Selected as a Financial Times Best Summer Book of 2025: Economics
Selected as a New Statesman Book of the Year 2025
The Centre for Enterprise, Markets and Ethics is delighted to announce the official release today of our latest publication, a book by Brian Griffiths (Lord Griffiths of Fforestfach) which addresses the problem of inflation – Inflation Is About More Than Money: Economics, Politics and the Social Fabric.
Further details can be found below.
Purchase Details
Available for purchase at London Publishing Partnership, Amazon, and can be obtained from retailers and booksellers.
It is also downloadable as a PDF.
The Centre for Enterprise, Markets and Ethics (CEME) is pleased to announce the publication of a report on the topic of non-executive directors.
Is the Non-Executive Director Worth Saving?
Richard Turnbull
Is the non-executive director (NED) an endangered species?
Does it matter?
This publication argues that the continued role of the NED matters not only to the individual director, to business and companies but also to society as a whole. The contention is that without effective NEDs, corporate governance will be weaker, companies more exposed and society less well served. If that is the case, then education is as important as law in enabling NEDs themselves, policymakers, media and wider society to understand and appreciate both the responsibilities and the limits of the NED role.
It is axiomatic that NEDs should discharge their duties competently in accordance with the law and with moral intent in the service of society. However, any lack of clarity over those duties, particularly in law, or potential exposure to regulatory action as a consequence of confusion over roles or responsibilities, will not only reinforce unrealistic expectations but also discourage NEDs from taking on this important corporate and social duty.
Non-executive directors should be reminded of their duties and responsibilities and given clarity as to society’s expectations. The answer is not further liabilities. Knee-jerk reactions to scandal are unhelpful – not all failures involve scandal and some, in the normal course of business, afford opportunity to learn lessons. We should clarify and celebrate. The NED is a bridge between business and society – ensuring proper corporate governance while playing a wider role in societal leadership. We need people of character and experience to discharge this role.
Richard Turnbull is the Director of the Centre for Enterprise, Markets and Ethics. He holds degrees in Economics and Theology and a degree of Doctor of Philosophy in Theology from the University of Durham. He is also a chartered accountant. He has authored or edited numerous books, articles and other publications in church history and business ethics, including an acclaimed biography of the Earl of Shaftesbury. He is a visiting Professor at St Mary’s University, Twickenham and a Fellow of the Royal Historical Society.
The author would also like to thank his colleagues at the Centre for Enterprise, Markets and Ethics, Andrei Rogobete (Associate Director) and Dr John Kroencke (Senior Research Fellow), who also contributed.
Of growing popularity at present is the phenomenon of the ‘mystery box’: a box or case purchased – usually from an online provider – that contains various ‘unknown’ objects. A fairly typical example would cost somewhere in the region of £90 and will be described by the seller as either unclaimed luggage from an airport or a collection of items including lost deliveries or goods returned to online retailers. Numerous questions can be raised with regard to the supply of the contents. We might wonder how these goods came to be lost in the first place and were never returned to or reclaimed by the original sellers or travellers, but have somehow made their way to online vendors. There are, however, interesting and salient considerations regarding the consumption of such boxes – the demand side of the equation, as it were. Is there anything unique or unusual about the market for mystery boxes and people’s engagement with them? And is its emergence indicative of any social or cultural trends?
Gambling and Games of Chance
There are certain features common to buying a mystery box and forms of gambling: the purchaser parts with money in the hope of a decent return, but there is also the prospect of loss. When the box arrives, it might contain something far more valuable than the outlay, such as a new laptop, but equally might contain something that the buyer will consider useless, such as some ill-fitting footwear and a damaged photograph frame. There are therefore elements of risk and luck involved, which might go some way towards explaining the growing popularity of mystery boxes. However, since there are no stated or calculated odds to inform the buyer’s decision, the comparison with conventional forms of gambling is limited. The absence of any clear element of play also puts strain on the idea that buying a mystery box is akin to well-known, small-scale games of chance, like hook-a-duck or a tombola. In spite of the similarities with gambling therefore, the transaction remains a purchase. That is to say, the buyer parts with money and expects to receive goods, even if he or she does not know what those goods will be. Moreover, the fact that the transaction is a purchase and not a bet in the usual sense is reinforced by the experience of disappointment frequently reported by buyers and their willingness to complain about the goods that they receive – a response that would be out-of-place in a casino or at a village fete.
The Experience Economy
Perhaps a more fruitful approach to making sense of the phenomenon of the mystery box would be to understand it as part of the experience economy. Reports indicate a shift among consumers towards the purchase of an experience rather than some concrete good – hence the growing importance of attending gigs over buying downloads of music. There is an increasing prevalence of themed evenings in the hospitality sector and a growing trend among some readers to visit a bookshop and pay for a book wrapped in brown paper, presumably with a view to being exposed to a kind of literature that they might not normally choose. In this light, the mystery box can be interpreted as the purchase of a certain type of experience involving uncertainty and excitement – an understanding that makes more sense when we consider that buyers will often upload to social media an ‘unboxing’ video when their purchase arrives. Thus, the mystery box purchase becomes a shared experience, additionally attracting followers to a social media channel, which itself potentially brings various emotional and often pecuniary rewards for the buyer (though it is unclear whether the financial return for attracting ‘views’ would cover the cost of the box itself). Nevertheless, we are still faced with the fact of disappointment. When customers buy experiences such as a bungee jump or a climb over the O2 Arena, there is an expectation of a certain quality or level of experience, commensurable with the price. Unlike mystery boxes, people do not make these purchases with the expectation that they might well be disappointed. Part of the appeal of a mystery box is doubtless lies in the ‘experience’ but it is not clear that the phenomenon is simply reducible to this.
Consumption, Desire and Catholic Thought
The philosopher Arthur Schopenhauer described boredom as a situation in which the pressure of the will remains but has no object towards which it can be directed – hence the prevalence of card games and habits such as smoking, as humanity devises means of passing time which is felt to be a burden. Schopenhauer’s famously pessimistic account of human existence was based on a very particular metaphysics but his account of boredom, by which we are led to ‘go in quest of society, diversion, amusement, luxury of every sort, which lead many to extravagance and misery’ might inform our understanding of the market for mystery boxes. Rather than having its explanation in a will that has no object, perhaps buying a mystery box is suggestive of an urge to consume, only without a clearly desired object. Thus, the act of buying itself becomes the object and in this, the purchase differs from normal transactions. However, when the goods arrive and prove not to have been worth the outlay, the usual norms of purchasing reassert themselves and the buyer feels disappointed.
If this is indeed what is going on – at least in part – then Catholic thought has something to contribute and might offer an analysis in terms of ‘disordered concupiscence’ or cupidity. Human beings have an array of natural and necessary desires, such as for life or food, but desires often extend beyond our needs and will reach for wealth, fashion or fame. Such ‘non-natural’ desires are potentially infinite and can run out of control. When unrestrained and no longer subordinate to reason, which aims at the good of the whole person, these appetites can affect our judgement, leading us to excess, intemperance and a focus on gratification, rather than the pursuit of a life of flourishing, informed by a correct understanding of goods and their relative importance in life. In short, we are lured away from our ultimate purpose.
No single account is able to explain entirely the emergence of the market for mystery boxes. Buyers are likely to be driven by different motives, but it seems clear that there are elements of risk, the hope of rewards beyond the outlay, the enjoyment of the experience itself and the potential to share this with others via social media. Importantly, the purchase – unconventional as it is – remains a purchase. The moral question arises when we consider the possible end or source of such transactions.
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Neil Jordan is Senior Editor at the Centre for Enterprise, Markets and Ethics. For more information about Neil please click here.
Abraham Kuyper (1837–1920), the Dutch theologian, philosopher, and statesman, is renowned for his comprehensive vision of Christian engagement in the world, especially in the realms of politics, education, and culture. As one of the founding tenants of Dutch Neo-Calvinism, Kuyper’s theology emphasises the sovereignty of God over every aspect of life and the notion that all spheres of society – such as government, family, and science – operate under God’s authority. Though Kuyper’s years much precede the rise of modern technological advancements like artificial intelligence (AI), his theological principles and philosophical framework offer profound insights into how we might approach the challenges and opportunities presented by contemporary technology.
Kuyper’s Doctrine of Common Grace and Technology
A central aspect of Kuyper’s thought that can be applied to the technological age is his doctrine of common grace. Kuyper articulated this idea as God’s grace sustaining the world even after the Fall, allowing human culture and society to flourish despite sin. Common grace, in Kuyper’s framework, explains why people of faith and of no faith make good and beneficial contributions to society. It provides a theological foundation for the development of technology, science and other socioeconomic advancements.
