Bellow are a small collection of essays and technical documents I wrote as part of my masters degree.

 Critical and Creative Media Research 

Does using AI generated art in the advertisement of free to play puzzle games on the Google Play Store make a game less likely to be downloaded in Ireland? 

By Ross Huebner
Semester 1
December 2024 

Introduction 

I knew going into this project that I wanted to touch on two research goals specifically. Firstly, I wanted to discuss the spread of AI generated media. Generative AI like ChatGPT and Midjourney are currently a hot button topic, and I believe that making this the focus of my research is practical as I can more readily find and access up to date, relevant material. Secondly, I want to discuss the consequences of the unchecked spread of AI generated content on media industries and public opinion. Due to my chosen career path as a writer and journalist I feel that I have a personal investment in this topic and wish to both educate myself more on it and explore the ways in which governments, media companies, research institutions and individuals can recognise and interact with non-human media. This approach suited me well as I benefitted from a strong investment in the subject matter. However, early in the process I found that my research and writing had been subject to a degree of unconscious bias against AI generated Media. To generate a more nuanced, holistic research question I made the conscientious choice to amend the criteria I gave myself and consider viewpoints that I otherwise would have considered ancillary to generate a more varied perspective on the topic. I found this shake up to my methodology to be a more intellectually stimulating approach as it allowed me to generate a more compelling argument that should firmly stand up to scrutiny. With my research goals in place, I considered my options and settled on the following research question: “Does using AI generated art in the advertisement of free to play puzzle games on the Google Play Store make a game less likely to be downloaded?” hereafter referred to as my research question or RQ.   

AI generated artwork is a controversial topic in most creative industries. Businesses and hobbyist's laude the software's ability to cheaply and infinitely generate artwork of anything one can imagine. Advertisements, websites, product designs, game and movie assets or even entire pieces of entertainment media can in theory be generated and sold for next to no cost or time commitment form the creator. Proponents claim this would decrease financial and time costs for businesses immensely. It would also enable non artists to create and distribute “art” of their own without the need to hire a trained artist to forge their vision or to learn the craft themselves. On the other hand, opponents of the technology describe a bleaker outlook. AI generated art is a threat to the livelihoods of artists, designers and creators in all industries. They fear that companies whose main mission is profit would be eager to replace a position as costly as an artist with a machine and in the process would destroy countless jobs across all branches of the media industry. Another aspect is the creative act itself, will this be lost to the endless variations on a theme without the creative spark, that synthesizes something totally new and possibly brilliant. 

AI art also raises questions of legality. To generate illustrations, providers of programs like Artbreeder and Midjourney train their AI on the already existing work of other artists. The fact that this is as simple as copying and pasting an image found on the internet into one such program raises concerns of ownership and copyright infringement. Many artists feel like they are powerless to stop this due to the universally accessible nature of the internet and the current lack of legislation limiting such new software. The technology also raises ethical questions. If humans are no longer the ones creating art, can it even be called art? The Oxford dictionary defines art as “the expression or application of human creative skill and imagination”. Can an AI apply skill or imagination? What effects will AI art have on future generations of art and the generations of artists that create it? How will our culture develop when our media no longer comes from us?  

My research question focuses on the mobile games industry as it is a highly saturated marketplace where often more emphasis is placed on the marketing than the games themselves. Mobile games tend to be simple, have broad appeal and encourage the player to engage with them in regular short bursts rather than prolonged gaming sessions. This is done to maximise the players exposure to advertisements or encourage in app purchases to boost one's progress within the game briefly. Such games can be produced easily and, on a budget, leading to app stores such as the google play store being inundated with hundreds of derivatives every year. Most commonly these tend to be some sort of puzzle or tycoon game as their core gameplay loop can be reused repeatedly with changes to the art style.  

Standing out amongst the crowd is therefore difficult and costly to do. By utilizing AI a developer can create promotions for their game for next to no cost. Reducing the costs of the creators venture even further. However, as it stands AI art remains an unpopular form of media. This is due to the often unappealing and “uncanny valley” look of such pieces. Furthermore, many developers utilize pornographic or offensive pieces to catch the attention of potential customers. This has led to such games being rather stigmatized and considered raunchy and low effort. For my research I wanted to explore the actual effects of using AI art in promotional material and determine whether the use of AI is truly such a detrimental business strategy. It would be unfeasible to track the downloads and popularity of games across multiple distribution platforms and genres. As such I decided to limit my research to the Google Play Store as it is more readily accessible. I also focused on the puzzle game genre as it is statistically more popular on mobile. Sales trends and popularity of such games are also easily tracked by the in-app popularity filter and public available records on the industry such as statista.com.  

