely critiques digital capitalism, which celebrates innovation while overlooking the workers who sustain it. By foregrounding invisible labour, the narrative challenges the myth of AI as purely machine-driven and raises ethical concerns about exploitation, economic inequality, and global power hierarchies. Recognizing this labour is essential to understanding the social realities behind technological progress.
3. Politics of Representation
Representation in cinema refers to how identities, cultures, and institutions are portrayed and interpreted. From available publicity and reviews, Humans in the Loop appears to contrast advanced technological environments with the lived reality of Adivasi life. This contrast draws attention to issues of marginalization and visibility.
Adivasi communities are rarely centered in narratives about science and technology. By placing an Adivasi woman at the center of an AI-related story, the film potentially challenges dominant narratives that associate technological knowledge only with urban or elite groups. It may also question how digital systems categorize and interpret cultural identities.
Technology is often represented as neutral and progressive; however, the film likely presents it as shaped by social power structures and knowledge hierarchies. Through this lens, representation becomes political. The portrayal of Nehma may emphasize agency, dignity, and cultural identity rather than victimhood.
Thus, the film seems to explore how both technology and indigenous culture are framed, inviting viewers to critically reflect on visibility, power, and epistemological authority.
POINTS TO PONDER WHILE WATCHING
1. Narrative & Storytelling
• How does the film situate Nehma’s personal life within larger algorithmic structures? What narrative turns foreground labour, family, and knowledge systems?
While watching the film, observe how Nehma’s everyday life is connected to global technological systems. The narrative likely moves between her domestic space, community life, and digital workspace. Pay attention to how scenes of family interactions, village environment, and traditional practices are placed alongside scenes of data-labelling work.
Consider how the story structure highlights the contrast between lived experience and algorithmic systems. Notice whether emotional or personal moments are interrupted by technological demands. Identify key turning points in the narrative where labour becomes central — for example, moments when Nehma questions the task she is performing or confronts the limitations of the AI system.
Reflect on how the film uses storytelling to show that global AI infrastructures depend on individual human lives. The narrative may suggest that behind every automated system, there are real families, identities, and cultural knowledge systems shaping and sustaining it.
- When Nehma “teaches” AI, what does this suggest about human-machine learning loops beyond technological jargon?
While observing scenes where Nehma labels data or corrects AI outputs, think about the meaning of “teaching” in this context. Although AI is often described as autonomous and intelligent, it depends on human instruction. The phrase “human in the loop” itself implies that machines require continuous human guidance.
Consider what it means for an Adivasi woman to train advanced technology. Does the film portray this as empowerment, exploitation, or a complex mix of both? Notice whether her cultural understanding conflicts with the rigid categories required by the system.
Beyond technical language, the human-machine loop may symbolize interdependence rather than replacement. The film might challenge the idea that machines are superior to human knowledge. Instead, it may reveal that AI systems are shaped by the people who train them, including their experiences, biases, and worldviews.
2. Representation & Cultural Context
How are Adivasi culture, language, tradition, and ecological knowledge represented?
While watching the film, observe how Adivasi life is visually and narratively framed. Pay attention to language use, clothing, rituals, community interactions, and the depiction of natural landscapes. Consider whether these elements are shown as living, dynamic practices or merely as background settings.
Notice how ecological knowledge—such as understanding of forests, land, seasons, and sustainable living—is portrayed. Is it treated as valuable knowledge or as something outdated in comparison to technological systems? Reflect on whether the film presents indigenous knowledge as equal to scientific or algorithmic knowledge.
Also consider the tone of representation. Are cultural practices shown with dignity and authenticity? Does the camera perspective allow space for Adivasi voices, or does it position them as objects of observation? The way the film frames these aspects may reveal its ideological stance toward indigenous epistemologies.
• Does the film challenge or reinforce dominant media stereotypes about tribal communities and modern technology?
In mainstream media, tribal or Adivasi communities are often stereotyped as backward, disconnected from modernity, or resistant to technological change. While watching, analyze whether the film disrupts these simplified portrayals.
