In September 2021, Helga Nowotny, a leading science and technology scholar and former president of the European Research Council (ERC), published a book titled In AI We Trust: Power, Illusion and Control of Predictive Algorithms (Polity). While this book – as the title suggests - has a lot to say about how human beings can retain meaningful control over machines, it is also relevant to discussions of digitisation and policy in much broader ways. It shows how the ways in which we enact ‘the digital’ – and how we make sense of what we are doing – renders some policy solutions, and some futures, more likely than others. Nowotny’s book helps us to understand our own human predicament during the pandemic, and what we need to change. I will illustrate this with three key insights from the book.

The magical role of numbers

People think in stories, but they trust in numbers. The pandemic has illustrated this yet again. Policy makers want ‘hard numbers’ to justify measures. News items feature arrows and graphs. In the public imagination, numbers are the mark of precision; they suggest privileged access to the truth about nature. But, as science and society scholar Daniel Sarewitz reminds us, “Many numbers that appear to be important for informing policy discussions and political debates describe made-up things, not actual things in nature. They are, to be sure, abstractions about, surrogates for, or simulations of what scientists believe is happening – or will happen – in nature. But they are numbers whose correspondence to something real in nature cannot be tested, even in theory.”

Consider the much discussed Rt number, for example, the so-called effective reproduction number. It indicates the number of people that one infected person will give the virus to on average. It is not an observable property of the virus, or of people; in fact, it cannot be observed at all. It is calculated by inferring from statistics on COVID-19 deaths, ICU-admissions, or hospitalisations to how fast the virus spreads. Like other COVID-19 related metrics, Rt articulates a societal convention rather than a natural ‘fact’. Nowotny’s book shows where the problem lies with this. If a policy problem is explained, predicted, and framed in a technical, ‘hard numbers’ kind of way, then it calls for a technical solution. It leads to vaccination programmes and mask mandates without knowing how to effectively implement them, and without the knowledge of why people make use of these, and why not. There is a “fundamental incompatibility”, Nowotny argues, between the logic of numbers and algorithm-based prediction on the one hand, and policy-making on the other: “Policy decisions usually include trade-offs between multiple, often incommensurable, aims and interests. The algorithms in machine learning systems, by contrast, are utilitarian maximizers of what is ultimately a single quantity based on explicitly weighted decision criteria. They do not tolerate ambiguity.” According to Nowotny, planning for the future does not only require numbers and precision, but also the accommodation of ambivalence, ambiguity, and complexity.

The privatisation of happiness

“Welcome to the Mirror World” reads the title of one chapter in Nowotny’s book. Since the British television series ‘Black Mirror’, looking glasses have become a symbol of dystopian futures within which the Covid-19 pandemic would have made good subject matter. Nowotny uses the mirror metaphor to describe a society in which we “cannot stop staring at ourselves”. Our quest for prediction is also to be understood in that way. We act upon what we believe the future holds for us. Because we are looking into a mirror, however, we only see ourselves.

Pandemic management that ignores the knowledge of historians and other humanities scholars is an example of this. American historian Sara Silverstein reminds us that improving so-called socio-economic determinants – the circumstances in which people live and work – is the most effective form of protection against pandemics. One reason for this is that people living in poor economic and social conditions are particularly strongly affected by the consequences of pandemics such as lockdowns. Another reason is that factors such as stable and affordable housing, good education for all, and a strong and accessible healthcare system improve the general health of the population.

In the first half of the 20th century, the focus of pandemic control was precisely on these social and economic factors. It was not until the second half of the 20th century, with the development of effective biomedical strategies such as antibiotic therapies, and the idea that infectious diseases could be controlled, that the emphasis changed. No longer were entire societies the main focus of intervention, but individuals. Also the responsibility for preventing health crises shifted increasingly from the collective actors to individual people and families, who were supposed to behave ‘healthily’ and ‘carefully’ to reduce risks.

Nowotny’s diagnosis, that happiness is no longer a collective state but an individual goal is immediately relevant to this. To obtain better pandemic preparedness, we should stop looking into the mirror but look at and talk to each other – and learn from previous generations. To paraphrase Nowotny, we need to understand life backwards if we want to live well forwards. Which brings me to my next and final point.

The need for ‘cathedral thinking’

The people who planned and built the cathedrals that we visit today knew that they would not live to see them completed. Time did not matter in the same way in the Middle Ages as it does today. Nowotny argues that ‘cathedral thinking’ is highly relevant to our current challenges: in the midst of the pandemic, some tend to forget that we are facing an even bigger danger than Covid-19, in the form of climate change. “The Anthropocene [era]”, Nowotny writes, “obliges us to relate human timescales with ecological and planetary timescales.” The notion of ‘cathedral thinking’ underscores not only the need for collaboration between different skills and disciplines, but also the importance of long-term thinking.

In sum, going far beyond other volumes that reduce the complexities of living in the digital era to the human-machine interface, Nowotny’s book is a thoughtful, nuanced, and at the same time passionate plea for the reign of wisdom. “Future needs wisdom,” she writes. If we reduce thinking about the future to trying to predict it merely based on ‘hard data’, we are disempowering ourselves.