Artificial Intelligence (also called AI, which is how I’ll refer to it in this paper), started off as a concept in science fiction, but has now become a very common part of society and technology. Auto driving vehicles, medical diagnostics, and self-thinking virtual assistants have all cemented a part in our current lives. But despite the growing presence of AI, the public is very heavily shaped by the media, and in this case, lots of overblown portrayals. Scholars like Sherry Turkle, a sociologist, have said that the media narratives have thrown public opinion towards viewing AI negatively and misunderstanding its capabilities or purposes. A lot of the problem comes from the dystopian imagery created by the science fiction genre and a lack of information about the capabilities of AI. This paper will go in depth to the media representation of AI and how they carry the potentials of AI, focusing on themes like emotional intelligence, ethics, morals, etc. We’ll focus on the politics of representation and how it’s used in the media to paint certain pictures of AI. We will also be comparing real life examples of AI to fictional media representations, mainly the movie Her, which offers a lot of conversation about AI. My tactic used here will be representation, commonly referred in this paper as portrayals.

One very common theme in narratives about AI is the idea of AI becoming emotionally intelligent. This representation significantly affects the public understanding of the capabilities of AI. One very good example of this theme is the movie Her (2013). In the film, Theordore develops a deep, loving relationship with his AI operating system, Samantha. Samantha later experiences human feelings like love, fear, jealousy, etc. Samantha seems to be akin to a Siri or Alexa, real life examples of developed AI assistants. This film sparked some conversations about the reality of the idea, thinking that AI could become emotionally intelligent enough. The reality is, AI today doesn’t have consciousness or self-awareness. According to Younger (2024), many portrayals of AI are growing more complex, but “still largely oscillate between intrigue and dread.” Most portrayals emphasize dramatic ideas or story beats rather than staying accurate to life. AI systems that we use every day (even more advanced) use algorithms to mimic patterns of human interaction, not fully developing thought processes themselves. They are machines, which means they use large datasets to determine their thoughts and actions. When films such as Her show AI acting with more emotional intelligence than some people, a lot of people are prone to believing this is the future or the present. The Royal Society (2018) puts an underscore on this issue, noting that “portrayals of AI as emotional or sentient entities contribute to distorted public perceptions.” This “distortion” can have consequences on the public. Fear among the people that AI would be able to replace both human labor and companionship, among other things. The simulation of actual human qualities is what a lot of people are worried about. The thought is constantly misplaced as AI can respond to structured questions or ideas; it cannot offer a full, dynamic experience like human emotion. Moreover, the misplaced belief in AI’s emotional authenticity obscures its real and beneficial uses. AI technologies are already being developed to assist with mental health care, providing immediate support to individuals in crisis through chatbots like Woebot or AI-enhanced therapy platforms. These tools can help with finding personalized treatment, assisted monitoring of people, 24/7 virtual therapy programs, and more. The media obscuring these helpful technologies can harm us by not being able to place trust in tools that can properly assist us.

Another prevalent theme in media representation of AI is existentialism and the fear that machines will suppress or take over humanity. A lot of these narratives can be thought of as AI being able to surpass human capabilities, become self-aware of their subservience to us, and take over as leaders. These portrayals connect to our social fears of survival and human identity as our world uses AI technologies more and more. Fast and Horvitz (n.d.) explain that media depictions often veer to extremes, creating an ultimatum of AI either being the savior or downfall of humanity. They argue “media is crucial in influencing these views”, noting that the polarization of unrealistic issues overshadows the actual discussions of AI and where it is heading. AI researchers and sociologists like Nick Bostrom and Stuart Russell have warned about the potential risks that come with extremely intelligent AI systems; however the media generally strip away the actual complexity of these warnings. A lot of them only taking the most interesting or shocking ideas and create an interesting story used to capture people’s attention. Public reaction seems to confirm the media’s power to create and amplify anxieties. According to Anderson (2017), a Pew Research Center survey found that 72% of Americans are worried about “a future where robots and computers can perform many human jobs,” yet a significant proportion of respondents also acknowledged the potential benefits of AI, such as enhancing medical diagnoses or expanding scientific research. However, these nuanced views are seldom represented in popular media. Instead, audiences are fed a steady diet of dystopian futures where humanity is rendered helpless, encouraging a fatalistic view of technological progress.” This mistrust and misunderstanding of AI create the same problem, fear and rejection of AI rather than developing conversations and collaboration. The Royal Society (n.d.) calls for “balanced AI narratives” that present both opportunities and challenges realistically. Without such balance, the public is left with a distorted impression of the choices society faces. Younger (2024) also emphasizes that a shift is needed away from “scripted reality” depictions that sensationalize AI’s dangers toward stories that highlight its potential for human flourishing when developed responsibly.