Technological progress, including AI, is understood as a manifestation of common grace. The ability of humanity to create and innovate is a reflection of God’s sustaining grace in the world. In his major work, On Business and Economics, Kuyper writes:
To work every day that God gives us, to accomplish something that makes up for the length of that day, indeed, to do work so well that when we retire at night the result of the day’s work is finished and ready—that is a divine ordinance. It applies to human beings not just after the fall but also before it. To work and to be busy is our high calling as human beings (page 376).
For Kuyper, the use of human reason, creativity, and ingenuity – faculties given by God to all people – are a demonstration of humanity’s mandate to steward the earth (Genesis 1:28). He viewed work as calling of the highest order. The development of technology can thus be seen as part of the God-given task of dominion over creation. Kuyper would likely view AI as a further step in humanity’s ongoing mandate, where human ingenuity, enabled by God’s common grace, continues to shape and direct the created order.
However, Kuyper also recognized that while common grace permits societal development, sin profoundly distorts human endeavour. This dual reality of grace and sin means that technology, like all human inventions, can be used for both evil and good. AI holds the potential for great benefit – improving healthcare, augmenting human labour, enhancing decision-making processes – but also presents significant ethical challenges, including privacy concerns, job displacement, misinformation, and the potential for dehumanisation.
Having lived in the shadow of the Industrial Revolution and amidst the period of widespread electrification, Kuyper became all too familiar with the repercussions of rapid technological change. He spoke vociferously against the commodification of human capital and had stern words for unscrupulous employers:
The incredible revolution wrought by the improved application of steam power and machine production… has freed capital almost completely from its earlier dependence on manual labour. […] The magical operation of iron machines has unfortunately led the capitalist to regard his employees as nothing but machines of flesh that can be retired or scrapped when they break down or have worn out. […] You [employers] shall honour the workingman as a human being, of one blood with you; to degrade him to a mere tool is to treat your own flesh as a stranger (see Mal 2:10). The worker, too, must be able to live as a person created in the image of God. He must be able to fulfil his calling as husband and father. He too has a soul to care for, and therefore he must be able to serve his God just as well as you (for more on this see Erin Holmberg’s article).
The Imago Dei, Sphere Sovereignty, and the Ethical Use of AI
Kuyper calls for a discerning approach to technology, recognizing both its God-given potential and the inherent risks posed by human sinfulness. At the heart of Kuyper’s anthropology is the belief in the imago Dei – the doctrine that human beings are made in the image of God. This belief undergirds Kuyper’s view of human dignity and responsibility in the world. From this perspective, the ethical use of AI must be grounded in a robust understanding of what it means to be human.
AI, for all its benefits, raises profound questions about human identity and dignity. The automation of tasks traditionally performed by humans, the replication of decision-making processes, and the potential for creating AI that mimics human behaviour challenge our understanding of human uniqueness. Kuyper’s assertion of the imago Dei affirms that human beings are distinct from machines, endowed with moral responsibility, creative capacity, and relationality. Technology, in this view, must serve humanity, not replace or diminish it.
Another key element of Kuyper’s thought is his doctrine of sphere sovereignty. Kuyper proposed that different areas of life – such as education, politics, science, and religion – are distinct spheres, each with its own God-given authority and autonomy. No single sphere, not even the church or government, should dominate the others; each operates according to its own principles and is directly accountable to God.
When applied to AI and technological innovation, sphere sovereignty provides a framework for understanding the limits and responsibilities of technology in society. A Kuyperian approach would caution against excessive forms of influence that overreach into other spheres. For example, AI should not be used to violate personal privacy (an issue in the sphere of human dignity and ethics), nor should it lead to an erosion of political accountability by automating decisions that require human judgment and responsibility.
For Kuyper, the use of AI must be regulated by ethical considerations that prioritize the dignity of human beings. This includes ensuring that AI technologies do not dehumanize individuals by treating them as mere data points or reducing human interactions to automated processes. Instead, AI should be used to enhance human capabilities and alleviate suffering, reflecting the biblical mandate to love one’s neighbour. The goal of technological innovation, according to Kuyper, should be the flourishing of human life in a way that reflects God’s original purpose for creation.
A Kuyperian Vision for AI in the 21st Century
Abraham Kuyper’s theological insights provide a rich framework for thinking through the ethical and social implications of technological advancement. His doctrines of common grace, sphere sovereignty, and the importance of the Imago Dei offer valuable principles for navigating the complex issues raised by AI today.
First, AI can be seen as a product of human ingenuity, a gift of common grace that contributes to our socioeconomic development. Second, Kuyper’s doctrine of sphere sovereignty offers a useful approach to thinking about AI boundaries and ensuring that technology does not usurp the role of human responsibility in areas like justice, politics, and ethics. Finally, AI must remain subservient to human dignity, recognising that humans, made in the image of God, hold unique status and responsibility within creation.
In embracing Kuyper’s vision, Christians are called to engage thoughtfully with AI, recognising both its potential for human flourishing as well as the dangers of misuse. Kuyper’s legacy offers a valuable and theologically grounded approach to the opportunities and challenges of the technological age.
Andrei E. Rogobete is Associate Director at the Centre for Enterprise, Markets & Ethics. For more information about Andrei please click here.
Reports abound on the potential of artificial intelligence to transform workplaces, whether in its capacity to process vast quantities of data – data that would require weeks of careful analysis on the part of human beings – in a matter of hours, or its ability to deal with routine tasks, thus freeing employees to engage more fully with other concerns. Opinion is likely to differ on the benefits of AI at work, but what of its capacity to assist those looking for employment? Generative AI models are apparently being used by growing numbers of job applicants to create CVs and covering letters, in the hope that their applications will stand out from others, which consist of too much text on a white (or plain) background. Anyone who has been involved in recruiting staff will of course be familiar with the phenomenon of receiving a large volume of applications, with a significant number being from candidates who are very similar in terms of qualifications and experience. Thus, the question arises of how to differentiate between them and form an initial judgement about which applicants would appear to be best-suited to the role advertised, and so be called for interview.
The Difficulty of Selection
Such a situation might be described as one in which the recruiting manager has received too many CVs and letters, which consist of too much text on too much plain background – but such a characterisation would be misleading. The difficulty (‘problem’ is surely the wrong term for a situation in which an organisation looking for staff is faced with a wealth of apparently equally well-qualified applicants) is not generally with the ‘presentation’ of applications, but their content. Nevertheless, a belief that ‘appearance’ is what helps an application to stand out seems to lie behind the use of certain AI-enabled features, such as animations or graphics, while in some cases, the letter of application itself is generated automatically from information taken from the advertised post and content from the candidate’s CV.
Outstanding Applications
If the challenge for the recruiter is finding the best candidate(s) for the role, there are very few situations in which this task is likely to be facilitated by an unusual-looking CV. What makes a CV and letter stand out for the right reasons is not that some of the text and plain background have given way to pictures and animations; rather, an outstanding application is one in which the candidate tells the recruiting manager what she needs to know: that is, why this candidate is suitable for the position, how his skills and experience have prepared him for it, and are demonstrative of a genuine aptitude and interest in the role. Eye-catching colours and animations are unlikely to achieve this of themselves. It might be tempting to believe that, based on relevant data pulled from a job description and the candidate’s CV, an AI model will generate a ‘better’ application than the individual can manage himself, but there are almost no situations in which this would produce an outstanding application. It is scarcely surprising if applicants who adopt such an approach often find their applications turned down. If anything, what this method displays is an unwillingness to devote the time to writing an application that demonstrates one’s interest in and suitability for a post – the opposite of what a recruiter would hope to see. Moreover, as reports indicate, where several candidates use the same AI model to produce their application, far from standing out, their applications, somewhat predictably, all appear rather similar.
Applications and the Value of the Individual
This is perhaps indicative of the fundamental reason for which, at present, while artificial intelligence evidently has a role to play in a variety of workplace settings and can, via apps and websites, help those seeking work to find suitable employment, it is difficult to see how it can assist in the application process itself, beyond providing assistance with language or basic formatting. Reports suggest that letters and CVs produced using AI tend to be ‘samey’, which in all probability results from the fact that, ingenious as such technology is, it is likely to produce outcomes to a formula, based on data. The result, while differing in specific details, will therefore be somewhat general. Put differently, the technology is insufficiently capable of focusing on or recognising individuality – both of the role and of the aspiring employee – in ways that matter. (The errors made by AI models in web searches, which produced images of black Nazi soldiers, for example, suggest that the technology certainly can recognise individual difference, but fails to grasp its significance or meaning.) As such, an application based on limited data from a CV and job description, which are then matched, is unlikely to result in a compelling application that captures the attributes and skills of that unique individual, or shows why these make that individual the right person for a particular job. Where employers are serious about seeking suitable individuals (rather than types) for specific roles – and value those employees as individuals – and as long as the purpose of a CV and letter is to demonstrate that the applicant is that individual, the generated (or generic) application is unlikely to serve either recruiter or candidate well.
