The concept of unknown unknowns highlights the importance of introspection in assessing knowledge. It suggests that finding our way in the set of known-knowns, known-unknowns, unknown-knowns and unknown-unknowns, reduces to asking:
how uncertain are we? and
how aware are we of uncertainty?
When a problem involves a decision-making team, rather than a single individual, we also need to ask:
how do context and perception affect what we know?
What are the research hotspots in the Science of Team Science (SciTS) field? How have they evolved in the last decade?
We used conference programs from the annual International Science of Team Science (INSciTS) conferences held between 2010-2019 and the CorTexT Platform (https://www.cortext.net/) to select the top terms used with high frequency in the 852 titles and abstracts.
What are the core arguments that critics of interdisciplinarity employ? Which of these criticisms can help to clarify what interdisciplinarity is and what it isn’t?
While some of the criticisms of interdisciplinarity stem from a general misunderstanding of its purpose or from a bad experience, others seem well-founded. Thus, while some must be rejected, others should be accepted.
I outline five different types of criticisms drawn from three main sources:(1) academic writings (see reference list), (2) an empirical survey on interdisciplinarity (Sauzet 2017) (3) informal discussions.
As we enter a new decade with numerous looming social and environmental issues, what are the challenges and opportunities facing the scientific community to unlock the potential of socio-environmental systems modeling?
What is socio-environmental systems modelling?
Socio-environmental systems modelling:
involves developing and/or applying models to investigate complex problems arising from interactions among human (ie. social, economic) and natural (ie. biophysical, ecological, environmental) systems.
can be used to support multiple goals, such as informing decision making and actionable science, promoting learning, education and communication.
is based on a diverse set of computational modeling approaches, including system dynamics, Bayesian networks, agent-based models, dynamic stochastic equilibrium models, statistical microsimulation models and hybrid approaches.
What is it about complex social systems that keeps reproducing old problems, as well as adding new ones? How can public policy move away from what I call the Mencken Syndrome (in reference to a quotation from American journalist Henry Mencken) – that is, continually proposing clear and simple solutions to complex social problems – that are also wrong!
With this goal in mind, I have compiled a list of fifteen major characteristics of complex social systems based on the system dynamics and complexity sciences literatures, as well as my own research.
Why do very few people enjoy sitting comfortably with their unknown unknowns? Why is there an uncomfortable liminality ‘betwixt and between’ the known and unknown worlds?
How can we explore unknowns in a more speculative, playful, creative capacity, through our imaginations? How can we use lack of knowledge to learn about ourselves and let it teach us how to be comfortable and curious in the midst of unknowing?
The power and allure of unknown unknowns have long been recognised by creative practitioners as a holy grail for inspiration.
How can academic researchers working in transdisciplinary teams establish genuine collaborations with people who do not work in academia? How can they overcome the limitations of their discipline-based training, especially assigning value and hierarchy to specialized forms of knowledge production that privileges certain methodologies and epistemologies over others?
We argue that to truly engage in collaborative work, academics need to participate in deliberate processes of critical unlearning that enable the decentering of academia in the processes and politics of transdisciplinary knowledge production and knowledge translation. What we mean by this is that academics have to be willing to acknowledge, reflect upon, and intentionally discard conventional avenues of designing and conducting research activities in order to be authentically open to other ways of exploring questions about the world in collaboration with diverse groups of social actors.
Change can be expected, envisioned and known, and even created, accelerated or stopped. But change does not always follow a linear and predictable path, nor is it always controllable. Novelty and surprise are inescapable features of life. Non-linear change can involve threats or opportunities.
Although it defines the world we live in, who we are, the outlooks we have and what we do, we often do not relate to non-linear change in a meaningful way. What is holding us back from engaging with it? How do we deal with non-linear change? And what are promising ways forward?
Sometimes, we wonder why decisions in Asia are being made at gargantuan speed. How do Asians deal with uncertainty arising from unknown unknowns? Can yin-yang thinking that is typical for several Asian cultures provide a useful answer?
Let’s look at differences between Asian and Western thinking first. Western people tend to prefer strategic planning with linear extrapolation of things past. The underlying mantra is risk management to buffer the organization and to protect it from harmful consequences for the business. But juxtaposing risk and uncertainty is critical. Under conditions of uncertainty, linearity is at stake and risk management limited.
By Maria Helena Guimarães, Olivia Bina and Christian Pohl
If disciplines shape scientific research by forming the primary institutional and cognitive units in academia, how do researchers start being interested in and working with a transdisciplinary approach? How does this influence their career development?
How can we distinguish between knowledge and ignorance and our meta-knowledge of these – that is, whether we are aware that we know or don’t know any particular thing? The common answer is the 2×2 trope of: known knowns; unknown knowns; known unknowns; and unknown unknowns.
For those interested in helping people navigate a complex world, unknown unknowns are perhaps the trickiest of these to explain – partly because the moment you think of an example, the previously “unknown unknown” morphs into a “known unknown”.
My interest here is to demonstrate that this 2×2 division of knowledge and ignorance is far less crisp than we often assume.
This is because knowledge is not something that exists in the world but rather in individual minds. That is, whether something is ‘known’ depends not on whether someone, somewhere, knows it; but on whether this person, here-and-now does.