Morph: AI Safety Education Adaptable to (Almost) Anyone

Very nice template project! I think it looks at an interesting research area (an LLM’s tendency to produce human-seeming responses) and makes reasonable effort to investigate it within the time constraints of a hackathon. I think some ways to further improve the paper itself could be to clearly definite the term “anthropomorphic” in the introduction (within the context of the presented work), draw more on the existing literature on the subject (e.g. “Anthropomorphic response: Understanding interactions between humans and artificial intelligence agents” by Kim, 2023) and expanding the discussion section. Love that the project includes a nice, freely available github repo and would be excited to see the dataset expanded, perhaps by providing further sub-categories of different aspects of the generated text's anthropomorphism or a rating on an ordinal scale.

Really cool project and excited to see continued work in this direction! It's a clear improvement over Park et al. (2024) in terms of getting uniform elicitation across dark pattern categories compared to the ShareGPT90k dataset. Interestingly, we seem to replicate the anthropomorphism results with Claude from our short experiments in https://www.apartresearch.com/project/anthroprobe. It would have been interesting to see the correlation with human expert coders (read; the researchers) and spot any annotation mistakes given the difference in annotation adherence. I can see a bunch of great directions to take this benchmark. Great work.

Excellent work you've put into this project!

Here are some things I particularly enjoyed:

- I love the idea of having badges to encourage users to do more learning and engage in particular ways.

- I love the idea of coming up with curated pathways for specific people looking to get into AIS. This is definitely a question many people have on their minds. This tool is a great way to help people to see more directly how AI affects their professional and personal lives.

Here are some things I thought could be improved:

- I love the ambition of trying to include many different features in your project. For future, I would suggest picking your most unique and impactful feature and focusing on building that out fully. In particular, I think the bit about personalising the user journey or learning is most unique and helpful. Try to make the smallest possible thing work well and then build on top of that!

I'm very excited about this project and hope that you will continue to develop it!

Great job on "Morph"! The personalized approach to learning is a super strong value add (and literature-backed!). The idea of meeting learners where they are at, customizing content to suit their own familiar context, both enhances learner engagement and lays the groundwork for improved comprehension, recall, and application across more culturally diverse contexts. This displays creative thinking, strong product development skills, and a solid knowledge of education fundamentals.

For future development – I would recommend further lowering the bar for onboarding by integrating C.V. or LinkedIn profile imports so that users can one-click create their personalized profile complete with a robust career background. This could further streamline the onboarding experience for a learner, and provide even more data to further customize content experience on the product side. This was an extremely robust MVP, and with that robust complexity also comes optimization opportunities in the overall user experience flow. I found it difficult to know where to start, and would recommend further clarifying the numerous product features and how they integrate into a cohesive learner journey.

Overall, job well done!