Martijn Kieft (2018). 'Algorithms Rule Us All'
https://www.youtube.com/embed/NFF_wj5jmiQ
Synopsis: "algorithms Rule Us All speaks to data scientists and programmers themselves to answer the question of what they think is unfolding with the so-called Big-Data society and how we’re continuing to hand over our lives and societies to the whim of machines that are driven by rapacious profit-driven companies, for the goal of commodification of everything. What are the implications for human autonomy, society, democracy?" (Martijn Kieft, 2018). https://thoughtmaybe.com/algorithms-rule-us-all/ Transcript: "I think we're [ProPublica] best known for our analysis of criminal risk scores so this is software that used across the US to give a score predicting whether somebody who has been arrested is likely to go on to commit future crimes in the next two years and so this is you know software that has not been analysed by anyone independently so we went and obtained through public records requests the scores that were assigned 18,000 people in two years in one jurisdiction in Florida then we went to see where was it accurate did they really truly predict whether those people went on to commit crimes and it was only about 60 percent accurate so a little bit better than a coin toss but when it was wrong it was wrong really differently it was twice as likely to say that a black defendant was gonna commit a crime when they actually weren't and it was twice as likely to say a white defendant would not go on to commit a crime when they did so it had a real disparity in the error rates which was something that no one in that field had ever really noticed or recognized before and it's kicked off like a nationwide debate in computer science about how to balance this type of error rates in the future." https://www.youtube.com/watch?v=NFF_wj5jmiQ&t=1389s Transcript: "the Facebook algorithm seen by many as the most influential in the world is receiving a great deal of criticism recently because the way the algorithms function on social media do not always appear to correspond with the users interests [as data scientist, Cathy O'Neil https://en.wikipedia.org/wiki/Cathy_O%27Neil explains] 'we define success in a very narrow biased way in the way that works for us but not doesn't work necessarily for the people we're targeting doesn't work necessarily for the for the public good that I think a good example there is the Facebook algorithm the Facebook News Feed algorithm has been optimized to to engagement which is to say to keeping us on Facebook which is a proxy for their profit but it has not been optimized to something that would actually be good for the public namely truth or a civil dialogue or or just knowledge or information'." https://www.youtube.com/watch?v=NFF_wj5jmiQ&t=1726s Related: "algorithms are limited tools for understanding the world, frequently as flawed and biased as the humans who create and interpret them. In this brief animation, which was adapted from a 2017 presentation at the Royal Society of Arts (RSA) in London, the US data scientist Cathy O’Neil, author of Weapons of Math Destruction (2016), argues that algorithms can be useful tools when thoughtfully deployed. However, their newfound ubiquity and massive power calls for ethical conduct from modellers, regulation and oversight by policymakers, and a more skeptical, mathematics-literate public" (Stephenson, A., 2018). https://aeon.co/videos/algorithms-are-opinions-not-truth-machines-and-demand-the-application-of-ethics Quote: as Jaron Lanier https://en.wikipedia.org/wiki/Jaron_Lanier observes "the social media by itself doesn't do anything it's waiting for energy coming in from people; it's people's attention and interest that is the fuel that allows the social media engines to make money through engagement. And so when the often times these social movements are started by young idealistic people who are the most engaged the most tech-savvy as they say the most able to do so and they start generating engagement the, the young young people in the Arab Spring, the young people in Black Lives Matter and so forth so suddenly they have input this fuel into the system now the algorithms have to say what can we do with this fuel and so one option is we will allow this feel to only engage those people who started it that is not very efficient what's more efficient is to say how can we use this fuel to engage other people and let us be clear about something there is a an asymmetry which is tragic but it's very real and the asymmetry is that negative emotions are more engaging and powerful and easier to bring up and efficient and profitable and intense than positive emotions so if you have all these positive emotions coming in saying we want something better we want to support these people the algorithms naturally without any evil plan will turn them into negativity by