Augmenting Intelligence
Augmenting Intelligence is a multidisciplinary course at CMU’s Human-Computer Interaction Institute. We explore how to design and evaluate technologies aimed at augmenting & amplifying human cognitive capabilities.
Oh! Hey there! I’m so glad you could join us!
Course resources
Prof. Ken Holstein
Course calendar
Week 1
(Aug 25 - 29)
Welcome!
Please review the course syllabus. The syllabus includes directions to the classroom + information about the course structure and policies.
INTRO TO THE COURSE
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A BRIEF HISTORY OF THE FUTURE OF “AUGMENTED INTELLIGENCE”
Required Readings:
Early Visions, Branching Paths
(due by Tuesday night, Aug 26)
How to read a paper — Keshav, 2007
suggested reading/skimming time: 20 min
AI and HCI: Two fields divided by a common focus — Grudin, 2009
suggested reading/skimming time: 45 min
Man-computer symbiosis — Licklider, 1960
suggested reading/skimming time: 45 min
Augmenting human intellect:
A conceptual framework – Engelbart, 1962
suggested reading/skimming time: 1 hr, 15 min
meta-skills
Other assignments
(due before class on Wednesday, Aug 27)
Sign up in groups of 3-4 students to present readings for one upcoming class, using this sign-up sheet
context
concepts
concepts
Submit your reading
responses here
Week 2
(Sep 2 - 5)
A BRIEF HISTORY OF THE FUTURE OF “AUGMENTED INTELLIGENCE”
(continued)
Required Readings:
HCI, AI, Human Factors, & MIS
(due by Tuesday night, Sep 2)
Principles of mixed-initiative user interfaces — Horvitz, 1999
suggested reading/skimming time: 1 hr
A model for types and levels of human interaction with automation — Parasuraman & Sheridan, 2000
suggested reading/skimming time: 1 hr
Guidelines for human-AI interaction – Amershi et al., 2019
suggested reading/skimming time: 1 hr
Human Factors, CHI, and MIS – Grudin, 2015
suggested reading/skimming time: 45 min
concepts
No class on Monday
(Labor Day)
concepts
concepts
concepts
Submit your reading
responses here
Optional Additional Readings
As we may think — Bush, 1945
The intertwined histories of artificial intelligence and education — Doroudi, 2023
Direct manipulation vs. interface agents — Shneiderman & Maes, 1997
A literature review on the levels of automation during the years. What are the different taxonomies that have been proposed? — Vagia et al., 2016
Human factors in automation design — Lee & Seppelt, 2009
Week 3
(Sep 8 - 12)
Required Readings:
Human-Human & Human-AI
Augmentation
(due by Sunday night, Sep 7)
A BRIEF HISTORY OF THE FUTURE OF “AUGMENTED INTELLIGENCE”
(continued)
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AUGMENTING DECISION-MAKING
Augmenting social cognition — Chi et al., 2008
suggested reading/skimming time: 20 min
Hybrid intelligence — Dellerman, 2019
suggested reading/skimming time: 45 min
Designing for human–AI complementarity in K-12 education — Holstein & Aleven, 2021
suggested reading/skimming time: 45 min
concepts
concepts
case studies
Submit your reading
responses here
Required Readings:
(due by Tuesday night, Sep 9)
Unremarkable AI: Fitting intelligent decision support into critical, clinical decision-making processes — Yang et al., 2019
suggested reading/skimming time: 1 hr
Improving human-AI partnerships in child welfare: Understanding worker practices, challenges, and desires for algorithmic decision-support — Kawakami et al., 2022
suggested reading/skimming time: 1 hr
A taxonomy of human and ML strengths in decision-making to investigate human–ML complementarity – Rastogi, Liu et al., 2023
read Sections 1-3 only
suggested reading/skimming time: 1 hr, 15 min
case studies
case studies
concepts
Submit your reading
responses here
Optional Additional Readings
Hybrid workplaces of the future — Kamar, 2016
Hybrid-augmented intelligence: Collaboration and cognition — Zheng et al., 2017
Artificial intelligence, human intelligence and hybrid intelligence based on mutual augmentation – Jarrahi et al., 2022
Cognitive science of augmented intelligence — Dubova et al., 2022
Fostering Collective Intelligence in Human–AI Collaboration: Laying the Groundwork for COHUMAIN – Gupta et al., 2025
Week 4
(Sep 15 - 19)
Required Readings
(due by Sunday night, Sep 14)
AUGMENTING
DECISION-MAKING & SENSEMAKING
Trust in automation: Designing for appropriate reliance — Lee & See, 2004
suggested reading/skimming time: 1 hr, 15 min
Beyond recommendations: From backward to forward AI support of pilots’ decision-making process – Zhang et al., 2024
suggested reading/skimming time: 1 hr
Towards human-AI deliberation: Design and evaluation of LLM-empowered deliberative AI for AI-assisted decision-making — Ma et al., 2024
suggested reading/skimming time: 45 min
concepts
case studies
case studies
Submit your reading
responses here
Required Readings:
(due by Tuesday night, Sep 16)
Other assignments
(due before class on Wednesday, Sep 17)
Add a note in the course project brainstorming doc with at least one idea for a project direction you’d be interested in exploring.
