PERSONALISED EXPERIENCES : WORLD-CLASS RESULTS AN INTERNATIONAL LEADER IN APPLIED INFRASTRUCTURE RESEARCH

UNSIMPLE TRUTHS….. Graham Harris UoW SMART Infrastructure Facility FBA, Windermere, UK

AN INTERNATIONAL LEADER IN APPLIED INFRASTRUCTURE RESEARCH

Drawing on experience from LEC UK, DEFRA and DTC

science evidence policy

plans actions impacts benefits

outputs outcomes

PREDICT ACT BENEFITS

EVIDENCE-BASED POLICY WANTS THESE

EVERYBODY REPORTS THESE ?

EVIDENCE

“SYSTEM” MODELS EVIDENCE

inputs

THE RATIONALIST “SCIENCE PUSH” VIEW

THE KNOWLEDGE-BASED LINEAR MODEL – “The Faustian bargain”

Perverse outcomes with….

• Ecosystems, watersheds, climate change – Environmental flows, river restoration

• Systems Biology, Genomics, GWAS – Medicine, health care, big pharma

• Infrastructure, energy, transport, water, IT • Economics: the GFC, M&A for corporations • Warfare, strategy, nation states • In fact anything which has living, reflexive,

behaving, adaptive, evolving components!

complexity

Engineering Physics

Scientific management

Known Knowns

Directives

Adaptive management

Bayesian statistics

Frequentist statistics

Precautionary Principle

Unknown Unknowns

Robust Decision Making

Ecology Climate Rivers Infrastructure

Complete Uncertainty

Complete certainty

Causal thickets

“Black Swans”

EXACT SCIENCES

Science and society 21st Century • Scientific method reveals axiomatic “laws” of

Nature (process of abstraction – externalities) – Cause-effect deduced from axiomatic laws:

• Evidence and refutation drive new knowledge: strong inference: adaptive management – Rationalist, realist, materialist worldview – science,

engineering, economics • Physics envy, liberal humanism, sociology,

economics: naïve realism – Risk assessments: CGE models, finance, the GFC – Individualism, markets, instrumental reason – Market-based instruments, biodiversity offsets

The “framing issue” • Managers and scientists assume can apply an EXACT

SCIENCE; rationalism, mathematics=causes, realism – Theory, data collection and analysis issues

• Built-in bias in expert opinion (e.g. economists) • Science-based normative framework, “noise” is averaged

– Universality and transportability • Philosophical basis is idealised (Wimsatt, Mitchell)

– Not appropriate for complex systems (Ulanowicz) – Science underestimates uncertainty (Wynne)

• JONAH’S 1ST LAW, world is predictable but can’t be changed

Plans and strategies

• It’s top down planning and strategies that fail • Largely due to mind-set of naïve realists and

rationalists • Something – COMPLEXITY - messes up our

mind-set for universality, predict-act • Planning, strategy, institutions, economics,

politics

complexity

Engineering Physics

Scientific management

Known Knowns

Directives

Adaptive management

Bayesian statistics

Frequentist statistics

Precautionary Principle

Unknown Unknowns

Robust Decision Making

Ecology Climate Rivers Infrastructure

Complete Uncertainty

Complete certainty

Causal thickets

“Black Swans”

Biology SOCIETY Systems Science

NO (few) UNIVERSAL LAWS

THE SPECIAL SCIENCES

The “special sciences” deal with a contextually different set of problems

(the humanities realise this)

they are “complex” and are about formation – the formation of structures – and how this formation affects the objects causing it.

Non-equilibrium, reflexivity, context, information

To use tools based on “physics envy” makes what in philosophy is called a category error

e.g. economics is about rationalist models of allocation and not the formation of markets

So what is complex?

• Driven “bottom up” by localism • Plesionic – neighbours, trust, cooperation • 2nd order interactions – reflexive • 2nd and 3rd thoughts: “thinking about

thinking” • No system without observer (Luhmann) • System defines environment • Key role for reflexive social interactions

Kirchner and Neal (2013) PNAS: fractal water chemistry

Non stationarity – normal statistics do not exist

Distributed robustness (Wagner) • Robustness is like a ball rolling about in a basin of attraction. • The position of the ball is not static. • Life exploits the adjacent possible. Equifinality is the norm. • Many complementary networks and options • Robustness involves the whole of the system, provides long

term security and solutions, is self-regulating or self organising, actively exploits variability, is persistent, and is only amenable to indirect management.

• Monitoring will not provide evidence of outcomes; statistical power will be low. Surprises will be expected.

