# Different but Equal: Comparing User Collaboration with Digital Personal Assistants vs. Teams of Expert Agents

arXiv: https://arxiv.org/abs/1808.08157 · HTML: https://mlsanity.com/paper/1808.08157/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Aug 2018.

## Built on by (most cited first, 2 of 2)

- [MAGPIE: A dataset for Multi-AGent contextual PrIvacy Evaluation](https://mlsanity.com/paper/2506.20737/) (2025)
- [Incorporating Different Verbal Cues to Improve Text-Based Computer-Delivered Health Messaging](https://mlsanity.com/paper/2404.13633/) (2024)

## Abstract (arXiv)

This work compares user collaboration with conversational personal assistants vs. teams of expert chatbots. Two studies were performed to investigate whether each approach affects accomplishment of tasks and collaboration costs. Participants interacted with two equivalent financial advice chatbot systems, one composed of a single conversational adviser and the other based on a team of four experts chatbots. Results indicated that users had different forms of experiences but were equally able to achieve their goals. Contrary to the expected, there were evidences that in the teamwork situation that users were more able to predict agent behavior better and did not have an overhead to maintain common ground, indicating similar collaboration costs. The results point towards the feasibility of either of the two approaches for user collaboration with conversational agents.