AI and Its Impact: What SRI Investors Need to Know

By Kofi Kodua, Managing Director and Portfolio Manager

You’ve probably been hearing a lot about Artificial Intelligence (AI) lately, and that’s not likely to change anytime soon. As new technologies utilizing AI are developed, its reach into industries and economies the world over will only grow. But while AI technology represents a transformative opportunity for innovation, efficiency, and growth, it also carries the potential for negative environmental and social impacts. So what does that mean for those who seek to invest responsibly? 

At Clean Yield, your commitment to responsible investing is our top concern. AI has already become a part of our daily news cycle, tied to our present socio-political development, and integrated into our daily lives — and we are dedicated to understanding its complex and multifaceted impact. Below we provide an overview of some of the opportunities — from optimizing energy consumption and reducing waste to driving inclusion and transforming healthcare — as well as the critical ethical concerns new AI technologies raise. Those include potential privacy violations, job displacement, and environmental strain from data centers. 

In this thought piece, we take it all under consideration, setting out to review how our client’s investment portfolios can incorporate ethical AI implementation in line with Clean Yield’s social and environmental screening process. Our criteria are designed to identify companies that contribute positively to society and the environment, including those that contribute to ethical, sustainable development in AI.

The Environmental Pros and Cons of AI

High Energy & Water Consumption of Data Centers: AI models, especially those used in large-scale applications, require massive amounts of data to function effectively. Processing and storing this data typically occur in data centers, which are known for their high energy consumption. According to estimates, data centers contribute to approximately 2% of global greenhouse gas emissions, a figure expected to rise as AI technologies become more widespread. While the short-term environmental costs of AI technology currently outweigh the benefits, there are applications in the works for improving energy efficiency, conservation, and climate change mitigation.

Energy Efficiency and Conservation: AI can significantly enhance energy efficiency by optimizing energy consumption across industries, buildings, and transportation systems. For instance, AI algorithms can analyze energy usage patterns in real-time, identifying inefficiencies and suggesting adjustments to reduce consumption. This is especially valuable for smart grids, where AI can balance energy supply and demand, integrate renewable energy sources more effectively, and minimize energy waste.

Climate Change Mitigation and Adaptation: AI is increasingly being used to monitor, model, and predict climate patterns, enabling better forecasting of extreme weather events and long-term climate trends. By analyzing vast amounts of climate data, AI can help policymakers, scientists, and organizations develop more effective strategies for mitigating climate change and adapting to its impacts. For example, AI-driven insights can guide the development of more resilient infrastructure, optimize agricultural practices, and improve disaster response planning.

Pros and Cons of Resource Use and Waste

Resource-Intensive Hardware: E-Waste and Lifecycle Impacts of AI Hardware: The hardware required to run AI systems, including specialized processors like GPUs and TPUs, also has a considerable environmental impact. The production of these components involves the extraction of rare earth metals and other resources, which can lead to environmental degradation and human rights abuses in mining regions. Additionally, the disposal of outdated hardware contributes to electronic waste, further exacerbating environmental concerns.

Waste Reduction and Circular Economy: AI can play a crucial role in reducing waste and promoting circular economy practices. For instance, AI-powered sorting systems can enhance recycling efficiency by accurately identifying and separating recyclable materials. AI can also help manufacturers optimize production processes, reducing material waste and enabling the reuse and recycling of resources. These applications support a more sustainable, resource-efficient economy.

Pros and Cons of AI’s Social Impact

Data Privacy and Security: AI systems often rely on vast amounts of personal data to function effectively. This raises significant privacy concerns, particularly when data is collected without informed consent or is used in ways that individuals may not be aware of. Moreover, the risk of data breaches and cyberattacks increases as more data is collected and processed, potentially leading to severe consequences for individuals and organizations. SRI investors should evaluate the data privacy policies and practices of companies involved in AI, ensuring they prioritize ethical data usage and robust security measures.

