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² D Rolnick et al, “Tackling Climate Change with Machine Learning” (2022) 55 ACM Computing Surveys 42.

³ E Strubell, A Ganesh and A McCallum, “Energy and Policy Considerations for Deep Learning in NLP” (arXiv, 5 June 2019) <http://arxiv.org/abs/1906.02243> (last accessed 14 February 2023).

⁴ S Robbins and A van Wynsberghe, “Our New Artificial Intelligence Infrastructure: Becoming Locked into an Unsustainable Future” (2022) 14 Sustainability 4829.

⁵ LH Kaack et al, “Aligning Artificial Intelligence with Climate Change Mitigation” (2022) 12 Nature Climate Change 518; C-J Wu et al, “Machine Learning at Facebook: Understanding Inference at the Edge”, 2019 IEEE International Symposium on High Performance Computer Architecture (HPCA) (2019).

⁶ K Crawford, The Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence (New Haven, CT, Yale University Press 2021).

⁷ P Dauvergne, AI in the Wild: Sustainability in the Age of Artificial Intelligence (Cambridge, MA, MIT Press 2020).

⁸ F Creutzig et al, “Leveraging Digitalization for Sustainability in Urban Transport” (2019) 2 Global Sustainability e14; Z Wadud, D MacKenzie and P Leiby, “Help or Hindrance? The Travel, Energy and Carbon Impacts of Highly Automated Vehicles” (2016) 86 Transportation Research Part A: Policy and Practice 1.

⁹ A Korinek and JE Stiglitz, “Artificial Intelligence and Its Implications for Income Distribution and Unemployment” (National Bureau of Economic Research, December 2017) <https://www.nber.org/papers/w24174> (last accessed 14 February 2023).

¹⁰ A Gallego and T Kurer, “Automation, Digitalization, and Artificial Intelligence in the Workplace: Implications for Political Behavior” (2022) 25 Annual Review of Political Science 463; M Anelli, I Colantone and P Stanig, “Individual Vulnerability to Industrial Robot Adoption Increases Support for the Radical Right” (2021) 118 Proceedings of the National Academy of Sciences of the United States of America e2111611118; C Boix, “AI and the Economic and Informational Foundations of Democracy” in JB Bullock et al (eds), The Oxford Handbook of AI Governance (Oxford, Oxford University Press) <https://doi.org/10.1093/oxfordhb/9780197579329.013.64> (last accessed 14 February 2023).

¹¹ PRB Fortes, PM Baquero and DR Amariles, “Artificial Intelligence Risks and Algorithmic Regulation” (2022) 13 European Journal of Risk Regulation 357.

¹² ibid.

¹³ J Pitt, J Dryzek and J Ober, “Algorithmic Reflexive Governance for Socio-Techno-Ecological Systems” (2020) 39 IEEE Technology and Society Magazine 52.

¹⁴ T Aitamurto and K Chen, “The Value of Crowdsourcing in Public Policymaking: Epistemic, Democratic and Economic Value” (2017) 5 The Theory and Practice of Legislation 55; T Aitamurto and H Landemore, “Crowdsourced Deliberation: The Case of the Law on Off-Road Traffic in Finland” (2016) 8 Policy & Internet 174.

¹⁵ T Aitamurto et al, “Civic CrowdAnalytics: Making Sense of Crowdsourced Civic Input with Big Data Tools”, Proceedings of the 20th International Academic Mindtrek Conference (Association for Computing Machinery, 2016) <https://doi.org/10.1145/2994310.2994366> (last accessed 14 February 2023).

¹⁶ P Cavaliere and G Romeo, “From Poisons to Antidotes: Algorithms as Democracy Boosters” (2022) 13 European Journal of Risk Regulation 421.

¹⁷ ibid.

¹⁸ N Stern and M Romani, “The Global Growth Story of the 21st Century: Driven by Investment and Innovation in Green Technologies and Artificial Intelligence” (Grantham Research Institute on Climate Change and the Environment, 2023) <https://www.lse.ac.uk/granthaminstitute/publication/the-global-growth-story-of-the-21st-century/> (last accessed 20 February 2023).

