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Week DateTopicReadingLink to Reading MaterialDiscussion LeadAssignments
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121-JanIntroduction/ AI Primer
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23-JanHCI Primer
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228-JanLLM Prompt Engineering Hands on Tutorial Session 1 of 2 (Must Bring Laptop)
Take Survey: https://forms.gle/Gr5BqsGKYvrYYanZ7
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30-JanLLM Prompt Engineering Hands on Tutorial Session 2 of 2 (Must Bring Laptop)
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34-FebFATE - FairnessParticipation in the Age of Foundation Modelshttps://dl.acm.org/doi/pdf/10.1145/3630106.3658992
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Generative AI and Perceptual Harms: Who’s Suspected of using LLMs?https://arxiv.org/pdf/2410.00906Presenter: Muhammad Danish
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”Because AI is 100% right and safe”: User Attitudes and Sources of AI Authority in Indiahttps://dl.acm.org/doi/10.1145/3491102.3517533Pesenter: Zeel Desai
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6-FebFATE - AccountabilityTrends and Trajectories for Explainable, Accountable and Intelligible Systems: An HCI Research Agenda
https://jovermeulen.com/uploads/Research/AbdulVermeulenWangLimKankanhalli_chi2018.pdf
Pesenter: Adithya Harish
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Hidden Technical Debt in Machine Learning Systems
https://proceedings.neurips.cc/paper_files/paper/2015/file/86df7dcfd896fcaf2674f757a2463eba-Paper.pdf
Pesenter: Matthew Brenningmeyer
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All That’s ‘Human’ Is Not Gold: Evaluating Human Evaluation of Generated Texthttps://aclanthology.org/2021.acl-long.565.pdfPesenter: Kirk
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411-FebNo Class: Instructor is out of town (AI and Counterspeech Workshop)
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13-Feb
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518-FebFATE - Transparency - 1Uncovering and Quantifying Social Biases in Code Generation
https://papers.nips.cc/paper_files/paper/2023/file/071a637d41ea290ac4360818a8323f33-Paper-Conference.pdf
Presenter: Yoseph
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Perturbation Sensitivity Analysis to Detect Unintended Model Biaseshttps://aclanthology.org/D19-1578/Presenter: Tyler Buxton
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Is Your Toxicity My Toxicity? Exploring the Impact of Rater Identity on Toxicity Annotationhttps://arxiv.org/abs/2205.00501Presenter: Shuvam
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20-FebFATE - Transparency - 2Impact of Model Interpretability and Outcome Feedback on Trust in AIhttps://dl.acm.org/doi/pdf/10.1145/3613904.3642780Pesenter: Shilong Zong
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AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Promptshttps://dl.acm.org/doi/abs/10.1145/3491102.3517582Pesenter: Yuhang
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Will You Accept an Imperfect AI? Exploring Designs for Adjusting End-user Expectations of AI Systems
https://www.microsoft.com/en-us/research/uploads/prod/2019/01/chi19_kocielnik_et_al.pdf
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625-FebProject Pitch Presentations
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27-FebProject Pitch Due (PPTX and PDF files due by Feb 27 11:59pm)
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74-MarFATE - EthicsUsing the Veil of Ignorance to Align AI Systems With Principlesof Justice (And the Supplementary Information)https://www.pnas.org/doi/epdf/10.1073/pnas.2213709120Presenter: Adithya Harish
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Language Model Alignment in Multilingual Trolley Problemshttps://arxiv.org/abs/2407.02273Presenter: Amal Alamri
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Investigating machine moral judgement through the Delphi experimenthttps://www.nature.com/articles/s42256-024-00969-6Presenter: PeiQing Guo
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6-MarDesigning Human-AI Interactions - 1Guidelines for Human-AI Interactionhttps://dl.acm.org/doi/abs/10.1145/3290605.3300233
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Yang et al., Re-examining Whether, Why, and How Human-AI Interaction Is Uniquely Difficult to Design (CHI 2020)https://dl.acm.org/doi/10.1145/3313831.3376301Presenter: Khoulood
