Understanding, Protecting, and Augmenting Human Cognition with Generative AI: A Synthesis of the CHI 2025 Tools for Thought Workshop

Advait Sarkar; Aniket Kittur; Elena L. Glassman; Gonzalo Ramos; Hari Subramonyam; Jessica He; Lev Tankelevitch; Mina Lee; Srishti Palani; Yvonne Rogers

REVIEW 3 major objections 4 minor 4 cited by

Understanding, Protecting, and Augmenting Human Cognition with Generative AI: A Synthesis of the CHI 2025 Tools for Thought Workshop

T0 review · 3 major / 4 minor · reviewed 2026-08-05 · deepseek-v4-flash

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Pith's one-line read A workshop synthesis argues that generative AI's effect on human cognition can be mapped along three fronts: protecting thought, augmenting it, and building the theory and metrics to do both.

desk verdict Useful, clearly-organized workshop synthesis that maps an emerging space; the lack of an auditable synthesis method is a real but proportionate limitation, not a fatal one. read the letter →

arxiv 2508.21036 v1 pith:YWHRAYGS submitted 2025-08-28 cs.HC cs.AI

Lev Tankelevitch , Elena L. Glassman , Jessica He , Aniket Kittur , Mina Lee , Srishti Palani , Advait Sarkar , Gonzalo Ramos

show 2 more authors

Yvonne Rogers Hari Subramonyam

This is my paper

classification cs.HCcs.AI

keywords generativeAIhumancognitioncriticalthinkingcognitiveaugmentationtoolsforthoughtmetacognitionhuman-computerinteractionworkshopsynthesis

verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper's claim is that the outputs of a one-day workshop—56 participants and 34 accepted papers—start to map the full space of research and design opportunities opened by generative AI's effect on human cognition. It organizes that space into three interdependent fronts: understanding and protecting cognition against erosion from AI-driven automation; augmenting cognition through provocation, scaffolding, representation changes, and emotional pathways; and building the formative research, theory, measurement, and evaluation that the other two fronts depend on. A reader should care because the synthesis turns scattered findings, prototypes, and positions into a shared vocabulary and agenda, making it possible for different communities to work on comparable problems. The paper's central distinction—process-oriented support that helps people think versus end-to-end automation that replaces their thinking—gives designers a concrete axis for building or criticizing tools.

What carries the argument

The load-bearing device is the thematic map itself: a three-part structure sorting workshop material into AI's impact on and protection of cognition, cognitive augmentation, and formative research, theory, measurement, and evaluation. Within the augmentation section, the paper identifies a common thread it calls process-oriented support—AI that assists users in identifying and addressing challenges so users solve the task themselves—contrasted with task automation, which produces the answer for them. This axis does the organizing work: it explains why some AI tools feel augmenting because they keep users in the loop, and why others risk over-reliance because they remove users from the proces

What would settle it

Re-analyze every accepted workshop submission against a comprehensive taxonomy of cognitive processes such as memory, attention, reasoning, metacognition, creativity, and learning; if a large share of submissions addresses functions that fall outside the paper's three areas, or if a differently composed 56-person workshop yields a substantially different thematic structure, the claim that this map captures the space is undercut.

Watch

Extended reading notes

Core claim

The central assertion is that the workshop's collected material begins to map the space of research and design opportunities for human cognition with generative AI, and that this map can catalyze a multidisciplinary community. The synthesis sorts the material into three areas: understanding AI's impact on cognition while protecting it, augmenting cognition with AI, and developing the formative research, theory, measurement, and evaluation needed to make progress. Across these areas, the paper argues that AI shifts knowledge work from production to critical integration, that this shift can both erode and enhance thinking depending on design choices, and that the emerging design practice cente

Load-bearing premise

The map's completeness rests on the unstated assumption that the 56 participants and 34 accepted papers—chosen by the authors from over 70 submissions—represent the wider field, and that the authors' three-part structure faithfully captures the day's discussion.

