smart seminar series: formal models of social processes

Formal Models of Social Processes

Computational Justice for Fair and Sustainable

Resource Allocation in Socio-Technical Systems

Jeremy PittDepartment of Electrical and Electronic Engineering

SMART Institute, University of Wollongong, 28/11/2014

Agenda

Problem statement: resource allocation in open system

Formalisation of Ostrom’s institutional design principles forsustainable resource allocation

Formalisation of Rescher’s theory of distributive justice for fairresource allocation

Computational justice in socio-technical systems(Why It Matters)

Summary and conclusions

Jeremy Pitt Formal Models of Social Processes 2 / 22

Context

Open systems

I autonomous, heterogeneous, (possibly) competing components

‘Technical’ systems – composed of purely computing agentsI Grid computing, cloud computing, . . .I Ad hoc networks, sensor networks, vehicular networks, . . .I Virtual organisations, . . .I Reconfigurable manufacturing, evolvable manufacturing, . . .I Power systems, . . .

Common problem: a requirement for the agents (akaappropriators) to collectivise and distribute resources,in the context of . . .


Key Features of Open Systems

Self-determination (no centralised ‘authority’)

I Selection and modification of the rules for resource allocationare determined by the entities themselves

Expectation of error and corrective actionI Sub-ideal behaviour is to be expected (be it by accident,

necessity or malice), as is the enforcement of sanctions fornon-compliance

Economy of scarcityI Sufficient resources to keep appropriators satisfied at the

long-term, but insufficient to meet all demands at a particulartime-point

Endogeneous resourcesI Computing a resource allocation must be ‘paid for’ from the

same resources being allocated

No full disclosureI Appropriators are autonomous and their internal states cannot

be checked


Methodology

Introspection – how do people solve this sort of problem?

Aside – sociologically-inspired computing

Pre-formalTheory

Calculus1. . .

Calculusn

ComputerModel

ObservedPhenomena

ObservedPerfomance

Expressive capacity Requirements coverage⇐ ⇒

Conceptual granularity Computational tractability⇐ ⇒

Consistency Usability

formal characterisation principled operationalisation

theoryconstruction

controlledexperimentation

I Communication – speech act theoryI Socialisation – trust, forgiveness and social networksI Organisation and Deliberation – normsI Governance – selection and modification of rulesI (In progress: justice and social capital)

Answer: the evolution of institutions for collective action


Common-Pool Resource Management

People are very good at “making stuff up”

In particular, making up and writing down conventional rulesto (voluntarily) regulate/organise their own behaviour

Elinor Ostrom (Nobel Laureate for Economic Science, 2009)

Common-pool resource (CPR) management byself-governing institutionsAvoidance (not refutation) of ‘the tragedy of the commons’Alternative to privatisation or centralisation

Role-based protocols for implementing conventionalprocedures

Self-organisation: change the rules according to other(‘fixed’, ‘pre-defined’) sets of rules

Self-determination: those affected by the rules participate intheir selection


Self-Governing the Commons with Institutions

Definition: “set of working rules that are used to determinewho is eligible to make decisions in some arena, what actionsare allowed or constrained, ... [and] contain prescriptions thatforbid, permit or require some action or outcome” [Ostrom]

Conventionally agreed, mutually understood, monitored andenforced, mutable and nested

Nesting: tripartite analysis

operational-, collective- and constitutional-choice rules

Decision arenas [Action Situations]

Requires representation of Institutionalised Power


Sustainability of the Commons

Analysis: necessary conditions for successful enduringinstitutions

‘Supply’: handbook of institutional design principles

P1 Clearly defined boundariesP2 Congruence between appropriation and provision rules and the

state of the prevailing local environmentP3 Collective choice arrangementsP4 Monitoring by appointed agenciesP5 Flexible scale of graduated sanctionsP6 Access to fast, cheap conflict resolution mechanismsP7 No intervention by external authoritiesP8 Systems of systems

Apply the methodology to Ostrom’s principles


Self-Organising Electronic Institutions (SOEI)

Electronic InstitutionsFormalise structural, functional and procedural aspects ofinstitutions in mathematical or computational formSelf-Organising: selection and modification of structures,functions, and procedures are determined by the members

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Figure 1: Rules relationships: solid lines denote input and output of the rules; dashed lines denote chair assignment. (a) ...(b) ...

