30 days after the official outbreak of the Covid-19 pandemic UK’s Wellcome Trust issued a statement Sharing research data and findings relevant to the novel coronavirus (Covid-19) outbreak to help ensure that:
- all peer-reviewed research publications relevant to the outbreak are made immediately open access, or freely available at least for the duration of the outbreak
- research findings relevant to the outbreak are shared immediately with the WHO upon journal submission, by the journal and with author knowledge
- research findings are made available via preprint servers before journal publication, or via platforms that make papers openly accessible before peer review, with clear statements regarding the availability of underlying data
- researchers share interim and final research data relating to the outbreak, together with protocols and standards used to collect the data, as rapidly and widely as possible – including with public health and research communities and the WHO
- authors are clear that data or preprints shared ahead of submission will not pre-empt its publication in these journals.
Global scientific community has immediately waged war against the pandemic (which is a very problematic concept in its own right) and news media have written elegies for open science. In the heat of the moment, Kelly Crowe of CBC News wrote: “When the story of the coronavirus (2019-nCOV) is finally written, it might well become a template for the utopian dream of open science — where research data is shared freely, unrestrained by competition, paywalls and patents.”
It soon became obvious that the promise of open science is not all it’s cracked up to be. On 28 February 2020 a simple Google Scholar search on Covid-19 returned 2,140 unique results, meaning that scholars in the field needed to read 36 new articles every day. As I write this text on 12 November, the same search returns about 1,310,000 results, meaning that scholars in the field now need to read 4132 articles per day. The viral behaviour of SARS-CoV-2 has leaked into the world of information and knowledge, where it now causes scientific equivalents of sneezing and loss of taste.
Discounting for all restrictions to this simple Google experiment (curated databases such as Web of Science offer less material, and most scientists read only works in their narrow disciplines), it is clear that human scholars simply cannot read all material relevant for Covid-19 research. In a recent editorial I recently wrote: “This leaves us with two choices and combinations thereof: we can either play the game of popularity, and read only the most cited papers, or we can process all papers using some sort of artificial intelligence. Needless to say, both choices are highly unsatisfactory (see Peters et al. 2020a). How can we know whether the most popular papers offer the best contributions to the problem? And how can we trust our artificial intelligences which have shown so many biases in the past?”
The problem of undiscovered public knowledge dates back to 1986 and has already been documented in a range of disciplines. Similar viral behaviours have already been identified in a range of techno-social phenomena from obvious computer viruses to post-truth. Nevertheless, it took a full-blown pandemic for the concept of viral modernity to slowly move from academic fringes towards the mainstream. Today, it is fair to say that this curious bioinformational mix of “blurred and messy relationships between physics and biology, old and new media, humanism and posthumanism, knowledge capitalism and bio-informational capitalism” defines the postdigital condition and creates new postdigital knowledge ecologies.
Many interactions between biology and information do not end up in viral behaviour, yet they are all mutually constitutive with bioinformational capitalism “based on a self-organizing and self-replicating code that harnesses both the results of the information and new biology revolutions and brings them together in a powerful alliance”. Landing in the cluttered space of new concepts such as data capitalism, algorithmic capitalism, communicative capitalism, surveillance capitalism, technoscientific capitalism, high tech and low pay capitalism, and others, bioinformational capitalism adds a postdigital overtone to a long line of inquiry from Jeremy Bentham’s Panopticon through cybernetics to Michel Foucault’s biopolitics. In the midst of the pandemic, it is almost impossible to disagree with Freeman Dyson’s 2007 conclusion that “the twentieth century was the century of physics and the twenty-first century will be the century of biology”.
However, our current knowledge ecologies are still deeply imbued in a logic which relies on bigger databases, faster computers, and stronger energy-intensive artificial intelligences. This logic, which has recently initiated a torrent of bombastic titles such as AI Could Save the World, If It Doesn’t Ruin the Environment First, can be optimized only up to a point. Our sciences are dialectically intertwined with our social arrangements, and our current version of capitalism is based on the unsustainable principle of infinite growth on a limited planet. Therefore, sustainable postdigital knowledge ecologies can emerge only in alliance with new politics. This is an important point of intersection between natural sciences, social sciences, arts, and other areas of human activity.
So how may this new bioinformational politics look like? We need to critique bioinformational capitalism, and we also need to dare and imagine different worlds. We need new utopias, fit for our pandemic moment and our age of the Anthropocene. Tyson Lewis shows that critical utopia serves ‘both a cognitive (critique of the present through imaginative reconstruction of the future) and affective (opening up the possibility for hope, for desiring differently) function’. In our forthcoming article, Derek Ford and I develop this thought further and say that “speaking of the cognitive function, we urgently need to develop a better understanding of living systems and their interactions with technology at all scales – from viruses, through human beings, to Earth’s ecosystem. Focusing on the affective function, we need to align our hopes and desires with our (post-)Anthropogenic reality, acknowledging and negating our affectivity—our capacity to affect and to be affected by others known and unknown, human and machine, animal and mineral, subjective and objective, cognitive and affective.”
Before we try and develop new postdigital knowledge ecologies, we first need to conscientize our own role in current systems of knowledge production and dissemination. We are not innocent by-standers, or modest witnesses, or heroes in the war against the virus. Writing this article for The Post-Pandemic University, I am the bioinformationalist virus of Covid-19 research publication. Having published so many wonderful articles and podcasts, its founders and editors are super-spreaders of the virus. We, academics and researchers, are the key constituents of our knowledge ecologies. Paraphrasing Antonio Machado, we make postdigital knowledge ecologies of tomorrow through our practices of today.
Our exact goals and strategies are impossible to foresee because they will depend on the cognitive and affective dimensions of our collective imaginings for the future of scientific research. What we now know, is that these imaginings cannot come into being within existing systems of knowledge development and dissemination. This does not imply that we should stop doing what we know best: traditional scientific research is a great gift to humankind. However, we should urgently replace the reductive notion of post-pandemic research methods with a broader and deeper concept of postdigital knowledge ecologies. These new ecologies require new philosophies, new research methodologies, new politics, and much more. To develop all these, we need to collectively and imaginatively reconstruct our futures within our present and open up spaces for desiring differently. The post-pandemic university needs to take up a central role in these processes: our disciplinary spaces of analysis and critique need to also become post-disciplinary spaces of desire, hope, and utopian imagination. Postdigital knowledge ecologies are in their early days, really in their infancy; our collective imaginings of today will be our collective reality of tomorrow.
PS. If you would like to actively participate in development of postdigital knowledge ecologies, please take a look at the call for chapters for the new book in Postdigital Science and Education book series: Bioinformational Philosophy and Postdigital Knowledge Ecologies edited by Michael Peters, Petar Jandrić, and Sarah Hayes.
Petar Jandrić (PhD) is a Professor at the University of Applied Sciences in Zagreb (Croatia), Visiting Professor at the University of Wolverhampton (UK), and Visiting Associate Professor at the University of Zagreb (Croatia). His research interests are focused to the intersections between critical pedagogy and information and communication technologies.