Companies are using AI to:
- Reduce their carbon footprint. A 2019 study jointly developed by Microsoft and PwC forecasted that responsible use of AI can lead to a 4% (2.4 giga tons) drop in worldwide Green House Gas (GHG) emissions by 2030. To tackle climate change, companies are already using AI to reduce carbon footprint. AI can help companies optimize their energy intake and thereby reduce their carbon footprint. AI is already being used to optimize carrier routes, predict and forecast supply/demand, predict and forecast maintenance, and manage autonomous transportation. All these optimizations will directly and indirectly lead to reductions in carbon footprints.
- Optimize the use of natural resources. AI is helping companies predict output green energy (e.g., solar, wind, and hydro-based energy) and thus ensuring minimal waste of these natural resources. AI also helps conserve water usage in residential, manufacturing, and agricultural areas. Predictive algorithms have helped develop new agricultural processes like precision farming, where the exact amount of water required is used and only ripe crops are picked. Algorithms also assist in farm-land planning and monitoring the health of plantation and livestock. AI also helps in developing efficient power generation schemes and setups for power generators and power consumers alike.
- Optimize the usage of AI to reduce AI's own carbon footprint. Although AI offers dramatic process improvements, helps create innovative new processes, and is the main catalyst in disrupting some sectors, it does not come without costs. A 2019 study developed by the University of Massachusetts Amherst concluded that training a common large AI model would have 300 times the carbon footprint of flying from San Francisco to New York. Companies are offsetting this carbon footprint by utilizing green renewable energy to power their AI models. Companies are also beginning to include carbon footprint in their cost/benefit analyses for deploying AI selectively and responsibly.
While it is recognized that the term sustainability encompasses broader governance and social aspects, the focus of this module is solely on environmental effects. Governance and social benefits and costs are covered in various other modules included in the toolkit. Environmentally, AI can transform and optimize numerous current practices to reduce carbon footprints. However, AI can also contribute to the increased emissions if not used responsibly. It falls under the board’s oversight to ensure management is performing its role well. Boards should ensure that AI is being applied to tasks that matter most and should drive offsetting AI’s carbon emissions by ensuring the responsible use of AI.
While the G20/OECD Principles of Corporate Governance do not specify sustainability in their list of responsibilities, boards cannot carry out their oversight duties without considering how their companies use and manage technology as well as their management’s major technology plans, investments and partnerships.
Many responsibilities that apply to other modules pertain to sustainability:
- To act in good faith, with due diligence and care, boards should be fully informed about plans for applying AI in strategy, AI’s alignment with core values and ethical standards, the risks associated with AI strategy, and regulations affecting the use of AI. Directors should have access to accurate, relevant and timely information.
- To oversee corporate strategy, major plans of actions, risk management, and budgets and business plans, boards should review and guide management’s vision, goals, actions and expenditures for AI, its support for innovation and the use of new AI resources, management’s awareness and plans for legal and environmental compliance and ameliorating AI risk, and competitors’ use and plans for AI.
- To oversee corporate performance, expenditures and acquisitions, boards should review and guide AI’s alignment with strategy, shareholder values, ethics, performance and risk indicators including ESG indicators, implementation of AI plans, the effectiveness of AI to accelerate processes and improve productivity, major investments in AI systems and talent, and acquisitions.
This section includes three tools to help directors oversee management as it uses AI responsibly to sustain the environment.
The knowledge management tool helps board members assess whether they possess, or have access to, the knowledge required to independently judge management’s actions on using AI to sustain the environment.
The performance review tool consists of questions boards can ask management about their knowledge of AI and sustainability, and the progress and performance of their actions. It offers the SCEPTIC framework to help directors assess the answers they receive.
The guidance tool offers possible suggestions for further action in an “If, then” format.
Reports: SDGs for Boards
- United Nations, “Sustainable Development Goals Knowledge Platform”.
- United Nations, “SDG Compass Guide”.
- PwC, “Navigating the SDGs: a business guide to engaging with the UN Global Goals”.
Reports: AI and Sustainable Development
- World Economic Forum, “Unlocking Technology for the Global Goals”, 2020
- World Economic Forum, “Harnessing AI for the Earth”, 2018.
- World Economic Forum, “The New Physics of Financial Services – How artificial intelligence is transforming the financial ecosystem”, 2018.
- PwC, “How AI can enable a sustainable future”.
- Michael Chui, James Manyika et al., “Notes from the AI Frontier: Applications and Value of Deep Learning”, McKinsey Global Institute, 2018.
- Michael Chui, Martin Harrysson, James Manyika et al., “Applying Artificial Intelligence for Social Good”, McKinsey, November 2018.
- Landing AI, “AI Transformation Playbook”.
- Accenture, “AI Explained – A Guide for Executives”.
- McKinsey, “An Executives’ Guide to AI”.
- Deloitte, “State of AI in the Enterprise, 2nd edition”.
- Global Reporting Initiative, “GRI’s Contribution to Sustainable Development”
- John Fullerton, Capital Institute, “Regenerative Capitalism - How universal principles and patterns will shape our new economy”, 2015.
- PwC, “The Low Carbon Economy Index 2019: Tracking the progress G20 countries have made to decarbonise their economies”, 2019.
- Ajay Agrawal, Avi Goldfarb & Joshua Gans, “Prediction Machines: The Simple Economics of Artificial Intelligence”, Harvard Business Review Press, 2018.
- Paul Hawken, “Drawdown: The Most Comprehensive Plan Ever Proposed to Reverse Global Warming”, New York: Penguin Books, 2017.
- H. James Wilson and Paul R. Daugherty, “Human + Machine – Reimagining Work in the Age of AI”, Harvard Business Review Press, 2018.
- Max Tegmark, “Life 3.0: Being Human in the Age of Artificial Intelligence”, Random House Publishing Group, 2017.
- Anastassia Lauterbach and Andrea Bonime-Blanc, “The Artificial Intelligence Imperative: A Practical Roadmap for Business”, Praeger, 2018.
- Kai-fu Lee, “AI Superpowers: China, Silicon Valley, and the New World Order”, Houghton Mifflin Co, 2018.
- John Elkington, “25 Years Ago I Coined the Phrase “Triple Bottom Line.” Here’s Why It’s Time to Rethink It”, Harvard Business Review, June 25 2018.
- J. Jay, S. Gonzalez, M. Swibel, “Sustainability-Oriented Innovation: A Bridge to Breakthroughs”, MIT Sloan Review, November 10 2015.
- Sam Ransbotham, David Kiron et al., “Reshaping Business with Artificial Intelligence: Closing the Gap Between Ambition and Action”, MIT Sloan Management Review in collaboration with Boston Consulting Group, 2017.
- Gartner, “Lessons from AI Pioneers”, 9 February 2018.
- Thomas H. Davenport and Rajeev Ronanki, “Artificial Intelligence for the Real World”, Harvard Business Review, 2018.
- Jacques Bughin, James Manyika, "Your AI Efforts Won’t Succeed Unless They Benefit Employees", Harvard Business Review, July 2019.