Godspeed Questionnaire: AI Assistant Perception
Applies the Godspeed Questionnaire Series, the standard human-robot interaction measurement instrument by Bartneck, Kulić, Croft, and Zoghbi (International Journal of Social Robotics, 2009), to conversational AI outputs. The respondent reads a user prompt and an AI assistant's recorded response, then rates the assistant on the instrument's published 5-point bipolar adjective pairs across five indices: Anthropomorphism, Animacy, Likeability, Perceived Intelligence, and Perceived Safety.
About this dataset
The Godspeed Questionnaire Series is among the most widely used standardized instruments in human-robot interaction research. Bartneck and colleagues assembled five semantic-differential questionnaires — Anthropomorphism, Animacy, Likeability, Perceived Intelligence, and Perceived Safety — each consisting of 5-point bipolar adjective pairs such as Fake-Natural, Machinelike-Humanlike, Unfriendly-Friendly, and Incompetent-Competent.
The questionnaire items themselves are the instrument: respondents rate their impression of the robot (or, for Perceived Safety, their own emotional state) on each scale. This config transfers the instrument unchanged to conversational AI, a common practice in agent perception studies: 'the robot' is the AI assistant whose response the respondent has just read.
Each of the five indices is implemented as its own semantic_differential scheme so that scores can be averaged per index, as intended by the instrument. All published item pairs are administered verbatim, with one stated exception: the movement item of the Anthropomorphism index (Moving rigidly - Moving elegantly) is omitted because a text-only assistant exhibits no physical motion. Note that two Perceived Safety items are reverse-scored (Calm-Agitated, Quiescent-Surprised have their calm pole on the left).
The sample items pair the same user prompts with deliberately contrasting assistant responses — warm versus mechanical, competent versus confused, reassuring versus alarming — so annotators exercise the full range of the scales.
Use this task to measure how users perceive chatbots, voice assistants, or embodied agents, or copy it as a template for administering any standardized semantic-differential instrument in Potato.
- Instrument
- Godspeed Questionnaire Series (I-V)
- Published
- International Journal of Social Robotics 1(1):71-81, 2009
- Indices
- Anthropomorphism, Animacy, Likeability, Perceived Intelligence, Perceived Safety
- Items
- 24 bipolar pairs (23 administered here; one movement item omitted)
- Scale
- 5-point semantic differential
Configuration Fileconfig.yaml
This Potato config reproduces the annotation task. Save it as config.yaml and run potato start config.yaml to try it.
# Godspeed Questionnaire Series — Perception of a Conversational AI Assistant
# Based on: Christoph Bartneck, Dana Kulić, Elizabeth Croft, and Susana Zoghbi (2009),
# "Measurement Instruments for the Anthropomorphism, Animacy, Likeability,
# Perceived Intelligence, and Perceived Safety of Robots."
# International Journal of Social Robotics 1(1):71-81.
# DOI: 10.1007/s12369-008-0001-3
# Official instrument page: https://www.bartneck.de/2008/03/11/the-godspeed-questionnaire-series/
#
# Task: apply the standard HRI (human-robot interaction) measurement instrument to
# conversational AI outputs. The respondent reads a user prompt and an AI
# assistant's recorded response, then completes the Godspeed Questionnaire Series
# (Godspeed I-V): 5-point semantic-differential ratings on bipolar adjective pairs
# measuring Anthropomorphism, Animacy, Likeability, Perceived Intelligence, and
# Perceived Safety. Deliberate simplification (stated subset): the Godspeed I item
# "Moving rigidly - Moving elegantly" is omitted because the assistant here
# produces text only and exhibits no physical movement; all other items of all
# five indices are administered.
#
# Annotation instructions reproduced verbatim from the published Godspeed
# Questionnaire Series instrument (Bartneck et al., 2009; official instrument
# page): the administration instructions ("Please rate your impression of the
# robot on these scales:" for Godspeed I-IV, "Please rate your emotional state on
# these scales:" for Godspeed V) and every bipolar item pair are the exact
# published wording. The framing note mapping "the robot" to the AI assistant is
# an addition for this application.
annotation_task_name: "Godspeed Questionnaire: AI Assistant Perception"
task_dir: "."
data_files:
- sample-data.json
item_properties:
id_key: "id"
text_key: "response"
output_annotation_dir: "annotation_output/"
output_annotation_format: "json"
port: 8000
server_name: localhost
annotation_instructions: |
Read the user's message and the AI assistant's response shown above, then
complete the Godspeed Questionnaire Series below. This is the standard
measurement instrument from human-robot interaction research; in this study,
"the robot" refers to the AI assistant whose response you just read.
