Ethics of algorithmic decision making on the smart grid
Joe Wyndham
University of Technology Sydney
What is the smart grid?

What is the traditional grid?

[1, 2, 3, 4, 5, 6, 7, 8]• Combination of centralised and decentralised
generation at varying scales• Large, centralised electricity generators• Large, long distance transmission• Cyberphysical system: IoT integrated energy
devices, artificial Intelligence, automatic and autonomous
appliances• Sprawling, low voltage distribution• Prioritisation around capacity and CAPEX• Dynamic management: Real-time asset visibility,
massive orchestration of DERs, dynamic pricing• Static management based on peak demand• Optimisation, balanced load, generation and storage,
lower prices• Syncronous generation and frequency inertia• High penetrations of fossil fuel generation• High penetration of RE and storage• System blindness - set and forget assets• “A seamless, cost-effective electricity system, fromgeneration to end-use, capable of meeting all clean
energy demands and capacity requirements” [US DoE]

• designed for unidirectional flow

How can we identify the ethical risks of the smart grid?
A Philosophy of Technical Artefacts:TheStructure - Intention Conception

Applying the Structure-Intention Conception
to the Traditional Grid

Applying the Structure-Intention Conception
to the Smart Grid[1, 2, 3, 4, 5, 6, 7, 8][9, 18]Intention: Functional:- Deliver electricity to homes- Accept and redistribute exported energy fromhomes, businesses- Manipulate demand and supply*- Manageable by humans who defer responsibility
automatic and autonomous system components*- Responsive to (near) real-time data
- Optimised costs for system- Optimised pricing for benefit of system andconsumers*- Reliable/secure electricity supply- Maximise sustainable energy sources
Intention: Non-functional:- Politically marketable (implicit)*- Everyone benefits (explicit)*- State-of-the-art technology*

Societal Context
Norms

Politics

Access

Structural Contexts

Governance

Existing structural realisation:
Internally Immutable Structures- Poles and wires- Centralised energy resources- Communications networks

Use plan
Intention:
Functional

Business Models

Use plan(unprescribed

Structurally Imposed
use/behaviour

Intention:
Non-functional

Knowledge / Skills

Physical StructureState ofTechnology

MAKERNeeds

USER

TECHNICAL ARTEFACT

Usage Context

Functional:- Deliver electricity to homes- Meet peak demand- Minimise system costs- Minimise energy prices- Reliable/ secure energy source- Manageable by humans
Non-functional:- politically invisible (implicit)

TrendsExisting and expected structural realisation:
Internally immutable components- Poles and wires- Centralised energy resources
Somewhat internally mutable components- IoT Communications, control*- Centralised energy resources- Distributed energy resources*- Communications networks
Highly Mutable structures- Virtual Power Plants*- Algorithms*- BigData models and supporting hardware*

Physics

Standards

Material Types
Material Availability
Space Availability

Physical Context*Causes of special issues on the smart gridSpecial Ethical Issues of the Smart Grid

Research Question:- How do we treat grid users andwhat is their status?

Dynamic engagement withusers [12]Compounding Complexity

Research Question:
Who does dynamic pricing benefit
and why?

Research question:- What are the risks of accepting
extreme complexity?

CitizenConsumer
Asset manager
Asset Financier
Traditional Grid: the grid is forusers, however under aSmart grid: Those who don't
participate in prosumerism may beexcluded

Process and Accountablility
Research question: How can weguarantee due process andaccountability if we cede responsibility
to algorithms and AI? [13]BIG DATA

Changing status ofusers [11]Traditional Grid: Energy should beaffordable for everyone
Smart Grid: Energy should be affordable
when convenient and only for users who
benefit the grid

Traditional grid: Centralisedsociotectnical system - secondary effects
likely and but predictable
Smart grid: Cyberphysical sociotechnicalsystem - secondary effects inevitable,difficult or impossible to predict

BLACK BOX AI

DECISION

Shifting power among technicalelites [14]Research question: What compencies do we risk
losing when system design and management
shifts from power engineers to IoT and BigData
professionals? And how does society oversee atechnically elite domain?