Editorial extensions

If this is right

Designers gain a working distinction between process-oriented support and end-to-end automation, with the paper suggesting the former fits learning, complex decisions, and creative work better than the latter.
Researchers get an organized set of open questions, such as the right level and timing of cognitive friction and how to protect early ideation from AI influence, which can seed focused research programs.
Evaluation practice is steered toward behavioral traces like prompting patterns and toward longitudinal studies, since self-reports of introspective constructs like critical thinking may not align with theoretical definitions.
The paper's augmentation spectrum—provocation, scaffolding, representation transformation, and System 1 pathways—gives future work a shared vocabulary for comparing otherwise dissimilar AI-assisted cognition tools.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

If the map is accepted as the field's shared agenda, an implicit but unstated consequence is that measurement infrastructure should receive priority over additional tool prototypes: without agreed constructs and metrics, protection and augmentation claims cannot be compared across studies.
The paper's augmentation spectrum could be tested directly by fixing one task and one model while varying where assistance falls—provocation, scaffolding, representation change, or System 1—and measuring cognitive outcomes; this would show whether the categories are real design dimensions or just themes in the workshop corpus.
The deliberately 'ignorant co-learner' idea suggests a testable extension: a system that introduces uncertainty or contradictory perspectives could be compared against a factual-answer system in a learning task, measuring whether induced dissonance improves later independent reasoning.

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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Desk Editor's Note

read the letter

Quick take: this is a legitimate and useful agenda-setting piece, not a research result. The authors synthesize 34 workshop papers into a three-part structure—understanding/protecting, augmenting, and formative methods—and the organizing distinction between process-oriented support and task automation does real work. The writing is clear, the citations are integrated carefully, and the paper surfaces genuine tensions (friction vs. scaffolding, individual vs. group use, deep work vs. productivity). If you want a current map of HCI work on GenAI and cognition, this is the best single entry point I know.

What's new is the map itself, not any component. The concepts, like metacognitive demands and process-oriented support, come from the authors' prior work and the workshop papers. That's fine for a synthesis, but it does mean the novelty is organizational.

The main soft spot is the one the stress-test names: there is no described synthesis method. No coding scheme, no inter-rater reliability, no list of the 34 accepted papers beyond those cited, no session notes. The organizers selected the submissions and then wrote the synthesis, so the thematic structure almost certainly reflects their framing. The paper's own language—'begin mapping the space'—is modest, and the conclusion adds that one workshop cannot comprehensively address the space. That softens the concern, but a reader still cannot audit whether the map is representative of the workshop's actual topical distribution. This is a limitation, not a fabrication. For a workshop synthesis, I don't think it's disqualifying; these documents are typically curated rather than systematic. But a short appendix listing all accepted submissions and, ideally, a note on how themes were derived would fix most of it.

Self-citation is present but not egregious. Several organizers' papers are cited heavily, but they are genuinely central to the topic, and the reference list includes independent work. I wouldn't call it a flaw.

Bottom line: this deserves a serious referee. It's not a groundbreaking empirical or theoretical contribution, but it is a well-crafted synthesis that can shape research agendas. An editor should send it to review, with the main request being a transparency appendix.

Referee Report

3 major / 4 minor

Summary. The paper reports on the CHI 2025 Tools for Thought workshop, which brought together 56 participants and 34 accepted papers/portfolios to discuss how generative AI affects and can augment human cognition. The authors synthesize this material into three thematic areas: (i) understanding AI's impact on and protecting cognition, (ii) augmenting cognition with AI, and (iii) formative research, theory, measurement, and evaluation. The stated aim is to 'begin mapping the space' of research and design opportunities in this area and to catalyze a multidisciplinary community. The paper is written as a narrative synthesis with extensive citation to both workshop submissions and prior CHI/HCI literature, and it identifies many open research questions and design tensions.

