Search Results for author: Justin D. Weisz

Found 10 papers, 0 papers with code

Facilitating Human-LLM Collaboration through Factuality Scores and Source Attributions

no code implementations30 May 2024 Hyo Jin Do, Rachel Ostrand, Justin D. Weisz, Casey Dugan, Prasanna Sattigeri, Dennis Wei, Keerthiram Murugesan, Werner Geyer

To address this issue, we conducted a scenario-based study (N=104) to systematically compare the impact of various design strategies for communicating factuality and source attribution on participants' ratings of trust, preferences, and ease in validating response accuracy.

Toward General Design Principles for Generative AI Applications

no code implementations13 Jan 2023 Justin D. Weisz, Michael Muller, Jessica He, Stephanie Houde

We anticipate these principles to usefully inform design decisions made in the creation of novel human-AI applications, and we invite the community to apply, revise, and extend these principles to their own work.

A Case Study in Engineering a Conversational Programming Assistant's Persona

no code implementations13 Jan 2023 Steven I. Ross, Michael Muller, Fernando Martinez, Stephanie Houde, Justin D. Weisz

The Programmer's Assistant is an experimental prototype software development environment that integrates a chatbot with a code editor.

Chatbot Language Modelling +1

Investigating Explainability of Generative AI for Code through Scenario-based Design

no code implementations10 Feb 2022 Jiao Sun, Q. Vera Liao, Michael Muller, Mayank Agarwal, Stephanie Houde, Kartik Talamadupula, Justin D. Weisz

Using scenario-based design and question-driven XAI design approaches, we explore users' explainability needs for GenAI in three software engineering use cases: natural language to code, code translation, and code auto-completion.

Code Translation Explainable Artificial Intelligence (XAI)

Using Document Similarity Methods to create Parallel Datasets for Code Translation

no code implementations11 Oct 2021 Mayank Agarwal, Kartik Talamadupula, Fernando Martinez, Stephanie Houde, Michael Muller, John Richards, Steven I Ross, Justin D. Weisz

However, due to the paucity of parallel data in this domain, supervised techniques have only been applied to a limited set of popular programming languages.

Code Translation Machine Translation +1

Expanding Explainability: Towards Social Transparency in AI systems

no code implementations12 Jan 2021 Upol Ehsan, Q. Vera Liao, Michael Muller, Mark O. Riedl, Justin D. Weisz

We suggested constitutive design elements of ST and developed a conceptual framework to unpack ST's effect and implications at the technical, decision-making, and organizational level.

Decision Making Explainable Artificial Intelligence (XAI)

Do's and Don'ts for Human and Digital Worker Integration

no code implementations15 Oct 2020 Vinod Muthusamy, Merve Unuvar, Hagen Völzer, Justin D. Weisz

Robotic process automation (RPA) and its next evolutionary stage, intelligent process automation, promise to drive improvements in efficiencies and process outcomes.


AutoAIViz: Opening the Blackbox of Automated Artificial Intelligence with Conditional Parallel Coordinates

no code implementations13 Dec 2019 Daniel Karl I. Weidele, Justin D. Weisz, Eno Oduor, Michael Muller, Josh Andres, Alexander Gray, Dakuo Wang

Artificial Intelligence (AI) can now automate the algorithm selection, feature engineering, and hyperparameter tuning steps in a machine learning workflow.

AutoML Feature Engineering

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