technology – The Sense of Fairness blog

Even given my cynicism regarding the current hype about artificial intelligence (AI)*, I have to admit that it’s very clear this new technology will transform the world of work. The societal excitement about Chat GPT and other large language models (LLMs) has been matched by corporate excitement. Companies across the world are experimenting broadly, many of them keen to deploy this as a cost-saving tool.

Of course, as with every technology shift, cost-saving comes in the form of replacing people with machinery. Efficiency means being able to do things more quickly with less human intervention. If the current experiments with AI deliver, perhaps companies will redeploy those humans to other work. More likely they will remove those people, and their costs, from their business.

That’s how business, and economies as a whole, operate: moving to more efficient ways of delivering what customers and society want, to enable higher profits or simply to enable companies to compete with rivals which are also trying to reduce their costs. On the whole, this is good for economies too as more efficiency allows national resources to the deployed to where they deliver most value.

But that redeployment takes time, and technology transitions are painful processes, for individuals and for society. Discussions of efficiency, cost savings or redeploying resources divorce us from the very real human and emotional impacts of these changes, which are of individuals losing their jobs and livelihoods, and subsequently struggling for money and self-esteem. Even where a technological shift does create new opportunities (which has been the case with every such transition previously and so seems likely once again), that takes time – time in which individuals feel unanchored, unvalued, and perhaps reach an age where further employment is unavailable to them. That can serve to destabilise society further. We shouldn’t let the economics blind us to the personal and emotional.

There is much talk in sustainable investment circles of the need for a just transition (sometimes a fair and just transition) to a decarbonised world, ensuring that care is taken to protect and support those individuals whose jobs are impacted by the dramatic shift to economic activity that must come as the world finally faces up to the realities of climate change. There is also likely to need to be a fair and just transition to an AI-enabled world.

Recent work from the International Monetary Fund (IMF) begins to open a window on this challenge, building on the sentiment of managing director Kristalina Georgieva in a blog from a year ago called AI Will Transform the Global Economy. Let’s Make Sure It Benefits Humanity. The organisation is developing approaches to consider which jobs – and which economies overall – will be impacted by the advent of AI.

Most recently, IMF staff considered impacts in Asia. A blog this month, How Artificial Intelligence Will Affect Asia’s Economies, tries to map this out in more detail, based on analysis of the breakdown of jobs in each economy. The blog reflects a deeper discussion within the analytical note attached to the Fund’s most recent Asia and Pacific Regional Economic Outlook. This analysis suggests a greater exposure to AI impacts in the region in what IMF jargon terms advanced economies, while emerging economies are likely to face lower impacts. However, they also seek to assess whether those impacts will be positive or negative for jobs: around half the impacts in advanced economies are where AI is complementary to the job, potentially driving economic benefits; meanwhile in emerging economies the majority of impacts are where there is much more likelihood of workers finding their jobs replaced. The economists hedge this analysis with language such as ‘low complementarity’ and ‘displacement’ of work, but the thinking is clear.

The language was more blunt in some earlier less detailed work, suggesting AI “could endanger 33 percent of jobs in advanced economies, 24 percent in emerging economies, and 18 percent in low-income countries”. Those conclusions look more worrying than the most recent analysis, but even the lower levels of estimated disruption are very significant.

According to the most recent analysis, there is also a gendered split in the potential impacts, again potentially exacerbating existing inequalities:

The blog reads:

“The concentration of such [complementary] jobs in Asia’s advanced economies could worsen inequality between countries over time. While about 40 percent of jobs in Singapore are rated as highly complementary to AI, the share is just 3 percent in Laos.
“AI could also increase inequality within countries. Most workers at risk of displacement in the Asia-Pacific region work in service, sales, and clerical support roles. Meanwhile, workers who are more likely to benefit from AI typically work in managerial, professional, and technician roles that already tend to be among the better paid professions.”

Georgieva was clear about the risks: “In most scenarios, AI will likely worsen overall inequality, a troubling trend that policymakers must proactively address to prevent the technology from further stoking social tensions.”

The IMF economists are increasingly clear about what needs to be done about these inequality risks. According to them, a just transition will require:

Effective social security nets
Reskilling programmes for affected workers
Education and training to enable effective application of the AI opportunity, particularly for those economies where AI is currently seen to have low impacts – so that the positive benefits can be enjoyed
Regulation to promote ethical AI use and data protection

The IMF, in its AI Preparedness Index, suggests that there is a broad spread in the readiness of global economies for this coming wave of technological disruption:

Again, as things stand it seems that the greatest likelihood is for AI to exacerbate existing inequalities. Preparing for this major economic shift will demand fresh policies and investment. These are significant challenges for world economies, for companies as they embed AI into their workflows, and for global investors, to rise to.

*I have my doubts about each of the A and the I in artificial intelligence: calling an activity ‘artificial’ when it depends on the horrific grinding work of many people to scrub its results seems inaccurate; and calling it ‘intelligent’ when it is simply a logic puzzle about the likelihood of putting one word after another – the stochastic parrots as described in that prescient article (I particularly like the analogy of Emily Bender, one of the authors of that article and a professor at the University of Washington, that AI is reproducing text in the way people might if they had unrestricted access to the National Library of Thailand but without pictures or dictionaries to enable them actually to understand or translate the language). A more recent article touching on these matters is the excellent Ask me Anything! How ChatGPT got Hyped into Being, which among other things states this fundamental truth: “LLMs are not designed to represent the world. There is no understanding by the artificial agent (chatbot) of the meaning of the output it creates. It is us humans who create that meaning.” More directly, the word soups that I have been presented with by colleagues show very clearly the limits of the technology in doing anything without clear instruction and precise pre-existing materials to work with.