• NOT EFFICIENT, NOT OPTIMAL, NOT PREDICTABLE

So we have a problem with “weak inference”… (low power)

There is no safe methodology of induction (Goodman, 1978)

The problem with “Black Swans” Unkown unknowns will always exist

And everyone has a different perspective so evidence is hard to come by and it debatable

Meaning and intention

• Sampling the statistical properties of their environment by local agents (hence ABMs) – No central processor: no central “meaner”

• Sampling requires both randomness and probabilities to explore and exploit the world – Meaning in the context of intentional behaviour

• Metabolism, immune system, eco-systems, society, cars/drivers… – Uncertainty, noise, information, meaning, context,

design: what is a system??

Life computes • The questions become:

– How much information is stored? – In what architecture? – How is new behaviour produced?

• Big data and statistics will not do: adaptive recursion (structure function) and equifinality

• Life is anti-fragile and “infinitely stupid”: distributed robustness

• Life computes but is not computable

New physics • New physics of networks, patterns and

information; limits of predictability – What information is stored? What does it mean?

• Entirely new approaches to computation – Agent based models, meta-statistics, meta-models – Discrete, sequential dynamical systems

• Advances in physics, theoretical computation – Not being picked up in important areas of biology,

economics, infrastructure (except Wagner) – New work in systems biology, some in genomics

• Uncertainties, Cal/Val problems, scenarios

So maybe….

• We admit that these problems are complex and qualitatively different from the “old physics” – Models and predictions will always be flawed – We try to explore the limits of knowledge

• We urgently seek new epistemologies, “framings” that lead to greater understanding

• We must also rethink the social, institutional, economic, political and moral aspects of this – A weakening of “scientific” (rationalist) authority and

a collaboration with a new political economy

We have made the mistake of assuming that social engagement was all we needed to do…. There’s

more to it that that..

The risks are underestimated and we have no ethical framework by which to set values

(other than money!) Contextualisation and meaning imply a

concern for moral philosophy

So we need to rethink our political economy

Rail

Government

science

Society

Trusts, CMAs NGOs CRCs

Devolution States

Regional Utilities Water Companies

Local Govts

Commonwealth

Self organisation

Philanthropy

Subsidiarity Double democratisation

Community solar PV Water Trusts

Data for robust local decisions is not the same as data for (realist) modelling and prediction

Road/rail

New infrastructure/technologies

• Exploit the “high frequency wave of the future” (Kirchner) – self-org, socio-technical systems

• Web-based tools: science in the hands of the community e.g. OPAL UK, Peta-Jakarta

• e.g. iphones as sensors, GridStix, acoustic sensors, motes, GPS, RFD tags, cameras

• Distributed expertise, extend and democratize science • Pluralism trumps expertise when uncertain • Society is the de facto regulator anyway

– Ulrich Beck “Remodernisation”, sub-politics,

How do we live? • Predominantly liberal political economy

– Lack of ethics in debate – corporatism, utilitarianism “whatever works”, market-based solutions

• Individualism – “rational individuals” – Predominant emotivism: just preferences

• How to deal with “me and us” and with “us and them”? A dumbed down debate – Tragedy of the moral commons – “me” first – Debate about “how do we live”

• Moral problem solving: imaginative moral deliberation: new problems, new solutions

Virtue • Classical idea from Homer, Aristotle • Virtue linked to the way life is lived in a

social context – the Greek polis and telos – The concept of “good” and the good life – Denied by individualism; utilitarian and

instrumental view of life which “uses” others: “we have lost our virtue”

So virtue is linked to intrinsic values both of Nature and of human life: and to the telos

– Moral practice: not individuals but social animals – higher level challenge

Artifactual structure (North)

• Effective use of institutions • Layered governance

– Self organised communty groups – Review of incentives, market structures, – institutional, legal (constitutive) design – Innovation, subsidiarity, fast failure,

• Define the rules of the game and who can play – Consider issues of moral philosophy and engagement

• Redefine “reform” – agents and constraints

TACKLING THE ASYMMETRY

Past revolutions: PPE

• Three and a half revolutions – Thomas Hobbes: the nation state,

Leviathan (1651) – JS Mill: the liberal state (1859) – Beatrice Webb: the welfare state

(1910 – followed by 2 World Wars) – Thatcher & Reagan (c. 1980 – present)

• Throwback to liberalism • Individuals and their values seen as

formed prior to social interactions – Perhaps liberalism has “met its

Waterloo” with global constraints?

The 4th revolution • Balancing material, social, moral and

environmental goods and services – Recovering the full economic, social,

environmental and aesthetic benefits – New SO intermediaries are arising from

the bottom up, coupled to technology (SOST)

– Paying compensation, respecting constraints, conserving moral goods – A discourse to tackle to tragedy of the social and moral commons

• Between “left” and “right”- smaller government but not none.. Merger of new science and new political economy

Infrastructure as art?

Beyond “post-normal” science Beyond “citizen science” Beyond “anything goes”

Philosophical objects Beauty, design, values

Evaluation and response Community engagement

Moral philosophy, aesthetics Political engagement

Redefine “reform”

We don’t know how the future will unfold….

But we can change it!!