Any notes you add at this stage are tentative. So don’t worry: you are not committing to pursuing a particular direction for your actual project.
The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis – Pirolli & Card, 2005
suggested reading/skimming time: 40 min
Selenite: Scaffolding online sensemaking with comprehensive overviews elicited from large language models – Liu et al., 2024
suggested reading/skimming time: 1 hr
Accelerating scientific paper skimming with augmented intelligence through customizable faceted highlights — Fok et al., 2024
suggested reading/skimming time: 1 hr
concepts
case studies
case studies
Submit your reading
responses here
Optional Additional Readings
In search of verifiability: Explanations rarely enable complementary performance in AI-advised decision making — Fok & Weld, 2023
Cognitive challenges in human–artificial intelligence collaboration: Investigating the path toward productive delegation — Fügener et al., 2021
The placebo effect of human augmentation: Anticipating cognitive augmentation increases risk-taking behavior — Villa et al., 2023
“It makes you think”: Provocations help restore critical thinking to AI-assisted
knowledge work – Drosos et al., 2025
Supporting serendipity: Opportunities and challenges for human-AI collaboration in qualitative analysis — Jiang et al., 2021
Week 5
(Sep 22 - 26)
AUGMENTING
LEARNING &
PERCEPTION
Required Readings:
(due by Sunday night, Sep 21)
Do we learn from each other: Understanding the human-AI co-learning process embedded in human-AI collaboration – Lu et al., 2024
suggested reading/skimming time: 1 hr
Supporting human and machine co-learning in citizen science: Lessons from Gravity Spy — Østerlund et al., 2024
suggested reading/skimming time: 1 hr
Improving student learning with hybrid human-AI tutoring: A three-study quasi-experimental investigation – Thomas et al., 2024
suggested reading/skimming time: 45 min
case studies
case studies
case studies
Submit your reading
responses here
Required Readings
(due by Tuesday night, Sep 23)
Other assignments
(due before class on Wednesday, Sep 24)
If you haven’t done so already, look over the notes your classmates have added in the course project brainstorming doc. Use the commenting feature in Google Docs to indicate any of the project directions that you would be interested in potentially collaborating on! In your comments, please briefly note what skills you could contribute to the given project.
During Wednesday’s class, we will use this information to form project teams!
A design space for vision augmentations and augmented human perception using digital eyewear — Langlotz et al., 2024
suggested reading/skimming time: 1 hr
Persistent Assistant: Seamless everyday AI interactions via intent grounding and multimodal feedback – Cho et al., 2025
suggested reading/skimming time: 1 hr
concepts
case studies
Submit your reading
responses here
Optional Additional Readings
A conceptual framework for human–AI hybrid adaptivity in education — Holstein et al., 2020
Investigating use cases of AI-powered scene description applications for blind and low vision people — Gonzalez, Collins, et al., 2024
Look once to hear: Target speech hearing with noisy examples – Veluri, Itani et al., 2024
Week 6
(Sep 29 - Oct 3)
Required Readings:
(due by Sunday night, Sep 28)
AUGMENTING
CREATIVITY
Inkspire: Supporting design exploration with generative AI through analogical sketching – Lin et al., 2025
suggested reading/skimming time: 1 hr
Luminate: Structured generation and exploration of design space with large language models for human-AI co-creation — Suh, Chen et al., 2024
suggested reading/skimming time: 1 hr
Exploring the potential for generative AI-based conversational cues for real-time collaborative ideation – Rayan et al., 2024
suggested reading/skimming time: 45 min
case studies
case studies
case studies
Submit your reading
responses here
Required Readings:
(due by Tuesday night, Sep 30)
Other assignments
(due before class on Wednesday, Oct 1)
1) Each project team should submit a brief blurb about their planned project focus in this folder. Please feel free to keep it short for now (e.g., 4 to 6 sentences). We will have the next couple of weeks to brainstorm further!
