paper-with-me

홈 › Papers

An Experimental Comparison of Cognitive Forcing Functions for Execution Plans in AI-Assisted Writing: Effects On Trust, Overreliance, and Perceived Critical Thinking

2026-01-25 · Ahana Ghosh, Advait Sarkar, Siân Lindley, Christian Poelitz arxiv

Generative AI (GenAI) tools improve productivity in knowledge workflows such as writing, but also risk overreliance and reduced critical thinking. Cognitive forcing functions (CFFs) mitigate these risks by requiring active engagement with AI output. As GenAI workflows grow more complex, systems increasingly present execution plans for user review. However, these plans are themselves AI-generated and prone to overreliance, and the effectiveness of applying CFFs to AI plans remains underexplored. We conduct a controlled experiment in which participants completed AI-assisted writing tasks while reviewing AI-generated plans under four CFF conditions: Assumption (argument analysis), WhatIf (hypothesis testing), Both, and a no-CFF control. A follow-up think-aloud and interview study qualitatively compared these conditions. Results show that the Assumption CFF most effectively reduced overreliance without increasing cognitive load, while participants perceived the WhatIf CFF as most helpful. These findings highlight the value of plan-focused CFFs for supporting critical reflection in GenAI-assisted knowledge work.

📄 PDF Abstract BibTeX arXiv:2601.18033

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Cognitive Agency Surrender: Defending Epistemic Sovereignty via Scaffolded AI Friction

2026-03-23 · Kuangzhe Xu, Yu Shen, Longjie Yan, Yinghui Ren arxiv

The proliferation of Generative Artificial Intelligence has transformed benign cognitive offloading into a systemic risk of cognitive agency surrender. Driven by the commercial dogma of "zero-friction" design, highly flu…

To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-making

2021-02-19 · Zana Buçinca, Maja Barbara Malaya, Krzysztof Z. Gajos

People supported by AI-powered decision support tools frequently overrely on the AI: they accept an AI's suggestion even when that suggestion is wrong. Adding explanations to the AI decisions does not appear to reduce th…

Decision Making

Explicit Cognitive Allocation: A Principle for Governed and Auditable Inference in Large Language Models

2026-01-19 · Héctor Manuel Manzanilla-Granados, Zaira Navarrete-Cazales, Miriam Pescador-Rojas, Tonahtiu Ramírez-Romero arxiv

The rapid adoption of large language models (LLMs) has enabled new forms of AI-assisted reasoning across scientific, technical, and organizational domains. However, prevailing modes of LLM use remain cognitively unstruct…

TacForcing: Streaming Action Generation with Execution-Time Tactile Feedback

2026-08-26 · Jianbo Zhou, Boyuan Zhao, Yuzheng Zhang, Yiyang Chen 외 arxiv

Contact-rich manipulation requires adapting to contact states that can evolve substantially within an action horizon. However, chunk-based vision-language-action models predict complete action chunks from observations co…

Topological data analysis suggests human brain networks reconfiguration in the transition from a resting state to cognitive load

2023-05-21 · Ilya Ernston, Arsenii Onuchin, Timofey Adamovich

The functional network of the brain continually adapts to changing environmental demands. The environmental changes closely connect with changes of active cognitive processes. In recent years, the network approach has em…

Functional ConnectivityTopological Data Analysis