Scam Detective: Using Gamification to Improve AI-Powered Scam Awareness

Angelica Marie M. Casuela

This project outlines the development of an interactive web application aimed at involving users in understanding the AI skills for both producing believable scams and identifying deceptive content. The game challenges human players to determine if text messages are genuine or fraudulent against an AI. The project tackles the increasing threat of AI-generated fraud while showcasing the capabilities and drawbacks of AI detection systems. The application functions as both a training resource to improve human ability to recognize digital deception and a showcase of present AI capabilities in identifying fraud. By engaging in gameplay, users learn to identify the signs of AI-generated scams and enhance their critical thinking abilities, which are essential for navigating through an increasingly complicated digital world. This project enhances AI safety by equipping users with essential insights regarding AI-generated risks, while underscoring the supportive functions that humans and AI can fulfill in combating fraud.

Reviewer's Comments

Reviewer's Comments

Arrow
Arrow
Arrow

Tarin

This was a really fun and engaging way to educate audiences on multiple levels. You successfully communicated risks and capabilities of AI while simultaneously empowering users, educating them on how to proactively identify already-common AI scams and protect themselves from harm. The UI itself was also a clean and elegant user experience.

This was a strong MVP, and I'm excited about its continued development opportunities. For example, as you mentioned, the current difficulty level is relatively low. I would love to see more investment in escalating difficulty levels to further demonstrate the strength in capabilities of these systems. This could also further incorporate more explicit learning, like incorporating OpenAI's Persuasion risk-level identifiers which you called out in the paper, or further emphasize the reality of these harms by including and specifically identifying real-life scam examples.

Overall, this was a great multi-purpose game to capture learner attention, educate them on broader AI risk categories, communicate the reality of AI-powered harm, and empower themselves against realistic threats. Well done!

Li-Lian Ang

Great work on this project!

Here are some things I particularly enjoyed:

- I love the clean UI!

- I think this could be a good tool to educate the public on how to detect scam messages by teaching them what to look out for.

Here are some things I thought could be improved:

- I would have loved to see more instructions or context when I first opened the web app. I was a bit confused at first about what the AI assessment was meant to be.

- I think it would be useful to set an end state for the user otherwise it might feel like they would keep playing forever! I'm not sure whether I'm supposed to feel like AI systems are very good at scamming or if I'm simply meant to educate myself on detecting phishing attempts. Perhaps showing different types of phishing attempts?

- An interesting addition to this project might have been to see how AI can create realistic, targeted phishing attempts based on a target's user profile. Perhaps this veers into the realm of dual-use concerns, but an idea nonetheless!

Cite this work

@misc {

title={

@misc {

},

author={

Angelica Marie M. Casuela

},

date={

3/10/25

},

organization={Apart Research},

note={Research submission to the research sprint hosted by Apart.},

howpublished={https://apartresearch.com}

}

May 20, 2025

EscalAtion: Assessing Multi-Agent Risks in Military Contexts

Our project investigates the potential risks and implications of integrating multiple autonomous AI agents within national defense strategies, exploring whether these agents tend to escalate or deescalate conflict situations. Through a simulation that models real-world international relations scenarios, our preliminary results indicate that AI models exhibit a tendency to escalate conflicts, posing a significant threat to maintaining peace and preventing uncontrollable military confrontations. The experiment and subsequent evaluations are designed to reflect established international relations theories and frameworks, aiming to understand the implications of autonomous decision-making in military contexts comprehensively and unbiasedly.

Read More

Apr 28, 2025

The Early Economic Impacts of Transformative AI: A Focus on Temporal Coherence

We investigate the economic potential of Transformative AI, focusing on "temporal coherence"—the ability to maintain goal-directed behavior over time—as a critical, yet underexplored, factor in task automation. We argue that temporal coherence represents a significant bottleneck distinct from computational complexity. Using a Large Language Model to estimate the 'effective time' (a proxy for temporal coherence) needed for humans to complete remote O*NET tasks, the study reveals a non-linear link between AI coherence and automation potential. A key finding is that an 8-hour coherence capability could potentially automate around 80-84\% of the analyzed remote tasks.