Algorithmic Bias and Discrimination: AI algorithms are only as good as the data they are trained on. If this data is biased or unrepresentative, the AI systems can perpetuate and even exacerbate existing social inequalities. For example, biased AI algorithms have been shown to result in discriminatory practices in areas such as hiring, lending, and law enforcement. As SRI investors, we need to assess how companies are addressing algorithmic bias and whether they are implementing measures to ensure fairness, transparency, and accountability in their AI systems.

Job Displacement and Economic Inequality: The automation capabilities of AI have the potential to disrupt labor markets significantly. While AI can create new jobs, it is also likely to displace many existing ones, particularly in industries reliant on routine tasks. This shift could exacerbate economic inequality, as those who lose their jobs may struggle to find new employment in an increasingly automated world. As SRI investors, we should consider how companies are preparing for and managing the social impact of AI-driven automation, including their efforts to reskill and support displaced workers.

Unethical Surveillance and Human Rights Violations: Clearview AI, a facial recognition technology company, has been criticized for scraping billions of images from the internet without consent and using AI algorithms to identify individuals. Its technology has been used by law enforcement agencies worldwide, raising serious concerns about mass surveillance, privacy violations, and potential misuse for targeting and discriminating against marginalized groups. This technology could arguably lead to wrongful arrests and infringements on human rights, particularly in authoritarian regimes.

Clearview AI made some changes in response to global criticism of its privacy practices, including reducing access to its facial recognition software and restricting its use to law enforcement agencies in certain regions. The company also expressed a commitment to improving the accuracy of its technology to reduce misidentifications, which could help mitigate some human rights concerns. However, many human rights organizations argue that these efforts do not go far enough, and as a result the company continues to face lawsuits and regulatory scrutiny.

Improved Healthcare and Medical Research: AI has the potential to revolutionize healthcare by improving diagnostic accuracy, personalizing treatment plans, and accelerating medical research. AI-driven tools can analyze medical images, detect diseases at earlier stages, and provide real-time assistance to healthcare professionals. This can lead to better health outcomes, especially in underserved communities with limited access to medical expertise. Moreover, AI’s ability to analyze vast datasets can accelerate the discovery of new treatments and drugs, ultimately improving public health.

Enhanced Accessibility and Inclusion: AI technologies can break down barriers for individuals with disabilities, promoting greater accessibility and inclusion. For example, AI-powered speech recognition and natural language processing enable more effective communication for people with hearing or speech impairments. AI-driven tools can also assist individuals with visual impairments by providing real-time descriptions of their surroundings. These advancements contribute to a more inclusive society, where technology supports people of all abilities.

Education and Skill Development: AI has the potential to transform education by personalizing learning experiences and improving access to quality education. AI-powered learning platforms can adapt to individual students’ needs, offering customized content and support to enhance learning outcomes. This is particularly valuable in addressing educational disparities, as AI can provide tailored resources to students in underserved communities. Additionally, AI-driven training programs can support skill development and workforce retraining, helping individuals adapt to the changing job market.

Social Good and Humanitarian Efforts: AI is increasingly being used to address social issues and support humanitarian efforts. For example, AI can help identify and respond to human trafficking by analyzing patterns in online data, enabling faster detection and intervention. In disaster response scenarios, AI-powered tools can analyze satellite imagery to assess damage, prioritize relief efforts, and coordinate rescue operations more effectively. These applications demonstrate AI’s potential to contribute to social good and improve outcomes for vulnerable populations.

Navigating AI’s Risks with Responsible Investing

For more on these issues, access a deeper dive into the topics covered in this article, which includes examples of companies that demonstrate both the potential positive and negative environmental and social impacts of AI. The guide also includes four key evaluation criteria for Socially Responsible Investing and AI: Assess Environmental Impact, Examine Social Practices, Prioritize Ethical AI Development, and Engage in Active Stewardship. Check out the guide for real-life examples of the opportunities and potential risks of AI, and how to take a proactive approach when evaluating AI investments.