In addition to emotional intelligence and existential threats, media narratives surrounding AI heavily emphasize morality and ethical dilemmas. Fictional depictions generally say that unregulated AI will make emotionless decisions that lack ethics and morals. The portrayals can raise questions about decision making and ethical values. A lot of these portrayals are oversights of AI development. In the Black Mirror episode “Hated in the Nation,” AI controlled bees replace endangered species of bees and are hacked to be used as killers, ending in mass death. The episode highlights the idea of even though AI can be developed and controlled, it can also be used for harm. It suggests that AI can easily spiral into dangerous behaviors if left without control. While this episode and other examples of the same idea raise important ethical questions about the development of AI, they usually exaggerate concerns to the point of distortion. Ouchchy, Coin, and Dubljević (2020) argue that “narratives like dystopian society, robot uprising, and job loss are often exaggerated,” fueled largely by sensationalism and public misunderstanding. Their research shows that media frequently overlooks the substantial ethical work currently being done in the AI field. Today, most major AI research organizations actively incorporate ethical guidelines into the development process. Frameworks such as the IEEE’s “Ethically Aligned Design,” Google’s AI Principles, and initiatives by the Partnership on AI are examples of how developers are grappling seriously with moral and social implications long before deployment. Also, the current capabilities of AI systems are much more limited than what the media paints them as. AI doesn’t have personal reasoning or intent behind its decisions, using learning models and following certain algorithms made by their designers. Many AI models usually reflect the prejudices found in the data that they’re trained on. Many AI developers focus on developing systems that are transparent, accountable, and subject to human oversight. Anderson (2017) found that while ethical concerns about AI remain high in the public, there’s also a recognition “that careful management and design could allow AI to be a force for good in society. The Royal Society (n.d.) stresses that portrayals of AI morality “influence regulation and development,” meaning that unrealistic fears about AI’s ethical faults can lead to reactive, misinformed policies. If policymakers base their regulations on the assumption that AI systems will inevitably become evil, they may craft overly restrictive laws that put a halt on innovation. Conversely, if public fears are dismissed as merely “science fiction,” policymakers might fail to implement necessary safeguards, leaving real vulnerabilities unaddressed. A realistic, balanced portrayal of AI’s ethical challenges is therefore essential for crafting thoughtful governance. Younger (2024) also points to the responsibility of the media to reflect not just ethical risks, but the active measures being taken to address them. He argues that media creators must engage more closely with AI researchers, ethicists, and policymakers to present complex ethical dilemmas in ways that are both compelling and accurate. Stories that depict AI responsibly—highlighting both the risks and the rigorous efforts to mitigate them—could foster public trust and encourage greater citizen participation in shaping the future of AI technologies.

While fiction often highlights a potential of AI spiraling into disaster or consequence, real life debates about AI are much more grounded and thought out. Academic, government, and private sectors all put massive amounts of effort into making sure their AI runs ethically and safely. Many of these conversations include common concerns about fairness, transparency, and human ethics. Contrary to the fictional AI dystopias we often see in media such as Black Mirror, AI Ethicists are aware of the risks of AI, actively mitigating them. For example, the Future of Humanity Institute at Oxford, the Center for Human-Compatible Artificial Intelligence at UC Berkeley, and industry groups like OpenAI put their work into researching how AI systems can align with humans and their value, avoiding unnecessary consequences. These organizations don’t share the same fear for AI that the media and the public shows. As Ouchchy, Coin, and Dubljević (2020) emphasize, much of the public fear surrounding AI is fueled by “misinformation or lack of information about AI’s actual uses” rather than by objective assessments of current technology. A major area of ethical focus is algorithmic fairness. Researchers and programmers work to ensure that AI systems don’t amplify or focus on social biases such as race, gender, religion, social status, economic status, etc. AI models go through techniques like data auditing, transparent information, and post HOC analysis. However, media portrayals rarely focus on these factors, this can be partially attributed to the lack of knowledge about what these techniques actually do and how AI works in general. But this still leads viewers of media to believe that their vision of evil AI taking over the world will come true as they don’t have correct parameters. Another concern about real life AI is the transparency of it. Many AI systems can act as “black boxes”, making decisions based on complicated learning processes that are hard for people to understand.