¹⁹ ibid.

²⁰ Cement and steel production combined are responsible for over 10% of all global greenhouse gas emissions. See: M Fischedick et al, “Industry” in Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge, Cambridge University Press 2015) PNNL-SA-103522.

²¹ N Bernards et al, “Interrogating Technology-Led Experiments in Sustainability Governance” (2020) 11 Global Policy 523.

²² LM Schaffer, B Oehl and T Bernauer, “Are Policymakers Responsive to Public Demand in Climate Politics?” (2022) 42 Journal of Public Policy 136.

²³ R Escher and M Walter-Rogg, “The Effects of Democratic and Nondemocratic Institutions on CO₂ Emissions” [2023] Politische Vierteljahresschrift <https://doi.org/10.1007/s11615-023-00458-2> (last accessed 12 May 2023).

²⁴ D Miller, “Deliberative Democracy and Social Choice” (1992) 40 Political Studies 54; J Knight and J Johnson, “Aggregation and Deliberation: On the Possibility of Democratic Legitimacy” (1994) 22 Political Theory 277; JS Dryzek and C List, “Social Choice Theory and Deliberative Democracy: A Reconciliation” (2003) 33 British Journal of Political Science 1.

²⁵ C List et al, “Deliberation, Single-Peakedness, and the Possibility of Meaningful Democracy: Evidence from Deliberative Polls” (2013) 75 The Journal of Politics 80.

²⁶ V Ottonelli and D Porello, “On the Elusive Notion of Meta-Agreement” (2013) 12 Politics, Philosophy & Economics 68; SR Rad and O Roy, “Deliberation, Single-Peakedness, and Coherent Aggregation” (2021) 115 American Political Science Review 629.

²⁷ M Kneuer, “E-Democracy: A New Challenge for Measuring Democracy” (2016) 37 International Political Science Review 666; M Kneuer and M Datts, “E-Democracy and the Matter of Scale. Revisiting the Democratic Promises of the Internet in Terms of the Spatial Dimension” (2020) 61 Politische Vierteljahresschrift 285.

²⁸ A Benabdallah et al, “Analysis of Blockchain Solutions for E-Voting: A Systematic Literature Review” (2022) 10 IEEE Access 70746.

²⁹ S Park et al, “Going from Bad to Worse: From Internet Voting to Blockchain Voting” (2021) 7 Journal of Cybersecurity tyaa025.

³⁰ D Yermack, “Corporate Governance and Blockchains” (2017) 21 Review of Finance 7; A Lafarre and C Van der Elst, “Shareholder Voice in Complex Intermediated Proxy Systems: Blockchain Technology as a Solution?” (2020) 4 Stanford Journal of Blockchain Law & Policy 29.

³¹ L Blume, J Müller and S Voigt, “The Economic Effects of Direct Democracy – A First Global Assessment” (2009) 140 Public Choice 431.

³² A Vatter, B Rousselot and T Milic, “The Input and Output Effects of Direct Democracy: A New Research Agenda” (2019) 47 Policy & Politics 169.

³³ S Gonçalves, “The Effects of Participatory Budgeting on Municipal Expenditures and Infant Mortality in Brazil” (2014) 53 World Development 94; T Peixoto, FM Sjoberg and J Mellon, “A Get-Out-the-Vote Experiment on the World’s Largest Participatory Budgeting Vote in Brazil” (2020) 50 British Journal of Political Science 381.

³⁴ S Gherghina and P Tap, “Ecology Projects and Participatory Budgeting: Enhancing Citizens’ Support” (2021) 13 Sustainability 10561.

³⁵ M Touchton, B Wampler and P Spada, “The Digital Revolution and Governance in Brazil: Evidence from Participatory Budgeting” (2019) 16 Journal of Information Technology & Politics 154.

³⁶ S Mahajan et al, “From Do-It-Yourself (DIY) to Do-It-Together (DIT): Reflections on Designing a Citizen-Driven Air Quality Monitoring Framework in Taiwan” (2021) 66 Sustainable Cities and Society 102628.

