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Oct 29, 2026 | 1215 words | 12 min read

6.1.2. Engineering AI Ethics

As future engineers, ethical considerations should always be at the forefront of your decision making when working on any project. This is especially true with the increased prevalence of AI tools that can assist with your work as an engineer but may also lead to new ethical considerations that need to be accounted for in your tasks moving forward. The abilities of AI are constantly growing, and with them regulations around AI and how to use AI ethically are changing at a rate that can be difficult to keep up with. It is always a good idea to check in with your discipline’s code of ethics for engineers. The National Society of Professional Engineer’s Code of Ethics for Engineers serves as a baseline for all engineers to follow. Your discipline may have additional ethical considerations, so always keep up with the professional societies associated with your discipline to be aware of any major considerations.

The NSPE has published a statement related to the ethics of AI in Engineering. It was first adopted by the organization in September of 2023 and was most recently revised in February of 2026.

The following is a copy of the statement [(Artificial Intelligence | National Society of Professional Engineers, 2023)]:

NSPE Position Statement No. 03-1774

It is the position of NSPE that individuals who design, develop, deploy, or oversee AI systems which have a direct impact on public safety should be held to the same standards as professional engineering licensure. NSPE believes that in upholding ethical standards, prioritizing safety, and promoting resiliency, transparency and accountability, Professional Engineers play a pivotal role in ensuring AI benefits society while minimizing its risks.

Discussion:

1. Ethical and Environmental Responsibility: NSPE emphasizes the ethical and environmental responsibility of engineers and AI professionals in the design, development, deployment, and oversight of trustworthy AI systems. Engineers and AI professionals must prioritize ethical considerations to ensure AI technologies are designed and used in ways that do not harm individuals, society, or the environment. Ethical guidelines should be at the forefront of AI development to address issues such as bias, transparency, accountability, and environmental sustainability.

Note

Example: An engineering team could use AI to adjust heating and cooling in a campus building. Before choosing a system, the team would compare its energy savings and computing needs with a simpler timer-based system. It would also check that energy savings do not come at the expense of comfortable temperatures in study spaces. This makes environmental impact and the needs of different users part of the design decision.

2. Safety and Reliability: Safety and reliability are paramount in AI systems. NSPE advocates for rigorous verification & validation, testing, and continuous monitoring of AI systems to minimize risks and ensure their dependable operation. Hardware, software, and infrastructure upgrades, and integration should be held to the same standard of care as the initial launch. Engineers should apply their expertise to establish robust safety standards for AI applications, particularly in critical domains such as energy, water, healthcare, transportation, and infrastructure.

Note

Example: An AI-controlled sorting robot could be designed to stop when its sensors cannot reliably tell whether a person is nearby. Engineers would test that response under different lighting conditions before using the robot and repeat the tests after software updates. Choosing to stop when the system is uncertain puts worker safety ahead of keeping the production line moving.

3. Professional Licensure: NSPE maintains that individuals who consult, design, develop, or oversee AI systems that have a direct impact on public safety should be held to the same professional licensure standards as professional engineers. Licensing AI engineers ensures that those engineers working on AI systems possess the necessary qualifications, experience, commitment, and accountability to uphold the public’s well-being. Other technical professionals in the field should also be held to the same professional and ethical standards with respect to public safety and accountability to ensure the entire technical team holds paramount the public’s safety, health, and welfare.

Note

Example: A team using AI to suggest the size of a building support beam would have an appropriately qualified engineer check the loads, assumptions, and material requirements before approving the design. Where professional licensure is required, the review and approval would follow those requirements. The AI recommendation would support the work, while the responsible engineer would still need the competence and authority to approve it.

4. Transparency and Accountability: AI systems should be designed to be transparent, explainable, and accountable as part of being a trustworthy system. NSPE supports initiatives that promote transparency in AI algorithms and data, enabling users to understand how decisions are made. Additionally, accountability mechanisms must be in place to address unintended consequences or errors arising from AI applications.

Note

Example: An AI maintenance tool could flag a pump for inspection and show the unusually high vibration readings behind its warning, along with the limits of its assessment. A designated engineer would review the warning and record the decision to inspect, repair, or continue operating the pump. The explanation helps people understand the recommendation, while the review record makes responsibility for the decision clear.

5. Privacy Protection: NSPE emphasizes the importance of safeguarding individual privacy in the era of AI. Engineers and AI professionals should respect privacy laws and best practices in the collection, storage, and use of personal data. NSPE encourages collaboration with privacy experts to ensure compliance with evolving privacy standards.

Note

Example: Engineers developing an AI system to count pedestrians at an intersection could process camera footage on the device and retain only the counts needed to adjust signal timing. They could avoid storing identifiable images and limit access to any footage temporarily needed for testing. This allows the system to serve its purpose while reducing the personal information collected and retained.

6. Continuous Education and Training: NSPE underscores the need for continuous education and training for engineers and AI professionals to stay current with advancements in AI technology and ethics. We support initiatives that provide opportunities for professionals to enhance their AI knowledge and skills, fostering a culture of lifelong learning.

Note

Example: Before using a new version of an AI design tool, an engineering team could complete training on its capabilities and limitations and test it on problems with known answers. If the tool produces an incorrect result, the team would investigate the error and update its review procedures. Keeping skills current helps engineers recognize when an AI output needs further checking.

7. Collaboration and Interdisciplinary Approach: NSPE advocates collaboration among engineers, data scientists, ethicists, policymakers, and other stakeholders to address the complex challenges posed by AI. An interdisciplinary approach is essential to creating trustworthy and resilient AI systems that align with societal values and priorities.

Note

Example: A team designing AI-controlled pedestrian signals could work with traffic engineers, software developers, accessibility specialists, and residents. A wheelchair user might point out that the proposed crossing time is too short, while a privacy specialist could suggest collecting less camera data. Including these perspectives would help the team revise the design before installation rather than discover the problems after people begin using it.

Other Guidelines

Organizations beyond those specific to engineering have also published guidelines for ethical considerations related to AI. The United Nations Educational, Scientific and Cultural Organization (UNESCO) has also published their recommendations on the Ethics of Artificial Intelligence, which can be accessed here: https://www.unesco.org/en/artificial-intelligence/recommendation-ethics.

Citations

Artificial Intelligence | National Society of Professional Engineers. (2023). Nspe.Org. https://www.nspe.org/nspe-advocacy/explore-issues/professional-policies-and-position-statements/artificial-intelligence