Does Nehma appear as passive and marginalized, or as intelligent, reflective, and capable of engaging critically with technology? Consider whether the narrative presents her as merely a victim of exploitation or as an active participant shaping AI systems.
Examine how technology is represented in relation to tribal identity. Is modern technology shown as incompatible with indigenous life, or does the film suggest a more complex coexistence?
If the film foregrounds Nehma’s agency and highlights the intellectual contribution of her lived experience to AI systems, it may challenge dominant stereotypes. However, if it overemphasizes victimhood or romanticizes tradition without nuance, it may risk reinforcing them.
While watching, reflect critically on whether the film creates a balanced and empowering representation of Adivasi identity within the digital age.
3. Cinematic Style & Meaning
• Mise-en-scène & Cinematography
While watching the film, carefully observe the mise-en-scène — this includes setting, lighting, costume, props, framing, and spatial arrangement within the frame.
Notice how the forest landscape is framed. Are wide shots used to emphasize openness, depth, and connection with nature? Is natural lighting employed to create authenticity and realism? The forest may symbolize organic knowledge, continuity, and lived experience.
In contrast, observe how computer screens and workspaces are presented. Are they framed through close-ups, static shots, or confined compositions? Does artificial lighting dominate these scenes? Such framing may visually suggest restriction, surveillance, or mechanization.
Pay attention to the visual contrast between ritual spaces and digital work environments. The positioning of the body within these spaces can reflect power structures — for example, whether Nehma appears empowered, isolated, or fragmented within the frame.
Through cinematography and spatial composition, the film may visually construct the tension between ecological life and algorithmic systems.
• Sound Design & Editing
Sound design and editing rhythms are crucial in shaping thematic contrast.
Observe the soundscape of the forest and village — natural ambient sounds such as birds, wind, footsteps, or community voices may create a sense of continuity and relational existence. These sounds often produce a slower, organic rhythm.
In contrast, the digital workspace may feature mechanical sounds, keyboard clicks, notification alerts, or low electronic hums. These artificial sounds can create a repetitive or monotonous rhythm, reflecting the mechanical nature of data-labelling labour.
Consider the editing pace. Are rural scenes edited with longer takes and smooth transitions, while digital labour scenes are cut more sharply or rhythmically? Faster cuts may represent the speed and pressure of algorithmic systems, whereas slower pacing may evoke reflection and embodied time.
Together, mise-en-scène, cinematography, editing, and sound design contribute to the film’s deeper meaning. They do not simply illustrate the story but actively construct the contrast between analog life and digital labour, shaping the viewer’s emotional and ideological understanding.
4. ETHICAL & POLITICAL QUESTIONS
What ethical dilemmas are depicted when training AI with culturally specific data?
While watching the film, pay close attention to moments where culturally specific knowledge is translated into algorithmic categories. Ask yourself: What happens when lived experience is reduced to data?
Notice whether the AI system simplifies complex traditions, ecological knowledge, or cultural practices into rigid labels. Does this process create distortion or loss of meaning? Observe if Nehma appears conflicted while categorizing information that may not fit the system’s predefined structure.
Consider issues of consent and ownership. Who controls the data? Who benefits from it? Are the communities whose knowledge is being used adequately acknowledged or compensated?
Also reflect on power imbalance. If algorithmic frameworks are shaped by dominant knowledge systems, how are indigenous epistemologies positioned within them? The film may visually or narratively suggest that technological progress can unintentionally marginalize cultural specificity.
• How does the film’s “human-in-the-loop” metaphor operate beyond the technical term—politically, socially, and culturally?
As you watch, think about the metaphor beyond its technical definition (human supervision in AI training).
Politically, does the film reveal inequalities in global digital labour? Who performs the work, and who holds decision-making power? Observe how Nehma’s labour connects to larger technological structures.
Socially, reflect on whether the film challenges the idea that machines are independent or superior. Does it emphasize human dependency within AI systems?
Culturally, consider whether the “loop” represents a tension between indigenous knowledge and technological logic. Is it a space of conflict, negotiation, or coexistence?