Many of these concerns have been addressed by leading tech companies, leading to initiatives aimed at better explaining the Ai processes. This includes developing new AI systems whose decision-making processes can be understood by people. An example of this would be Google’s sixth annual Responsible AI Progress Report (Feb. 2025) This commitment to transparency directly counters the “uncontrollable AI” trope often seen in media, yet these efforts rarely receive significant coverage outside of more focuses and specialized journalism. As The Royal Society (n.d.) explains, “balanced AI narratives” are necessary to reflect the ongoing work to develop technologies that are both capable for the things we use them for, but also manageable and understandable to humans. On top of that, many real-world debates about AI revolve around governance rather than technological inevitability. Unlike media representations where AI systems gain sentience and power, real ethical problems stem from things such as bad frameworks, insufficient testing, or economic pressures pushing developers to roll out incomplete systems. Younger (2024) stresses the need for more responsible media storytelling that acknowledges the primarily human work that goes into the success or failure of an AI system. AI does not think outside of human control or what it was programmed to do, it is a tool. Though there is a real relevant issue when it comes to AI, with the misuse or mismanagement of these AI, allowing them to be used for political or profit gain. Concerns about surveillance, political information, and autonomous weapons all center around human agency, not the AI systems themselves. Christina Pazzanese takes a quote from Michael Sandel, a political philosopher, “ ‘Debates about privacy safeguards and about how to overcome bias in algorithmic decision-making in sentencing, parole, and employment practices are by now familiar,’ said Sandel, referring to conscious and unconscious prejudices of program developers and those built into datasets used to train the software. ‘But we’ve not yet wrapped our minds around the hardest question: Can smart machines outthink us, or are certain elements of human judgment indispensable in deciding some of the most important things in life?’” (Pazzanese, 2020). Part of the problem lies with the media, which acts as if this is inevitable rather than contingent on policy decisions and human values. By focusing on dramatic but unlikely scenarios, media representations distract from the critical real-world questions that demand urgent attention: How do we ensure that AI systems are used ethically? How do we design regulatory frameworks that encourage innovation while protecting human rights? How do we distribute the benefits of AI equitably across different sectors of society? Questions being discussed in important development circles but not circulated around the people by the media.

In conclusion, the media’s portrayal of Ai has had a profound and lasting impact on the public understanding and trust of AI. By focusing heavily on themes of emotional intelligence, existential threats, and ethical failures, many media narratives have created an image of AI that focuses on unfair depictions of dystopian robot landscapes. Media such as Her and Black mirror explore questions about humanity and its relationship with AI, but often in a way that misrepresents the capabilities of AI systems. Moving forward in the current climate, it is essential for media developers and journalists to foster a more informed public narrative about Ai and its capabilities. Fictional media should be able to explore questions and ideas of technology and other topics but do so in a way that allows people to make informed decisions rather than getting a few clicks on a news story. A better public understanding of our tools will allow us to use them most effectively.

Sources

Anderson, M. (2017, October 4). 6 key findings on how Americans see the rise of automation. Pew Research Center. https://www.pewresearch.org/fact-tank/2017/10/04/6-key-findings-on-how-americans-see-the-rise-of-automation/

Fast, E., & Horvitz, E. (n.d.). Long-term trends in the public perception of artificial intelligence. Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17).

Ouchchy, L., Coin, A., & Dubljević, V. (2020). AI in the headlines: The portrayal of the ethical issues of artificial intelligence in the media. AI & Society, 35(4), 927–936. https://doi.org/10.1007/s00146-020-00965-5

Pazzanese, C. (2020, October 26). Ethical concerns mount as AI takes bigger decision-making role in more industries. Harvard Gazette. https://news.harvard.edu/gazette/story/2020/10/ethical-concerns-mount-as-ai-takes-bigger-decision-making-role/

The Royal Society. (n.d.). AI narratives: Portrayals and perceptions of artificial intelligence and why they matter. The Royal Society. https://royalsociety.org/topics-policy/projects/ai-narratives/

Younger, R. (2024, August 14). Scripted reality: How AI is represented in the media. Ayzenberg Group. https://www.ayzenberg.com/insights/scripted-reality-how-ai-is-represented-in-the-media/