A Further Consideration
Should the technology advance to a point at which it can produce a convincing application that shows why an individual, with her professional and educational background, qualities and experience, should be considered for a particular role, then AI might well have a role to play. At that stage, it will be important for employers to ask themselves whether there is nonetheless something preferable about a personal application, which would serve to distinguish such candidates; whether, in writing an application herself, a candidate makes a commitment or investment in thought, application and time, that ought not to be delegated to an AI model.
Neil Jordan is Senior Editor at the Centre for Enterprise, Markets and Ethics. For more information about Neil please click here.
This paper is part of a series of essays that seek to explore the current and prospective impact of AI on business. A PDF version can be accessed here.
The previous paper in this series looked at the impact of AI on work through the lens of Peter Drucker’s concept of the ‘Knowledge Worker’. In this paper we turn our attention to existing and emergent evidence on the impact of AI upon worker productivity. We contend that it is misguided to myopically focus on the perpetrated gains in productivity. Equal importance ought to be given to furthering our understanding of the impact of AI upon concepts of meaningful work, self-esteem and job satisfaction. The Judaeo-Christian framework discussed in the first paper in this series offers a moral basis that upholds the importance of human dignity and the intrinsic value of humanity as the sole bearers of the imago Dei (image of God).
The structure here is comprised of three parts. The first will look at both existing evidence and predictions for the impact of AI on productivity, highlighting the often-overlooked time delay between the arrival of new AI capabilities and their materialisation into beneficial productivity tools. The second section turns the attention to matters of meaningfulness, job satisfaction and employee wellbeing in relation to the use and integration of AI tools. The third and final section offers some concluding remarks on how we might begin to think about developing a morally robust symbiosis between AI and work.
‘AI productivity gains may be smaller than you’re expecting’, reads the headline of a recently published report by ING Bank.[1] In May 2023, just 10 months earlier, the Brookings Institute published a research paper titled ‘Machines of mind: The case for an AI-powered productivity boom’[2]. What is the current state of AI when it comes to productivity? Previously we have seen how knowledge worker productivity, though important, presents us with challenges of measurability and accurate prediction. It is important to note here that when talking about AI we are referring primarily to generative AI rather than infrastructure AI which began spreading in the early 2010s and operates largely behind the scenes.
At almost two years from initial public release of ChatGPT we have an emerging story of two tales: there is a dichotomy of evidence between the Macro and Micro levels when it comes to AI-driven productivity gains. Let’s briefly detail some of the existing evidence for each in part.
As of the first half of 2024 there is very little, if any, evidence of AI-driven productivity gains at the Macro level. This perhaps shouldn’t come as much of a surprise since some economists, including Charlotte de Montpellier and Inga Fechner, argue that the biggest impact on productivity growth will be seen in 10-15 years’ time. This assumes that AI does indeed lead to the much-needed complementary innovations that are expected to be dispersed across an array of different fields.[3]
The concept of ‘complementary innovations’ (i.e. innovations that follow and are enabled by the arrival of new technology) is an important one when it comes to gauging the potential impact of AI-driven productivity. General Purpose Technologies like electricity, the internet, personal computers and so on face what is known in productivity theory as a ‘J curve’ (note: ‘GPTs’ – not to be confused with ChatGPT which stands for Generative Pretrained Transformer).[4] This holds that the arrival of new GPTs counterintuitively leads to an initial decrease in short-term productivity measurements followed by a gradual increase in the medium-to-long term productivity – closely resembling a ‘J curve’. The J curve is largely due to difficulties in accurately measuring the initial GPT adoption investment in intangible capital, as economists like Erik Brynjolfsson et al.[5] point out:
As firms adopt a new GPT, total factor productivity growth will initially be underestimated because capital and labour are used to accumulate unmeasured intangible capital stocks. Later, measured productivity growth overestimates true productivity growth because the capital service flows from those hidden intangible stocks generates measurable output. The error in measured total factor productivity growth therefore follows a J-curve shape, initially dipping while the investment rate in unmeasured capital is larger than the investment rate in other types of capital, then rising as growing intangible stocks begin to contribute to measured production.[6]
So it would be reasonable to assume a degree of delay between the period of initial investment, development and adoption of AI tools, and their derived productivity increases at the Macro level. Some long-term predictions remain optimistic: Goldman Sachs estimates a 7% (or almost $7 trillion) increase in global GDP and a lift in productivity growth by 1.5 percentage points over a 10-year period – though it should be noted that this estimate is dependent upon AI’s future capabilities and adoption rates.[7] Other predictions are more conservative: Daron Acemoglu, Professor of Economics at MIT, estimates that AI-driven GDP growth is unlikely to exceed circa 0.93% − 1.16% over the next 10 years, with a total factor productivity (TFP) of no more than 0.66% over the same period.[8]
Thankfully, at the Micro level the picture is less murky. About half a dozen studies provide us with reliable data, three of which will be discussed here. The first is authored by E. Brynjolfsson, D. Li and L. Raymond and looked at the effects of using a generative AI conversational assistant (or AI chatbot) by 5,179 customer support agents.[9] This likely represents the largest generative AI-workplace study of 2023 and its findings point to some positive outcomes for AI integration within this particular business scenario.
The productivity of each customer support agent was measured in resolutions per hour (RPH). Those that worked with the assistance of the AI chatbot completed on average 14% more RPH than those who didn’t.[10] The research also found that ‘AI assistance improves customer sentiment, increases employee retention, and may lead to worker learning’.[11]
What is even more interesting is the dispersion amongst high-skilled and low-skilled workers. Figure 1 illustrates the change produced in RPH (y-axis) following AI deployment to the lowest skilled workers (x-axis, Q1), through to the highest skilled workers (x-axis, Q5). The results point to a significant productivity gain of 35% for the lowest skilled workers (Q1), but negligible change in productivity for the highest skilled workers (Q5).[12]
The study found ‘… suggestive evidence that the AI model disseminates the best practices of more able workers and helps newer workers move down the experience curve’.[13] In other words, the AI chatbot proved to be an effective tool at learning from the best resolutions for certain problems and distributing this knowledge at greater pace and with higher accuracy to the most novice and low-skilled employees. It is important to note that the AI chatbot in this particular study was designed to augment and assist each particular issue and resolution. The final decision of whether to adopt or reject the AI’s suggestions remained entirely at the discretion of the customer support agent.[14]
A second notable study by S. Peng et al. looked at GitHub’s ‘Copilot’, an AI assistant utilised in computer programming.[15] A group 95 programmers recruited via Upwork, a freelance jobs platform, were tasked with implementing an HTTP server in JavaScript as quickly as possible (though the technical details are not essential for the lay reader). Of the 95 programmers, 45 were in the treated group and 50 in the control group. Performance was measured by (A) task success and (B) task completion time. The results revealed no difference of statistical significance in (A) task success – in other words, both groups completed the challenge with a high rate of success. However, the results did show a 55.8% decrease in (B) completion time for the treated group compared to the control group. This translates to 71.17 minutes versus 160.89 minutes – a net reduction in completion time of 89.72 minutes for the treated group of programmers that utilised GitHub Copilot.[16] It is important to note however, that the study did not evaluate the quality of the code produced by the two groups, and discrepancies here may be significant for the real-world impact of relying on AI tools in programming.[17] So programmers that utilised GitHub’s Copilot finished the challenge an average of 1h 30min quicker than those who did not.
The third study worth mentioning is entitled ‘Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence’, authored by S. Noy and W. Zhang, both from MIT.[18] As the title suggests, the research took an empirical look at the effects of using ChatGPT for a variety of mid-level business-related writing tasks.[19] The study recruited 444 professionals with a higher degree of experience from fields such as data science, human resources, consultancy and marketing. They were all tasked with completing 20–30-minute assignments such as writing a more important email, a short report, press releases, an analysis of various bits of data and so on – all encounters designed to resemble a real-world work environment.[20]
Between task 1 and task 2, 50% of the participants (i.e. the treatment group), were given the possibility of using ChatGPT for their second task (neither group used AI for the first task). The results in productivity were measured in earnings per minute, with each piece of final documentation being independently evaluated for content quality, writing and originality, and assigned a score. The results reveal a substantial increase in productivity by reducing the average task completion time from 27 minutes to 17 minutes. What is perhaps more interesting is that the blind evaluations in quality produced reveal an improvement of 4.54 with ChatGPT versus 3.79 without (on a scale of 1-7).[21]
The evidence presented thus far broadly points to the adoption of generative AI tools having a positive impact on productivity. However, myopically focusing on productivity gains at the expense of other factors that are relevant to work such as meaning, self-esteem and job satisfaction, risks giving us a distorted and incomplete understanding of the multifaceted implications of adopting and integrating generative AI within the workplace. Indeed, a closer look at some of the relevant studies reveal a more complex picture. Let’s start with the concept of meaning and self-esteem.
