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H. Avery and B. Nordén
Higher education thus faces a fundamental double constraint: to provide new generations of professionals and researchers with adequate competences and to develop
the specific types of scientific knowledge that are needed (see Miller et al. 2011), we
must know in advance what these needs will be. At the same time, our forecasting
tools cannot provide such answers in an era of rapid and unprecedented change. As in
ecosystems, sufficient diversity is therefore essential for HEIs to increase resilience
and to create hotbeds in which solutions can reach maturity and be ready for use at
the precise moment they are needed.
Such creativity presupposes experimenting at a small scale, and the willingness to
accept that the large majority of experiments will not lead to viable solutions. Driving
HEIs through “performance” criteria that mainly reward “success” thus blocks one of
the most important services HEIs can render. In terms of methodologies, emphasising
predictability gears our forecasting tools towards regularity and systemic conditions
relevant to the past, rendering them increasingly inadequate to describe a future
characterised by systemic instability, variability and conditions that differ from any
witnessed before (see Miller et al. 2011; Spangenberg 2019).
5 Limits to and Risks with the “Technological” Approach
It has been argued that increasing efficiency, above all through technological means
(see, for instance, von Weizsäcker et al. 2014), offers a way out of the situation
so that growth can continue through decoupling. While the intelligent use of technology is certainly needed to reduce environmental impacts, over-reliance on technology to solve the major challenges we face today may instead generate new sets
of problems that we are not able to solve (see also Adloff and Neckel 2019). Seen
globally, improvements through the use of less resource-consuming technologies
have been offset by economic growth, demographic growth and the new challenges
that appear as various tipping points are reached. Even at the local level, many
improvements correspond to outsourcing negative environmental and social impacts
to other parts of the planet. Although we may not yet have entirely exhausted all our
potentials for growth and expansion, there are limits to indefinite growth (Alexander
2012; Gough 2017; Raworth 2017), and denial amounts to placing the burden of
undoing our mistakes on the next generation. Transitions are therefore not simply a
matter of developing sustainable alternatives and supporting their implementation,
but also involve working proactively with phasing out unsustainable structures and
technologies.
All transitions involve deep-reaching rapid change. Although the precise future
impacts of different decisions are difficult to assess, certain conclusions can nevertheless be drawn regarding the disruptive effects of change (Miller et al. 2011). One
of the fundamental aspects to consider is how to develop the necessary expertise, and
how to develop institutions that are capable of continuous development, to respond
adequately to the demands that emerge. In times of environmental, technological
and societal shifts, much former expertise loses its relevance, and the organisation of
H. Avery and B. Nordén
Higher education thus faces a fundamental double constraint: to provide new generations of professionals and researchers with adequate competences and to develop
the specific types of scientific knowledge that are needed (see Miller et al. 2011), we
must know in advance what these needs will be. At the same time, our forecasting
tools cannot provide such answers in an era of rapid and unprecedented change. As in
ecosystems, sufficient diversity is therefore essential for HEIs to increase resilience
and to create hotbeds in which solutions can reach maturity and be ready for use at
the precise moment they are needed.
Such creativity presupposes experimenting at a small scale, and the willingness to
accept that the large majority of experiments will not lead to viable solutions. Driving
HEIs through “performance” criteria that mainly reward “success” thus blocks one of
the most important services HEIs can render. In terms of methodologies, emphasising
predictability gears our forecasting tools towards regularity and systemic conditions
relevant to the past, rendering them increasingly inadequate to describe a future
characterised by systemic instability, variability and conditions that differ from any
witnessed before (see Miller et al. 2011; Spangenberg 2019).
5 Limits to and Risks with the “Technological” Approach
It has been argued that increasing efficiency, above all through technological means
(see, for instance, von Weizsäcker et al. 2014), offers a way out of the situation
so that growth can continue through decoupling. While the intelligent use of technology is certainly needed to reduce environmental impacts, over-reliance on technology to solve the major challenges we face today may instead generate new sets
of problems that we are not able to solve (see also Adloff and Neckel 2019). Seen
globally, improvements through the use of less resource-consuming technologies
have been offset by economic growth, demographic growth and the new challenges
that appear as various tipping points are reached. Even at the local level, many
improvements correspond to outsourcing negative environmental and social impacts
to other parts of the planet. Although we may not yet have entirely exhausted all our
potentials for growth and expansion, there are limits to indefinite growth (Alexander
2012; Gough 2017; Raworth 2017), and denial amounts to placing the burden of
undoing our mistakes on the next generation. Transitions are therefore not simply a
matter of developing sustainable alternatives and supporting their implementation,
but also involve working proactively with phasing out unsustainable structures and
technologies.
All transitions involve deep-reaching rapid change. Although the precise future
impacts of different decisions are difficult to assess, certain conclusions can nevertheless be drawn regarding the disruptive effects of change (Miller et al. 2011). One
of the fundamental aspects to consider is how to develop the necessary expertise, and
how to develop institutions that are capable of continuous development, to respond
adequately to the demands that emerge. In times of environmental, technological
and societal shifts, much former expertise loses its relevance, and the organisation of