While watching, ask: Is the human truly “in control,” or merely sustaining the system? The metaphor may function as a critique of digital capitalism, knowledge hierarchies, and power structures embedded within AI development.
POST-VIEWING REFLECTIVE ESSAY TASKS
TASK 1 — AI, BIAS, & EPISTEMIC REPRESENTATION
Technology and Human Knowledge in Humans in the Loop (2024)
Directed by Aranya Sahay, Humans in the Loop explores the complex relationship between artificial intelligence (AI) and human knowledge through the story of Nehma, an Adivasi woman from Jharkhand working in AI data-labelling. The film challenges the common belief that AI is neutral and purely technical. Instead, it presents technology as culturally shaped, socially embedded, and politically influenced. Through narrative structure and cinematic techniques, the film exposes algorithmic bias and highlights epistemic hierarchies—raising questions about whose knowledge is valued in digital systems.
Algorithmic Bias as Culturally Situated
AI is often described as objective and rational. However, the film shows that AI systems learn from human-generated data. Because data reflects social realities, AI can reproduce existing inequalities. In the film, Nehma’s task is to label and categorize data so that machines can “learn.” This process reveals that AI depends on human interpretation. When culturally specific knowledge—such as ecological understanding or traditional practices—is translated into fixed categories, complexity is reduced.
The narrative shows moments where lived experience does not easily fit into algorithmic structures. These scenes suggest that bias is not simply a programming mistake but a result of dominant cultural frameworks embedded in technology. From the perspective of ideology in film studies, AI in the film operates as a system that appears neutral but actually reflects power relations. The categories used by the system are shaped by particular social viewpoints, not universal truths.
Thus, the film argues that algorithmic bias is culturally situated. It emerges from the social and political contexts in which AI systems are designed and trained.
Epistemic Hierarchies: Whose Knowledge Counts?
A major theme in the film is epistemic hierarchy—the ranking of knowledge systems according to perceived value. In technological discourse, scientific and computational knowledge is often seen as superior, while indigenous knowledge is marginalized. Through Nehma’s experience, the film highlights this imbalance.
Although Nehma’s cultural and ecological knowledge is essential for training the AI, it is not treated as authoritative knowledge. Instead, it is converted into data for technological use. Decision-making power remains outside her control. This reflects broader power relations in digital economies, where marginalized communities provide labour but lack authority.
Using representation theory, we can observe that the film challenges stereotypes about Adivasi communities. Rather than portraying Nehma as backward or disconnected from technology, the film represents her as skilled, thoughtful, and intellectually engaged. However, it also shows the limits of her agency within larger technological structures.
The film therefore exposes how technological systems privilege certain forms of knowledge while subordinating others. Knowledge becomes legitimate only when it fits within algorithmic frameworks.
Cinematic Representation and Ideology
The film’s visual style reinforces its critique. The forest and village spaces are shown with natural light, open framing, and ambient sound, suggesting relational and ecological modes of knowing. In contrast, the digital workspace is visually confined and structured, often centered around screens and artificial lighting. This contrast between organic space and technological environment symbolizes the tension between embodied knowledge and algorithmic logic.
Editing rhythms also contribute to meaning. Slower pacing in rural scenes contrasts with repetitive sequences of digital labour. This formal contrast reflects ideological tension—between lived time and machine time.
Drawing on Foucault’s idea of power/knowledge, the film suggests that knowledge is always connected to systems of control. AI functions as a contemporary structure of power that defines categories, determines relevance, and organizes reality. Nehma’s role within this structure shows how individuals participate in sustaining systems that may not fully recognize their knowledge.
Beyond the Technical “Human-in-the-Loop”
Technically, “human in the loop” refers to systems where human supervision is necessary for AI training. However, the film expands this term into a broader metaphor. Politically, it reveals the dependence of advanced technology on marginalized labour. Socially, it challenges the myth that machines function independently of humans. Culturally, it represents a negotiation between indigenous epistemology and algorithmic classification.
The “loop” becomes a space of both connection and inequality. Humans are essential to AI, yet they are not equally empowered within its structure. The film therefore critiques digital capitalism, where innovation is celebrated while human contributors remain invisible.