Explaining my chosen literatures 

To support my research, I went about finding existing academic papers that I could use as a base to work off. To support my claims, I looked for articles that engaged in topics of AI art advertising. How such art is perceived, how that perception involves downloads from customers and whether the stigmas associated with AI art impact a game’s marketability. I also investigated mobile gaming advertisement in general to see whether trends were developing with regards to AI generated art.  

AI vs. Human: Ad Creator Influence: How Ad Creators Shape Consumer Responses and Acceptance of AI in Advertising. 

This thesis by Louisa Elsa Ester Horgby and Daniele Galizzi aims to “investigate the effects of the belief of AI versus human made ads on consumer behaviour dimensions”. The paper is a comparative analysis that compares the results gathered from two survey groups (A and B). Both groups were shown the same ad, but group A was told that the ad was generated by AI. Meanwhile, group B was told that the ad was not generated by AI. The goal of the paper was to determine what factors influenced the participants opinion on the use of AI in the ad.  

At the core of my own research question is the customers relationship to the product in question. The knowledge of the existence of AI art within a digital product is the first hurdle in a customer's potential acquiring of it. The initial discovery of the product notwithstanding. I believe that understanding a customer's first impressions of a product is a vital step in the sales (download) pitch for that product. “First impressions set the stage for the remainder of a consumer relationship. Companies don’t get a second chance to make a good first impression...” - (Reichheld.F, 2024) and included this paper as a source of empirical data. 

Evaluating consumer responses to AI-generated imagery in social media advertisements 

This thesis by N. Van der Steppen much like the work of Horgby and Galizzi discussed above aims to investigate the effects of how AI art is perceived on digital apps. But Van der Steppen’s research differs in two ways. Firstly, Van der Steppen focusses broadly on apps in general not just games. The author analyses the effects that disclosing the existence of AI art in products has on a customer's opinion of the product and its producer. The author does so by means of an online experiment that discloses the existence of AI to a participant in one of three different ways. Immediately and voluntarily disclosing the use of AI art. Involuntary disclosure (This is done after exposure to the ad through a separate form) and no disclosure where the use of AI is not revealed at all. 



Participants were later given a set of open questions to explain their behaviour towards AI generated art. This neatly demonstrates my second reason for including this paper, namely that unlike the qualitative nature of Horgby and Galizzi’s comparative analysis that focuses on understanding social data, Van der Steppen’s work is a quantitative online experiment designed to produce raw numerical data that can be used to form a statistic.

The Impact of the Rise of Mobile Games on the Creativity and Structure of the Games Industry in China 

This chapter from the book mobile gaming in Asia by Anthony Fung serves as an early insight into the nature of the mobile gaming industry. The author analyses how the mobile gaming industry developed in Asia and in particular China as well as how creativity among developers was moulded and changed by the emergence of this gargantuan industry. I included this article in my research as way of highlighting the nature of the Mobile gaming industry and how marketing and advertisement were generally handled in a time before AI art existed. That way I could compare and see if trends were already developing or are currently emerging and maybe gain some insight into how new technology alters the industry.  

Retention in free-to-play mobile games: a case study 

This case study by Timo Toski seeks to understand what makes players want to spend time with the games that they play. What game design decisions can be made to encourage longer gaming sessions in free to play games and how can a developer encourage its player base to keep returning to play. This research was carried out as a literary review and by direct subject interview. Game developers and publishers were interviewed on what game mechanics they used to hook players and keep them playing their games and how exactly these mechanics accomplish the required effect. To support my own research, I wished to include analysis of player behaviour to illustrate what makes people want to engage with games at all. Advertisements lure customers in but with games, players often already know what genres and styles they like. I wish to know if AI art is a factor that can influence their decisions as well. 