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Generating Automatic Feedback on UI Mockups with Large Language Modelshttps://dl.acm.org/doi/pdf/10.1145/3613904.3642782Pesenter: Tyler Buxton
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811-MarSpring Break
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13-Mar
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918-MarDesigning Human-AI Interactions - 2Why Johnny Can’t Prompt: How Non-AI Experts Try (and Fail) to Design LLM Promptshttps://dl.acm.org/doi/10.1145/3544548.3581388Presenter: Shuvam
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What is Human-Centered about Human-Centered AI? A Map of the Research Landscape
https://dl.acm.org/doi/pdf/10.1145/3544548.3580959?casa_token=CSI-09HLcPAAAAAA:vU3e4puJMInltS6hq68v1KU4k-foXcjcF1pDzOEwwrcuODpTtcIYcY4hVORjhq_a653-x0P7c47t
Presenter:
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A Design Space for Intelligent and Interactive Writing Assistantshttps://arxiv.org/abs/2403.14117Presenter: Sangwook Lee
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20-MarAI for HCI ResearchEvaluating Large Language Models in Generating Synthetic HCI Research Data: a Case Studyhttps://dl.acm.org/doi/10.1145/3544548.3580688Pesenter: Nayan Chawla
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OmniActions: Predicting Digital Actions in Response to Real-World Multimodal Sensory Inputs with LLMshttps://dl.acm.org/doi/pdf/10.1145/3613904.3642068Pesenter: Gayatri Milind Bhatambarekar
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Social Simulacra: Creating Populated Prototypes for Social Computing Systemshttps://dl.acm.org/doi/abs/10.1145/3526113.3545616Presenter: Rodney Okyere
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1025-MarMachine Reasoning and Learning - 1Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processinghttps://arxiv.org/abs/2107.13586Presenter:
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Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelshttps://arxiv.org/abs/2201.11903Presenter: Yoseph
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"The Trajectory of ACL and the Next 60 years" - Talk by Yejin Choihttps://www.youtube.com/watch?v=lLCEy2mu4JsPresenter: khoulood
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Can Computers Learn Common Sense?, The New Yorker, 2022
https://www.newyorker.com/tech/annals-of-technology/can-computers-learn-common-sense
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27-MarMachine Reasoning and Learning - 2Understanding Social Reasoning in Language Models with Language Modelshttps://arxiv.org/abs/2306.15448Pesenter:Zeel Desai
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Passive Learning of Active Causal Strategies in Agents And Language Models
https://papers.nips.cc/paper_files/paper/2023/file/045c87def0c02e3ad0d3d849766d7f1e-Paper-Conference.pdf
Pesenter: David Barron
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Language Models Still Struggle to Zero-shot Reason about Time Serieshttps://arxiv.org/pdf/2404.11757Pesenter:
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111-AprPresentation of Prototype
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3-AprPrototype Assignment Due (Apr 3, 11:59pm)
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128-AprGen AI and Mental HealthGPT-4 Shows Potential for Identifying Social Anxiety From Clinical Interview Datahttps://www.nature.com/articles/s41598-024-82192-2?fromPaywallRec=falsePresenter: PeiQing Guo
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Understanding Human-AI Collaboration in Music Therapy Through Co-Design with Therapistshttps://arxiv.org/abs/2402.14503Presenter: Rodney Okyere
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How Developments in Natural Language Processing Help Us in Understanding Human Behaviourhttps://www.nature.com/articles/s41562-024-01938-0Presenter: Gayatri Milind Bhatambarekar
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“This Chatbot Would Never. . . ”: Perceived Moral Agency of Mental Health Chatbotshttps://dl.acm.org/doi/pdf/10.1145/3637410Presenter:
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10-AprGen AI and Mental HealthFacilitating Self-Guided Mental Health Interventions Through Human-Language Model Interaction: A Case Study of Cognitive Restructuringhttps://dl.acm.org/doi/10.1145/3613904.3642761Pesenter: Jaehoon Pyon
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Gen AI and Mental Health
