IT Giants and Their Operations: Should We Be Concerned? 

The following is an adapted extract from The Cultural Industries, fifth edition, by David Hesmondhalgh. 

The increasing presence of information technology (IT) corporations in business and everyday life has been referred to at a number of points in my book, The Cultural Industries. There are numerous reasons to be concerned about their growing presence:  

• IT firms have been much more lightly regulated than rival firms in sectors such as media, telecoms and consumer electronics. Indeed, this helped to fuel their spectacular growth in the 21st century (cf Chapter 6).  

• They exert considerable lobbying power, potentially distorting public policy in their favor – see the discussion of the ‘fifth wave’ of policy in section 6.5.  

• We saw above that dubious forms of surveillance and data gathering are at the heart of their operations.  

• They assiduously avoid tax (see this BBC report).  

• They have spread their operations across the world and in spite of some well publicised efforts to claim that they are bringing benefits to poorer countries or regions, they have done so on terms that some have labelled using concepts such as ‘digital colonialism’ (see Chapter 14).  

• There is considerable evidence that, in spite of some efforts to conform to green goals, their business models, based on cycles of obsolescence and replacement, are deeply damaging to the environment (see Jennifer Ellen Good’s paper on iPhones and Richard Maxwell and Toby Miller’s 2012 book Greening the Media).  

The tech companies are further extending their reach over our experience of the world, and capturing huge amounts of data about us as they do so. Since the early 2010s, there have been increasing calls by commentators and policymakers for stronger scrutiny and regulation, and there have been some movements in this direction, though mainly on the grounds of competition law, such as the European Commission’s €2.4 billion fine of Alphabet/Google in 2017 for promoting its own online shopping service in its search results. In the United States during the 2021–2025 presidential administration of Joseph Biden, the Federal Communications Commission under Lina Khan sought to move in the direction of limiting their power (Kang 2024), filing lawsuits against Amazon and Meta based on anti-competitive behavior and investigating relationships between tech giants and AI start-ups.

Donald Trump has sent mixed messages, working closely with Elon Musk and allowing other tech billionaires to court him. Yet even such actions, based on principles of competition rather than on broader questions about the well-being of citizens and societies, represent only small dents in the armor of these vastly powerful corporations. Some critics advocate much more radical interventions such as the public ownership of data repositories, under systems of democratic control by citizens. But this seems a distant prospect. 

Meanwhile, the onset of artificial intelligence threatens to worsen further the effects of digital networks on climate change and to entrench yet further the dubious power of the IT sector. The relentless drive for power evident in the development of search and social media is even more apparent in the recent evolution of those technologies that are generally and problematically known as AI. I use the word ‘problematically’ here because of the profound uncertainties surrounding how to define ‘intelligence’ in general (see pages 89–101 of Karen Hao’s 2025 book Empire of AI).

Moreover, many of the recent developments are associated with just one type of AI method, generally known by scientists as ‘machine learning’ (a term not without problems of its own – see Melanie Mitchell’s description of pages 109–39 of her 2019 book Artificial Intelligence: A Guide for Thinking Humans), whereby and specifically a development known as ‘deep learning’ or ‘neural networks’, which is reliant on vast data capture and computer processing capacity. But when, from the early 2000s onwards, the internet made available vast amounts of data, and as businesses such as Amazon, Alphabet and Microsoft invested some of their vast profits into cloud computing, significant advances in the results of ‘deep’ machine learning were made. 

In this context, some key figures and organizations began to claim that something increasingly labelled as ‘artificial general intelligence’ (AGI) was on the horizon: a supposed state where computers could achieve human levels of intelligence. There have been debates since the 1950s about whether this would ever be possible, and if it were, when, and also whether the results would be a terrifying loss of human control over machines or beneficial (see Mitchell again). By the 2010s, businesses and scientists were claiming that AGI was around the corner, and it could indeed be harnessed for good – and this was an excellent way of gaining financing (see also Ruha Benjamin’s essay The New Artificial Intelligensia).

One particularly prominent company was OpenAI, founded by a mix of Silicon Valley investors and computer scientists in 2015, including Elon Musk and the company’s later CEO Sam Altman. In her intriguing book about this company, Hao has written about how they became ‘the poster child’ for a line of thought that made grandiose promises about the potential of AGI – that it would ‘solve climate change, enable affordable health care, provide equitable education.’ But, as Hao observes, OpenAI ‘cannot say how the technology will deliver on these promises – only that the staggering price society needs to pay for what it is developing will someday be worth it’ (p. 93).