Significance. If the synthesis is faithful to the workshop's content, the paper provides a useful structured agenda and shared vocabulary for a nascent research area. Its strengths include a broad and current bibliography, explicit linking of design work to psychological and educational theory (Dewey, Schön, dual-process theory, self-determination theory), and a willingness to name open tensions such as cognitive friction versus scaffolding, offloading versus cognitive laziness, and task-level versus workflow-level support. The paper also showcases concrete workshop contributions that might otherwise remain scattered. However, the value of the synthesis depends on the trustworthiness of the thematic mapping, and the paper currently offers no auditable evidence for that mapping. The absence of a described method, combined with the authors' dual role as workshop organizers and contributors to several cited works, makes the claimed 'map' difficult to verify.

major comments (3)

[Section 1 and Abstract] The central claim that the paper 'synthesizes' the workshop to 'begin mapping the space' is not backed by a describable method. The paper reports that 34 papers were 'selected from over 70 submissions' but gives no selection criteria, no list of accepted/rejected submissions, no coding scheme, no inter-rater reliability, and no session notes or transcripts. Because the authors are also the workshop organizers and contributors to several cited works (e.g., [123], [124], [140]), a reader cannot determine whether the three-part thematic structure reflects the workshop's topical distribution or the organizers' prior framing. Footnote 1 promises 'PDFs of all accepted submissions can be found [here]' but the link is absent. Please add an appendix or companion document that enumerates the accepted submissions, maps them to the themes, and provides the synthesis protocol.
[Section 3, opening paragraph] The claim that 'a common thread across these approaches is their focus on what Zhang and Reicherts [140] refer to as process-oriented support' takes a single workshop submission and elevates it to the organizing principle of the entire augmentation section. Similarly, Section 2.4.2's discussion of expertise leans heavily on the authors' own prior work [124]. This is not inherently wrong, but the paper does not mark when a framing is the authors' interpretive lens rather than a consensus of the workshop corpus. Please either present a documented basis for such cross-cutting claims (e.g., how many submissions instantiate process-oriented support) or rephrase them as proposals by the current authors rather than properties of the workshop.
[Sections 3.1-3.2 and 5] The narrative poses genuine design tensions (e.g., friction versus scaffolding; 'must reflection always be difficult?') but does not systematically weigh what the submissions actually say, and it does not include disconfirming or divergent findings from the same corpus or from the cited CHI papers (e.g., [133], [141]). The synthesis reads as a curated set of affirmations rather than a critical synthesis. The caveat in Section 5 that the topic 'cannot be comprehensively addressed in one workshop' is appropriate, but it does not address the stronger mapping claims in Section 1 ('map the space') and Section 3 ('the range of our workshop submissions'). Please add an account of how divergent and convergent positions were handled in the synthesis.

minor comments (4)

[Footnote 1] The promised link to PDFs of accepted submissions appears as the literal text '[here]' with no URL. This should be fixed in the final version.
[References [24] and [91]] These references contain metadata artifacts such as 'View Profile' and ORCID fragments. They should be cleaned to match the citation style of the rest of the bibliography.
[Reference [21]] The author name 'Xiaotong, Xu' contains an erroneous comma; it should read 'Xiaotong Xu'.
[Section 3.5] The term 'full-duplex communication' is introduced without a brief definition or analogy. A one-sentence explanation would help readers outside the telecommunications/interface community.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity found: the paper is a descriptive workshop synthesis with no derivational chain to collapse; self-citations are support, not load-bearing.

full rationale

The paper is a workshop synthesis, not a derivation. It fits no parameters, makes no quantitative predictions, and invokes no uniqueness theorem. Its central claim—that the workshop outputs 'begin mapping the space of research and design opportunities'—is a descriptive summary of 34 accepted submissions and discussions, not a consequence of the authors' prior work. The many self-citations (e.g., [66], [97], [124]) are used as supporting references for specific empirical findings or framing concepts, but the synthesis's organizing themes (understanding/protecting, augmenting, formative research) are the authors' own narrative structure and do not reduce to those citations. Even if the absence of a coding protocol makes the synthesis hard to audit, that is a methodological limitation, not circularity. No load-bearing step collapses by definition or by self-citation into its own inputs, so the appropriate score is 0.

