Balancing Creativity and Automation: The Influence of AI on Modern Film Production and Dissemination
- URL: http://arxiv.org/abs/2504.19275v1
- Date: Sun, 27 Apr 2025 15:21:38 GMT
- Title: Balancing Creativity and Automation: The Influence of AI on Modern Film Production and Dissemination
- Authors: Yiren Xu,
- Abstract summary: This study explores the dual impact of AI on modern cinema through three objectives.<n> defining the optimal human-AI relationship, balancing creativity with automation, and developing ethical guidelines.<n>Findings highlight the risks of surveillance capitalism in AI-driven markets and the ethical dilemmas of deepfake technology.
- Score: 0.0
- License: http://creativecommons.org/publicdomain/zero/1.0/
- Abstract: The integration of Artificial Intelligence(AI) into film production has revolutionized efficiency and creativity, yet it simultaneously raises critical ethical and practical challenges. This study explores the dual impact of AI on modern cinema through three objectives: defining the optimal human-AI relationship, balancing creativity with automation, and developing ethical guidelines. By employing a mixed-method approach combining theoretical frameworks (auteur theory, human-technology relations) and case studies (The Safe Zone, Fast & Furious 7, The Brutalist), the research reveals that positioning AI as an "embodiment tool" rather than an independent "alterity partner" preserves human authorship and artistic integrity. Key findings highlight the risks of surveillance capitalism in AI-driven markets and the ethical dilemmas of deepfake technology. The study concludes with actionable recommendations, including international regulatory frameworks and a Human Control Index (HCI) to quantify AI involvement. These insights aim to guide filmmakers, policymakers, and scholars in navigating the evolving AI-cinema landscape while safeguarding cultural diversity and ethical standards.
Related papers
- A Conceptual Exploration of Generative AI-Induced Cognitive Dissonance and its Emergence in University-Level Academic Writing [0.0]
This work explores how Generative Artificial Intelligence (GenAI) serves as both a trigger and amplifier of cognitive dissonance (CD)<n>We introduce a hypothetical construct of GenAI-induced CD, illustrating the tension between AI-driven efficiency and the principles of originality, effort, and intellectual ownership.<n>We discuss strategies to mitigate this dissonance, including reflective pedagogy, AI literacy programs, transparency in GenAI use, and discipline-specific task redesigns.
arXiv Detail & Related papers (2025-02-08T21:31:04Z) - What is Ethical: AIHED Driving Humans or Human-Driven AIHED? A Conceptual Framework enabling the Ethos of AI-driven Higher education [0.6216023343793144]
This study introduces the Human-Driven AI in Higher Education (HD-AIHED) Framework to ensure compliance with UNESCO and OECD ethical standards.<n>The study applies a participatory co-system, Phased Human Intelligence, SWOC analysis, and AI ethical review boards to assess AI readiness and governance strategies for universities and HE institutions.
arXiv Detail & Related papers (2025-02-07T11:13:31Z) - Augmenting Minds or Automating Skills: The Differential Role of Human Capital in Generative AI's Impact on Creative Tasks [4.39919134458872]
Generative AI is rapidly reshaping creative work, raising critical questions about its beneficiaries and societal implications.<n>This study challenges prevailing assumptions by exploring how generative AI interacts with diverse forms of human capital in creative tasks.<n>While AI democratizes access to creative tools, it simultaneously amplifies cognitive inequalities.
arXiv Detail & Related papers (2024-12-05T08:27:14Z) - Towards Bidirectional Human-AI Alignment: A Systematic Review for Clarifications, Framework, and Future Directions [101.67121669727354]
Recent advancements in AI have highlighted the importance of guiding AI systems towards the intended goals, ethical principles, and values of individuals and groups, a concept broadly recognized as alignment.
The lack of clarified definitions and scopes of human-AI alignment poses a significant obstacle, hampering collaborative efforts across research domains to achieve this alignment.
We introduce a systematic review of over 400 papers published between 2019 and January 2024, spanning multiple domains such as Human-Computer Interaction (HCI), Natural Language Processing (NLP), Machine Learning (ML)
arXiv Detail & Related papers (2024-06-13T16:03:25Z) - Towards an Ethical and Inclusive Implementation of Artificial Intelligence in Organizations: A Multidimensional Framework [0.0]
This article analyzes the impact of artificial intelligence on contemporary society and the importance of adopting an ethical approach to its development and implementation within organizations.
Various actors, such as governments, academics, and civil society, can play a role in shaping the development of AI aligned with human and social values.
arXiv Detail & Related papers (2024-05-02T19:43:51Z) - Hacia una implementación ética e inclusiva de la Inteligencia Artificial en las organizaciones: un marco multidimensional [0.0]
The article analyzes the impact of artificial intelligence on contemporary society and the importance of adopting an ethical approach to its development and implementation within organizations.
Various actors, such as governments, academics and civil society, can play a role in shaping the development of AI aligned with human and social values.
arXiv Detail & Related papers (2024-04-30T22:11:05Z) - Now, Later, and Lasting: Ten Priorities for AI Research, Policy, and Practice [63.20307830884542]
Next several decades may well be a turning point for humanity, comparable to the industrial revolution.
Launched a decade ago, the project is committed to a perpetual series of studies by multidisciplinary experts.
We offer ten recommendations for action that collectively address both the short- and long-term potential impacts of AI technologies.
arXiv Detail & Related papers (2024-04-06T22:18:31Z) - Fairness in Agreement With European Values: An Interdisciplinary
Perspective on AI Regulation [61.77881142275982]
This interdisciplinary position paper considers various concerns surrounding fairness and discrimination in AI, and discusses how AI regulations address them.
We first look at AI and fairness through the lenses of law, (AI) industry, sociotechnology, and (moral) philosophy, and present various perspectives.
We identify and propose the roles AI Regulation should take to make the endeavor of the AI Act a success in terms of AI fairness concerns.
arXiv Detail & Related papers (2022-06-08T12:32:08Z) - Trustworthy AI: A Computational Perspective [54.80482955088197]
We focus on six of the most crucial dimensions in achieving trustworthy AI: (i) Safety & Robustness, (ii) Non-discrimination & Fairness, (iii) Explainability, (iv) Privacy, (v) Accountability & Auditability, and (vi) Environmental Well-Being.
For each dimension, we review the recent related technologies according to a taxonomy and summarize their applications in real-world systems.
arXiv Detail & Related papers (2021-07-12T14:21:46Z) - Building Bridges: Generative Artworks to Explore AI Ethics [56.058588908294446]
In recent years, there has been an increased emphasis on understanding and mitigating adverse impacts of artificial intelligence (AI) technologies on society.
A significant challenge in the design of ethical AI systems is that there are multiple stakeholders in the AI pipeline, each with their own set of constraints and interests.
This position paper outlines some potential ways in which generative artworks can play this role by serving as accessible and powerful educational tools.
arXiv Detail & Related papers (2021-06-25T22:31:55Z) - An interdisciplinary conceptual study of Artificial Intelligence (AI)
for helping benefit-risk assessment practices: Towards a comprehensive
qualification matrix of AI programs and devices (pre-print 2020) [55.41644538483948]
This paper proposes a comprehensive analysis of existing concepts coming from different disciplines tackling the notion of intelligence.
The aim is to identify shared notions or discrepancies to consider for qualifying AI systems.
arXiv Detail & Related papers (2021-05-07T12:01:31Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.