Conclusion
Humans in the Loop presents AI not as a neutral technological achievement but as a system shaped by culture, ideology, and power relations. By centering an Adivasi woman within a technological narrative, the film exposes algorithmic bias as socially constructed and highlights epistemic hierarchies that determine whose knowledge counts.
Through narrative contrast and cinematic techniques, the film invites viewers to critically examine the relationship between human knowledge and artificial intelligence. It ultimately argues that ethical AI development requires recognizing cultural diversity, redistributing authority, and acknowledging the human labour that sustains technological systems.
How does the narrative expose algorithmic bias as culturally situated rather than purely technical?
The narrative of Humans in the Loop (2024), directed by Aranya Sahay, demonstrates that algorithmic bias is not simply a technical error but a cultural and social issue. The film shows that AI systems learn from data labeled and categorized by humans. Since this data comes from particular social contexts, it carries the assumptions, values, and limitations of those contexts.
Through Nehma’s work as a data-labeller, the narrative reveals how culturally specific knowledge must be adjusted to fit rigid algorithmic categories. When her lived, ecological, and community-based understanding does not align with predefined digital labels, tension emerges. This shows that AI systems are built upon dominant frameworks of knowledge that may not accommodate diverse cultural realities.
The film suggests that bias occurs not because machines “fail,” but because the systems are designed within particular ideological and cultural boundaries. By connecting Nehma’s personal experience with global technological structures, the narrative makes clear that algorithmic bias reflects power relations embedded in society rather than being a neutral computational problem.
In what ways does the film highlight epistemic hierarchies—that is, whose knowledge counts in technological systems?
The film highlights epistemic hierarchies by showing that certain forms of knowledge are privileged over others within technological systems. Scientific, technical, and algorithmic knowledge is treated as authoritative, while indigenous and experiential knowledge is required to adapt itself to technological frameworks.
Although Nehma’s cultural and ecological knowledge is essential for training AI, it is not recognized as independent intellectual authority. Instead, it is transformed into data that serves the system. This demonstrates that marginalized communities contribute significantly to technological production, yet they do not control it.
By portraying an Adivasi woman as central to AI training, the film challenges stereotypes about tribal communities being disconnected from modern technology. However, it also reveals that decision-making power remains concentrated elsewhere. In this way, the film exposes how technological systems reproduce broader social hierarchies—determining whose knowledge is visible, valued, and legitimized.
Ultimately, Humans in the Loop argues that technology is not neutral; it reflects existing structures of cultural and epistemic power.
THEORETICAL LENS SUGGESTIONS:
Apparatus Theory is a film theory that developed in the 1970s, mainly influenced by Marxist and psychoanalytic thinkers such as Jean-Louis Baudry and Christian Metz. The theory argues that cinema is not just a storytelling medium but an ideological apparatus that shapes how viewers see and understand reality.
According to Apparatus Theory, the “apparatus” includes the entire cinematic system—camera, editing, projection, screen, and viewing situation. These technical elements are not neutral. They position the spectator in a specific way and unconsciously guide interpretation. The camera’s framing, point of view, and editing patterns create an illusion of realism and authority, which makes the ideology embedded in the film appear natural and unquestionable.
When applying Apparatus Theory to Humans in the Loop (2024), directed by Aranya Sahay, we can examine how both cinema and AI function as ideological apparatuses. Just as cinema constructs meaning through framing and representation, AI systems construct reality through categorization and data classification. Both systems appear objective but are shaped by social power structures.
For example, the way the film frames Nehma within digital workspaces versus natural landscapes may guide viewers to critically question technological authority. The representation of AI interfaces and surveillance-like screens can mirror societal hierarchies, where marginalized individuals contribute labour but lack decision-making power.
Thus, Apparatus Theory helps us understand that technology in the film is not neutral. It reflects and reproduces ideological structures—just as cinema itself does. The film therefore becomes self-reflexive: it uses the cinematic apparatus to critique technological apparatuses.
