Chatbots as Conversational Recommender Systems in Urban Contexts
Pavel Kucherbaev
Achilleas Psyllidis
Alessandro Bozzon
In this paper, we outline the vision of chatbots that facilitate the interaction between citizens and policy-makers at the city scale. We report the results of a co-design session attended by more than 60 participants. We give an outlook of how some challenges associated with such chatbot systems could be addressed in the future.
CitRec2017.tex
\documentclass[sigchi]{acmart}

\usepackage{booktabs} % For formal tables

\usepackage{adjustbox}
% Copyright

%\settopmatter{printacmref=false}

%Conference


%\acmPrice{15.00}


\begin{document}
\settopmatter{printacmref=false} % Removes citation information below abstract
\renewcommand\footnotetextcopyrightpermission[1]{} % removes footnote with conference information in first column
\pagestyle{plain} % removes running headers
\title{Chatbots as Conversational Recommender Systems in Urban Contexts}


\author{Pavel Kucherbaev}
\affiliation{%
  \institution{Delft University of Technology}
  \streetaddress{Mekelweg 4}
  \city{Delft} 
  \state{the Netherlands} 
  \postcode{2628 CD}
}
\email{p.kucherbaev@tudelft.nl}

\author{Achilleas Psyllidis}
\affiliation{%
  \institution{Delft University of Technology}
  \streetaddress{Mekelweg 4}
  \city{Delft} 
  \state{the Netherlands} 
  \postcode{2628 CD}
}
\email{a.psyllidis@tudelft.nl}

\author{Alessandro Bozzon}
\affiliation{%
  \institution{Delft University of Technology}
  \streetaddress{Mekelweg 4}
  \city{Delft} 
  \state{the Netherlands} 
  \postcode{2628 CD}
}
\email{a.bozzon@tudelft.nl}

% The default list of authors is too long for headers}
\renewcommand{\shortauthors}{P. Kucherbaev et al.}


\begin{abstract}
In this paper, we outline the vision of chatbots that facilitate the interaction between citizens and policy-makers at the city scale. We report the results of a co-design session attended by more than 60 participants. We give an outlook of how some challenges associated with such chatbot systems could be addressed in the future.
\end{abstract}

\begin{CCSXML}
<ccs2012>
<concept>
<concept_id>10002951.10003317.10003347.10003350</concept_id>
<concept_desc>Information systems~Recommender systems</concept_desc>
<concept_significance>300</concept_significance>
</concept>
</ccs2012>
\end{CCSXML}

\ccsdesc[300]{Human-centered computing~Ubiquitous and mobile computing systems and tools}

\keywords{Conversational Recommender Systems, Chatbots, Cities}

\maketitle

\section{Introduction}
Messenger applications, such as Messenger, Telegram, Whatsapp and WeChat, represent a popular medium of communication, which people use to interact with friends, family members and various brands. In 2015 the total number of active users of such applications surpassed the total number of users of conventional social network applications \cite{BIIntelligence}. Chatbots, on the other hand, are computer programs living in messenger applications and emulating a conversation with a human to provide a certain service \cite{McTearCallejasGriol16}. Conversational recommender systems derive user preferences by conversing with users in natural language \cite{Christakopoulou2016}. There are several examples of using chatbots in urban contexts, such as for pedestrian navigation \cite{Janarthanam2013} %sightseeing \cite{Kashioka2011}%
and policy decisions \cite{Augello2009,Boden2006}. While these examples serve users in very specific use cases, our vision is to develop a chatbot system that provides various recommendations to people in city regions and, further, helps citizens interact with the municipality.

While the open data movement is spreading wide, the majority of municipal datasets remain siloed, making it difficult for people to use. Solutions provided by municipalities are usually implemented in the form of standalone applications or web portals, which citizens are usually reluctant to install or visit. With the proposed chatbot system we help citizens (a) receive recommendations, based on open data sources (e.g. good kindergartens, parking lot locations etc.); (b) provide information to municipal authorities (e.g. to report a pothole); and (c) directly communicate with municipality employees or with other citizens, if the requested information is not available in any data source. To understand if such a chatbot system is needed, to derive requirements and collect use cases that both citizens and policy-makers want to see in it, we organised a co-design workshop.

\section{Co-design Workshop}
We organised a workshop on February 17, 2017 at \emph{Pakhuis de Zwijger} in Amsterdam, which is a platform for discussing city-related topics. More than 60 people with diverse backgrounds (e.g. students, industry employees, researchers, municipality employees), representing various nationalities, attended the session. The age of the participants ranged from 20 to 75 years, and around 40\% were women. About 50\% of the audience expressed their prior familiarity with chatbots. We wanted to brainstorm with the participants about possible use cases and requirements of chatbot systems for urban data retrieval and recommendation. To give them an idea of what is possible to do with chatbots, we created a mockup\footnote{More info on the co-design workshop is available at: \url{http://bit.ly/2uwuujO}} showing how citizens can ask information and recommendations about Amsterdam, provide extra information to the chatbot system, and even be asked proactively by it. Table 1 summarises the examples developed together with our participants. %about what citizens could ask the chatbot about, and what they could provide the chatbot with.
Later, we asked people in the audience to pick any use case and come up with a paper mockup of the conversation with the system.