Read More

Mar 31, 2025

Model Models: Simulating a Trusted Monitor

We offer initial investigations into whether the untrusted model can 'simulate' the trusted monitor: is U able to successfully guess what suspicion score T will assign in the APPS setting? We also offer a clean, modular codebase which we hope can be used to streamline future research into this question.

Read More

May 20, 2025

EscalAtion: Assessing Multi-Agent Risks in Military Contexts

Our project investigates the potential risks and implications of integrating multiple autonomous AI agents within national defense strategies, exploring whether these agents tend to escalate or deescalate conflict situations. Through a simulation that models real-world international relations scenarios, our preliminary results indicate that AI models exhibit a tendency to escalate conflicts, posing a significant threat to maintaining peace and preventing uncontrollable military confrontations. The experiment and subsequent evaluations are designed to reflect established international relations theories and frameworks, aiming to understand the implications of autonomous decision-making in military contexts comprehensively and unbiasedly.

Read More

Apr 28, 2025

The Early Economic Impacts of Transformative AI: A Focus on Temporal Coherence

We investigate the economic potential of Transformative AI, focusing on "temporal coherence"—the ability to maintain goal-directed behavior over time—as a critical, yet underexplored, factor in task automation. We argue that temporal coherence represents a significant bottleneck distinct from computational complexity. Using a Large Language Model to estimate the 'effective time' (a proxy for temporal coherence) needed for humans to complete remote O*NET tasks, the study reveals a non-linear link between AI coherence and automation potential. A key finding is that an 8-hour coherence capability could potentially automate around 80-84\% of the analyzed remote tasks.

Read More

May 20, 2025

EscalAtion: Assessing Multi-Agent Risks in Military Contexts

Our project investigates the potential risks and implications of integrating multiple autonomous AI agents within national defense strategies, exploring whether these agents tend to escalate or deescalate conflict situations. Through a simulation that models real-world international relations scenarios, our preliminary results indicate that AI models exhibit a tendency to escalate conflicts, posing a significant threat to maintaining peace and preventing uncontrollable military confrontations. The experiment and subsequent evaluations are designed to reflect established international relations theories and frameworks, aiming to understand the implications of autonomous decision-making in military contexts comprehensively and unbiasedly.

Read More

Apr 28, 2025

The Early Economic Impacts of Transformative AI: A Focus on Temporal Coherence

We investigate the economic potential of Transformative AI, focusing on "temporal coherence"—the ability to maintain goal-directed behavior over time—as a critical, yet underexplored, factor in task automation. We argue that temporal coherence represents a significant bottleneck distinct from computational complexity. Using a Large Language Model to estimate the 'effective time' (a proxy for temporal coherence) needed for humans to complete remote O*NET tasks, the study reveals a non-linear link between AI coherence and automation potential. A key finding is that an 8-hour coherence capability could potentially automate around 80-84\% of the analyzed remote tasks.

Read More

May 20, 2025

EscalAtion: Assessing Multi-Agent Risks in Military Contexts

Our project investigates the potential risks and implications of integrating multiple autonomous AI agents within national defense strategies, exploring whether these agents tend to escalate or deescalate conflict situations. Through a simulation that models real-world international relations scenarios, our preliminary results indicate that AI models exhibit a tendency to escalate conflicts, posing a significant threat to maintaining peace and preventing uncontrollable military confrontations. The experiment and subsequent evaluations are designed to reflect established international relations theories and frameworks, aiming to understand the implications of autonomous decision-making in military contexts comprehensively and unbiasedly.

Read More

Apr 28, 2025

The Early Economic Impacts of Transformative AI: A Focus on Temporal Coherence

We investigate the economic potential of Transformative AI, focusing on "temporal coherence"—the ability to maintain goal-directed behavior over time—as a critical, yet underexplored, factor in task automation. We argue that temporal coherence represents a significant bottleneck distinct from computational complexity. Using a Large Language Model to estimate the 'effective time' (a proxy for temporal coherence) needed for humans to complete remote O*NET tasks, the study reveals a non-linear link between AI coherence and automation potential. A key finding is that an 8-hour coherence capability could potentially automate around 80-84\% of the analyzed remote tasks.

Read More

This work was done during one weekend by research workshop participants and does not represent the work of Apart Research.
This work was done during one weekend by research workshop participants and does not represent the work of Apart Research.