In philosophy the relationship between work and meaning is well-established, with notable studies by Diddams and Whittington,[22] J.B. Ciulla,[23] C. Michaelson[24] and others. Within the social sciences we also find a convoluted landscape that encompasses meaningful work, drawing upon contributions from organizational studies, psychology, economics, political theory, and sociology.[25] [26] What exactly does it mean for something to take on the adjective ‘meaningful’? The etymology of the word ‘meaning’ expresses the importance or value of something.[27] To become ‘meaningful’ is to give significance, intentionality and a purpose that pervades the action or the subject in question.
Work is therefore not just a means of economic survival but also a fundamental source of self-identity, worth, and purpose. Work carries repercussions that move beyond the mere intellectual or physical act itself. C. Cordasco from the University of Manchester highlights two broad categories from which work derives meaning and self-esteem: intrinsic and extrinsic. Intrinsic factors involve pride in one’s unique personal or collective skills, a genuine interest and enjoyment in the work itself (be that physical or cerebral) and contributions to an organisation or indeed a wider field. Extrinsic factors include the ability to provide for oneself and one’s family, the recreational freedom that work provides, the affiliation with certain groups and social networks, and so on.[28]
The first paper within this series we considered a Judaeo-Christian approach to AI and work. We highlighted how this implicitly raises wider questions of purpose, meaning and a sense of calling that pervades the mere temporal dimension of work. The Judaeo-Christian perspective therefore seeks to re-evaluate of the gift and place of human agency and responsibility within creation. The foundational texts can be found in Genesis 1:28 and 2:15 where humanity is called to ‘Be fruitful and increase in number; fill the earth and subdue it. Rule […] over every living creature that moves on the ground. […] The Lord God took the man and put him in the Garden of Eden to work it and take care of it.’[29] The command here is here is one of teleological reflection through human capabilities of that which is divine: humanity is given freedom and authority to order, create, steward, and against the backdrop of original sin, also to destroy.
Judaeo-Christian teaching therefore places the concept of work as a key part of what it means to be made in the Imago Dei (the image of God), and to actively partake in the eschatological realisation of creation. Work is thus an integral element of Christ’s redemptive transformation of the individual and indeed the world. Meaning therefore, finds its ultimate source in the creator God, and this of course encompasses meaning within the realm of work. It is a distinctly human pursuit – no other species on earth searches for meaningful work. Indeed, no other species even reaches a point of asking the question: ‘Why am I doing what I am doing?’. As David Atkinson rightly points out in his commentary on Genesis: ‘To be in his image is to be aware of ourselves as his creatures’.[30]
This ability for profound self-reflection is a core characteristic of what it means to be image bearers of the divine. It informs and shapes the meaning of work: if humanity has been gifted with intellectual abilities such as creativity, problem-solving skills, discernment, a capacity to learn new skills and to avoid past mistakes, and has been entrusted with these abilities to care for and steward over creation, then anything that risks compromising these qualities warrants careful attention and scrutiny. The Judaeo-Christian perspective on meaningful work is in some sense dualistic: on one hand God is the ultimate source of purpose and meaning, and on the other, human capabilities play a role in fulfilling and partaking in the larger narrative of God’s redemption of creation.
If we turn back to AI, what is the likely impact going to be on meaningful work and job satisfaction? The evidence, while still in its infancy, is patchy. Emergent studies point to both positive and negative outcomes. S. Noy and W. Zhang found that augmentation with ChatGPT in the variety of common office tasks, ‘…increases job satisfaction and self-efficacy and heightens both concern and excitement about automation technologies’.[31] The study points out that the recorded increases in job satisfaction are likely due to a heightened sense of achievement when completing a more difficult or tedious task with the assistance of ChatGPT, and in a shorter amount of time than would have otherwise been possible.[32]
However, another study by P.M. Tang et al. cautions against an overdependence on AI systems as a leading factor in social disconnection and worker loneliness:
This coupling of employees and machines fundamentally alters the work-related interactions to which employees are accustomed, as employees find themselves increasingly interacting with, and relying on, AI systems instead of human coworkers. This increased coupling of employees and AI portends a shift towards more of an “asocial system” wherein people may feel socially disconnected at work.[33]
Similarly, C. Cordasco points out that while AI development poses a significant threat to traditional sources of self-esteem derived from work, halting AI is neither feasible nor the best solution. Instead, society should explore new ways of cultivating self-esteem that align with the evolving technological landscape.[34]
A report by Boston Consulting Group’s (BCG) Henderson Institute investigated how people can ‘create and destroy’ value with Generative AI and found that, ‘…it isn’t obvious when the new technology is (or is not) a good fit, and the persuasive abilities of the tool make it hard to spot a mismatch. This can have serious consequences: When it is used in the wrong way, for the wrong tasks, generative AI can cause significant value destruction’.[35] The study had access to over 750 BCG consultants as subjects and found that in areas such as creative product innovation, AI tools boosted productivity by 40%, but in areas like business problem solving, generative AI actually led to a 23% reduction in productivity. The report also highlighted an important trade-off when it comes to collective creativity. Whilst individual performance may be boosted by 40%, collective diversity of ideas may fall by 41%. This is largely because AI chatbots tend to produce the same or similar responses to the same specific prompts – resulting in positive outcomes at the individual level but repetitive and less diverse outcomes at the collective level.[36] The potential impact of AI tools on human creativity also seems to be an issue of concern: out of a group of 60 BCG consultants, 70% expect a negative impact on creativity, 26% do not anticipate a negative creative impact, and 4% are unsure.[37]
It is important to note that when attempting to draw conclusions about the impact of AI upon the world of work, we are (whether we like it or not), operating along several core variables, or axes. The first would be the level of automation (high) versus augmentation (low). The second represents the level of skill of the employee or group of employees in question. Here it is becoming increasingly apparent that there seems to be a positive reduction in productivity inequality, with at least in these nascent stage, low-skilled workers standing to benefit the most from AI tools. There is also a challenge of AI discernment, what some authors have called a ‘jagged technological frontier’, whereby the most successful employees and managers will learn to distinguish which tasks are best suited for AI assistance and which aren’t.[38] The third is perhaps less a variable than a recognition that the business world represents a plethora of highly distinct work contexts and scenarios where AI implementation may or may not play an important role.
All of these factors are essential when attempting to understand the impact that generative AI has upon work. Broadbrush conclusions about the impact of AI are at best generic, and at worst, inaccurate. Therefore, at least in these early stages, we have to operate on a case-by-case basis and seek to identify and understand areas where AI is a net contributor, and not a hindrance, to both productivity and matters surrounding meaningful work.
Central to the Judaeo-Christian framework is the importance of humanity as the sole image bearer of the divine, tasked with responsibilities of stewardship over nature. In fulfilling the stewardship command, humanity also has the duty of recognising and protecting distinct human attributes such as meaning, purpose, self-esteem and creativity. Emergent technologies therefore ought to be developed and harnessed in harmony with the qualities conferred by humanity’s uniqueness, not against them.
Andrei E. Rogobete is Associate Director at the Centre for Enterprise, Markets & Ethics. For more information about Andrei please click here.
[1] Charlotte de Montpellier, Inga Fechner, ‘AI productivity gains may be smaller than you’re expecting’, ING Bank, April 2024, https://think.ing.com/articles/macro-level-productivity-gains-ai-coming-artificial-intelligence-the-effect-smaller/.
[2] Martin Neil Baily, Erik Brynjolfsson, Anton Korinek, ‘Machines of the Mind: The Case for an AI-powered Productivity Boom’, Brookings Institute, May 2023, https://www.brookings.edu/articles/machines-of-mind-the-case-for-an-ai-powered-productivity-boom.
[3] Charlotte de Montpellier, Inga Fechner, ‘AI productivity gains may be smaller than you’re expecting’, ING Bank, April 2024, https://think.ing.com/articles/macro-level-productivity-gains-ai-coming-artificial-intelligence-the-effect-smaller/.
[4] Erik Brynjolfsson, Daniel Rock, Chad Syverson, ‘The Productivity J-Curve: How Intangibles Complement General Purpose Technologies’, American Economic Journal: Macroeconomics, Vol. 13(1): 333-72, (January 2021), DOI: 10.1257/mac.20180386.
[5] Ibid. p.1
[6] Ibid. p.3
[7] Goldman Sachs, ‘Generative AI could raise global GDP by 7% ‘, April 2023, https://www.goldmansachs.com/insights/articles/generative-ai-could-raise-global-gdp-by-7-percent.html
[8] Daron Acemoglu, ‘The Simple Macroeconomics of AI’, paper prepared for Economic Policy, Massachusetts Institute of Technology, (April 2024), p.4.
[9] Erik Brynjolfsson, Danielle Li, Lindsey R. Raymond, ‘Generative AI at Work’, National Bureau of Economic Research – Working Paper 31161, https://www.nber.org/papers/w31161.
[10] Ibid. p.10
[11] Ibid.
[12] Ibid. p.15
[13] Ibid.
