
## The AI Revolution in Education

The emergence of powerful generative AI tools like ChatGPT, Claude, and Bard (oh man, remember when that was a thing?) has sparked significant changes in how we approach engineering education. These tools can generate code, solve complex problems, and produce written content that closely resembles human work.

## Challenges for Assessment

Traditional assessment methods in engineering education often rely on problem sets, written reports, and exams. With generative AI, students can now produce solutions to these assessments with minimal effort, raising questions about:

- How do we measure individual understanding?
- What skills should we be assessing in an AI-augmented world?
- How can we design "AI-proof" assessments?

Questions like this were the motivation for my CAREER grant, which focuses on understanding faculty members' mental models of AI and how they might be changing assessment strategiesin response to the tools.

### Rethinking Evaluation Methods

Our research suggests that effective assessment in the age of AI requires:

1. **Process-focused evaluation** - Assessing how students approach problems rather than just the final product
2. **In-person demonstrations** - Having students explain their work verbally
3. **Collaborative projects** - Emphasizing teamwork and communication skills

## Opportunities for Enhanced Learning

Despite the challenges, generative AI offers tremendous opportunities for engineering education:

- Students can receive immediate feedback on their work
- AI can serve as a personalized tutor, adapting to individual learning styles
- More time can be devoted to higher-order thinking and creative problem-solving

## Preliminary Research Findings

Our initial studies with engineering faculty show mixed reactions to AI tools. While the majority express concern about academic integrity, they also see potential for improving educational outcomes when these tools are properly integrated into the curriculum.

The path forward requires thoughtful curriculum redesign and clear policies that acknowledge AI as a tool that students will use throughout their careers. 

Exploring how generative AI tools like ChatGPT are transforming engineering education and what it means for assessment practices.

The Impact of Generative AI on Engineering Education


## The Invisible Hand of System Prompts

When interacting with AI language models like ChatGPT or Claude, users typically see only their own prompts and the AI's responses. However, there's an invisible layer of instruction - the system prompt - that fundamentally shapes these interactions. These hidden prompts define the AI's personality, capabilities, and behavioral boundaries. The whole issue motivating this post is the recent suggestion that the system prompt for Grok 3's "thinking" mode was explicitly instructed not to name certain public figures as possibly being the biggest spreaders of misinformation. That level of misaligned behavior is a problem when the company purports to be a platform for free speech and, by extension, maximum transparency.

## Why System Prompts Matter

System prompts matter for serveral reasons, including but not limited to:

1. **Behavior Definition**: They establish the AI's role, tone, and interaction style. Common practices in system prompt instructions include statements to the effect of "You are a helpful assistant" or "You are a helpful AI assistant that can answer questions and help with tasks."
2. **Safety Guardrails**: They implement ethical boundaries and content restrictions. This is a practice made popular with Anthropic's Claude and their 3H principle (Helpful, Honest, and Harmless).
3. **Capability Framing**: They define what the AI can and should attempt to do. For example, the system prompt may instruct the model about tools available to it, or it may instruct the model to answer in specific formats.

## The Transparency Problem

The practice of hiding system prompts from users creates several challenges:

- **Unclear Limitations**: Users don't know why an AI might refuse certain requests
- **Inconsistent Behavior**: The same user prompt can yield different results across platforms, especially over time if there are updates to the system prompt
- **Hidden Biases**: System prompts may introduce biases that users can't detect or account for

### Real-World Implications

Consider a researcher using multiple AI platforms for analysis. Without knowing the system prompts, they can't:
- Properly document their methodology
- Understand why different AIs produce varying results
- Replicate their findings consistently

See any problems with this? 

Of course, it would be rare to interact with such a system without any prompt. And of course, companies have a vested interest in protecting their proprietary prompts. But the point is that system prompts matter, and users should be able to see them (or at least be aware of their existence and potential impact(s)).

## The Case for Transparency

Ideally, we need a shift toward greater transparency in AI interactions. This could involve:

1. **Optional Visibility**: Letting users view system prompts when desired
2. **Documentation**: Clear documentation of core behavioral guidelines
3. **Version Control**: Tracking changes to system prompts over time

In the absence of those, we can at least raise awareness of the issue and the potential impact of system prompts.

## Moving Forward

The path to better AI interactions requires balancing:
- The need for safety and ethical behavior
- Users' right to understand the systems they're using
- Commercial interests in protecting proprietary prompts

The solution likely involves finding middle ground - perhaps not exposing full system prompts, but providing clear documentation of key behavioral principles and limitations. Or just use open-weights models and exert a little more control over the process.

Exploring how hidden system prompts shape AI behavior and why transparency matters for users and developers.

Research Insights

The Impact of Generative AI on Engineering Education

The Hidden Impact of System Prompts in AI Interactions

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