AI and environmental challenges
The growth of artificial intelligence is impossible to ignore, but how does it intersect with climate and the environment? Law professor Cary Coglianese and engineering professor Benjamin Lee weigh in on the roles AI may play.
Cary Coglianese is the Edward B. Shils Professor of Law and a Professor of Political Science. He is the founding Director of the Penn Program on Regulation. Coglianese is a specialist in the study of administrative law and regulatory processes and has recently written on climate change policy and the use of artificial intelligence (AI) by government agencies and environmental programs; in particular, he has written Deploying Machine Learning for a Sustainable Future, and Regulating Machine Learning: The Challenge of Heterogeneity. He is an affiliate of The Warren Center for Network & Data Sciences and AI@Wharton, as well as a non-resident fellow of the Information Society Law Center at the University of Milan.
Benjamin Lee is a Professor in the Departments of Electrical and Systems Engineering, and Computer and Information Science at Penn. He is an affiliate of The Warren Center for Network & Data Sciences and was recently a Visiting Researcher at Meta AI. His research focuses on computer architecture, energy efficiency, and system security. Lee was previously featured in Penn Today, in conversation surrounding the energy and resource problems associated with artificial intelligence (AI) computing. He will be presenting at the upcoming workshop, Towards Environmentally Sustainable AI, part of the year-long AI and Climate Change series hosted by the Penn Program on Regulation.
Algorithm: In the context of artificial intelligence, an algorithm may be understood as the “rulebook,” or a recipe, that guides a machine or program to learn, make decisions, and operate independently.
Climate change: Climate change refers to the long term variations of natural processes - like weather patterns, global temperatures, sea level shifts, etc. - that occur naturally or by humans. Since the Industrial Revolution (1800s), human activities have been the overwhelming catalyst of climate change, particularly from rising greenhouse gas emissions associated with the burning of fossil fuels.
Data center: A data center is the physical facility which houses the infrastructure required to support computing machines and equipment, such as the information technology (IT) infrastructure required for a business to run applications, services, and manage operations.
Energy efficiency: Energy efficiency is a concept that refers to the use of less energy to achieve the same output or end result. Processes that are energy efficient minimize the amount of energy that is wasted, thus reducing energy costs and carbon emissions. For instance, a home equipped with energy-efficient appliances (e.g. washing machine, refrigerator, HVAC) will have lower electricity bills as compared to a home with standard appliances. This is because the technology in the energy-efficient appliances requires less energy to achieve the same output, or complete the same function.
Environmental justice: Environmental justice is a concept that describes the fair and equitable treatment of all people regardless of race, class, national origin, gender, etc. in environmental policy planning and regulation. The Department of Energy (DOE) further defines “fair treatment,” explaining that “...no population bears a disproportionate share of negative environmental consequences resulting from industrial, municipal, and commercial operations or from the execution of federal, state, and local laws; regulations and policies.”
Environmental racism: Environmental racism is a form of systemic racism, and is defined by the disproportionate burdening of environmental and public health hazards, like air and water pollution, on communities of color. These impacts are created by policies and practices which locate industrial sources of toxic waste, such as power plants, landfills, mines, and sewage treatment operations, in close proximity to communities of color who, as a result, experience higher incidents of health impacts. The NAACP asserts race as the “...number one indicator for the placement of toxic facilities in this country.”
According to the World Economic Forum, Civil rights leader Benjamin Chavis coined the term in 1982, defining it as: “Racial discrimination in environmental policymaking, the enforcement of regulations and laws, the deliberate targeting of communities of color for toxic waste facilities, the official sanctioning of the life-threatening presence of poisons or pollutants in our communities, and the history of excluding people of color from leadership of the ecology movements.”
Fossil fuels: Fossil fuels are energy sources that are naturally derived from Earth’s geological past, hence the term “fossil.” Fossil fuels are non-renewable resources, which means their stocks are depleted as they are used. Fossil fuels contain hydrocarbons, and their combustion results in the emission of greenhouse gasses like carbon dioxide, methane, and nitrous oxide. Examples of fossil fuel sources include coal, oil, and natural gas.
Machine learning: Machine learning is a type of artificial intelligence. It refers to the ability of machines to mimic human learning and intelligent behavior through the use of data and algorithms. A machine learning algorithm is taught to recognize patterns, and make decisions and predictions, by being fed large amounts of preprocessed data. Essentially, data can be thought of as the “food” or fuel that powers machine learning. Examples of machine learning include facial recognition and personal recommendations from a streaming service, like Netflix.
Renewable energy: Renewable energy refers to energy that has been derived from a natural source that cannot be depleted, or is self-replenishing. Examples of renewable energy sources include wind, solar (sun), hydroelectric (water), and biomass power.
Sustainability: At its most basic level, sustainability may be understood as the ability to meet the various needs (social, economic, environmental, etc.) of the present without compromising or sacrificing the ability for future generations to meet their various needs. Sustainability as a concept emphasizes the interconnectedness of issues such as social equity, environmental health and wellbeing, economic vitality, and long-term resilience. Overall system sustainability depends on a balance of social, environmental, and economic sustainability factors. Specific definitions from Circular Ecology: 
Environmental: “Environmental sustainability means that we are living within the means of our natural resources. To live in true environmental sustainability, we need to ensure that we are consuming our natural resources, such as materials, energy fuels, land, water…etc, at a sustainable rate. Some resources are more abundant than others and therefore we need to consider material scarcity, the damage to environment from extraction of these materials, and if the resource can be kept within circular economy principles.”
Economic: “Economic sustainability requires that a business or country uses its resources efficiently and responsibly so that it can operate in a sustainable manner to consistently produce an operational profit. Without an operational profit, a business cannot sustain its activities. Without acting responsibly and using its resources efficiently, a company will not be able to sustain its activities in the long term.”
Social: “Social sustainability is the ability of society, or any social system, to persistently achieve a good social well being. Achieving social sustainability ensures that the social well being of a country, an organization, or a community can be maintained in the long term.”