³⁷ C-C Ho, L-J Chen and J-S Hwang, “Estimating Ground-Level PM_2.5 Levels in Taiwan Using Data from Air Quality Monitoring Stations and High Coverage of Microsensors” (2020) 264 Environmental Pollution 114810.

³⁸ However, technological innovation can facilitate non-governmental organisation and civil society communication and links across countries. This could arguably help counterbalance the politically influential organised interests that benefit from a non-sustainable status quo.

³⁹ S Zhang et al, “Deep Learning Based Recommender System: A Survey and New Perspectives” (2019) 52 ACM Computing Surveys 5; D Acemoglu and S Johnson, Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity (New York, PublicAffairs 2023).

⁴⁰ N Stern, Why Are We Waiting?: The Logic, Urgency, and Promise of Tackling Climate Change (Cambridge, MA, MIT Press 2015); N Stern, “A Time for Action on Climate Change and a Time for Change in Economics” (2022) 132 The Economic Journal 1259.

⁴¹ PJ Loftus et al, “A Critical Review of Global Decarbonization Scenarios: What Do They Tell Us about Feasibility?” (2015) 6 WIREs Climate Change 93.

⁴² R Ahmed et al, “A Review and Evaluation of the State-of-the-Art in PV Solar Power Forecasting: Techniques and Optimization” (2020) 124 Renewable and Sustainable Energy Reviews 109792; VN Nguyen, R Jenssen and D Roverso, “Automatic Autonomous Vision-Based Power Line Inspection: A Review of Current Status and the Potential Role of Deep Learning” (2018) 99 International Journal of Electrical Power & Energy Systems 107.

⁴³ JJ Cohen, J Reichl and M Schmidthaler, “Re-Focussing Research Efforts on the Public Acceptance of Energy Infrastructure: A Critical Review” (2014) 76 Energy 4.

⁴⁴ BK Sovacool et al, “Conflicted Transitions: Exploring the Actors, Tactics, and Outcomes of Social Opposition against Energy Infrastructure” (2022) 73 Global Environmental Change 102473.

⁴⁵ M Ho, “Exploring Worldwide Democratic Innovations – A Case Study of Taiwan” (2022) Exploring Worldwide Democratic Innovations 78.

⁴⁶ E Posner and E Weyl, “Voting Squared: Quadratic Voting in Democratic Politics” (2015) 68 Vanderbilt Law Review 441.

⁴⁷ ibid; EA Posner and EG Weyl, “Quadratic Voting and the Public Good: Introduction” (2017) 172 Public Choice 1.

⁴⁸ “Audrey Tang on What We Can Learn from Taiwan’s Experiments with How to Do Democracy” (80,000 Hours, 2022) <https://80000hours.org/podcast/episodes/audrey-tang-what-we-can-learn-from-taiwan/> (last accessed 23 February 2023).

⁴⁹ ibid.

⁵⁰ J Ober, “Equality, Legitimacy, Interests, and Preferences: Historical Notes on Quadratic Voting in a Political Context” (2017) 172 Public Choice 223.

⁵¹ C Small et al, “Polis: Scaling Deliberation by Mapping High Dimensional Opinion Spaces” (2021) 26 RECERCA. Revista de Pensament i Anàlisi <https://www.e-revistes.uji.es/index.php/recerca/article/view/5516> (last accessed 15 February 2023).

⁵² KMd’I Treen, HTP Williams and SJ O’Neill, “Online Misinformation about Climate Change” (2020) 11 WIREs Climate Change e665.

⁵³ N Bontridder and Y Poullet, “The Role of Artificial Intelligence in Disinformation” (2021) 3 Data & Policy e32.

⁵⁴ K-C Yang et al, “Arming the Public with Artificial Intelligence to Counter Social Bots” (2019) 1 Human Behavior and Emerging Technologies 48.

⁵⁵ R Bommasani et al, “On the Opportunities and Risks of Foundation Models” (arXiv, 12 July 2022) <http://arxiv.org/abs/2108.07258> (last accessed 21 February 2023).

