Amanda Weissman

I am a Principal Systems Engineer and Associate Fellow at Lockheed Martin, where I lead large-scale engineering efforts to deliver advanced land-based test capabilities. I am a 2009 RIT graduate with a BS in Electrical Engineering and an MS in Materials Science and Engineering.

1. How do you use AI and Applied Critical Thinking in your professional practice, teaching, or research, and what are your favorite resources?

I use AI to strengthen my technical communication, brainstorm and refine ideas, and conduct research across a wide range of topics. I also automate routine tasks wherever possible to improve efficiency. I pair these capabilities with applied critical thinking to validate outputs, challenge assumptions, and ensure decisions are grounded in sound engineering judgment. In my role, there is rarely a single “right” answer. Success comes from determining the best answer by synthesizing inputs from diverse sources. I apply critical thinking to analyze those inputs, distinguish between opinion and fact, and look beyond surface-level information to understand underlying intent and implications. This enables me to make well-informed decisions and deliver the best outcomes for my customers. My go-to tools are ChatGPT, Gemini, and Copilot. Each offers different strengths and varying levels of cybersecurity, allowing me to choose the right tool based on the sensitivity and nature of the work.

2. Can you share or describe an example of an effective use of AI?

One effective use of AI I’ve seen is in developing interpersonal and communication skills. A colleague introduced me to using AI as a practice partner—providing realistic prompts for challenging conversations, helping generate and refine responses, and even offering feedback on tone, clarity, and effectiveness. This created a low-risk environment to rehearse scenarios we regularly face in the workplace. When combined with guidance from strong mentors, this approach allows us to build confidence and capability before engaging in real-world conversations. It ensures that when we step into critical discussions, it’s not the first time we’ve practiced—leading to more thoughtful, clear, and authoritative communication.

3. What do you tell others about using AI?

I encourage others to use AI—but to do so thoughtfully and with a critical mindset. AI is a powerful tool, but it’s not hard for it to hallucinate or generate confident-sounding but incorrect information, so it’s essential to validate outputs and not take them at face value. I also caution against unintentionally creating an echo chamber, where the tool reinforces your existing assumptions rather than challenging them. The real value comes from using AI as a thinking partner, not a decision-maker—leveraging it to explore ideas, pressure-test your reasoning, and expand perspectives while maintaining ownership of the final judgment.

4. How has using AI challenged you or your critical thinking?

Using AI has challenged me to become both more efficient and more intentional in my thinking. With these tools readily available, there’s an expectation to stay current and use them effectively—but that also means being disciplined about not outsourcing my judgment. I’ve had to be more deliberate in treating AI as a tool, not a crutch. Even generating the right prompt to get a useful answer requires me to think critically about how I frame questions, the level of detail I provide, and the clarity of my intent—reinforcing the idea that “bad data in, bad data out.” At the same time, it has reinforced the importance of critical thinking as a distinctly human skill. To remain relevant and effective, I have to actively question outputs, validate information, and apply context and experience in ways AI cannot. Embracing that balance—leveraging AI for speed and scale while maintaining ownership of analysis and decision-making—has ultimately strengthened how I approach my work.

5. How do you think AI has or will impact your domain?

I believe AI will significantly expand our ability to design and deliver increasingly complex systems faster and more efficiently. Rather than replacing engineers, it will augment our capabilities—handling more routine, time-consuming tasks and enabling us to focus on higher-order thinking, system-level trade-offs, and complex problem-solving. This shift means engineers who effectively leverage AI will be able to move faster, explore more design options, and make more informed decisions. The role doesn’t go away—it evolves.