finding the people who are annoyed the anti people and milking and milking and milking because negativity is more efficient more profitable more engaging so if you want to have an anti-fascist message that'll be used to find all the fascists and introduce them to each other and put them into a cycle of more and more and more incitement and that is the only way for these companies under their present business models to maximise their engagement and maximise their profits" https://www.youtube.com/watch?v=NFF_wj5jmiQ&t=1928s Quote: "In the process, Dataism inverts the traditional pyramid of learning. Hitherto, data was seen as only the first step in a long chain of intellectual activity. Humans were supposed to distil data into information, information into knowledge, and knowledge into wisdom. However, Dataists believe that humans can no longer cope with the immense flows of data, hence they cannot distil data into information, let alone into knowledge or wisdom. The work of processing data should therefore be entrusted to electronic algorithms, whose capacity far exceeds that of the human brain. In practice, this means that Dataists are sceptical about human knowledge and wisdom, and prefer to put their trust in Big Data and computer algorithms" (Harari, Y. N., 2017, p.214). Quote: "Research found 276,149 sexual deepfakes on a single dedicated site in 2023, with 96% depicting women. Worldwide, 24 million people visited ‘nudification’ services in September 2023 alone and 9 ?in?10?reports to the Internet Watch Foundation of child sexual abuse online?sadly contain images taken by?children?themselves, often coerced by predators and with potentially devastating consequences" (Kendall, L. and Phillips, J., 2025. Quote: "The 'put her in a bikini' trend began quietly at the end of last year before exploding at the start of 2026. Within days, hundreds of thousands of requests were being made to the Grok chatbot, asking it to strip the clothes from photographs of women. The fake, sexualised images were posted publicly on X, freely available for millions of people to inspect. ... This unprecedented mainstreaming of nudification technology triggered instant outrage from the women affected, but it was days before regulators and politicians woke up to the enormity of the proliferating scandal. The public outcry raged for nine days before X made any substantive changes to stem the trend. By the time it acted, early on Friday morning, degrading, non-consensual manipulated pictures of countless women had already flooded the internet. ... As people slowly started to understand the full potential of the tool, the increasingly degrading images of the early days were quickly superseded. Since the end of last week, users have asked for the bikinis to be decorated with swastikas... While in the past, people had to download specialist apps to create AI deepfakes, the upgraded image-generation tools available on X made the nudification function easily available to millions of users, without requiring them to stray to darker corners of the web. 'The fact it is so easy to do it, and it is created within a minute – it has caused a huge violation, it shows these companies don’t care about the safety of women,' Evie said" (Gentleman, A. and Horton, H., 2026). Bibliography: Kieft, M. (2018). 'Algorithms Rule Us All' VPRO https://en.wikipedia.org/wiki/VPRO Retrieved from YouTube on December 02, 2025. Gentleman, A. and Horton, H. (2026). "‘Add blood, forced smile’: how Grok’s nudification tool went viral". [online] the Guardian. Available at: https://www.theguardian.com/news/ng-interactive/2026/jan/11/how-grok-nudification-tool-went-viral-x-elon-musk [Accessed 11 Jan. 2026]. Martijn Kieft. (2018). 'Algorithms Rule Us All'. Thought Maybe. https://thoughtmaybe.com/algorithms-rule-us-all/ Yildiz, M. (2022). 'The Human Algorithmic Question : A Social Justice Imperative. International Council for Media Literacy'. [online] Available at: https://ic4ml.org/journal-article/the-human-algorithmic-question-a-social-justice-imperative/ [Accessed 11 Jan. 2026]. Harari, Y. N. (2017). 'Homo Deus : a brief history of tomorrow' (First U.S. edition). Harper, an imprint of HarperCollins Publishers. https://readandlaugh.wordpress.com/wp-content/uploads/2018/04/homo_deus_a_brief_history_of_tomorrow_pdf.pdf Kendall, L. and Phillips, J. (2025). 'Protecting young people online at the heart of new VAWG strategy'. [online] UK Home Office, Department for Science, Innovation and Technology. Available at: https://www.gov.uk/government/news/protecting-young-people-online-at-the-heart-of-new-vawg-strategy [Accessed 12 Jan. 2026]. Stephenson, A. (2018). 'Algorithms are opinions, not truth machines, and demand the application of ethics' | Aeon Videos. [online] Aeon. Available at: https://aeon.co/videos/algorithms-are-opinions-not-truth-machines-and-demand-the-application-of-ethics.