Methodologies 

My research is built around the opinions of people and the statistics that these opinions inform. As such I knew from the outset that I wanted to take a quantitative research approach. My aim was to gather quantitative data on what kind of game advertising is most affective and then contextualise that data with qualitative data on people's opinions towards AI art. This strategy allows me to make the work more credible and limit any biases present in the project. Based on this strategy I settled on the following two methodologies. 

Methodology one: Quantitative Survey 

A quantitative survey is a research method used to generate numerical data on a participating group of people. This is typically done by means of a questionnaire where participants answer structured questions, ticking boxes next to predefined answers to signal their opinions on the subject in question. This creates measurable data that researchers can then use to draw conclusions from. In my case my research would involve a questionnaire that would include questions to categorize demographics of players by age range, nationality and gaming habits such as play time and financial investment. It would also have questions to determine the players attitude towards AI art. Whether a game containing or being marketed with AI art affects a player’s opinions on playing or downloading it and what aspects of AI art inform this decision (ethics, appeal, etc). My target group are mobile game players that use the Google Play Store so as a method of gaining participants, I decided I would distribute the survey among online communities such as r/AndroidGaming on reddit and various Android Gaming groups on Facebook and Steam. Horgby and Galizzi’s thesis demonstrates this tactic to great effect. By creating two Surveys and comparing the data gathered the researchers were able to understand what aspects of AI are appealing or unappealing to a majority crowd. 

I believe this methodology is sound, however it comes with certain difficulties. Ethically speaking gathering data of such a personal nature from participants requires the participant to submit information on their habits and beliefs which not all participants may be comfortable with. By including a waver informing a potential participant of the intended use of the data and ensuring that the information will remain anonymous and not be misused is helpful but for many surrendering such private information is simply not acceptable. Additionally Quantitative data is always statistical in nature and is as such limited in its capacity to depict complex opinions and feelings making the data gathered somewhat limiting in nature.  

Methodology two: Statistical analysis experiment 

Statistical analysis is a process by which researchers collect, compare, interpret and summarize numerical data sets to identify trends, biases or other patterns within what the data represents. Statistics can be analysed and depicted in different ways. A descriptive analysis can interpret complex data and display it in an easily understandable form such as a graph, chart or table. Inferential analysis draws conclusions and makes informed predictions for an entire group based on the relationship between individual variables. Predictive analysis predicts future events by analysing and contextualizing past trends. Prescriptive analysis allows one to reliable predict likely outcomes based current trends. Exploratory analysis also makes informed predictions but does so with data associations that are unknown to the researcher but have potential to exist based on past trends. Finally, Casual analysis focuses on the relationships between data sets, how one informs the other and draws conclusions on how one data set affects the other.  

By applying inferential analysis and gathering multiple varied data sets to then later compare the findings and draw my conclusions. I would do this by creating several ads for fake games and market them on social media like Reddit, X and Facebook. Some ads would utilize real art commissioned and bought from independent artists with the artists' consent while others would be entirely AI generated. Each piece would be unique but employ different marketing strategies in their design. Clicking on a fake ad would cause a counter for that ad to go up. This would be done either by utilizing the social media platforms internal voting system such as the system employed by Reddit or may even be done on a website created and hosted by me specifically for the experiment. 

This is an effective research method that would allow me to compare varied data sets to determine which ads were more popular and then draw conclusions. But there are difficulties in its execution. Financially, this would be an expensive project as soliciting art from a professional artist can cost between fifty to two-hundred euro depending on the level of effort put into the work. The ethics of utilizing AI generated art even in a research context is muddy at best also. Unless I receive consent from an artist, I would feel unjustified in doing so. The same goes for the ads themselves. Advertising a product that doesn't exist raises some legal questions, particularly related to fraud. The ethics of gathering data from people without consent, even when the data is as harmless as a yes or no response is ethically questionable as well.  

