Wearable Reasoner:
Towards Enhanced Human Rationality
A wearable system capable of analyzing if an argument is stated with supporting reasons or not to prompt people to question and reflect on the justifications of their own beliefs and the arguments of others. Read more.
Keywords:
Assisted Reasoning, Cognitive Enhancement, Augmented Humans, Argumentation Mining, Natural Language Processing.
Publication:
ACM Augmented Humans 2020.
Exhibition:
MIT Museum: AI Mind The Gap.
Press:
Hackster.io
Soylent News
Role:
Initiator and concept-creator, developer of machine learning model, conductor of experimental study, lead on write-up.
Don’t Just Tell Me, Ask Me: AI Systems that Intelligently Frame Explanations as Questions Improve Human Logical Discernment Accuracy over Causal AI explanations
This project presents the idea of AI-explanations that reframe information as questions to actively engage people's thinking and scaffold their thinking. In a study with 210 subjects, we compared the effects of AI systems that ask questions to systems telling people answers and found that AI-framed questioning significantly increased human discernment accuracy of logically flawed information. Read more.
Keywords:
Human-AI Interaction, Assisted Reasoning, Cognitive Enhancement, Augmented Humans, Argumentation Mining, Natural Language Processing.
Publication:
ACM CHI 2023.
Press:
”A chatbot that asks questions could help you spot when it makes no sense”, MIT Technology Review
Role:
Initiator and concept-creator, developer of machine learning model, conductor of experimental study, lead on write-up.
Deceptive AI Explanations Can Amplify Beliefs in Misinformation
We explore the impact of deceptive AI generated explanations on misinformation and find that people more easily believe false information when an AI system gives them deceptive explanations for why it is true.
Keywords:
Human-AI Interaction, Assisted Reasoning, Misinformation, Computational Social Science.
Publication:
ACM CHI 2025
Awards:
ACM CHI Best Paper Honorable Mention
Role:
Initiator and concept-creator, developer of machine learning model, designing experimental study, conductor of experimental study, lead on write-up.
Synthetic Visual Sensations: Augmenting Spatial Awareness with tACS
A wearable system that elicits visual sensations using neural stimulation, allowing you to “see” behind yourself. The system maps the outputs of a distance sensor to an alternating current that stimulates the retina. We ran a human subject experiment with 12 people and found the system to increase people’s ability to spot objects behind them.
Keywords:
Synthetic Sensations, Brain-Computer Interface, Brain Stimulation, Transcranial Alternating Current Stimulation, Cognitive Enhancement, Augmented Humans, Sensory Augmentation.
Publication:
Under Review
Role:
Initiator and concept-creator, electronics engineering, conductor of experimental study, lead on write-up.
Living Memories: AI-Generated Characters as Digital Mementos
Every human culture has developed practices and rituals associated with remembering those who have died. Our system that allows you to create an “interactive photograph” of a person based on any data source. We ran a study with 90 users interacting with living memories of the three historical figures “Leonardo Da Vinci”, “Murasaki Shikibu”, and “Captain Robert Scott” and found them to increase learning effectiveness and
motivation to learn.Read more.
Keywords:
Generative AI, Large Language Models, Vector Database, Learning, Motivation, Deepfakes.
Publication:
ACM Intelligent User Interfaces.
Role:
Built the system which is one of the first to use vector databases and semantic models together with LLMs. Developed evaluation metrics and, experimental methods, leading write-up.
