Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: What Would You Ask the Machine Learning Model? Identification of User
  Needs for Model Explanations Based on Human-Model Conversations   Recently we see a rising number of methods in the field of eXplainable
Artificial Intelligence. To our surprise, their development is driven by model
developers rather than a study of needs for human end users. The analysis of
needs, if done, takes the form of an A/B test rather than a study of open
questions. To answer the question "What would a human operator like to ask the
ML model?" we propose a conversational system explaining decisions of the
predictive model. In this experiment, we developed a chatbot called dr_ant to
talk about machine learning model trained to predict survival odds on Titanic.
People can talk with dr_ant about different aspects of the model to understand
the rationale behind its predictions. Having collected a corpus of 1000+
dialogues, we analyse the most common types of questions that users would like
to ask. To our knowledge, it is the first study which uses a conversational
system to collect the needs of human operators from the interactive and
iterative dialogue explorations of a predictive model.

11
The categories of this paper are: hep-lat
22
The categories of this paper are: chao-dyn
3
The categories of this paper are: physics
28
The categories of this paper are: alg-geom
24
The categories of this paper are: dg-ga
37
The categories of this paper are: supr-con
2
The categories of this paper are: math
13
The categories of this paper are: quant-ph
21
The categories of this paper are: adap-org
8
The categories of this paper are: hep-ex
27
The categories of this paper are: comp-gas
34
The categories of this paper are: chem-ph
20
The categories of this paper are: acc-phys
9
The categories of this paper are: nlin
18
The categories of this paper are: econ
6
The categories of this paper are: astro-ph