TASK 2 LABOR & THE POLITICS OF CINEMATIC VISIBILITY
Invisible Labour and Digital Capitalism in Humans in the Loop (2024)
Directed by Aranya Sahay, Humans in the Loop critically visualizes the hidden human labour that sustains artificial intelligence systems. The film foregrounds data-labelling work—often presented in mainstream discourse as automated or machine-driven—and reveals the emotional, cultural, and social dimensions of this invisible labour. Through its visual language and narrative structure, the film offers a critique of labour conditions under digital capitalism.
Visual Representation of Labelling Work and Emotional Experience
The film’s visual language plays a crucial role in making invisible labour visible. Data-labelling scenes are often framed through close-ups of screens, repetitive hand movements, and confined workspace compositions. This framing emphasizes monotony, precision, and constraint. The limited spatial depth of these scenes may visually reflect restricted agency within digital systems.
In contrast, scenes set in Nehma’s village or forest environment often use wider frames and natural lighting. This visual contrast highlights the shift from relational, embodied life to isolated digital work. The repetitive rhythm of typing, clicking, and categorizing data suggests mechanical routine, while facial expressions and pauses reveal emotional complexity—fatigue, hesitation, reflection, or quiet resistance.
By focusing on the physical and emotional dimensions of labelling work, the film challenges the myth that AI functions independently. It visually insists that behind every “intelligent” system, there is human effort, interpretation, and cognitive labour.
Cultural Valuation of Marginalised Work
The film suggests that digital capitalism depends heavily on marginalized labour while simultaneously rendering it invisible. Data-labelling work is essential for AI training, yet it is socially undervalued and economically undercompensated. The workers remain unseen by the end users who benefit from seamless technological services.
This dynamic reflects broader cultural hierarchies. Technological innovation is celebrated, but the human contributors—often from marginalized communities—are excluded from recognition and authority. The film shows that while Nehma’s knowledge and labour are indispensable, they are not acknowledged as intellectual or creative contributions. Instead, they are reduced to technical support roles.
In this way, the film critiques how capitalist systems assign value. Prestige and visibility are given to developers and corporations, while foundational labour remains peripheral. The invisibility of such work mirrors historical patterns where marginalized communities sustain economic systems without receiving equal status or power.
Empathy, Critique, and Transformation
The film invites empathy by centering Nehma’s perspective. Through close framing, attention to facial expressions, and integration of her personal life with her digital labour, viewers are encouraged to understand her emotional world. This humanization counters the abstraction of technological discourse.
At the same time, the film moves beyond empathy toward critique. By visually contrasting rural ecological life with repetitive digital tasks, it raises questions about exploitation, control, and power. It subtly critiques digital capitalism’s dependence on low-wage, invisible labour.
Importantly, the film also encourages transformation in how labour is perceived. By foregrounding data-labelling as skilled cognitive work rather than mechanical input, it reframes AI development as a collaborative human-machine process. The “human in the loop” metaphor emphasizes interdependence rather than replacement, suggesting that labour should be recognized, valued, and ethically treated.
Conclusion
Through its cinematic techniques and narrative focus, Humans in the Loop exposes the hidden labour sustaining AI systems and critiques the inequalities embedded in digital capitalism. The film not only makes invisible labour visible but also questions how societies value technological work. By inviting empathy and critical reflection, it challenges viewers to reconsider the cultural and economic structures that shape contemporary labour systems.
THEORETICAL LENS SUGGESTIONS:
1. Marxist and Cultural Film Theory
Marxist Film Theory is based on the ideas of Karl Marx, especially his analysis of class struggle, labour exploitation, and capitalism. In film studies, this theory examines how cinema represents economic systems, class relations, and the commodification of human labour.
According to Marxist theory, capitalism turns human labour into a commodity—something that can be bought and sold. Workers often become alienated from the products of their labour, meaning they do not control or fully benefit from what they create. Cultural Film Theory expands this approach by analyzing how films reflect and critique social structures, ideology, and power relations.
When applied to Humans in the Loop (2024), directed by Aranya Sahay, this lens helps us examine how digital capitalism depends on invisible labour. Nehma’s data-labelling work becomes an example of commodified cognitive labour. Although her work is essential for AI systems, she does not control the technology or receive recognition equal to its value.
