AI ethics: What is it and why does it matter?
AI ethics have become a major point of discussion and debate among artificial intelligence experts. Explore essential AI ethics concepts and their importance.
By: James M. Tobin, Edited by: Gabriela Pérez Jordán, Reviewed by: Jeff Le
Published: June 19, 2025
After decades of development, artificial intelligence (AI) has emerged as one of the most important technology trends of the 2020s. Yet, ethical concerns have grown as AI capabilities have reached new heights. Governments increasingly seek regulation to foster accountability and public discourse, while businesses grapple with balancing rapid adoption with responsible integration.
AI ethics issues extend to many domains, including privacy and security, discrimination and bias, transparency, accountability, and ecological sustainability. Explore key facets of these and other ethical concerns, and research strategies that can help you use AI both effectively and ethically.
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What is AI ethics, and why does it matter?
Ethical questions about artificial intelligence have persisted throughout the history of AI. They apply to both creators of AI-powered systems and the organizations and individuals who use them.
Creators seeking to build ethical AI technologies must prioritize user safety, system security, fairness, and environmental sustainability. Organizations should consider factors like policy transparency, cybersecurity, privacy, and inclusivity. They should also ensure their use case is ethical, since their employees and customers — and potentially the general public — could otherwise face adverse impacts.
AI developers, tech industry leaders, organizational decision-makers, and government regulators all share responsibility for ensuring users follow sound ethical guidelines. Understanding and preemptively addressing AI ethics issues makes for a strong starting point.
Ethical challenges of AI today
The table below introduces five examples of AI ethics issues, briefly describing the nature of the challenge and giving a real-world example.
| Ethical Challenge | Description | Example |
|---|---|---|
| Privacy and security | AI systems may extract sensitive or private data from users, potentially without their knowledge or consent. | Some AI systems can search for private information such as bank account numbers, creating the potential for criminal misuse. |
| Bias | The algorithms and training data developers use to guide AI systems can be tainted with biases, creating the potential for unfairness and discrimination. | If AI-powered facial recognition systems are primarily trained using images of people with lighter skin tones, they may misidentify people with darker skin. |
| Transparency | Users should have some way to find information about the algorithms that power AI systems and how those algorithms guide the system's decision-making processes. | AI-powered chatbots may offer advice or guide a company's customers to particular products or services. Users should be explicitly informed that they are interacting with AI and should understand the mechanisms guiding the chatbot's responses and recommendations. |
| Accountability | Organizations that use AI should have a particular person, group, or department responsible for actions taken by AI systems and the decisions those systems may make. | If a commercialized AI system contravenes legal regulations when extracting private or sensitive information, a human decision-maker should be accountable for the system's activities. |
| Ecological sustainability | Training and operating AI systems consume large quantities of electricity. Electronic waste from AI hardware can be difficult to recycle. | AI significantly increases electricity and water usage, often relying on power centers run by fossil fuels. The microchips and semiconductors used in AI systems are hard to extract and recycle due to their small size. |
An expert's take on ethical AI
Jeff Le
- Managing Principal, 100 Mile Strategies
- Visiting Fellow, National Security Institute, George Mason University
Q: What are the most pressing ethical challenges in AI today?
Le: The biggest ethical challenge in AI is the competing interests between economic innovation, consumer protection, environmental stewardship, and national security. These intersections represent a significant conundrum for policymakers and society. Each of these areas requires elements of tradeoffs that can be uneasy for many groups and community members. Fundamentally, how does society ensure everyone benefits from these advancements in a time of rapid change?
Q: What advice do you have for students or professionals interested in ethical AI?
Le: It's important to learn about large language models (LLMs), their design, and how they connect to outputs. I recommend that everyone regularly try different types, especially in comparison between open models and more closed models. It's also important to read and learn from wide schools of thought on ethics. Finally, the study of the past here could be relevant. As society has experienced technological change, there have been challenges. Some of these lessons could be applicable to this era.
How to use AI ethically
Individuals and organizations can improve their AI ethics practices by taking these actions:
1. Learn about AI
Organizational decision-makers and individual end users should learn how AI systems work, what they can and cannot do, and what they should and should not do. AI executive education programs are ideal for managerial professionals seeking targeted knowledge.
Learning about AI terms can also give users a vocabulary for studying AI and its ethical issues at a deeper level. As AI usage increases, so does its impact.
2. Emphasize transparency
Organizations seeking to implement AI technologies should be transparent with their employees and customers about how the AI systems will and will not be used.
For example, if you want to use AI technologies to collect data from online visitors to your company's website, you should explicitly disclose this to all visitors upon their arrival and allow them to opt out if they wish.
3. Follow applicable regulations
While the growth and proliferation of AI technologies have generally outpaced regulation, a growing number of countries and international jurisdictions have developed AI governance policies. For example, the EU has implemented the Artificial Intelligence Act to ensure the safe, transparent, and trustworthy use of AI.
First, research all privacy and AI-specific legal regulations that apply in your location and in the jurisdictions where your AI systems will operate. Then, abide by them. If necessary, assign an AI-focused compliance officer to ensure you follow all the rules.
Your next steps to learn AI ethics on edX
The edX platform supports a wealth of opportunities to learn about AI ethics and implementation practices. In addition to standalone AI courses and executive education programs, you can earn AI-focused academic certificates, a bachelor's degree in AI, or a master's in AI.
All learning opportunities available through edX partner providers offer flexible online formats that make it easier to balance learning with personal and professional commitments. Enhance your subject matter expertise in AI as you explore ethical ways to harness the power of artificial intelligence.