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Figure 2: Rules relationships: solid lines denote input and output of the rules; dashed lines denote chair assignment. (a) ...(b) ...Self-Organising electronic institutions represented in

framework of dynamic norm-governed systems (Artikis, 2012)SOEI encapsulating Ostrom’s institutional design principles canbe axiomatised in computational logic using the EventCalculus, and directly executedExperiments showed that the more principles that wereaxiomatised, it was more likely that the institution couldmaintain ‘high’ levels of membership and sustain the resource


“That’s Not Fair” – Distributive Justice and CPRs

Is the axiomatisation of the allocation method, and theoutcomes it produces, ‘fair’, now, (with respect to) the past,and in the future?

What fairness criteria to use to distribute the resources?

Egalitarian: maximise satisfaction of most disadvantaged agentEnvy-free: no agent prefers the allocation of any other agentProportional : all agents receive the same shareEquitable: each agent derives the same utility. . .

There are many objective metrics for measuring ‘fairness’outcomes

Limitations of existing fairness criteria:

Many not appropriate under an economy of scarcityFocus on a single aspect (monistic)Often disregard temporal aspects (e.g. repeated allocations)


Experimental Setting – Linear Public Good Game (LPG)

LPG commonly used to study free-riding in collective actionsituations

Variant game: LPG ′ – in each round, each agent:

Determines the resources it has available, gi ∈ [0, 1]Determines its need for resources, qi ∈ [0, 1]

In an economy of scarcity, qi > gi

Makes a demand for resources, di ∈ [0, 1]Makes a provision of resources, pi ∈ [0, 1] (pi ≤ gi )Receives an allocation of resources, ri ∈ [0, 1]Makes an appropriation of resources, r ′i ∈ [0, 1]

Agents may not comply, r ′i > ri

Utility in LPG ′: accrued resources Ri = r ′i + (gi − pi )

Ui =

{aqi + b(Ri − qi ), if Ri ≥ qi

aRi − c(qi − Ri ), otherwise


Rescher’s Legitimate Claims

Canons of distributive justice: treat people according to . . .

. . . as equals

. . . needs

. . . actual productive contribution

. . . efforts and sacrifices “

. . . a valuation of their socially-useful services

. . . supply and demand

. . . ability, merit or achievements

Each canon, taken in isolation, is inadequate to achieve‘fairness’

Distributive justice consists of evaluating and prioritisingagents legitimate claims, both positive and negative

Determine what the legitimate claims are, how they areaccommodated in case of plurality, and how they arereconciled in case of conflict


Representation of Legitimate Claims in LPG ′

EqualsAverage allocation

∑Tt=0 ri (t)T

Allocation frequency

∑Tt=0(ri (t)>0)

T

Needs Average demands

∑Tt=0 di (t)T

Contribution Average provision

∑Tt=0 pi (t)T

Effort Number of rounds present |{t|member(i ,C , t) = true}|

Social utility Time as head |{t|roles(i ,C , t) 3 head}|

Supply & demand Compliance |{t|r ′i (t) = ri (t)}|

Ability, merits... n/a

di (t) Demand of ...

...agent i at time tpi (t) Provision of ...ri (t) Allocation to ...r′i (t) Appropriation of ...member(i, C , t) i is a member of C at time t ...roles(i, C , t)(i, C , t) head is in the set of roles occupied by i in C at time t ...