The film can therefore be read as a critique of capitalist structures where corporations profit from technological innovation while marginalized workers remain economically and socially peripheral. It highlights class inequalities embedded in global digital economies.
2. Representation and Identity Studies
Representation and Identity Studies focus on how films construct identities related to gender, class, caste, race, ethnicity, and culture. This approach asks: Who is visible? Who speaks? Whose experiences are centered? How do cinematic portrayals challenge or reinforce stereotypes?
In technological narratives, marginalized communities are often excluded or portrayed as disconnected from modern innovation. By centering an Adivasi woman in a story about AI, Humans in the Loop challenges dominant assumptions about who contributes to technological systems.
The film represents Nehma not as technologically backward but as intellectually capable and essential to AI development. This shifts the narrative from viewing indigenous communities as passive recipients of modernity to recognizing them as active participants in shaping digital systems.
At the same time, the film also reveals structural inequality—showing that while marginalized identities contribute labour, authority and ownership remain elsewhere. Thus, identity and labour intersect in the cinematic portrayal to expose power imbalances within technological production.
1. Marxist and Cultural Film Theory
Marxist Film Theory is based on the ideas of Karl Marx, especially his analysis of class struggle, labour exploitation, and capitalism. In film studies, this theory examines how cinema represents economic systems, class relations, and the commodification of human labour.
According to Marxist theory, capitalism turns human labour into a commodity—something that can be bought and sold. Workers often become alienated from the products of their labour, meaning they do not control or fully benefit from what they create. Cultural Film Theory expands this approach by analyzing how films reflect and critique social structures, ideology, and power relations.
When applied to Humans in the Loop (2024), directed by Aranya Sahay, this lens helps us examine how digital capitalism depends on invisible labour. Nehma’s data-labelling work becomes an example of commodified cognitive labour. Although her work is essential for AI systems, she does not control the technology or receive recognition equal to its value.
The film can therefore be read as a critique of capitalist structures where corporations profit from technological innovation while marginalized workers remain economically and socially peripheral. It highlights class inequalities embedded in global digital economies.
2. Representation and Identity Studies
Representation and Identity Studies focus on how films construct identities related to gender, class, caste, race, ethnicity, and culture. This approach asks: Who is visible? Who speaks? Whose experiences are centered? How do cinematic portrayals challenge or reinforce stereotypes?
In technological narratives, marginalized communities are often excluded or portrayed as disconnected from modern innovation. By centering an Adivasi woman in a story about AI, Humans in the Loop challenges dominant assumptions about who contributes to technological systems.
The film represents Nehma not as technologically backward but as intellectually capable and essential to AI development. This shifts the narrative from viewing indigenous communities as passive recipients of modernity to recognizing them as active participants in shaping digital systems.
At the same time, the film also reveals structural inequality—showing that while marginalized identities contribute labour, authority and ownership remain elsewhere. Thus, identity and labour intersect in the cinematic portrayal to expose power imbalances within technological production.
TASK 3 — FILM FORM, STRUCTURE & DIGITAL CULTURE
In Humans in the Loop (2024), directed by Aranya Sahay, film form plays a central role in expressing philosophical concerns about digital culture and human-AI interaction. Through camera work, editing, and sound, the film makes abstract ideas about technology and labour visually and emotionally tangible.
The contrast between natural imagery and digital workspaces is especially important. Scenes set in the forest or village are often shown with wider shots, natural lighting, and ambient sounds. These create a sense of openness and lived experience. In contrast, digital spaces—computer screens and office interiors—are framed more tightly, with artificial lighting and static compositions. This visual difference highlights the tension between organic human life and the structured, mechanical world of algorithms.
Editing also shapes meaning. The repetitive cutting between screens, typing, and labelling tasks reflects the monotonous and fragmented nature of digital labour. The rhythm of these sequences allows the audience to feel the routine and cognitive strain of the work. Through this, invisible labour becomes visible and experiential.