⁵⁶ D Patterson et al, “Carbon Emissions and Large Neural Network Training” (arXiv, 23 April 2021) <http://arxiv.org/abs/2104.10350> (last accessed 14 February 2023).

⁵⁷ ibid; P Hacker, A Engel and M Mauer, “Regulating ChatGPT and Other Large Generative AI Models” (arXiv, 10 February 2023) <http://arxiv.org/abs/2302.02337> (last accessed 21 February 2023).

⁵⁸ D Patterson et al, “The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink” (2022) 55 Computer 18.

⁵⁹ Kaack et al, supra, note 5; Wu et al, supra, note 6.

⁶⁰ C Okereke, “Climate Justice and the International Regime: Climate Justice and the International Regime” (2010) 1 Wiley Interdisciplinary Reviews: Climate Change 462.

⁶¹ T Santarius, “Climate Justice and Digitalization: A Plea to Consider Broader Socio-Economic Implications of Digitalization and Climate Change” (2022) 31 GAIA – Ecological Perspectives for Science and Society 146.

⁶² ASG Andrae, “New Perspectives on Internet Electricity Use in 2030” (2020) 3 Engineering and Applied Science Letters 19.

⁶³ M Kummu et al, “Climate Change Risks Pushing One-Third of Global Food Production Outside the Safe Climatic Space” (2021) 4 One Earth 720.

⁶⁴ L Klerkx and D Rose, “Dealing with the Game-Changing Technologies of Agriculture 4.0: How Do We Manage Diversity and Responsibility in Food System Transition Pathways?” (2020) 24 Global Food Security 100347.

⁶⁵ JE Addicott, The Precision Farming Revolution: Global Drivers of Local Agricultural Methods (Berlin, Springer 2020); Santarius, supra, note 61.

⁶⁶ Santarius, supra, note 61.

⁶⁷ In the future, machine learning-based approaches could even generate near-future predictions of deforestation risk based on a range of contextual variables (topography, accessibility, precipitation seasonality, land use, socio-economic indicators), which could inform preventative patrolling and monitoring of relevant forest units.

⁶⁸ T Slough, J Kopas and J Urpelainen, “Satellite-Based Deforestation Alerts with Training and Incentives for Patrolling Facilitate Community Monitoring in the Peruvian Amazon” (2021) 118 Proceedings of the National Academy of Sciences of the United States of America e2015171118.

⁶⁹ R Montes, “El crimen organizado está matando a muchos líderes de las comunidades indígenas y tribales” (El País, 30 March 2021) <https://elpais.com/internacional/2021-03-30/el-crimen-organizado-esta-matando-a-muchos-lideres-de-las-comunidades-indigenas-y-tribales.html> (last accessed 14 February 2023).

⁷⁰ A Gupta, “The Advent of ‘Radical’ Transparency: Transforming Multilateral Climate Politics?” (2023) 2 PLoS Climate e0000117.

⁷¹ EA Page and C Heyward, “Compensating for Climate Change Loss and Damage” (2017) 65 Political Studies 356; R Mechler and T Schinko, “Identifying the Policy Space for Climate Loss and Damage” (2016) 354 Science 290.

⁷² CW Callahan and JS Mankin, “National Attribution of Historical Climate Damages” (2022) 172 Climatic Change 40; G Bettini, G Gioli and R Felli, “Clouded Skies: How Digital Technologies Could Reshape ‘Loss and Damage’ from Climate Change” (2020) 11 WIREs Climate Change e650.

⁷³ Stern and Romani, supra, note 18.

⁷⁴ Bettini et al, supra, note 72.

⁷⁵ Crawford, supra, note 6.

⁷⁶ H Jones, “EU Lawmakers Back Pulling More Companies into ESG ‘Due Diligence’ Net” (Reuters, 9 February 2023) <https://www.reuters.com/business/sustainable-business/eu-lawmakers-back-pulling-more-companies-into-esg-due-diligence-net-2023-02-09/> (last accessed 23 February 2023).