2) In addition, all students should nominate at least one reading for our upcoming ‘student-selected topics’ weeks, in this doc. You can add a reading that you would be interested in discussing and/or add a ‘+1’ to at least one of the readings others have added.
Generative AI enhances individual creativity but reduces the collective diversity of novel content – Doshi & Hauser, 2024
suggested reading/skimming time: 45 min
The ideation–execution gap: Execution outcomes of LLM-generated versus human research ideas – Si, Hashimoto, &
Yang, 2025
suggested reading/skimming time: 45 min
Productive vs. reflective: How different ways of integrating AI into design workflows affect cognition and motivation – Xu et al., 2025
suggested reading/skimming time: 1 hr
case studies
case studies
case studies
Submit your reading
responses here
Optional Additional Readings
Exploring challenges and opportunities to support designers in learning to co-create with AI-based manufacturing design tools — Gmeiner et al., 2023
Supermind Ideator: How scaffolding human-AI collaboration can increase creativity — Heyman, Rick et al., 2024
The knowledge accelerator: Big picture thinking in small pieces — Hahn et al., 2016
Week 7
(Oct 6 - 10)
Required Readings:
(due by Sunday night, Oct 5)
AUGMENTING COLLECTIVE INTELLIGENCE
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COURSE PROJECT STUDIO
A framework for Open Civic Design: Integrating public participation, crowdsourcing, and design thinking – Reynante et al., 2021
suggested reading/skimming time: 1 hr
How large language models can reshape collective intelligence – Burton et al., 2024
suggested reading/skimming time: 1 hr
Judgment Sieve: Reducing uncertainty in group judgments through interventions targeting ambiguity versus disagreement — Chen & Zhang, 2023
suggested reading/skimming time: 1 hr
concepts
concepts
case studies
Other assignments
(due by Tuesday night, Oct 7)
It’s time to propose!
Submit an initial draft of your group’s course project proposal in this folder. We will discuss your proposals in class on Wednesday, and iterate as needed!
Submit your reading
responses here
Other assignments
(due by Wednesday night, Oct 8)
Sign up to give an upcoming Student-Selected Topics presentation on one of the selected papers (in groups of up to 5 students), using this sign-up sheet.
Optional Additional Readings
Supporting reflective public thought with ConsiderIt — Kriplean et al., 2012
Using AI to enhance collective intelligence in virtual teams: Augmenting cognition with technology to help teams adapt to complexity — Woolley et al., 2023
Opportunities and risks of LLMs for scalable deliberation with Polis – Small et al., 2023
AI can help humans find common ground in democratic deliberation – Tessler et al., 2024
PolicyCraft: Supporting collaborative and participatory policy design through case-grounded deliberation – Kuo et al., 2025
Human-agent collectives – Jennings et al., 2014
Intermission:
Fall Break!
Week 8
Required Readings:
(due by Tuesday night, Oct 21)
(Oct 20 - 24)
COURSE PROJECT STUDIO +
TOOLS FOR THOUGHT
The metacognitive demands and opportunities of generative AI – Tankelevitch et al., 2024
suggested reading/skimming time: 1 hr
concepts
Submit your reading
responses here
Guest lecture on Wednesday:
Week 9
Required Readings:
(due by Tuesday night, Oct 28)
(Oct 27 - Oct 31)
COURSE PROJECT STUDIO
+
STUDENT-SELECTED TOPICS:
(TBD)
Student-selected readings (TBD)
Week 10
Required Readings:
(due by Tuesday night, Nov 4)
(Nov 3 - 7)
COURSE PROJECT STUDIO
+
STUDENT-SELECTED TOPICS:
(TBD)
Student-selected readings (TBD)
Week 11
(Nov 10 - 14)
COURSE PROJECT STUDIO
Week 12
(Nov 17 - 21)
COURSE PROJECT STUDIO
Week 13
(Nov 24 - 25)
COURSE PROJECT STUDIO
No class on Wednesday
(Thanksgiving)
Week 14
(Dec 1 - 3)
Assignments
(due by Monday night, Dec 1)
Submit the materials for your team’s project presentation (e.g., a pdf of your team’s poster) in this folder.
Please remember to practice giving your presentations / demos!
COURSE PROJECT EXHIBITION
(public exhibition is on Dec 3)