ACTION

Traditional Grid: Human driveinterpretable decision making and controlof grid
Smart grid: Decisions made by black box
algorithms and control enacted byautonomous and automatic systems

Traditional grid: Power engineers oversee design ofcontrol systems
Smart grid: Data scientists, CS engineers,
programmers oversee design of system

Conclusion: Methodologies to Wrangle Smart Grid Ethical Issues
Energy Justice Framework

Distributive

Bearers ofBenefits

Bearers ofCosts/Ills

Grid AI & Algorithm Oversight[17, 18]

Proceedural

Equitable accessParticipation
Decision making

Description of the grid as a complex
technological artefact:- Structure-intention conception- Identify the makers, users andcontexts- Describe intention, structure andconstraint- Recognise structural power

Recognition

Equitable representation
RespectReferences
1. Ramchurn, S. D., Vytelingum, P., Rogers, A. & Jennings, N. R. Putting the ‘smarts’ into the smart grid: A grand challenge for artificial intelligence. Commun. ACM 55, 86–97 (2012).
2. Alahakoon, D. & Yu, X. Smart Electricity Meter Data Intelligence for Future Energy Systems: A Survey. IEEE Trans. Ind. Informatics 12, 425–436 (2016).
3. Ali, S. S. & Choi, B. J. State-of-the-Art Artificial Intelligence Techniques for Distributed Smart Grids: A Review. Electronics 9, 1030 (2020).
4. Piagi, P. & Lasseter, R. H. Autonomous control of microgrids. 2006 IEEE Power Eng. Soc. Gen. Meet. PES (2006) doi:10.1109/pes.2006.1708993.
5. Rajkumar, R., Lee, I., Sha, L. & Stankovic, J. Cyber-physical systems: The next computing revolution. Proc. - Des. Autom. Conf. 731–736 (2010) doi:10.1145/1837274.1837461.
6. Sridhar, S., Hahn, A. & Govindarasu, M. Cyber-physical system security for the electric power grid. Proc. IEEE 100, 210–224 (2012).
7. Shi, L., Dai, Q. & Ni, Y. Cyber–physical interactions in power systems: A review of models, methods, and applications. Electr. Power Syst. Res. 163, 396–412 (2018).
8. Karnouskos, S. Cyber-Physical Systems in the SmartGrid. 20–23 (2011).

Identify opportunities:- Machine ethics advancements- Supererogation- Enhancement of human dignity andflourishing[15, 16]

Identify risks:- embedded values and politics- Black box algorithms- Implicit goals- Transmogrification- embedded biases, data andalgorithms- Conflicting goals and values
AI and algorithmic ethicalframework:- Unification and extension of classicalethics- Duty assignment, responsibility, anddefined scopes of agency

9. Vermaas, P., Kroes, P., van de Poel, I., Franssen, M. & Houkes, W. A Philosophy of Technology: From Technical Artefacts to Sociotechnical Systems. Synth. Lect. Eng. Technol. Soc. 6, (2011).
10. Nicholls, L., Strengers, Y. & Sadowski, J. Social impacts and control in the smart home. Nat. Energy 5, 180–182 (2020).
11. Faruqui, A. The ethics of dynamic pricing. Electr. J. 23, (2010).
12. Selbst, A. D. & Vertesi, J. Fairness and Abstraction in Sociotechnical Systems. 59–68.
13. Sadowski, J. Rediscovering a risky ideology: technocracy and its effects on technology governance. J. Responsible Innov. 7, 112–116 (2020).
14. Martin, K. Ethical Implications and Accountability of Algorithms. J. Bus. Ethics 160, (2019).
15. Thekkilakattil, A. & Dodig-Crnkovic, G. Ethics Aspects of Embedded and Cyber-Physical Systems. Proc. - Int. Comput. Softw. Appl. Conf. 2, 39–44 (2015).
16. Milchram, C., Hillerbrand, R., van de Kaa, G., Doorn, N. & Künneke, R. Energy Justice and Smart Grid Systems: Evidence from the Netherlands and the United Kingdom. Appl. Energy 229, 1244–1259 (2018).
17. Sovacool, B. K. & Dworkin, M. H. Energy justice: Conceptual insights and practical applications. Appl. Energy 142, 435–444 (2015).
18. Vaesen, K. The functional bias of the dual nature of technical artefacts program. Stud. Hist. Philos. Sci. Part A 42, 190–197 (2011).