What Happened to the Post Covid Digital Boom and Why?
Moving out of Covid-19, many may have expected more from the digital boom that appeared to be occurring with the emergence of seemingly fully decentralized web platforms (Web3) and 3D virtual world interfaces (the ‘metaverse’). An article recently published in the journal American Affairs posits an unexpected root cause of the stagnation: the professionalization/standardization of the US academic research system.
Failures of Web3, Metaverse, and the Current Bursting Digital Bubble
Web3 and Metaverse, according to the article, are not only riddled with enormous shortcomings in design (for example, the resolution and brightness of VR headsets for instance) but also issues axiomatic to the innovations themselves, e.g. when it comes to blockchain, the impossibility of a decentralized but also ‘distributed’ program which requires replication of data and therefore a central authority to synchronise the software.
Evidence of the inadequacy of digital innovations to meet the challenges and satisfy the needs of consumers is evident in the disappointing economic growth of new technologies in the 2010s compared to the dot com bubble. Enormous cumulative losses of many businesses, as well as the cryptocurrency crash, further indicate market failure. Seventy-seven of the major American publicly traded technology firms have accrued cumulative losses greater than annual revenues, and such businesses are not providing lasting innovations (unlike e-commerce, digital media etc. in the wake of the dot com bubble burst). The FTX and other cryptocurrency crashes are also evidence of a lack of viability for some of the new digital ideas that have been popularized in recent times.
Effects of Professionalization/Standardization of Scientific Research
Funk, Vinsel and McConnell attribute the stagnation largely to the professionalization of scientific research, specifically due to:
1) the separation of increasingly specific areas of scientific research into professional worlds detached from other areas of research and study; and
2) the standardization of procedures and rubrics for assessing good or important research.
These two main modus operandi of professionalization prevent the emergence of truly impactful or creative innovations. The US research system’s funding of tertiary education institutions has, for instance drastically undermined pivotal considerations of commercial viability as a part of university research. That is, doctoral candidates are permitted and encouraged to focus on only the technical newness of their research in place of the worldly or practical uses of their innovations. The authors also note that universities today tend to value hyper-specialization, which prevents the holistic or cross-disciplinary thinking required to create meaningful change.
The highly detrimental effect on innovation effected by the professionalization of scientific research are also noticeable in the rampant “publish or perish” culture at universities. The popular h-indices system now bases professional viability as a researcher on the number of publications by a researcher and the extent of the citation of those publications by their peers. Scientific scholarship is therefore colonized by a demand for constant academic output at the expense of substantively meaningful work, which, due the more disruptive and divergent concepts and approaches it usually involves, requires riskier and more time-consuming consideration and testing. Peer-reviewing has moreover failed to resist the degradation of quality by the demand for quantity - “published papers that fail replication experiment are cited more than papers that pass because they make bolder claims”.
The culture of professionalism/standardization in research fields has also led to the proliferation of standard procedures and rubrics for assessing grant applications, which not only tends to focus on factors external to the actual value of the research (e.g. its ability to draw publicity to the researcher or school), but also inhibits discretionary decision-making. Schools therefore lose the capacity to distinguish truly impactful but unusual projects (from which innovative research tends to stem) from projects that have an inherited veneer of efficacy. In general, the increase in university procedure and bureaucracy prevents human decision-making that permits and encourages risk-taking and discovery.
The authors of the blog highlight that overall what has emerged from the current culture of hyper-specialization and standardization is an absurd rupture between efficacy and success in research professions. In the current research system, researchers hold onto their jobs and even achieve prestige by avoiding disruption and true innovation. The failure of the digital innovation landscape to provide any truly groundbreaking technologies in the past decade is in this regard far from wholly unexpected.
Furthermore, such standardization processes can spill over into the commercial world as well. Many cryptocurrency businesses that have failed spent significant sums creating “compliance structures” that were thorough but ineffective, in order to pass off as legitimate. Though a business may be “rubber stamped” with certifications and licenses, this does not guarantee business viability and success.
Valuable Alternatives
The article encourages us to take a more critical look at the operation of our institutions, and their interaction with corporate commercial growth. Instead of funding universities further, a more effective approach is likely to lie in reducing bureaucracy and hyper-specialization in favour of more discretionary decision-making and cross-disciplinary research.
Such changes would aim to promote and discern substantively daring and important research as opposed to proposals and pathways which serve existing administrative procedures and hierarchies. The authors note that this opposition to the powers that be means that, to at least some extent, actively nurturing scientific innovation will require some level of social disruption.
For bitcoin and metaverse enthusiasts, this might mean a second look at the capabilities of emerging digital innovation, keeping in mind that compliance metrics, or the standard formulas applied in the business and learned through research, may need to be questioned again, for practical use.