Empathy Toward Artificial Intelligence Versus Human Experiences and the Role of Transparency in Mental Health and Social Support Chatbot Design: Comparative Study
https://mental.jmir.org/2024/1/e62679/Pesenter:
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AI and Accessibility“It’s the only thing I can trust”: Envisioning Large Language Model Use by Autistic Workers for Communication Assistancehttps://dl.acm.org/doi/10.1145/3613904.3642894Pesenter: Kirk
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AI and Accessibility“The less I type, the better”: How AI Language Models can Enhance or Impede Communication for AAC Usershttps://dl.acm.org/doi/10.1145/3544548.3581560Pesenter: Sangwook Lee
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1315-AprAI and Creativity - 1Large Language Models are Fixated by Red Herrings: Exploring Creative Problem Solving and Einstellung Effect using the Only Connect Wall Dataset
https://papers.nips.cc/paper_files/paper/2023/file/11e3e0f1b29dcd31bd0952bfc1357f68-Paper-Datasets_and_Benchmarks.pdf
Presenter: Nayan Chawla
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AI as Humanity's Salieri: Quantifying Linguistic Creativity of Language Models via Systematic Attribution of Machine Text against Web Texthttps://arxiv.org/pdf/2410.04265Presenter:
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Metaphoria: An Algorithmic Companion for Metaphor Creationhttps://dl.acm.org/doi/pdf/10.1145/3290605.3300526Presenter: Shilong Zong
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17-AprAI and Creativity - 2Creative Writers’ A�ttitudes on Writing as Training Data for Large Language Modelshttps://arxiv.org/html/2409.14281v1Pesenter: Yuhang
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Generative-AI, the Media Industries, and the Disappearance of Human Creative Labourhttps://www.tandfonline.com/doi/full/10.1080/25741136.2024.2355597
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How Generative AI Can Augment Human Creativity, Harvard Business Review, 2023https://hbr.org/2023/07/how-generative-ai-can-augment-human-creativityPresenter: David Barron
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Foregrounding Artist Opinions: A Survey Study on Transparency, Ownership, and Fairness in AI Generative Arthttps://arxiv.org/abs/2401.15497
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1422-AprAI for Social GoodRace Adjustments in Clinical Algorithms Can Help Correct for Racial Disparities in Data Qualityhttps://www.pnas.org/doi/full/10.1073/pnas.2402267121Presenter: Matthew Brenningmeyer
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Generative AI for Elderly Well-being through the Computer as Social Actor Paradigmhttps://dl.acm.org/doi/pdf/10.1145/3675888.3676033Presenter: Yi Zeng""
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Understanding the Benefits and Challenges of Deploying Conversational AI Leveraging Large Language Models for Public Health Interventionhttps://dl.acm.org/doi/10.1145/3544548.3581503Presenter: Jaehoon pyon
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Leveraging Prompt-Based Large Language Models: Predicting Pandemic Health Decisions and Outcomes Through Social Media Languagehttps://arxiv.org/abs/2403.00994Presenter:
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24-AprAI and DemocracyPeople Who Share Encounters With Racism Are Silenced Online by Humans and Machines, but a Guideline-Reframing Intervention Holds Promisehttps://www.pnas.org/doi/10.1073/pnas.2322764121Pesenter:Amal Alamri
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Counterspeakers’ Perspectives: Unveiling Barriers and AI Needs in the Fight against Online Hatehttps://dl.acm.org/doi/pdf/10.1145/3613904.3642025Pesenter: Yi Zeng
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From Dogwhistles to Bullhorns: Unveiling Coded Rhetoric with Language Modelshttps://arxiv.org/abs/2305.17174Pesenter:
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Durably Reducing Conspiracy Beliefs Through Dialogues With AI - Shorthttps://www.science.org/doi/10.1126/science.adq1814Pesenter: Muhammad Danish
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1529-AprCHI - No Classes (Insturctor out of town for ACM CHI Conference); Work on final project
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1-May
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166-MayFinal Project PresentationFinal Presentation - Day 2; Note: Please expect to stay longer by 5:15pm
Final Project Presentation Due May 6th 11: 59pm; Final Prototype and Video Due on May 9th May 9, 2025
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