In the modern world, science and society often interact in a perverse way. We live in a technological society, and technology causes political problems. The politicians and the public expect science to provide answers to the problems. Scientific experts are paid and encouraged to provide answers. The public does not have much use for a scientist who says, “Sorry, but we don’t know”. The public prefers to listen to scientists who give confident answers to questions and make confident predictions of what will happen as a result of human activities. So it happens that the experts who talk publicly about politically contentious questions tend to speak more clearly than they think. They make confident predictions about the future, and end up believing their own predictions. Their predictions become dogmas which they do not question. The public is led to believe that the fashionable scientific dogmas are true, and it may sometimes happen that they are wrong. That is why heretics who question the dogmas are needed.
As a scientist I do not have much faith in predictions. Science is organized unpredictability.

As artificial intelligence (AI) systems increasingly become more widespread in society, many people regularly interact with them as a normal part of their everyday lives. The increasing prevalence of and seeming familiarity with everyday applications that employ AI may, however, easily betray its complexity. Diagnoses of the role of AI in society in public and scholarly discourse regularly depict AI as a uniform, monolithic phenomenon - almost like a force of nature that drives societal change. This is palpable, for instance, in statements that posit that AI will transform all aspects of social and economic life. However, while it is true that a certain set of technological advances largely rooted in computer science are responsible for an entire array of innovations in various domains, speaking of AI as a single technical entity conceals how elusive and multifaceted the term is.

AI systems often only form a technical component that is embedded in a social process. Together, they make up a more comprehensive socio-technical system, and the impacts of a given AI system always depend on this larger context in which they are implemented. The technical specification of an AI system does not predetermine the impact that it will have and the risks that it entails when it is implemented. A given technological solution, such as a lipreading device, may well be harmless or even vastly beneficial in one setting, for example, for deaf persons, but cause profound ethical and regulatory problems as part of a public video surveillance system - meaning that when an AI application is transposed from one setting to a different setting it may have radically different social consequences.