Behind the screen
Firstly. the main mystery is the technology and software behind AI platforms and applications. Even AI researchers have difficulties understanding eg how exactly the partly hidden multi-layers of neural networks interact in machine learning to produce language, voice, or visualization. Similarly, brain researchers have difficulties understanding how the 86 billion neurons and trillion synaptic connections of the human brain produce out of their constantly fluctuating electrochemical process human self-awareness, memories, cognitive functions, and all other contributors to intelligence.
Secondly, users of AI usually don't see behind the screen and thus they don't see what it needs to produce AI.
In response to the second mystery Kate Crawford and Vladan Joler produced already in 2018 an anatomy of an AI system. They chose the example of Amazon Echo which you may know as Alexa from your own home:
'A cylinder sits in a room. It is impassive, smooth, simple and small. It stands 14.8cm high, with a single blue-green circular light that traces around its upper rim. It is silently attending. A woman walks into the room, carrying a sleeping child in her arms, and she addresses the cylinder.
‘Alexa, turn on the hall lights’
The cylinder springs into life. ‘OK.’ The room lights up. The woman makes a faint nodding gesture, and carries the child upstairs.
This is an interaction with Amazon’s Echo device. 3 A brief command and a response is the most common form of engagement with this consumer voice-enabled AI device. But in this fleeting moment of interaction, a vast matrix of capacities is invoked: interlaced chains of resource extraction, human labor and algorithmic processing across networks of mining, logistics, distribution, prediction and optimization. The scale of this system is almost beyond human imagining.'
Crawford and Joler mapped what's needed in the background to produce this seemingly simple tool.
The map is comprehensive, and you have to zoom in to identify how important the Global South is, for example, to extract minerals needed for production or to prepare and label data.
The basics of AI include computing power, data, and algorithms but they work only with enormous input of finances, electricity, talent, research, creativity and an enabling regulatory framework. But at the beginning of the process stands the relation between value extraction and production and it represents one of the basic elements of a map, from the geological process, through life as a consumer AI product, and ultimately to death in an electronics dump.
While leaders in the tech industry underscore how much AI can increase opportunities and prosperity for all, authors like Crawford or Rachel Adams analyze how the new technologies and their global supply chain are already now exacerbating economic and social inequalities due to uneven rates of investment, adoption, and use of the new technologies. To quote from the paper by Crawford and Joler: 'Amnesty has documented children as young as 7 working in the mines. In contrast, Amazon CEO Jeff Bezos, at the top of our fractal pyramid, made an average of $275 million a day during the first five months of 2018, according to the Bloomberg Billionaires Index. A child working in a mine in the Congo would need more than 700,000 years of non-stop work to earn the same amount as a single day of Bezos’ income.'
This is one reason why researchers and practitioners from a broad range of disciplines and backgrounds founded earlier this month in Paris the International Association for Safe and Ethical Artificial Intelligence (IASEAI), stating, 'Ensuring safe and ethical artificial intelligence is a global challenge. We must work together to achieve it.'
A closing note for all those concerned about the governance of AI as a risk for the development of AI: Please compare other sectors like automobile, airplane, and train production and traffic. These are highly regulated industries where every essential screw or material to be used needs to be certified to reduce the risks of accidents. And users appreciate the security provided. To think that nothing similar is needed for AI safety and ethics is ignoring the risks. As the President of IASEAI and computer scientist Stuart Russel wrote "The development of highly capable AI is likely to be the biggest event in human history. The world must act decisively to ensure it is not the last event in human history."
References
Kate Crawford and Vladan Joler (2018) Anatomy of an AI System. The Amazon Echo as an anatomical map of human labor, data and planetary resources. https://anatomyof.ai/
Rachel Adams (2025) The New Empire of AI. The Future of Global Inequality. Polity Press, Cambridge.
Kate Crawford (2021) Atlas of AI. Yale University Press, New Haven and London.
Stuart Russel (2021/2024) Human Compatible. AI and the Problem of Control. Pinguin Random House, UK
International Association for Safe and Ethical Artificial Intelligence (IASEAI). https://www.iaseai.org/