[14] Ibid. p.9
[15] Sida Peng, Eirini Kalliamvakou, Peter Cihon, Mert Demirer, ‘The Impact of AI on Developer Productivity: Evidence from GitHub Copilot’, arXiv Accessibility Forum, (February 2023), arXiv:2302.06590 [cs.SE].
[16] Ibid. p.5
[17] Ibid. p.8
[18] Shakked Noy, Whitney Zhang, ‘Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence’, Science, Vol. 381(6654): 187-192, (July 2023), DOI: 10.1126/science.adh2586.
[19] Ibid. p.1
[20] Ibid. p.2
[21] Ibid. p.4
[22] Margaret Diddams, J.Lee Whittington, Daniel T. Rodgers, Joanne Ciulla, ‘Book review essay: Revisiting the meaning of meaningful work’, Academy of Management Review, Vol. 28(3):508-512, (June 2003), DOI: 10.2307/30040737.
[23] J. B. Ciulla, The working life: The Promise and Betrayal of Modern Work, (London: Times Books, 2000), pp.266.
[24] Christopher Michaelson, ‘Meaningful motivation for work motivation theory’, Academy of Management Review, Vol. 30(2): 235-238, (April 2005), https://doi.org/10.5465/amr.2005.16387881.
[25] Ruth Yeoman (ed.), Catherine Bailey (ed.), Adrian Madden (ed.), Marc Thompson (ed.), The Oxford Handbook of Meaningful Work, (Oxford: Oxford University Press, 2019), pp.544.
[26] Catherine Bailey, Marjolein Lips-Wiersma, Adrian Madden, Ruth Yeoman, Marc Thompson, Neal Chalofsky, ‘The Five Paradoxes of Meaningful Work: Introduction to the special Issue ‘Meaningful Work: Prospects for the 21st Century’’, Journal of Management Studies, Vol. 56(3): 481-499, (May 2019), https://doi.org/10.1111/joms.12422.
[27] Cambridge Dictionary, ‘Meaning, (July 2024), https://dictionary.cambridge.org/dictionary/english/meaning.
[28] Carlo Ludovico Cordasco, ‘Should We Halt AI to Protect Meaningful Work?’, ResearchGate, (December 2023), DOI: 10.13140/RG.2.2.22893.77288, p.7-18.
[29] The Holy Bible, (NIV Translation).
[30] David Atkinson, The Bible Speaks Today Series: The Message of Genesis 1—11: The Dawn of Creation, (Westmont, IL: InterVarsity Press, 1990), p. 37.
[31] Shakked Noy, Whitney Zhang, ‘Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence’, Science, Vol. 381(6654): 187-192, (July 2023), DOI: 10.1126/science.adh2586. p.1.
[32] Ibid. p.9
[33] Pok Man Tang, Joel Koopman, Ke Michael Mai, David De Cremer, Jack H. Zhang, Philipp Reynders, Chin Tung Stewart, and I-Heng Chen, ‘No Person Is an Island: Unpacking the Work and After-Work Consequences of Interacting with Artificial Intelligence’, Journal of Applied Psychology, Vol. 108(11): 1766–1789, (2023), https://doi.org/10.1037/apl0001103.
[34] Carlo Ludovico Cordasco, ‘Should We Halt AI to Protect Meaningful Work?’, ResearchGate, (December 2023), DOI: 10.13140/RG.2.2.22893.77288, p. 35-36.
[35] François Candelon, Lisa Krayer, Saran Rajendran, and David Zuluaga Martínez, ‘How People Can Create—and Destroy—Value with Generative AI’, Boston Consulting Group Henderson Institute, (September 2023), pp. 21.
[36] Ibid. p.15
[37] Ibid. p.16
[38] Fabrizio Dell’Acqua, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon and Karim R. Lakhani, ‘Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality’, Harvard Business School, Working Paper 24-013, (June 2024), p.2.
As part of the new government’s effort to raise the number of houses built and spur economic growth, Labour ministers plan to allow homebuilders to receive planning permission for projects currently impacted by nutrient neutrality rules that require new construction in areas with high levels of nutrients in waterways to not contribute additional nutrients. The permission would be granted with so-called Grampian conditions (the name derives from a Scottish legal case) that would allow the homebuilding to begin subject to future off-site mitigation, rather than the status quo which requires the mitigation to be worked out before the homebuilding begins. This is one quick way that the government seeks to address the fact that because of nutrient neutrality homes impacting much of the country, homes can only be built after the details of mitigation are worked out. This is a huge administrative burden and is holding up something like 160,000 homes from being built. Few think that this will solve the issue, but it is a positive development and one of a number of efforts dealing with environmental concerns. Past efforts have failed to fix the issue and descended into rancorous debates, despite the specific issue of pollution from new homes being minimal.
The crux of the issue in question is that in recent years the environmental concerns surrounding nutrients like phosphates and nitrates in rivers have meant that because of new court rulings, new homes in a large proportion of the UK must mitigate all run-off that they would create.[1] Nutrient runoff into rivers causes algal blooms which consume oxygen and set off a chain of species die offs. European and British court rulings have widened the impact of the rules, including most recently applying the rules to projects which had already received planning permission.
This plan was suggested by Angela Rayner and Steve Reed last September when the last government attempted to overhaul the rules surrounding nutrient neutrality more comprehensively. That effort failed when the House of Lords defeated the Government’s plan to remove the legal requirements on homebuilders while increasing taxpayer funding of a more comprehensive scheme. At the time, the Labour Party was expected to support the reform but altered course just days before the vote. For those who haven’t been following the issue closely, much of the commentary on it in the main newspapers offers little insight and instead treats it as an elementary decision on a good environmental outcome or a poor one. Rather than going through the tangled legal history—I’ll leave that to those who charge by the hour (e.g. Zack Simons or Simon Ricketts)—I want to focus on how this issue and the failure to fix it has been emblematic of a broader problem with environmental issues.
What is the Problem with the Status Quo?
The problem with the current situation, one recognized by many experts, is that it places an extraordinary burden on a socially useful function: residential development. Taking as a given that the levels of nutrient pollution outlined in the rules are sensible, it is reasonable to want to limit any pollution that might occur beyond that point. When rivers reach a point where added pollution is unacceptable—as Natural England claims to be the case in 74 local authorities across the UK including most of Norfolk, much of Wiltshire and Somerset, and the area around the Solent—it makes sense to stop it from getting worse. As a result of this worthy cause, the rules are estimated to be holding up over 160,000 homes (a number that will continue to grow).
In principle, it could be reasonable to stop the market from building more much-needed houses because once the harm of the marginal nutrients is considered there is no net value being created. However, the marginal pollution created by people living in new homes is tiny. In fact, the pollution directly created by all structures (i.e. including existing structures) is supposedly just 5% of the total.[2] Basic economics suggests that there are many ways to regulate such that valuable uses like homebuilding proceed while paying for the reduction in pollutants in whatever way can be done at the lowest cost.
In fact, this is what is supposed to be happening now. The rules are supposed to set a budget for the total amount of nutrients in an impacted area and allow new homes if the developers offset the added pollutants by the same amount. This should encourage bargaining between homebuilders and other polluters. Homebuilders should be able to pay agricultural users who are the biggest polluters and who could reduce pollution at much lower abatement cost than homebuilders. This abatement could be achieved by farming less intensively by using fewer polluting fertilizers or by letting land go fallow. Alternatively, homebuilders could pay for methods to capture agricultural producers’ pollutants, or be able to pay water companies whose disposal of wastewater is one of the key mechanisms by which disparate users’ waste ends up in waterways. The benefit of such a type of regulation is that it creates market incentives to deal with the environmental problem at the lowest cost.
These are examples of the type of offsite mitigation schemes encouraged by the proposed reforms that (at a minimum) will net out the impact of the new development by reducing the relevant pollutants that new housing contributes. This would allow much needed new homes at a much lower cost than catching all added nutrients via onsite mitigation, while also keeping rivers limited to the same level of nutrient runoff. The rules allow nutrient offsetting schemes (and some have been worked out) but they don’t work well in practice due to procedural barriers. There is no environmental or economic reason for this to not be encouraged.
However, as Zack Simons writes:
Nutrient neutrality involves quantifying a ‘nutrient budget’ for both phosphorous and nitrogen, and then using either on or off-site mitigation measures to show that your scheme will not cause any net harm to the protected sites – see some guidance from Natural England here. Measures might include e.g. creating new wetlands, retrofitting sustainable urban drainage systems and making arable farmland fallow to reduce nitrates. But in many authorities, there simply is no standard nutrient neutrality strategy. Or no strategy at all. Very often, nutrient neutrality simply cannot yet be achieved – either viably, or at all.
As bad as the status quo which emerged from legal machinations is, perhaps more worrying is the fact that this issue, like many others, has become mired in unthinking partisan debate. Perhaps the worst offenders are the environmental groups whose interest in the issue suggests that they must realize the need for a better, more comprehensive regulatory system, but who instead depict the problem as a result of homebuilders’ actions.