Conclusion 

My research question “Does using AI generated art in the advertisement of free to play puzzle games on the Google Play Store make a game less likely to be downloaded?” is relevant to my chosen discipline. By narrowing my area of research to free to play puzzle games on the Google Play Store I can make an overall more focused project. It is a topic I am morally and personally invested in as it is a key interest of mine and the topic affects my own chosen line of work. And due to its succinctness, I can carry out this research in a reasonable amount of time. I chose relevant research papers to support my claim and outlined their relevance to my proposed research question. And lastly, I chose methodologies that I believe are best suited to building a conclusive data set. A quantitative survey will allow me to create opinionated data sets depicting a consumer's attitude towards AI generated art and how that attitude informs a consumer's decision to download the app. The Statistical analysis experiment will give me multiple data sets from which I can pull numerical information on the preferences of the consumer. By crafting different images to emphasise different marketing strategies I will be able to compare what works and what doesn’t and determine which traits specifically inform a consumer's choice. I believe that a research project of this scale and scope is reasonable to commit to given the allotted time and my personal level of creativity and technical skill. I also hope that this project could inform the use of AI in the future and be used in the development of ethical guidelines for using this still nascent technology. 

Bibliography 

Boehman, Craig. “In Defense of AI Art.” Craig Boehman, 13 June 2023, craigboehman.com/blog/in-defense-of-ai-art. 

Corrall, Matt. “The Harm & Hypocrisy of AI Art.” Matt Corrall, 2023, www.corralldesign.com/writing/ai-harm-hypocrisy. 

Duncan, Rodger Dean. “Earning, and Keeping, Customer Loyalty—and How to Measure It.” Forbes, 29 Oct. 2020, www.forbes.com/sites/rodgerdeanduncan/2020/10/29/earning-and-keeping-customer-loyalty-and-how-to-measure-it/?sh=35d1444d4f98. 

Elsa, Louisa, and Daniele Galizzi. “AI vs. Human: Ad Creator Influence : How Ad Creators Shape Consumer Responses and Acceptance of AI in Advertising.” DIVA, 2024, www.diva-portal.org/smash/record.jsf?pid=diva2%3A1870682&dswid=-8655. Accessed 21 Dec. 2024. 

Greebook. “GreenBook: Find Market Research Companies and Focus Group Facilities.” Www.greenbook.org, www.greenbook.org/. 

Koski, Timo. “Retention in Free-To-Play Mobile Games : A Case Study.” Jyx.jyu.fi, 2019, jyx.jyu.fi/handle/123456789/64353, https://jyx.jyu.fi/handle/123456789/64353. Accessed 21 Dec. 2024. 

Mago, Zdenko. “FAKE-VERTISING and MOBILE GAMES: CASE STUDY of “PULL the PIN” ADS.” Communication Today, vol. 11, no. 2, 2020, pp. 132–147, www.ceeol.com/search/article-detail?id=911836. 

Meta. “Android GamingTM🎮 | Facebook.” Facebook.com, Facebook Groups, 2022, www.facebook.com/groups/androidgaming1/. Accessed 21 Dec. 2024. 

Oxford Dictionary. “Oxford Languages.” Oxford Languages, Oxford University Press, 2024, languages.oup.com/google-dictionary-en/. 

Reddit. “Reddit - Dive into Anything.” Reddit.com, 2024, www.reddit.com/r/AndroidGaming/. Accessed 21 Dec. 2024. 

Simplilearn. “What Is Statistical Analysis? Types, Methods and Examples | Simplilearn.” Simplilearn.com, 16 Nov. 2021, www.simplilearn.com/what-is-statistical-analysis-article. 

Tusla. “Quantitative Research MethodsTusla - Child and Family Agency.” Www.tusla.ie, 2023, www.tusla.ie/research/tusla-research-office/research-tools/quantitative-research-methods/. 

University of Copenhagen. “Strengths and Limitations | Better Thesis.” Betterthesis.dk, 2021, betterthesis.dk/research-methods/lesson-1different-approaches-to-research/strengths-and-limitations. 

Van der Stappen, N. 1 Evaluating Consumer Responses to AI-Generated Imagery in Social Media Advertisements. 2024, arno.uvt.nl/show.cgi?fid=175664. Accessed 18 Dec. 2024. 

Communication and Information Sciences Specialization Business Communication & Digital Media Supervisor: Dr. E. van Miltenburg Second Reader: Dr. F. Tomas. 

Turkel 

Berry, David M. 2025. “Synthetic Media and Computational Capitalism: Towards a Critical Theory of Artificial Intelligence.” AI & Society, March. https://doi.org/10.1007/s00146-025-02265-2.  