See also: What’s a fair use?

I am happy for confirm as ever that the Sense of Fairness blog is a purely personal endeavour.

AI Will Transform the Global Economy. Let’s Make Sure It Benefits Humanity, Kristalina Georgieva, IMF, 14 January 2024

How Artificial Intelligence Will Affect Asia’s Economies, Tristan Hennig, Shujaat Khan, IMF, 5 January 2025

Asia and Pacific Regional Economic Outlook, IMF, November 2024

Thought experiment in the National Library of Thailand, Emily Bender, Medium, 25 May 2023

Ask me Anything! How ChatGPT got Hyped into Being, Jascha Bareis, 2024

In a small (a very small) way, I collect 18^th and 19^th century company tokens. These symbolise for me the worst of the financial exploitation of the industrial revolution. It was not enough for the industrialists to ruthlessly exploit the excess availability of labour and pay badly the new industrial workforces of their dark satanic mills*. In many cases they also paid not in money that could be spent anywhere, but in scrip – tokens that could only be spent at the company’s own store. Prices there reflected the guaranteed market, so workers were exploited over again. These practices were progressively abolished in England from 1831 onwards by the oddly-named (at least to modern ears) Truck Acts. There is similar legislation to bar such abuses elsewhere in the world – though not everywhere.

As we know, this financial exploitation sat alongside brutal working conditions where injuries and even death were common, accepted outcomes of the industrial process. That was a lack of health and safety gone mad.

We’ve known for a while that the AI revolution depends on a similar exploitation of the health and safety of workers. The stories of the employees of Sama in Kenya, who helped train ChatGPT, are disturbing. The human training of these supposedly ‘artificial’ intelligence systems (ChatGPT is no worse in this regard than its rivals) involves individual people being exposed to the worst things that the draft forms of AI machines produce. As the machines’ training materials are the entire internet, this replicates the biases of the present and prejudices of the past, and includes all the filth that humankind has produced in recent years. The human job is to tell the AI not to produce further paedophilia, repeat racist incitement, and so on – but in order to do that, people need to read and look at truly horrific material.

Sadly, the people who did this work are not treated well. Their mental health disorders are the equivalents of the fingers on the floors of cotton mills. These seem not to trouble those who are making epoch-making amounts of money, and little enters the public discourse so that it has minimal impacts on consumer use of these products.

But it turns out that such physical exploitation of people’s health isn’t all that’s going on in the current technological revolution. Amazon has revived the company scrip model. It pays some of its MTurk workforce in Amazon gift cards, and severely constrains how those gift cards can be spent so that the workers are unable to get full value from them. MTurk – mechanical Turk in full – is the name for the distributed self-employed workers who perform tasks that help test and train much modern IT and so ensure its smooth working. The name aptly reflects the 18^th century supposedly mechanical chess board, called the Turk, that toured Europe playing matches. Instead of being an automaton, the Turk actually only worked because in place of a machine there was a skilled human chess player crammed uncomfortably into the space under the board.

In the same way, the human work that is necessary to help train current supposedly ‘artificial’ intelligence technologies suggests there is some artifice in calling them artificial.

The DAIR Institute (Distributed AI Research Institute in full) – the grouping formed by the authors of the Stochastic Parrots paper – have launched a Data Workers’ Inquiry trying to bring forward the stories of the people who are directly involved in facilitating the current technology revolution, and who all too often are its unhappy victims. Consistent with the DAIR philosophy, this includes putting the voices of the individual workers themselves at the heart of the work, and facilitating them in telling their stories in the forms they find most comfortable and appropriate.

One of the stories discussed on the launch webinar, and on which the Inquiry has published a short paper, highlights this issue. Though its author, Alexis Chávez, is from Venezuela, the use of gift cards as payment isn’t restricted to countries where currency or sanctions issues might limit payments in real money: Chávez shows that the practice applies in (at least) Brazil, Colombia, India, Kenya, Mexico, Pakistan, and the Philippines. The paper details the convoluted processes needed for these individuals to gain value from their gift card payments, which mean that they are in effect forced to take discounts of 20-30% in order to extract value. It’s like the mark-up in the company store.

And it’s hard to argue with Chávez: “Even though Amazon does not see them as employees but as independent contractors, it’s our right to be paid fairly and in a useful manner.” We fondly thought the worst of the financial practices of the industrial revolution were far behind us – they should be – but unfairness clearly persists in the very human side of the supposedly ‘artificial’ intelligence business.

The second event in the Data Workers Inquiry happens this week, and Chávez himself is due to speak on August 26^th.

* This phrase is from William Blake’s preface to his lengthy 1804 poem in praise of John Milton, words that are now known to us as Jerusalem. Please consider supporting the campaign to save Blake’s cottage in the West Sussex village of Felpham.

I am happy to confirm as ever that the Sense of Fairness blog remains a wholly personal endeavour.

Mental Health and Drug Dependency in Content Moderation, Fasica Berhane Gebrekidan, the Data Workers Inquiry, June 2024

Click Captives: The Unseen Struggle of Data Workers, Wilington Shitawa, the Data Workers Inquiry, June 2024

The African Women of Content Moderation, Botlhokwa Ranta, the Data Workers Inquiry, June 2024

OpenAI Used Kenyan Workers on Less Than $2 Per Hour to Make ChatGPT Less Toxic, Billy Perrigo, Time, 18 January 2023

Data Workers Inquiry

The Distributed AI Research Institute (DAIR Institute)

The Impact of Gift Card Payments on MTurk Workers, Alexis Chávez, the Data Workers Inquiry, June 2024

Tag: technology

A just AI transition?

Amazon resurrects worst of the industrial revolution