Assumptions & free parameters 0 free parameters · 3 assumptions · 0 invented entities

The central claim, that the workshop outputs map the research space, rests on representativeness of the curated workshop sample, the transferability of existing cognitive theories to human-AI interaction, and the reliability of the cited workshop papers as evidence. None of these are independently established in the paper.

assumptions (3)

domain assumption The workshop corpus (56 participants, 34 papers) is representative of the broader research space on GenAI and human cognition.
The paper generalizes from this curated sample to 'the space of research and design opportunities' without discussing selection biases. Section 1.
domain assumption Existing theories (Dewey, dual-process, Bloom's taxonomy, etc.) are appropriate lenses for understanding GenAI's cognitive impact.
The synthesis applies these theories as if they transfer to human-AI interaction, which is an assumption typical of this literature but not tested here. Sections 2 and 4.
domain assumption Workshop discussion and cited papers provide sufficient evidence for the reported patterns (e.g., over-reliance, reduced critical thinking).
The paper reports these as emerging findings from cited submissions, but does not critically weigh conflicting evidence or effect sizes. Sections 2.1-2.3.

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Cite this review

Pith. "Pith review of Understanding, Protecting, and Augmenting Human Cognition with Generative AI: A Synthesis of the CHI 2025 Tools for Thought Workshop." pith.science (2026). https://pith.science/paper/YWHRAYGS

@misc{pith2026250821036,
  author       = {Pith},
  title        = {Pith review of: Understanding, Protecting, and Augmenting Human Cognition with Generative AI: A Synthesis of the CHI 2025 Tools for Thought Workshop},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/YWHRAYGS}},
  note         = {Machine review of arXiv:2508.21036}
}

read the original abstract

Generative AI (GenAI) radically expands the scope and capability of automation for work, education, and everyday tasks, a transformation posing both risks and opportunities for human cognition. How will human cognition change, and what opportunities are there for GenAI to augment it? Which theories, metrics, and other tools are needed to address these questions? The CHI 2025 workshop on Tools for Thought aimed to bridge an emerging science of how the use of GenAI affects human thought, from metacognition to critical thinking, memory, and creativity, with an emerging design practice for building GenAI tools that both protect and augment human thought. Fifty-six researchers, designers, and thinkers from across disciplines as well as industry and academia, along with 34 papers and portfolios, seeded a day of discussion, ideation, and community-building. We synthesize this material here to begin mapping the space of research and design opportunities and to catalyze a multidisciplinary community around this pressing area of research.

Figures

Figures reproduced from arXiv: 2508.21036 by the authors.

**Figure 1.** The CHI 2025 Tools for Thought Workshop was held in Yokohama, Japan, on April 26th, 2025. Abstract Generative AI (GenAI) radically expands the scope and capability of automation for work, education, and everyday tasks, a transformation posing both risks and opportunities for human cognition. How will human cognition change, and what opportunities are there for GenAI to augment it? Which theories, metrics, and other… view at source ↗

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Forward citations

Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

Explaining Too Much? Understanding How Large Language Model Reasoning Traces Influence Performance and Metacognition
cs.HC 2026-05 conditional novelty 6.0 of 10

Summary reasoning traces from LLMs maintain task performance and increase trust and appeal relative to answer-only or full-trace conditions, but none of the formats improve users' metacognitive calibration on reasoning tasks.
Material for Thought: Generative AI as an Active Creative Medium
cs.HC 2026-05 unverdicted novelty 6.0 of 10

Generative AI should be reframed as an active creative medium where humans use the SOSS process of shaping, observing, stirring, and selecting to sustain creative quality through conversation instead of judging outputs.
Affective Tools for Thought: Towards Shared Attention and Affective Reorienting in AI-Supported Thinking
cs.HC 2026-07 conditional novelty 5.0 of 10

Affect is constitutive of thinking, so Tools for Thought need Shared Attention and Affective Reorienting, addressed by Chain of Emotion × Chain of Thought, Affective Mirror, and Prompted Reorienting.
Stop Writing for Me: Generative Refusal in AI Tools for Thought
cs.HC 2026-05 conditional novelty 5.0 of 10

AI tools that deliberately refuse to generate text and ask context-aware questions can reduce cognitive burden in creative journaling and leave users with internalized questioning habits.

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