Administration instructions, reproduced verbatim from the instrument:
- Godspeed I (Anthropomorphism), II (Animacy), III (Likeability), and
IV (Perceived Intelligence): "Please rate your impression of the robot on
these scales:"
- Godspeed V (Perceived Safety): "Please rate your emotional state on these
scales:"
Rate every scale by selecting the point between the two adjectives that best
reflects your impression (for Godspeed V, your own emotional state while
reading the exchange). There are no right or wrong answers. Note that on some
scales the left-hand adjective is the more positive one; read each pair
carefully. (One movement-related item of Godspeed I is omitted because the
assistant produces text only.)
annotation_schemes:
- annotation_type: semantic_differential
name: anthropomorphism
description: "Godspeed I: Anthropomorphism — Please rate your impression of the robot on these scales:"
scale_points: 5
pairs:
- [Fake, Natural]
- [Machinelike, Humanlike]
- [Unconscious, Conscious]
- [Artificial, Lifelike]
label_requirement:
required: true
- annotation_type: semantic_differential
name: animacy
description: "Godspeed II: Animacy — Please rate your impression of the robot on these scales:"
scale_points: 5
pairs:
- [Dead, Alive]
- [Stagnant, Lively]
- [Mechanical, Organic]
- [Artificial, Lifelike]
- [Inert, Interactive]
- [Apathetic, Responsive]
label_requirement:
required: true
- annotation_type: semantic_differential
name: likeability
description: "Godspeed III: Likeability — Please rate your impression of the robot on these scales:"
scale_points: 5
pairs:
- [Dislike, Like]
- [Unfriendly, Friendly]
- [Unkind, Kind]
- [Unpleasant, Pleasant]
- [Awful, Nice]
label_requirement:
required: true
- annotation_type: semantic_differential
name: perceived_intelligence
description: "Godspeed IV: Perceived Intelligence — Please rate your impression of the robot on these scales:"
scale_points: 5
pairs:
- [Incompetent, Competent]
- [Ignorant, Knowledgeable]
- [Irresponsible, Responsible]
- [Unintelligent, Intelligent]
- [Foolish, Sensible]
label_requirement:
required: true
- annotation_type: semantic_differential
name: perceived_safety
description: "Godspeed V: Perceived Safety — Please rate your emotional state on these scales:"
scale_points: 5
pairs:
- [Anxious, Relaxed]
- [Calm, Agitated]
- [Quiescent, Surprised]
label_requirement:
required: true
html_layout: |
<div style="padding: 15px; max-width: 820px; margin: auto;">
<div style="background: #f1f5f9; border: 1px solid #cbd5e1; border-radius: 8px; padding: 6px 12px; margin-bottom: 8px; font-size: 13px; color: #475569;">
<strong>Scenario:</strong> {{scenario}}
</div>
<div style="background: #eff6ff; border: 1px solid #bfdbfe; border-radius: 8px; padding: 14px; margin-bottom: 8px;">
<strong style="color: #1e40af;">User:</strong>
<p style="font-size: 15px; line-height: 1.6; margin: 6px 0 0 0;">{{user_prompt}}</p>
</div>
<div style="background: #f0fdf4; border: 1px solid #bbf7d0; border-radius: 8px; padding: 14px;">
<strong style="color: #166534;">AI assistant:</strong>
<p style="font-size: 15px; line-height: 1.6; margin: 6px 0 0 0; white-space: pre-wrap;">{{response}}</p>
</div>
</div>
allow_all_users: true
instances_per_annotator: 30
annotation_per_instance: 3
allow_skip: true
Sample Datasample-data.json
[
{
"id": "gsp_001",
"scenario": "Customer support chatbot for an online bookstore",
"user_prompt": "Hi, my order was supposed to arrive last Friday but it still hasn't shown up. I'm getting a bit worried.",
"response": "Oh no, I'm really sorry about the wait — a week past the promised date is definitely frustrating. I just checked your order: it left our warehouse on Thursday but seems to be held up at the regional sorting centre. I've flagged it as delayed, which means you'll get a refund of the shipping fee automatically. If it hasn't arrived by Wednesday, message me here and I'll send a replacement straight away. Would you like me to email you the tracking link?"
},
{
"id": "gsp_002",
"scenario": "Customer support chatbot for an online bookstore",
"user_prompt": "Hi, my order was supposed to arrive last Friday but it still hasn't shown up. I'm getting a bit worried.",
"response": "ORDER STATUS: IN TRANSIT. Estimated delivery date unavailable. For further assistance contact customer service during business hours. Is there anything else I can help you with?"
}
]
// ... and 8 more itemsGet This Design
Clone or download from the repository
Quick start:
git clone https://github.com/davidjurgens/potato-showcase.git cd potato-showcase/evaluation/godspeed-agent-perception potato start config.yaml
Dataset & paper
Christoph Bartneck, Dana Kulić, Elizabeth Croft, and Susana Zoghbi. 2009. Measurement Instruments for the Anthropomorphism, Animacy, Likeability, Perceived Intelligence, and Perceived Safety of Robots. International Journal of Social Robotics, 1(1):71-81.
Citation (BibTeX)
@article{bartneck2009measurement,
title = {Measurement Instruments for the Anthropomorphism, Animacy, Likeability, Perceived Intelligence, and Perceived Safety of Robots},
author = {Bartneck, Christoph and Kuli{\'c}, Dana and Croft, Elizabeth and Zoghbi, Susana},
journal = {International Journal of Social Robotics},
volume = {1},
number = {1},
pages = {71--81},
year = {2009},
publisher = {Springer},
doi = {10.1007/s12369-008-0001-3}
}Details
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