Like many other countries in Europe, the UK is and has been facing a dramatic set of economic headwinds. Real reforms are needed to enable investment in green energy generation and transmission, but these too face opposition from those who would be expected to support them. Let us hope that this government can fix what the last couldn’t.
[1] The rules allow pragmatic schemes to mitigate nutrient pollution offsite, but the process for doing so is unnecessarily complicated.
[2] Baroness Willis of Summertown suggests that this number may be closer to 30%. But this makes little difference for this argument given this still suggests that the marginal addition is quite small, since the number of existing homes is far larger than the number of new homes held up.
John Kroencke is a Senior Research Fellow at the Centre for Enterprise, Markets and Ethics. For more information about John please click here.
The company American Rounds is supplying vending machines from which gun owners can buy bullets, with machines currently available in food shops in the states of Alabama, Oklahoma and Texas. There are plans to expand this provision to states where hunting is popular, such as Louisiana and Colorado. Customers simply select the ammunition that they would like to buy using a touchscreen, scan their identification and collect their bullets below, the machine having used ‘built-in AI technology, card scanning capability and facial recognition software’ to match the buyer’s face to his or her ID and to ensure that he or she is over 18 years old.
The states in which such machines are available at present place no minimum age limit on the purchase of ammunition, do not require the vendor to keep a record of the purchaser, impose no licensing regime for the sale or purchase of ammunition and do not prohibit those disqualified from purchasing or owning firearms from buying ammunition (though federal laws might impose such a restriction, without necessarily obliging vendors to check whether a customer is in fact disqualified). It would therefore seem that in checking the ID of a purchaser and maintaining a record of the transaction, the machines provided by American Rounds arguably do more than state law requires. This might be for the purposes of ensuring that the machines are unquestionably within the law, or, by ensuring sales are made to adults only, it might be an exercise in reputation management – perhaps both – but it does mean that the machines are likely to be legally compliant when installed in other states where tighter restrictions may apply.
Artificial Intelligence, Risk and Trust
Without entering into the wider issue of gun ownership and its regulation, there are nonetheless moral questions regarding the provision of something so potentially dangerous by way of a vending machine. Can we be certain that the technology will always perform as it is supposed to? We might ask whether such machines capable of discerning a forged ID from a genuine one. Moreover, will they identify buyers correctly? After all, numerous cases (at least seven in the US last year) have been documented of wrongful arrest as a result of facial recognition technology and it would appear that some technologies of this kind are prone to reflecting and perpetuating biases in the data with which they are trained. Whether the technology in American Rounds’ vending machines will accurately match the purchaser’s face to a photograph on an identity document is therefore a legitimate question. These concerns raise the much broader question of responsibility.
Decisions, Decisions…
Where there exists a right to own firearms and ammunition, there is no prima facie reason to disallow sales of ammunition provided by technological means, provided that the technology is reliable and ensures that sales are only ever made to the right people. What, then, is the role of people in such transactions? In a jurisdiction in which would-be buyers of ammunition were checked against a register of individuals disqualified from buying or owning guns, one would expect purchases to be carefully monitored – not least because the shop-owner’s livelihood is likely to be at risk for breaches of regulations. Such verification would doubtless be conducted by means of access to a database, such that the checks, while instigated and concluded by a human-being who makes a decision ‘in store’, would nonetheless be dependent on technology. Ultimately, therefore, while relying on the information provided, the individual vendor would be responsible for the sale. The question, then, is whether this decision, based on the same information, might safely be deferred to a machine that uses facial recognition software and searches databases itself.
The risks involved are different, but a similar question can be asked about the sale of alcohol. Practices vary but in some countries, alcoholic drinks can be bought from vending machines, with the identification of the buyer being verified either by biometric data gained by scanning the customer’s fingerprint, or by simply supplying the purchaser with a wristband to show that his or her ID has been checked by a member of staff. In other countries, alcohol can only be bought at certain times from state approved vendors.
Decisions and Responsibility
Whether the sale is of alcohol or ammunition, are those businesses and states who continue to require and rely upon a human decision at some stage in the transaction doing so based on an unjustified our outdated mistrust of technology, or because they acknowledge that responsibility can ultimately only be attributed to free human beings, who recognise the potential consequences of error? The question, therefore, becomes one not only of trust, but also of responsibility in relation to technology. Where certain decisions handed over to technology – which, of course, can be done more easily and more safely in some areas than in others – we are left with the matter of where responsibility lies, particularly when the technology ‘gets it wrong’. Other things being equal, the owner of a hunting supplies store will be liable if he or she sells a firearm to someone who is underage or disqualified from purchasing guns. Where does responsibility lie if a vending machine sells alcoholic drinks to children in error? Does this rest with the corporate owners or suppliers of the machine? If the machine is on licensed premises, is the landlord responsible? Perhaps there is a case for holding the suppliers of the technology used by the machine liable. This might not be a straightforward matter, as fatalities involving self-driving cars demonstrate: in one case, the back-up driver of the vehicle was convicted while the operating company was judged not to be criminally liable. When an algorithm becomes involved in decisions relating to sentencing for criminal misdemeanours or the provision of social security, where does responsibility for those decisions lie?
Regardless of the scenario, responsibility, as a moral category, must always reside with a person or (human) organisation, never a machine. Machines, however ‘intelligent’, are neither conscious nor free and as such, they are not moral agents. Where decisions are devolved to technology – and that technology ‘decides’ incorrectly – the challenge is for us to identify the responsible subject.
Neil Jordan is Senior Editor at the Centre for Enterprise, Markets and Ethics. For more information about Neil please click here.
This article on Thatcher’s Monetarism and Timothy Lankester’s ‘Inside Thatcher’s Monetarism Experiment’ originally appeared at TheArticle
Sir Timothy Lankester has had a distinguished career of public service. He has served as Permanent Secretary at the Overseas Development Administration and the Department of Education; Director of the School of Oriental and African Studies; President of Corpus Christi College, Oxford; and Chairman of the Council, London School of Hygiene and Tropical Medicine. Inside Thatcher’s Monetarism Experiment (Policy Press, University of Bristol, 240 pp, £19.99) is about his time seconded as a member of the Administrative (not Government) Civil Service from H.M. Treasury to 10 Downing Street to serve as the Prime Minister’s Secretary for Economic Affairs, initially for James Callaghan (7 months) and then Margaret Thatcher (two and a half years).
The purpose of the book is to fill a gap in the economic history of the late 1970s and early 1980s and to show how Mrs Thatcher became infatuated with monetarism as an economic doctrine and implemented it as a laboratory experiment. However, this involved a vast cost of nearly one and a half million people becoming unemployed and thousands of firms going out of business. The author writes as a “disbelieving monetarist”: namely, someone who went along with monetarism because markets believed in it, even though he personally, in the best traditions of the UK Civil Service, did not.
While I am critical of Lankester’s understanding and assessment of monetarism, I thoroughly enjoyed reading the book. Its highlights are his relationship with the Prime Minister and colleagues, as well as his comments on the role and views of politicians, civil servants, special advisers, Bank of England officials, journalists, academic commentators and others.
He writes with admiration and affection for Mrs Thatcher, even though his view of the role and potential of government and the failures and imperfections of markets was very different from hers. “Mrs Thatcher and I got on well from day one,” is the way he describes his working relationship with the Prime Minister. He found her a kind and generous boss, including being invited regularly to the study for a drink in the early evening or supper in the flat with Dennis. He admired her in many ways, not least because, as he puts it, “she greatly valued those of us who worked most closely with her … there was a strong chemistry between us … the closeness of our relationship surprised me then and it surprises me to this day.” Yet he recognises that she had “a schizophrenic attitude to the Civil Service”, largely because of its ineffective delivery of services and its failure to get to grips with an increasingly bloated public sector.
The author makes clear that he approaches the subject with some personal history: he grew up in the lengthened shadow of the Great Depression, because his grandfather, a medical doctor, was forced to close his medical practice in 1930, leaving his father with no money to finish his schooling or attend university. In the Thatcher years, his wife’s family-run cotton textile manufacturing business in West Yorkshire was also forced to close.
This personal background and the great increase in unemployment from 1979 onwards leads him to a positively Augustinian confession: “Although only a minor player in this sad saga, I have always found it difficult to come to terms with the part I both wittingly and unwittingly played in it. … with hindsight, my admiration for her at a personal level, and my wish for her to succeed, made me work almost too hard on her behalf … I put to one side my reservations about monetarism and made myself see the world through her monetarist lens … I might have done more to push back on what Lawson would later call her ‘primitivist monetarism’ … this book is, in part, my attempt to achieve some kind of personal resolution.”