Additional sources listed above:  

Bassett, Caroline. 2021. Anti-Computing: Dissent and the Machine. Manchester: Manchester University Press.  

Fedorova, Ksenia. 2020. Tactics of Interfacing: Encoding Affect in Art and Technology. Leonardo. Cambridge, Massachusetts: The MIT Press.  

Weizenbaum, Joseph. 1976. Computer Power and Human Reason : From Judgment to Calculation. San Francisco: W. H. Freeman. 

A Close Reading of Kate Crawford’s Atlas of AI through the Lens of Yuval Noah Harari’s Sapiens and Nexus 

By Ross Huebner
Semester 2
August 2025 

Roughly 3000 years ago in ancient Mesopotamia in the city or Uruk (located in modern day Iraq) a clerk named Kushim took stock of barley deliveries that took place over the course of several months. He counted the quantity of the barley shipments as well as the period over which the deliveries were made and wrote them down as a receipt on a clay tablet. This clay tablet still exists today and is considered one of the oldest pieces of written language in the world. This story was taken from the book Sapiens by Yuval Noah Harari. It demonstrates what power the written word has held over the lives of people since the dawn of civilization. Sapiens, as well as Harari’s other book Nexus highlights humanity’s relationship with technology and how the tools and practices that we have developed came to define not just how humans control the natural world but also how we control one another. Particularly of note is the collection and compilation of data. Kushim’s tablet represents a measure of control an individual, or group held over other individuals or groups. A receipt. Physical proof of debt owed. This exertion of control through the storage of data has progressed significantly since then. The dawn of the modern age of generative AI and social media has made it so that algorithms trace every step we take on the internet. This data is stored and compiled much like Kushim’s cuneiform tablets were, but to what end exactly? How much control over ourselves do we surrender when we engage with the algorithms present in social media? In “Atlas of AI: Power, Politics and the Planetary Costs of Artificial Intelligence” Kate Crawford exposes the hidden value of data. She points out that rather than being an ephemeral, unaligned resource data holds quantifiable value as well as an environmental and human cost.   

I mentioned Harari’s work earlier in this essay as I believe it to be an ideal point of reference for discussing the relationship between power, information and civilization. Harari's works are at their core stories about stories. Both a historian and science writer, Harari analyzes human behavior as it relates to the world and society by framing it within the context of the history of mankind. For the purposes of this essay, I focused mainly on two books. Sapiens: A Brief History of Humankind and Nexus: A Brief History of Information Networks from the Stone Age to AI, the latter being particularly pertinent. Sapiens covers the evolution of Homo Sapiens from pre-history to modern times and how and why our species came to dominate the earth. At the core of the work is the thesis statement that humanity’s shared ability to believe in the value of ephemeral concepts such as gods, money, nationhood and authority coupled with our ability to cooperate has been our greatest asset in our development. As for Nexus, it is more generally applicable to my argument. The book explores humanities relation to information. The systems we developed to spread and collect information; the different means we developed to facilitate communication and how the control of knowledge has always been at the core of power and influence within society. Harari furthermore states that human advancement has always been predicated on how we share information, and as such AI is an unprecedented breakthrough.  

One of the key topics that Crawford discusses in Atlas of AI is the power awarded to those in possession of, or with the means to extract, data. In this case those would be the AI developers as well as those hosting the Data centers powering the technology. By using the historical precedent established by Harari I will be able to corroborate Crawfords claims as well as expand upon them with examples of my own.  

Atlas of AI concerns itself with the environmental, social and political costs that AI imposes on the world. Crawford argues in the chapter “Data” that AI representatives have gone to great lengths to downplay the ownership of data and instead promote it as a resource and source of capital. This kind of rhetoric aims to justify its extraction by framing it as an unrefined resource which isn't being used to its fullest potential. She states that: “data” has become a bloodless word; it disguises both its material origins and its ends. And if data is seen as abstract and immaterial, then it more easily falls outside of traditional understandings and responsibilities of care, consent, or risk. Crawford, Kate (Pg 113). This tactic mirrors those used by colonial powers as a way of justifying conquest over “primitive” peoples to extract resources without consent. The value of this gathered data cannot be understated. Data has been labeled as “the new oil” for its untapped potential as a source of easily accessible capital.  