Accommodation in Case of Plurality

Each canon Ci treated as a voter in a Borda count protocol,on agents

It ranks agents according to some features (e.g. needs,contribution...)It assigns a score to each agent, Bi (a)

To combine claims, a weight wi is attached to each canon

Final Borda score of agent a is:

B(a) =n∑

i=1

wi · Bi (a)

Use final Borda ranking as a queue to allocate resources

Allocate agents’ full requests until no more resources available


Reconciliation in Case of Conflict

Instead of fixing the weights of each canon, allow the agentsto modify them

At the end of each round

Agents vote for the canons in order of preference (according torank given by each canon) using a modified Borda count∗

Borda score computed for each canonCanons with better than average Borda score have weightincreased, otherwise decreased

This supports Ostrom’s Principle 3: “those affected by theoperational-choice rules participate in the selection andmodification of those rules”

∗Allowing for some candidates having the same number of pointsJeremy Pitt Formal Models of Social Processes 15 / 22

Some results

Compare self-organising legitimate claims, fixed weights,random and ration allocation methods

Self-organising legitimate claims...

... was the only method producing endurance of the systemand benefiting compliant agents... was the fairest† method (wrt to ration and fixed LC)... was preferred by the compliant agents... leads to a very fair overall allocation in spite of a series ofrather unfair allocations

0 0.05 0.1

0.15 0.2

0.25 0.3

0.35 0.4

0.45

0 20 40 60 80 100

Gin

i in

dex

Round

StepAccumulated

†Using Gini inequality index over accumulated allocations to measure fairnessJeremy Pitt Formal Models of Social Processes 16 / 22

Ramifications

Cost of monitoring and enforcementMonitoring is not freeIn a system with endogenous resources, the cost of monitoringhas to be ‘paid for’ from the very same resources that are tobe allocatedIt is as easy to deplete a resource by over-monitoring as under-

Unrestricted self-modificationSuber’s Thesis: any system that allows unrestrictedself-modification of its rules inevitably ends in paradox ofself-amendment, incompleteness or inconsistency

Computational justiceEnsuring the correctness of algorithmic deliberation anddecision-makingMulti-faceted: social —, distributive —, retributive —,procedural — and interactional justice

What happens when these mechanisms are injected back intothe society which inspired them⇒ socio-technical systems?


Why It Matters

Grid in 2050: for a variety of reasons

Economic(Geo)PoliticalRegulatoryEnvironmentalDemographic

It is to be expected at best power rationing, at worst blackouts

What is required

Unbundle the SmartMeter: generative platform for co-designSmart Appliances: programmable intelligence ‘at the edge’Community Energy Systems: localised provision, nestedenterprises, polycentric governance

Then we can use fairness algorithms for algorithmicself-governance and computational justice


Smart Grids as a Socio-Technical System

Generation, distribution and storage in (virtual)(decentralised) community energy systems

(1) Demand-side self-organisation: can we ‘supply’‘prosumers’ with a sustainable institution with which to self-*their own energy provision and appropriation?(2) Representation and reasoning in computational logic ofsocial capital mechanisms underlying collective action inconcurrent, co-dependent provision and appropriation systems(3) Address complex systems and ‘system of systems’ issues


Complex Systems and ‘Systems of Systems’

Aspects only partially explored/explained in Ostrom’s theories

Institutional powerFairnessPsychological processesComplex systemsNested enterprises, ‘system of systems’ and polycentricgovernance

Investigating algorithmic self-governance based onholonic institutions/institutionalised holonics

An alternative approach to smart(er) cities: Ostromopolis

stromopolis OJeremy Pitt Formal Models of Social Processes 20 / 22

Summary and Conclusions

Original problem – sustainable resource allocation in opensystems

Formal model of Ostrom’s institutional design principles

Issue of fairness – fair resource allocation in open systems

Formal model of Rescher’s theory of distributive justice

Fair and sustainable resource allocation in socio-technicalsystems

(Towards) Formal models of collective awareness, socialcapital, and computational justice

We end up with alternative approach to smart(er) cities:Ostromopolis

If the only solution you haveis an Ostrom-shaped hammer,then every problem you faceis a collective action-shaped nail


Acknowledgements

UK EPSRC and EU for funding

Many people for collaborations etc.


smart seminar series: formal models of social processes

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