# Who Wrote this? How Smart Replies Impact Language and Agency in the Workplace

arXiv: https://arxiv.org/abs/2210.06470 · HTML: https://mlsanity.com/paper/2210.06470/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 40 references that are in the map.
- First posted on arXiv 7 Oct 2022.

## Builds on (most cited first, 10 of 10)

- [Semantics derived automatically from language corpora contain human-like biases](https://mlsanity.com/paper/1608.07187/) (2016)
- [Efficient Natural Language Response Suggestion for Smart Reply](https://mlsanity.com/paper/1705.00652/) (2017)
- [Gmail Smart Compose: Real-Time Assisted Writing](https://mlsanity.com/paper/1906.00080/) (2019)
- [The Impact of Multiple Parallel Phrase Suggestions on Email Input and Composition Behaviour of Native and Non-Native English Writers](https://mlsanity.com/paper/2101.09157/) (2021)
- [Smart Reply: Automated Response Suggestion for Email](https://mlsanity.com/paper/1606.04870/) (2016)
- [Artificial intelligence in communication impacts language and social relationships](https://mlsanity.com/paper/2102.05756/) (2021)
- [Diversifying Reply Suggestions using a Matching-Conditional Variational Autoencoder](https://mlsanity.com/paper/1903.10630/) (2019)
- [OCC: A Smart Reply System for Efficient In-App Communications](https://mlsanity.com/paper/1907.08167/) (2019)
- [Machine Agency in Human-Machine Networks; Impacts and Trust Implications](https://mlsanity.com/paper/1602.08237/) (2016)
- [Language Scaling for Universal Suggested Replies Model](https://mlsanity.com/paper/2106.02232/) (2021)

## Built on by (most cited first, 5 of 5)

- [Evaluating Human-Language Model Interaction](https://mlsanity.com/paper/2212.09746/) (2022)
- [LLM-GLOBE: A Benchmark Evaluating the Cultural Values Embedded in LLM Output](https://mlsanity.com/paper/2411.06032/) (2024)
- [Reactive Writers: How Co-Writing with AI Changes How We Engage with Ideas](https://mlsanity.com/paper/2603.10374/) (2026)
- [Model-Based Simulation for Optimising Smart Reply](https://mlsanity.com/paper/2305.16852/) (2023)
- [Enhancing AI Assisted Writing with One-Shot Implicit Negative Feedback](https://mlsanity.com/paper/2410.11009/) (2024)

## Abstract (arXiv)

AI-mediated communication is designed to help us do our work more quickly and efficiently. But does it come at a cost? This study uses smart replies (SRs) to show how AI influences humans without any intent on the part of the developer - the very use of AI is sufficient. I propose a loss of agency theory as a viable approach for studying the impact of AI on human agency. This theory focusses on the transfer of agency that is forced by circumstances (such as time pressure), human weaknesses (such as complacency), and conceptual priming. Mixed methods involving a crowdsourced experiment test that theory. The quantitative results reveal that machine agency affects the content we author and the behavior we generate. But it is a non-zero-sum game. The transfers between human and machine agency are fluid; they complement, replace, and reinforce each other at the same time.