In her Introduction, Crawford sets out her stall by arguing that artificial intelligence (AI) is not a neutral set of technologies that can be utilized by humans to progress our society. Crawford outlines how AI is becoming ever more embedded in our social and political spheres. She argues that the technology is gaining in power as it gains knowledge and becomes more immersed in the world's extractive and exploitative systems.  

Crawford disagrees with the accepted narrative that AI operates autonomously and impartially, without bias or prejudice. In emphasizing how AI systems are embedded in the social and productive life of ordinary people and how the use and distribution of planetary and environmental resources are affected. She highlights how methods of data handling can and do greatly influence political power around the world, the now famous Cambridge Analytica scandal being a case in point. In her phraseology "Mapping the terrain of AI" Crawford is not just describing the advances in AI, she is also using the map or "atlas" as a metaphor for colonialism and colonization practices. As the imperial powers used maps of their newly acquired territories to further their exploitation and extraction policies, the Downs Survey of Ireland in 1655 being a prime example, AI systems gather data which they turn into valuable information. They then use this correlated data to map, categorize and create rules and policies that then influence how the world functions. It is striking how often these rules then reinforce existing biases, hierarchies and Hobbesian power centers.  

Crawford deftly introduces the concept of AI as an engine of extraction. She shows clearly its reliance not only on the extraction of data but of natural resources to run its data centers and human labor to provide the energy and to work with the data to make it more useful. Crawford exposes the deployment of AI as an infrastructural project following the play book of imperialism, colonialism and capitalism, just as the Dutch East India Company or VOC (Vereenigde Oostindische Compagnie) chartered in 1602 began the industrial level, government backed exploitation of India and Asia. Crawford posits that just as AI development and deployment are closely bound to the functioning of capitalism it is also interwoven with the global power structures of corporate, both national and transnational, and state actors. The lion's share of these power brokers are, not surprisingly, concentrated in the Global North, the area that benefited most from colonialism and extraction. She argues that AI now benefiting from this system is operating at the expense of the poorer communities and degraded ecosystems of the global south. 

Crawford outlines the connections between big data and power. She posits that data accumulation and institutional power go hand in glove. The ability to collect and process vast quantities of data confers immense power and influence on companies and governments. This can be seen in the new forms of digital enclosure and surveillance capitalism that we see today especially in places like China and the United States. Crawford builds a foundation for understanding AI not as a purely technological phenomenon, but as a socio-technical system. She calls attention to the material dangers implicit in unregulated AI. Her analysis through the lens of history demands that we require politicians to re-examine the AI discourse and legislate while considering the ethical consequences of how AI systems are built, trained, and deployed.  
 

Reading Crawford’s work in conjunction with Harari’s Sapiens and his even more pertinent Nexus, helps us to gain a broader understanding of the destructive effects the misuse of information can have on human organization, authority and autonomy. When taken together, Crawford and Harari expose big data as reinforcing the artificial ordering of the world that supports existing hierarchical structures while masquerading as objective and fair.  In Nexus, Harari explores the historical manipulation of information networks to achieve this same end. Harari outlines how humans began to organize themselves through abstract means, something no other animal could do. Humans construct the inter-subjective realities of myth, money, religion, bureaucracies and corporations and give them power. We literally breathe life into them by believing in them. In this framing data too is just a set of structured fictions, used to generate social, economic, and political outcomes. In "Sapiens" Harari offers further proof of this analysis by positioning the power of fiction as the foundation of cooperation between large groups of early humans. He argues that Homo Sapiens conquered the world not because of superior strength or speed, but because of our unique ability to believe in shared myths like Gods, money, nations and laws like human rights. According to Harari these "things" exist only in our collective imaginations. Crawford’s account of data categories, how faces are labeled, how emotions are read and how people are classified echoes this theme in that AI systems perpetuate powerful fictions under the guise of machine neutrality. For example, classification systems like ImageNet and the Amazon recruitment tool reinforced racial and gender stereotypes, not by accident, but as a result of long-standing industrial practices and traditions. Like Harari’s "imagined orders", these practices could acquire authority through repetition, institutional backing, and the illusion of objectivity. Crawford’s critique of data also aligns closely with Harari’s thoughts on Dataism, that is the emerging ideology that data is never wrong, if you can just get enough of it. In Nexus Harari describes Dataism as the beginnings of a shift in authority from humans to algorithms. He warns us that the value of human experience is being superseded by the presumed objectivity of machines as we start to believe that these machines "know us better than we know ourselves". AI could form a new network of illusions/delusions that could prevent future generations from even attempting to expose its lies and fictions. Crawford warns too that AI systems do not simply observe the world; they shape it in many facets of life by deciding who gets hired, who gets credit, who is most surveilled and who gets medical treatment. The ideology of Dataism makes these systems seem safe and reliable, obscuring their political foundations.  Societal power structures have gone from the mystical power of kings and priests to the more transparent collective human judgment, but AI is leading toward a more opaque, bureaucratic, corporate-controlled system. The danger is not just technological overreach, but a fundamental transformation in how power operates.  