Sound design further strengthens this contrast. Natural sounds such as wind and voices emphasize human presence, while keyboard clicks and notification tones mark technological control. The combination of these elements suggests that AI systems depend on human effort, even if that effort remains hidden.
Overall, the film’s aesthetic choices encourage viewers to reflect on labour, identity, and technology. Rather than presenting AI as purely innovative, the cinematic form reveals its human foundation and invites a critical understanding of digital culture.
Questions
How does the interplay of natural imagery versus digital spaces communicate broader thematic concerns?
In Humans in the Loop (2024), directed by Aranya Sahay, the contrast between natural imagery and digital spaces highlights a central philosophical tension between embodied human knowledge and algorithmic systems. Natural environments are presented as expansive, fluid, and rooted in lived reality. In contrast, digital workspaces appear confined, structured, and artificial. This visual opposition suggests that technology operates by simplifying and categorizing complex human experiences. The film uses this contrast to question whether AI can truly understand or represent nuanced cultural and social realities.
The aesthetic choices shape the viewer’s experience by making digital labour feel repetitive and cognitively demanding. Through close shots of screens and small gestures like typing or clicking, the film emphasizes the meticulous effort behind AI systems. These choices foster empathy for the worker and challenge the perception of technology as automated or self-sufficient. The viewer becomes aware that AI depends on hidden human labour, reshaping how labour and technological progress are perceived.
How do aesthetic choices shape the viewer’s experience of labour, identity, and technology?
In Humans in the Loop (2024), the interplay between natural settings and digital environments communicates broader concerns about displacement and transformation under digital culture. Natural imagery—open landscapes, ambient sounds, and slower pacing—creates a sense of identity grounded in place and community. Digital spaces, however, are visually rigid and repetitive, reflecting the standardized logic of algorithms. This contrast suggests that digital capitalism reorganizes human experience into data, reducing lived realities into measurable categories.
Aesthetic techniques strongly influence how viewers perceive labour, identity, and technology. The repetitive editing of labelling tasks mirrors the monotony of digital work, allowing the audience to feel its rhythm and strain. Sound design—mechanical clicks versus organic environmental sounds—reinforces the divide between human presence and machine processes. These choices create not only empathy but also critique. The film encourages viewers to question the cultural value assigned to technological systems while the human labour sustaining them remains invisible.
THEORETICAL LENS SUGGESTIONS:
1. Structuralism / Film Semiotics
Structuralism and Film Semiotics examine how meaning in a film is produced through systems of signs—images, symbols, narrative patterns, and visual contrasts. Instead of looking only at the story, this approach studies how the film functions as a structure made up of codes.
In Humans in the Loop, the contrast between forest landscapes and computer screens operates as a system of signs. The forest signifies tradition, lived knowledge, and cultural continuity. The computer interface signifies modernity, abstraction, and algorithmic control. These visual oppositions create a structural binary: nature vs. technology, human knowledge vs. machine logic, visibility vs. invisibility.
Nehma’s data-labelling work becomes a key signifier. Although she appears to perform small, repetitive digital tasks, these images signify a larger global system of AI production. The film uses recurring shots of screens, clicking, and reviewing data as visual codes representing digital capitalism. Through this semiotic structure, the film communicates that AI is not autonomous—it is built on hidden human labour.
2. Formalist and Narrative Theory
Formalist theory focuses on how cinematic techniques—camera, editing, sound, and narrative structure—create meaning. Rather than emphasizing social context first, it closely analyzes film form.
In Humans in the Loop, meaning is shaped through visual composition and pacing. The camera often frames Nehma in close-up while she works, drawing attention to her concentration and emotional engagement. Repetitive editing patterns during labelling sequences mirror the monotony of digital labour. The rhythm of these scenes creates a feeling of routine and cognitive strain.
Narratively, the film structures its story around the contrast between Nehma’s rural life and her digital employment. This parallel structure emphasizes the tension between her identity and the technological system she contributes to. The use of silence and minimal dialogue in work scenes strengthens the sense of isolation within digital spaces.
Through these formal choices, the film does not simply tell the viewer that labour is invisible—it makes the audience experience that invisibility. The techniques themselves generate meaning.
Reference
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