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Complexity and Futurity
Angela Wilkinson
Uncertainty, Digital Sciences and the Long Term : ImplicaBons for research? • The future is uncertain -‐ and this is an opportunity in acBon
but a problem in research! • Not trading one set of old certainBes for a new set –are the
future and the long term the same thing? • Big data : extending raBonality vs. a basis for shared
reasonableness • Research as predicBon or design? • Learning about THE future or learning with futures to create
new possibiliBes? • What is happening in the interdisciplinary, emerging field of foresight..
Uncertainty and VUCA!
Bounded raBonality Whose perspecBves on this new map maSers?
Messy puzzling situaBons, not simple problems: The future as the playing field of power…
Unclear and unfolding (Schoemaker 1993)
Messes (Ackoff 1979)
Ill-structured (Mitroff & Emshoff 1979)
Turbulent (Emery & Trist, 1965)
Wicked (Rittel & Webber 1973)
Big Data – Promises and Perils?
• Promises • Not just about large scale • More and different types of data • Cross scale insights • Global early warning systems • BeSer algorithms • Smarter ciBes and transport systems • PreventaBve health and producBon of care
• Perils • InformaBon overload or new quality of judgement • Making movement -‐ changing people’s minds? • Data doesn’t speak, it mumbles • Co-‐evoluBon of knowledge and ignorance • Keeping a seat for novelty, uncertainty • Data privacy and ownership • Not without cost • A new speed and depth in social learning?
Futures: messy emerging field!
Source: T. Kuosa, Futures (43), April 2011
Futurology vs. Foresight The search for situated reasonableness
• Before research comes search
• HosBng the future as an open and neutral space – framing and forecasBng – preferences and possibiliBes
• Keeping a seat for uncertainty at the table
• From predict-‐and-‐decide to co-‐create-‐
and-‐learn – the creaBve and undisciplined nature of anBcipatory
knowledge – The ambiguous, equivocal past and present: a
coevoluBon of knowledge and ignorance – CogniBve limits: focus and tunnelling; thinking fast and
slow – discounBng the distant – The acBve (ofen implicit) role of expectaBons,
assumpBons etc. – TemporaliBes
Strategic Foresight is the ability to create and maintain a high-‐quality, coherent and func;onal forward view, and to use the insights arising in useful organisa;onal ways. It represents a fusion of futures methods with those of strategic management.
Diversity of and within methods
Method Future(s) Temporal stance Futures thinking
Agtude (normaBve stance)
IntervenBon Approach
Epistemology of uncertainty Output
ForecasBng Single Linear: Past-‐to-‐future
Closed DescripBve: knowing/seeing
the future
Outside-‐in and adapBve
MathemaBcal treatment of uncertainty
Probable future
Visioning Single BackcasBng : future-‐back-‐to-‐
present
Closed NormaBve: responsibility for
the future
Inside-‐out and acBvist
Choices and values as basis for coping with uncertainty
Preferable future
Scenarios MulBple Entangled: mulBple
temporaliBes
Open DescripBve/ criBcal: creaBng opBons for the
future
Outside-‐in and can be either acBvist or adapBve
CogniBve biases, culture and social processes introduce addiBonal uncertainBes including ambiguity and
ignorance
(set of) Plausible futures
Source: Selsky, Wilkinson and Mangalagiu (2013) USING FUTURES METHODS IN CROSS SECTOR PARTNERSHIP PROJECTS: ENGAGING WICKED PROBLEMS RESPONSIBLY
InteracBve strategy
past present future
upframing
downframing
building
R Normann. Reframing Business using
Time concepBons – the future?
Me going towards (e.g. target)
coming towards me
Things from the past that will catch up with me
Top down forward looking science : GEA/IPCC/MEA
• Towards global foresight
• MulBple geographic scales
• Scenarios and modelling
• Different scales of meaning (Jasanoff)
• Second order back-‐casBng (Robinson et al)
Models AND Scenarios
12
models
scenarios
scenarios
models
Scenarios = sensitivity analysis
Scenarios = condiBons under which model might not be valid
CollaboraBve Foresight: Learning with futures to create the future
Reframing, not forecasBng
Networked Foresight
• Networked foresight approaches, designed with complexity concepts and tools, and enabled by social media technologies and web-‐based analysis are becoming vogue.
• These aim to enable faster, more inclusive and polycentric approaches to co-‐creaBng the future.
• Tools include emerging themaBc maps and real-‐Bme visualizaBon of story maps.
• Crowd sourcing is also presenBng new challenges – how to avoid malicious gaming.
Source: Noah Raford, Futurescape
Long term, virtual and uncertain: beyond forecasBng to reframing and creaBng
– Not neutral, the future as the playing field of power – More horizon scanning (and mulBple horizons) – Mixed methods (forecasBng vs. scenarios, visioning and back-‐casBng, sof systems thinking and hard models)
– Different purposes in engaging in explicit futures thinking: • exploratory (reveal and test assumpBons); decision support (ask beSer quesBons), values alignment (avoid conflict/forge new common ground)
– More collaboraBve, parBcipatory and networked foresight: social learning and feedback loops
• 4Ms: mulB-‐stakeholders, -‐dimensions, -‐scales, -‐temporaliBes – Different stances: learning about/preparing for; learning with futures to create the future
ImplicaBons for long term research: from knowing to (re)designing
Managing mulB-‐dimensional, grand scale transiBons under radical and irreducible uncertainty
– Irreducible uncertainty: in regard to means and goals and relaBonship between the two
– Deeper pasts, different starBng points, mulBple pathways, emergent interacBons
– Change as a social process – overcoming interBa and lock in: making movement ?