A particularly striking parallel between Crawford and Harari lies in their treatment of the invisibility of AI. Crawford emphasizes how the physical and human infrastructure of AI, the data centers powered by fossil fuels and low-wage workers often in the Global South is deliberately obscured. This is not only for the poor PR this image would generate, the industry also want to present AI as an almost magical tool, autonomous, and immaterial, it's in "the cloud" not in a data-center sweat-shop burning through cheap fossil fuel and choking the lives of people in some underprivileged area. Harari argues that the most effective myths are those we no longer see as myths. The myths that take on the illusion of being part of the natural order of things are what give "fictional orders" their power. Just as people once believed in the divine right of kings or in racial supremacy, modern societies increasingly accept algorithmic decisions as inevitable, natural, and fair. But fairness is complex and there are many different concepts of fairness.  

The approach of the two writers to the future differs somewhat, Crawford demands immediate political action where Harari is somewhat more circumspect. He takes a more historical and speculative long-term view. Crawford calls for new forms of governance, greater transparency, regulation, and what she calls data justice. Crawford suggests that in uncovering the extractive nature of the data industry, the labor, energy, and inequality that underpin the expansion of AI humans, will regain and maintain greater levels of control and autonomy.  

Both of them think that without knowledgeable intervention, the AI systems currently processing information will change our world in ways that we cannot predict. These AI may erode individual agencies, exacerbate inequality, and concentrate power in the hands of the one percent. Both claim technical and philosophical expertise is required to control and create the systems and decisions about what is fair and unbiased cannot be left solely to data scientists and the AI they work on. Such decisions can only be accepted as legitimate if society as a whole agrees on and accepts them.  

In conclusion, reading Crawford’s Data chapter alongside Harari’s Sapiens and Nexus reveals data not as a neutral natural product of the world but as just another curated fiction, embedded in the long-established industrial systems. It is controlled and shaped by corporate and political interests and wielded as a tool of control over the masses. The belief in data’s objectivity, like belief in human rights, money, corporations or nations is what gives it power. Crawford and Harari remind us; this power is neither eternal nor inevitable. It is just another story we are telling and believing, one we can still choose to rewrite. 

Bibliography 

Benjamin, Ruha. Race after Technology: Abolitionist Tools for the New Jim Code. Cambridge, Polity, 17 June 2019. 

Couldry, Nick, and Ulises Ali Mejias. The Costs of Connection : How Data Is Colonizing Human Life and Appropriating It for Capitalism. Stanford, Stanford University Press, 2019. 

Crawford, Kate. Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press, 2021. 

Harari, Yuval Noah. Sapiens: A Brief History of Humankind. Random House UK, 2011. 

Kodiyan, A.A., 2019. An overview of ethical issues in using AI systems in hiring with a case study of Amazon’s AI based hiring tool. Researchgate Preprint, 12(1), pp.1-9. 

Hutton, Ronald. The Witch: A History of Fear, from Ancient Times to the Present. New Haven ; London, Yale University Press, 2017. 

Noble, Safiya Umoja. Algorithms of Oppression: How Search Engines Reinforce Racism. New York, New York University Press, 8 Jan. 2018. 

Yuval Noah Harari. Nexus. Random House, 10 Sept. 2024. 

Zuboff, Shoshana. The Age of Surveillance Capitalism. 2018. London, Profile Books, 4 Oct.