Understanding emerging technologies via skin-in-the-game

Conciseness and clarity are rare in the world of communicating the functionality and impact of emerging technologies. This is attributable to the complexity of the endeavor. On the one hand, scientists and entrepreneurs make use of a different – a technical – language not shared by their audience. One the other hand, the creation of new concepts or the linking of two prior non-related ones can cause misunderstandings even amongst homogenous groups, that is in this case, groups consisting of professionals with the same occupation.



This communication is not as efficient as one might wish because of the so-called ‘idiosyncratic’ nature of the development of knowledge, independent of the field of study. ‘Idiosyncratic’, meaning ‘peculiar’ or ‘individual’, refers to the particular circumstances a person was in when they connected the idiomatic dots in their head and had an insight. Finding the right, sufficient words to describe this process therefore can be challenging and may complicate communication with peers and a broader audience. This is not only because formulating precisely what is intended is difficult but usually also because the context of the subject matter is constantly evolving with time which renders registering it problematic.


Additional to the perspective from academia shown above, there may be communicators from other fields who apply those insights. In the case of emerging companies that build their business model on distributed ledger technology, such as the blockchain concept, the audience is exposed to interpretations and explanations from the respective field. This means that another layer affecting the audience’s perspective and understanding has been added. One can imagine the layer as a filter altering the original information in order to make it more suitable for a certain target audience, as for instance news outlets focusing on asset management illustrate.


In order to develop an understanding of novel technologies, it is crucial to be aware of the direction of learning about the subject matter. A realistic scenario would be for the interested reader to see the various application possibilities of a certain technology, identify a certain pattern and subsequently be willing to go in depth and explore the technology’s subtleties. This approach, while not scientific by modern standards, gives a general view of developments in the technology’s range of application.


A more direct and immediate approach would be to expose oneself to ideally negative consequences stemming from applications of the technology. While counterintuitive, this line of reasoning is called having ‘skin-in-the-game’, as Wall-Street traders and most famously tail-risk expert Nassim Nicholas Taleb describe the strategy. It is a heuristic of strengthening one’s own decision-making by having to face also the negative consequences of one’s actions. Applied to our attempt to understand emerging technologies better this means creating a symmetrical risk- and win-incentive.


For instance, one could combine the two different aforementioned approaches and try to identify investment opportunities amongst the novel asset class of cryptocurrencies, many of which are based on the blockchain concept. Investing small amounts, thus bearing some risk and exposing oneself both to the negative and positive consequences of ones’ knowledge of the field will quite literally teach the student of the field valuable but inexpensive lessons.



Another example would be cooking for friends, which means taking some risk – potentially burning the food or seasoning it badly – will test your culinary sophistication and reward you with social capital as in this example or monetary capital as in the aforementioned one.


A key-takeaway for new students of emerging technologies is to be aware of the scaling trap. A mistake that ought to be avoided, this would mean to assume that the impact a certain technology has on an individual person can be scaled to societal level. The expectation to accurately predict the impact of technologies on entire societies based on their impact as experienced in small use-cases is a fallacy stemming from well-known but often overlooked dynamics.


These are called ‘nonlinear’ and imply that despite a certain pattern of impact has been identified on an individual level, the impact of the technology on a large group of people interacting with each other – which takes time – can be entirely different and is virtually unpredictable. The emerging complexity between the multifaceted technology and society quickly becomes too comprehensive – an important insight for policymakers, scientists, and journalists alike.


Keeping this in mind, one has a tool to detect and avoid simplifications, and approach novel technologies thoughtfully and cautiously.


Author: Patrick Lehner

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