One issue which he addresses inadequately is why Mrs Thatcher, as someone proud of her training as a scientist, became so committed to the importance of monetary policy in controlling inflation. Her conviction was far from some beatific vision: it took the best part of a decade to develop.
When Mrs Thatcher became Prime Minister in May 1979, she inherited an economy described at the time as “the sick man of Europe” and suffering from “the British disease”: low productivity, high inflation, rising unemployment, stagflation, militant trade unions, strikes, and so on. The real pre-tax rate of return on trading assets in the UK manufacturing sector, which averaged around 10% in the 1960s, fell to 2.7% in 1974 and 1.9% in 1975; in textiles and metal manufacture, the real return was negative. Between 1974 and 1979, inflation averaged 16% annually, productivity was stagnant and the Government found it easier to borrow through the nationalised industries than on the Government’s own credit. The conventional Keynesian orthodoxy in terms of policy-making was also proving equally bankrupt: the long-run trade-off between unemployment and inflation had broken down; extra public spending or lower taxes could not be relied on to create more jobs; and a succession of incomes policies, voluntary and statutory, had proved ineffective in controlling inflation under previous Conservative and Labour governments.
After sitting around Edward Heath’s Cabinet table for four years, Mrs Thatcher had become convinced that if inflation was to be brought down, it needed some overall financial discipline. Subsequently, in 1976, while she was Leader of the Opposition, the IMF granted a loan to the UK (when it was effectively bust), but did so only on the condition that the Government would place ceilings on public sector borrowing and money supply growth (in the form of domestic credit expansion). In the academic world, distinguished scholars such as Hayek, Friedman, Johnson, Brunner, Walters and others had conducted extensive research which established that money supply growth affected prices in the long term, but in the short term, mainly output and employment. In addition, the explanation put forward by the Bundesbank and the Swiss National Bank to account for the success of their policies in controlling inflation was their control of money supply growth in their respective countries. All of this was in marked contrast to the part that money played in the intellectual approach of the UK Treasury, Bank of England and distinguished members of the then highly influential Cambridge University economics department.
The author deserves credit for recognising some of this, but then concludes with two observations: first, that the assumptions according to which monetarism should work were incorrect; and, second, that the cost of implementing the policy in increased unemployment was unacceptably high.
Lankester is certainly right to point out that the optimism of some of the early monetarists, myself included, was unfounded. Over the short term there was no systematic relationship between money supply growth and prices – the time lag was two years or longer. There were also differences of outcome when using different measures of the money supply. In addition, the regulatory environment in which monetary policy was conducted was constantly changing. Innovations such as the introduction of Competition and Credit Control, regulation by the “corset” and the abolition of exchange controls, made time series analysis difficult. However, the demand for money (the inverse of the velocity of circulation) has turned out to be stable over the longer term, such that central banks are able to control a measure of broad money which will affect prices after two year time lag. The best advice for a central bank is to aim for a steady growth of the money stock which is in line with the trend growth of money income.
The additional objection the author has to monetarism is its enormous cost in human suffering: namely, over 1 million jobs made redundant.
When she became Prime Minister in 1979, Mrs Thatcher made a point of honouring the pay settlements carried over from the “Winter of Discontent”, as well as the public sector pay awards recommended by the Clegg Commission, which the previous Government had instituted. Both were factors which inevitably led to some increase in unemployment, as was the new policy of switching revenues from high rates of income tax to a higher rate of VAT. However, over the next six years, unemployment in the UK continued to rise: from 6% to 12% of the labour force.
What is equally remarkable is that between 1980 and 1985 unemployment increased on average in all European Economic Community (EEC) countries — and by a large amount, from 5.8% to 11.2%. In Belgium, Italy and the Netherlands it rose above 12%. Even in Germany the unemployment rate more than doubled from 3.4% to 8.4%. Among the causes of this increase were the quadrupling of the oil price following the Iranian revolution and “sticky” real wages, because trade union bargaining power was strong, especially in public sector industries. But research has shown that fiscal tightening was not the cause. In other words, even without Mrs Thatcher’s policy revolution, executed by her Chancellor of the Exchequer Geoffrey Howe, unemployment would have risen significantly, if not doubled.
Lankester also acknowledges that research by Stephen Nickell and Jan van Ours had estimated that the “natural” rate of unemployment over these years for the UK — that is, the level at which the rate of inflation would remain stable, whether it was 0%, 2% or 10% — had risen from 3.8% (1969-73) to 7.5% (1974-89) and then to 9.5% (1981-86).
He concludes by recognising that there are positives from the growth of monetarism: that money does matter, in both analysis and policy, although we are not told how exactly that is so; that there is a “natural” rate of unemployment and so no sustainable trade-off between unemployment and inflation; that monetary policy is to be preferred to fiscal policy in the management of aggregate demand; and that unacceptable levels of unemployment must be tackled through micro-economic not macro-economic policies.
Should Mrs Thatcher have introduced an incomes policy which might have restrained wage increases over these years? Incomes policy had been introduced on numerous occasions since the early 1960s. The evidence from all incomes policies — whether introduced by Labour or Conservative governments and regardless of whether they were voluntary or statutory — is that they had no lasting impact on inflation. While they did initially lead to some wage restraint, this was subsequently undone, usually accompanied by strikes and industrial unrest.
Could the “British disease” of high inflation and high unemployment have been remedied without shock treatment? In principle, of course, it could — but in practice I very much doubt it. The most difficult challenge for the Thatcher Government in 1979-81 was to confront the economic malaise and the entrenched expectations of future inflation by trade unions, companies and the general public. This required a belief that the Government had a clear policy, that it would stick to the policy even though unemployment was rising, and that it would not change course. This it did. Its anti-inflationary policy was strengthened later by trade union reforms which reduced their power to disrupt the economy.
The irony of all this is that the 1981 Budget, which was roundly condemned by 364 economists because it put up taxes in order to reduce public borrowing (which was already greater than planned), actually marked the moment from which the UK economy recovered. It was a recovery that endured for the rest of the decade.
Photograph at top: Valentin Poleac; reproduced from Wikimedia Commons in accordance with a Creative Commons Attribution-Share Alike 4.0 International licence.
When someone like me from an older generation is confronted with a new piece of technology, inevitably we must turn to a younger person for help. What is described as ‘user friendly’ is usually so only to those who are already familiar with the ways of the machines. ‘Well, they have grown up with the new technology’ we say, by way of excuse. And that is true, but might it also be true that they have grown up, not only with, but also in competition with, the new technology? Consider the experience of infants in recent decades. They have learned from experience that their cries get the attention of parents, but at the same time they have found themselves in competition with mobile phones whose ring tones are set to call attention to themselves even against the background of considerable ambient noise, just like babies’ cries. And they have seen these gadgets lifted up to mothers’ cheeks, and those mothers looking attentively (lovingly?) at screens, just as the infants desired to be so regarded. Even in the most intimate moments of mothers’ quality time with their children, that third other is always present, and always likely to interrupt with its incessant demand for attention.
I am not trying to lay blame, to accuse mothers of harming their children (though here the notorious line from Philip Larkin’s poem might be quoted) but am simply asking what happens to people who learn how to be human, how to love and relate, in this context. What happens to children formed and raised in a milieu in which they must compete for attention, not with other children, but with mysterious talking and crying machines? What do they learn about priorities in relationships, about securing their own identity and interests and desires in this complex world? How is interpersonal communication fostered or frustrated when it is so structured by the mediating technology? This is the kind of question that arises when we consider AI in the context of common goods.
The consequences of the denial of face-to-face encounter of pupils with teachers and children with their peers, required by lockdown in response to Covid-19, are becoming evident. Teachers now observe the effects of this interruption to the normal processes of socialisation. Children lack the ordinary skills of social interaction, that they would formerly have been expected to bring to their school experience. But might it be the case that our reliance on gadgets for communication and socialising is also likely to have a negative impact on our culture because in some way draining it of the shared capabilities and skills and knowledge that makes a decent social existence possible? This question can be sharpened specifically in relation to Artificial Intelligence and its increased usage in various domains of social life. Is our common good at risk from AI and its applications? To deal with this question, we need to specify what is involved in our common goods, and how AI might jeopardise them.
Distinction of Common Goods
We can consider two cases of common goods, practical and perfective. The practical sense is that wherever people cooperate, they have a good in common, a common good. That good in common might be a private good (school places for our children), a club good (networks for alumni of our school), a collective good (any school’s ambition for its students), or a public good (high levels of educational attainment conditioning political discourse and respect for the rule of law). Perhaps the less obvious but more important way in which cooperation is for a common good is the perfective sense of good.
Again, taking schooling as an example, we can see how education as accomplishment of persons and communities, enables people to be more and to realise to a greater extent their human potential. What fulfils people is for their good, enabling them to flourish. Hence a perfective sense of the good is relevant, that might not be at the forefront of our thinking when we collaborate in some project. Then we focus on the task in hand, but our performance also shapes us and our relationships.