⁷⁷ T Götz et al, “Digital Product Passport: The Ticket to Achieving a Climate Neutral and Circular European Economy?” (University of Cambridge Institute for Sustainability Leadership, 2022) <https://epub.wupperinst.org/frontdoor/deliver/index/docId/8049/file/8049_Digital_Product_Passport.pdf> (last accessed 12 May 2023).

⁷⁸ G van Capelleveen et al, “The Anatomy of a Passport for the Circular Economy: A Conceptual Definition, Vision and Structured Literature Review” (2023) 17 Resources, Conservation & Recycling Advances 200131; A Gumbau, “Digital Product Passports Become the Norm in EU’s Green Economy Plan” (<www.euractiv.com>, 21 November 2022) <https://www.euractiv.com/section/circular-economy/news/digital-product-passports-become-the-norm-in-eus-green-economy-plan/> (last accessed 23 February 2023); Götz et al, supra, note 77.

⁷⁹ Götz et al, supra, note 77.

⁸⁰ As of 30 January, the countries that have signed the declaration in addition to the EU Member States and the USA are: Albania, Andorra, Argentina, Australia, Belize, Bosnia and Herzegovina, Cabo Verde, Canada, Chile, Colombia, Costa Rica, Dominican Republic, Georgia, Iceland, Israel, Jamaica, Japan, Kenya, Kosovo, Liechtenstein, Maldives, Marshall Islands, Micronesia, Moldova, Monaco, Montenegro, New Zealand, Niger, North Macedonia, Norway, Palau, Peru, Republic of Korea, San Marino, Serbia, Taiwan, Trinidad and Tobago, the UK, Ukraine and Uruguay. “Declaration for the Future of Internet | Shaping Europe’s Digital Future” (28 April 2022) <https://digital-strategy.ec.europa.eu/en/library/declaration-future-internet> (last accessed 30 January 2023).

⁸¹ “A Declaration for the Future of the Internet” (2022) <https://www.whitehouse.gov/wp-content/uploads/2022/04/Declaration-for-the-Future-for-the-Internet_Launch-Event-Signing-Version_FINAL.pdf> (last accessed 30 January 2023).

⁸² ibid.

⁸³ “The European Union and the United States of America Strengthen Cooperation on Research in Artificial Intelligence and Computing for the Public Good | Shaping Europe’s Digital Future” (27 January 2023) <https://digital-strategy.ec.europa.eu/en/news/european-union-and-united-states-america-strengthen-cooperation-research-artificial-intelligence> (last accessed 31 January 2023).

⁸⁴ KW Abbott, “Strengthening the Transnational Regime Complex for Climate Change” (2014) 3 Transnational Environmental Law 57; T Bernauer, “Climate Change Politics” (2013) 16 Annual Review of Political Science 421; H Fuhr, T Hickmann and K Kern, “The Role of Cities in Multi-Level Climate Governance: Local Climate Policies and the 1.5°C Target” (2018) 30 Current Opinion in Environmental Sustainability 1.

⁸⁵ T Lee, “Global Cities and Transnational Climate Change Networks” (2013) 13 Global Environmental Politics 108.

⁸⁶ JS Bansard, PH Pattberg and O Widerberg, “Cities to the Rescue? Assessing the Performance of Transnational Municipal Networks in Global Climate Governance” (2017) 17 International Environmental Agreements: Politics, Law and Economics 229.

⁸⁷ E Posner and A Sykes, “Voting Rules in International Organizations” (2014) 15 Chicago Journal of International Law 195.

⁸⁸ On the other hand, oil-producing countries could have intense preferences against rapid decarbonisation and against ambitious climate policy. They still might be outvoted in a context in which there is also a group of countries intensely concerned with potentially irreversible climate-induced damage.

⁸⁹ A Vogt-Schilb and S Hallegatte, “Climate Policies and Nationally Determined Contributions: Reconciling the Needed Ambition with the Political Economy” (2017) 6 WIREs Energy and Environment e256; M Winning et al, “Nationally Determined Contributions under the Paris Agreement and the Costs of Delayed Action” (2019) 19 Climate Policy 947.

⁹⁰ To date, all 193 Parties to the Paris Agreement have put forward at least a first NDC.