Dr Valentina Amuso and Dr Lieve Van Woensel consider how policymakers can best approach technological change in an era of rapid disruption.
From crypto-assets to artificial intelligence and robotics, disruptive innovation is constantly reshaping our realities and the societal context in which we live. A persistent concern among policymakers is how to minimise risks stemming from technological advancement while harnessing their full potential. This conundrum is pervasive both in policy and governance. Innovation tends to develop along unexpected paths, leaving policymakers ill-prepared to address new challenges, and suggesting that a lack of preparedness is inevitable. How can policymakers make decisions when data are scarce or non-existent? A more worrisome risk lies in ignoring the societal context in which the technology develops.
Since the dawn of time, preparedness has been an acute concern for policymaking. Amassing sufficient resources to endure war or famine was often key to states’ survival. In more recent times, people have relied on forecasting to better understand possible trends and anticipate potentially adverse consequences. However, the benefits of forecasting might be painstakingly limited in the case of disruptive technology. How can historical data be useful in detecting a pattern in such cases? It is one thing to be able to predict the likelihood of future wars according to different scenarios defined by competing international hierarchies in the present and the past. Not to brush off the limits of such approaches, but the ability to predict the impact of artificial intelligence on our way of life is something else entirely. Policymaking in the context of radical technological change and disruptive advancements requires more careful consideration than in more traditional scenarios.
The problem, however, does not just concern historical data, or the lack thereof. Some knowledge and evidence can still be obtained through analogical reasoning. This may be less difficult if the innovation has similarities with disruptions that have already occurred. For instance, similarities between genetic engineering and Synthetic Biology (SynBio) helped policymakers to be more prepared when addressing risks stemming from SynBio. Even when technology is more pronouncedly novel, data can still be collected from early developments to derive possible scenarios. In the case of crypto-assets, early evidence pointed to the inherently instable and speculative nature of such assets. This prompted EU officials to think of possible remedies and evaluate the fitness of existing regulatory frameworks against potential evolutions and diffusion of the innovation.
However, preparedness requires moving beyond the available evidence, including estimates and partial data, to provide effective governance. Preparedness calls for a full-fledged immersion in the broader societal context. Although reflection on the societal context should be an integral part of any decision-making process, the potentially unexpected societal transformation triggered by technology makes consideration of the societal impact imperative. For instance, while the introduction of artificial intelligence in agriculture might improve our ability to efficiently monitor soil quality, thus improving the choice of fertiliser, sensitive political questions remain regarding the ownership and use of such data and cybersecurity.
Preparedness requires moving beyond the available evidence, including estimates and partial data, to provide effective governance. Preparedness calls for a full-fledged immersion in the broader societal context.
Foresight methodologies reflect on these shortcomings and offer a set of methods to systematically learn about possible futures and inform policymaking. Preparedness through foresight implies first and foremost ‘zooming out’ and, secondly, ‘slicing in’.
Zooming out: preparedness starts with knowing the ecosystem. Many would agree that a transition to electric cars is overwhelmingly beneficial for the planet. Yet a 360-degree approach would allow us to move beyond the most apparent benefits. Extracting the key materials used to build electric cars, such as cobalt, has often been associated with exploitation and less than “green” practices. Knowing the ecosystem implies being aware of the broader context of societal actors embedded in it, which extends to those able to influence how technology evolves, those who are and will be affected by it, and those who have manifested concerns.
Slicing in: achieving a broader perspective can be obtained through stakeholders’ participation in brainstorming discussions but fundamentally requires multidisciplinarity. There are several schemes that conduct foresight analysis and capitalise upon a variety of disciplines. Many foresight methods rely on STEEP. The approach emphasises the need to evaluate 1. societal consequences and benefits of technology; 2. technological-related impact (e.g., the use and efficacy of the innovation); 3. its influence on the economy; 4. environmental concerns; and 5. political consequences, which encompass questions stretching from democracy and human rights to geopolitics.
Since 2015, the Foresight Unit at the European Parliament Research Service (EPRS) added two further categories to STEEP: Ethics (E) and Demographics (D). While ethical consideration extends to collective wellbeing and justice, thinking of demographics makes it possible to consider the impact of technology in relation to education, gender, and age groups. STEEPED is the gold standard for carrying out foresight analysis in the European Parliament.
We live in an era characterised by unprecedented disruptive innovation. Revolutionary inventions or radical technological advancements are not anything new to humankind, but the pace of technological disruption has taken a new different, faster, and deeper turn. In light of such considerations, it might be valuable for governments to consider how best to approach technological change. Limited availability of data might be a concern. Beyond that, the ability to place the innovation in a wider context to assess its possible implications, the correct design of stakeholders’ involvement in addressing the technology ecosystem, and the necessity of a multidisciplinary approach, remain key to facing the challenges of the future.
Dr Valentina Amuso is a lecturer (teaching) in the Department of Political Science at UCL.
Dr Lieve Van Woensel is a foresight expert and former head of the Scientific Foresight Service within the European Parliamentary Research Service (European Parliament).
Image by Maxim Hopman on Unsplash.
The views expressed in this post are those of the author, and not of the UCL European Institute, nor of UCL.
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