When considering the relationship between AI and common goods it is understandable that people would spontaneously begin with common goods in the practical sense of the objectives they hope to achieve by relying on AI. There is the project of reducing drudgery and repetitiveness in work, so that machines can do what humans have had to do. There are projects of increasing effectiveness and efficiency as more accurate analyses and diagnoses are made possible, factoring out the fallibility of human processes. There are ambitions of increasing fairness when the processing of vast quantities of paper such as application forms, whether for jobs, or for mortgages, or for credit, or university places, can be done without risk of human tiredness or boredom or prejudice distorting the process. The list goes on. Many worthwhile objectives can be pursued with the use of AI bringing accuracy, reliability, efficiency, and fairness to the undertaking.
But what about the perfective common goods at stake? What impact is the use of AI having or likely to have on the development of human persons, and on the quality of the relationships between persons who interact with one another mediated by the relevant technology? What is it doing or likely to do to community, to the quality of the cooperation itself that is in turn capable of being an instance of flourishing, a perfective realization of human potential? In various areas in which AI is currently being deployed we find questions being raised that touch on these perfective goods in common. These are still questions, but sufficiently concerning as to suggest that we cannot be indifferent to the possible answers.
One area of concern is that signalled by the potential of large language models that are so sophisticated they can produce very plausible and convincing text in several genres. ChatGPT developed by OpenAI fascinates with its ability to engage in a conversation with the user, answering questions and producing convincing answers. This can be very useful, but what is its impact on our understanding of what is going on in a conversation, or in written communication? If I no longer must assume that there is another human being collaborating with me in such interaction, does it impact on how I participate in communication when other persons are involved? If language is no longer exclusively a medium between people, do I then hear words differently when I’m aware they could be generated by a machine and not spoken by a person? If the voice I hear on the phone might not be that of a person, does that reinforce a tendency to treat the speaker in an instrumental way, whether a machine or not?
The absence of persons from relevant decision making when aided by AI is another concern. The superiority of AI aided medical diagnoses (because standardised based on large data inputs) over those made by physicians is well established. But patients are concerned about the implications for treatment when it is not another person, a physician with compassion as well as competence, making the decision. Similarly, when decisions about the granting of credit, or mortgages for house-buying, or jobs, are made by machines benefiting from analyses of large databases, the people whose applications are rejected can be upset that decisions with life changing consequences for them are taken by a machine and not another person. Even international human rights adjudication can now be facilitated by automated management of documentation. One might argue that the benefits of fairer and more reliable decisions outweigh the distress occasioned for some. But that is not the issue here. The issue is what we are doing to our common life, and to the willingness of people to collaborate, and comply, and accept the burdens along with the benefits of social cooperation, when machines and not human partners seem to be in control.
Among the willingness to accept burdens in social life is Losers’ Consent, the willingness to accept unfavourable outcomes of democratic decision making, a fundamental precondition for peaceful democracy. Is it also jeopardised by the undermining of social bonds occasioned by the replacement of human decisions makers with AI powered machines? Formation for human relationships and its reinforcement through social interaction is a perfective common good that is also a public good. Human capacities for bonding are formed and strengthened through daily encounters. Now we must face the possibility that those capacities are not reinforced but are instead jeopardised when our daily social encounters are increasingly with machines, and not with people. Have some of the infants who once competed with iPhones for a touch of mother’s cheek become adults who prefer to relate online?
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Dr Patrick Riordan, SJ, an Irish Jesuit, is Senior Fellow for Political Philosophy and Catholic Social Thought at Campion Hall, University of Oxford. Previously he taught political philosophy at Heythrop College, University of London. His 2017 book, Recovering Common Goods (Veritas, Dublin) was awarded the ‘Economy and Society’ prize by the Centesimus Annus Pro Pontifice Foundation in 2021. His most recent books are Human Dignity and Liberal Politics: Catholic Possibilities for the Common Good (Georgetown UP, 2023) and Connecting Ecologies: Integrating Responses to the Global Challenge (edited with Gavin Flood [Routledge, 2024]).
Are drugs like semaglutide a quick fix, or might they be opportunities to practise virtue?
Obesity is thought to affect over 800 million adults worldwide and according to the World Health Organisation, has tripled since 1975. Indeed, estimates are that half of the world’s population will be overweight or obese by 2035 and very few currently have access to long-term treatment to address obesity or the conditions that accompany it. However, the development of several drugs that deliver significant weight-loss have the potential to revolutionise treatment. Semaglutide, for example, better known by its brand name, Wegovy, brings about a reduction in weight of up to 15 per cent in recipients. Given the clinical advantages, not least in the treatment of obesity related conditions such as diabetes or kidney disease, it has been approved for use within the National Health Service, where, in spite of soaring demand, it is prioritised for use by high-risk patients who need to lose weight prior to receiving surgery for cancer or organ transplants. Owing to the potential success of such drugs, pharmaceutical companies are keen find a share of a market that some recent reports estimate will be worth approximately $100 billion, or perhaps $200 billion, by 2030.
Some might argue that since, in most cases, obesity is caused by poor diet and lack of exercise, it a consequence of a failure of self-restraint on the part of the individual. It therefore constitutes a problem of willpower and should be treated as such. However, it can plausibly be argued that the emergence of drugs such as semaglutide, far from being a ‘quick fix’ for those who have failed to take responsibility for their own well-being, in fact represent an opportunity to practise virtues such as temperance.
Virtue Theory and the Question of Character
To adopt the language of the virtue ethics tradition, obesity can be seen as a failure of the virtue of temperance. As a virtue, temperance is recognised by both the ancient Greek philosopher Aristotle and the mediaeval theologian and philosopher St Thomas Aquinas, with Aristotle characteristically identifying it as an ‘excellence’ of character that lies between two vices: the deficiency of insensibility and the excess of self-indulgence. For neither Aquinas nor Aristotle is temperance a virtue that relates purely to the consumption of food and drink. Like the other virtues, it rests on the capacity to correctly apprehend one’s situation and respond appropriately. In Aquinas’ terms, this would mean being informed by ‘right reason’ and having a grasp of the truth. As such, temperance – sometimes better understood by the term ‘moderation’ – is a trait of character that pertains to various areas of life. For instance, it might be applied to the emotions, with the suggestion that someone should temper his anger (which of course is not to say that he shouldn’t ever be angry, but only that in the given situation, his anger is excessive). Temperance, then, helps to produce order and balance – and in connection with the body, this means health. In failing to grasp the truth of his situation, with regard to the order of goods (such as physical health, spiritual wellbeing, food and pleasure) or their respective value, the subject falls into self-indulgence. He fails to control or moderate his natural desires – for food or pleasure, in this case – and his well-being is sacrificed to transient goods. This outlook also reflects the wider teaching of Scripture on avoiding excess, developing character and personal responsibility. From such a perspective, then, one might argue that obesity is indeed a moral problem, or, rather, a problem of character, and must be addressed accordingly, with guidance, education and self-discipline.
Drugs as an Opportunity for Responsibility
This might very well be true in many cases, but it is not clear that the existence of weight-loss drugs does in fact undercut the exercise and training of virtue. Might it rather be the case that such treatments represent an opportunity to exercise moderation in a way that the subject has found impossible of late, his situation having become chronic and his attitude having degenerated into hopelessness? By way of comparison, one might say that smoking can be overcome by willpower alone – and for some people it can. For those who are heavily addicted to nicotine, however, and have been smokers for some thirty years, perhaps this is to expect too much. Nicotine patches, nicotine gum and e-cigarettes are, for some, a necessary aid to enable them to overcome their habit and, hopefully, to give up smoking for good, the idea being that they eventually rely on their own willpower. Obesity resulting from lack of exercise and excess calorie consumption is arguably different with regard to the question of physical addiction – and the cost of weight-loss drugs is far higher than that of e-cigarettes – but a similar principle can still be said to apply: at some point, the patient must rely on strength of will. Indeed, the nature of such treatments suggests as much. They are not to be taken forever; rather, they reduce weight to a certain point, after which it is for the individual to take responsibility. One of the major benefits reported by those researching the effects of the drug orforglipron (a tablet often known as Alii or Xenical) was that once they had lost a certain amount of weight, patients changed the way they thought about food and found that they were no longer constantly feeling hunger or thinking about it. What is this but an opportunity to begin to exercise temperance in a manner that had become impossible?
While there will remain questions about the desirability, costs and effects of an obesity market, it would appear that such a market is not of itself necessarily inimical to the exercise of the self-restraint that is so often central to maintaining health. Based on the indications of what certain treatments can achieve, it might well be the case that the development of weight-loss drugs provides some individuals with the means not only of avoiding some of the worst effects of obesity on their health, but, with judicious use, to regain the responsibility and personal agency which had become difficult for them.
Neil Jordan is Senior Editor at the Centre for Enterprise, Markets and Ethics. For more information about Neil please click here.
