# De-skilling, Cognitive Offloading, and Misplaced Responsibilities: Potential Ironies of AI-Assisted Design

arXiv: https://arxiv.org/abs/2503.03924 · HTML: https://mlsanity.com/paper/2503.03924/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 33 references that are in the map.
- First posted on arXiv 5 Mar 2025.

## Builds on (most cited first, 5 of 5)

- [Designing Participatory AI: Creative Professionals' Worries and Expectations about Generative AI](https://mlsanity.com/paper/2303.08931/) (2023)
- [Ironies of Generative AI: Understanding and mitigating productivity loss in human-AI interactions](https://mlsanity.com/paper/2402.11364/) (2024)
- [User Experience Design Professionals' Perceptions of Generative Artificial Intelligence](https://mlsanity.com/paper/2309.15237/) (2023)
- [Beyond Automation: How UI/UX Designers Perceive AI as a Creative Partner in the Divergent Thinking Stages](https://mlsanity.com/paper/2501.18778/) (2025)
- [Generative AI & Changing Work: Systematic Review of Practitioner-led Work Transformations through the Lens of Job Crafting](https://mlsanity.com/paper/2502.08854/) (2025)

## Built on by (most cited first, 11 of 11)

- [How Do AI Agents Do Human Work? Comparing AI and Human Workflows Across Diverse Occupations](https://mlsanity.com/paper/2510.22780/) (2025)
- [From Future of Work to Future of Workers: Addressing Asymptomatic AI Harms for Dignified Human-AI Interaction](https://mlsanity.com/paper/2601.21920/) (2026)
- [When Autonomy Breaks: The Hidden Existential Risk of AI](https://mlsanity.com/paper/2503.22151/) (2025)
- [Beyond Automation: Socratic AI, Epistemic Agency, and the Implications of the Emergence of Orchestrated Multi-Agent Learning Architectures](https://mlsanity.com/paper/2508.05116/) (2025)
- [Offloading Score: Measuring AI Reliance Through Counterfactual Workflows](https://mlsanity.com/paper/2605.29392/) (2026)
- [Tracing the Invisible: Understanding Students' Judgment in AI-Supported Design Work](https://mlsanity.com/paper/2505.08939/) (2025)
- [Dead Cognitions: A Census of Misattributed Insights](https://mlsanity.com/paper/2604.10288/) (2026)
- [Measuring Successful Cooperation in Human-AI Teamwork: Development and Validation of the Perceived Cooperativity and Teaming Perception Scales](https://mlsanity.com/paper/2604.24461/) (2026)
- [Concerns and Strategic Responses of Older Workers Navigating Generative AI in Bridge Employment](https://mlsanity.com/paper/2606.07543/) (2026)
- [SCAN: A Decision-Making Framework for Effective Task Allocation with Generative AI](https://mlsanity.com/paper/2606.15601/) (2026)
- [Structured pre-generation elicitation versus single-shot prompting in AI-assisted enterprise decision-making: a randomised online experiment](https://mlsanity.com/paper/2610.09593/) (2026)

## Abstract (arXiv)

The rapid adoption of generative AI (GenAI) in design has sparked discussions about its benefits and unintended consequences. While AI is often framed as a tool for enhancing productivity by automating routine tasks, historical research on automation warns of paradoxical effects, such as de-skilling and misplaced responsibilities. To assess UX practitioners' perceptions of AI, we analyzed over 120 articles and discussions from UX-focused subreddits. Our findings indicate that while practitioners express optimism about AI reducing repetitive work and augmenting creativity, they also highlight concerns about over-reliance, cognitive offloading, and the erosion of critical design skills. Drawing from human-automation interaction literature, we discuss how these perspectives align with well-documented automation ironies and function allocation challenges. We argue that UX professionals should critically evaluate AI's role beyond immediate productivity gains and consider its long-term implications for creative autonomy and expertise. This study contributes empirical insights into practitioners' perspectives and links them to broader debates on automation in design.