Participants worked on their mockups in 10 teams of 5-7 people. The co-design session allowed us to identify a number of domains where current solutions do not yet satisfy users well. At the same time, surprisingly, the navigation use case, which is discussed a lot in the literature \cite{Janarthanam2013, Kashioka2011}, did not arise during the session, suggesting that this particular use case is already well covered by other systems (e.g. GoogleMaps) or that participants did not consider it appropriate for a conversational interface. There is a big room for solutions recommending places (e.g for spending free time), and presenting municipal, governmental, and neighborhood-related information (e.g. planned interventions, trash bin status etc.).

%The audience was very engaged and appreciated the possibility of quickly getting relevant information (e.g. safety reviews, construction schedules, event recommendations based on realtime ambience), as well as reporting on various issues, without a burden of installing extra mobile applications or navigating unfamiliar websites.
\begin{table}
\caption{Chatbot usage ideas derived from the co-design workshop.}
\begin{adjustbox}{width=\columnwidth}
\footnotesize
\begin{tabular}{ll}
\multicolumn{1}{c}{\textbf{Citizens can ask the bot about}}                 & \multicolumn{1}{c}{\textbf{Citizens can provide the bot with}}         \\ \hline
\multicolumn{1}{|l|}{What is being built here?}                             & \multicolumn{1}{l|}{Report a pothole}                   \\ \hline
\multicolumn{1}{|l|}{What is the construction schedule?}                    & \multicolumn{1}{l|}{Report children-friendly places}     \\ \hline
\multicolumn{1}{|l|}{Where is the best place to buy X?}                     & \multicolumn{1}{l|}{Report full trash cans}            \\ \hline
\multicolumn{1}{|l|}{What is the closest open night market?}                & \multicolumn{1}{l|}{Report things available for free}   \\ \hline
\multicolumn{1}{|l|}{What is the best time to visit the office?} & \multicolumn{1}{l|}{Report sentiment and feelings}    \\ \hline
\multicolumn{1}{|l|}{What is a good place to dance?}                        & \multicolumn{1}{l|}{Report about neighbourhoods}  \\ \hline

\end{tabular}
\end{adjustbox}
\end{table}




\section{Outlook}
Taking into consideration the use cases from the co-design session, we introduce a conceptual schema of the interactions citizens and policy-makers are engaged in through the chatbot system (Figure \ref{schema}). We envision that \emph{citizens} can request information via the chatbot system from connected \emph{data sources} (e.g. municipal open data portals). Moreover, citizens can proactively report new information, which will be stored in associated data sources. \emph{Policy makers} can as well request relevant information for decision-making purposes. If it is not possible to automatically satisfy an information need of a citizen, a responsible municipality employee is assigned by the chatbot system, such that the citizen can interact with this employee through the chatbot directly. Similarly, some citizens can express their willingness to be contacted by policy makers to provide their feedback to new policies and regulations. %The chatbot system helps solve information needs of both citizens and policy makers by automatically retrieving relevant information from data sources or facilitating communication between citizens and policy makers.
% FEEL FREE TO EDIT THE FIGURE HERE https://docs.google.com/drawings/d/1sbwB5V2lXCmN2JBwqG29kZJK0SDbH0RCs4okHo4wVnw/edit
\begin{figure}[h]
\includegraphics[width=1.0\columnwidth]{figures/Chatbot_Architecture_right.pdf}
\centering
\caption{Conceptual schema of the chatbot system.}
\label{schema}
\end{figure}



Developing such a chatbot system is not trivial, but there are various approaches that make it possible to obtain comparable results today. \emph{Human computation} could be used to address limitations of fully automatic chatbots, such when they do not understand user requests and, therefore, cannot provide a useful response. %A Wikipedia-like approach encouraging contributions to create integration with new data sources can help make the chatbot work across different topics.%
\emph{Gamification} strategies can be implemented to motivate citizens to collect and report information about the city.% and its status.

We are confident that such a chatbot system can significantly improve the civic engagement of citizens, making it easy to contribute to the city and to be involved in discussions about urban issues. The accessibility of such a chatbot system is very high, as existing messaging systems facilitate the on-boarding of citizens and minimize the learning curve. %Eventually, it could even happen that citizens vote using systems similar to the chatbot we proposed.%
While implementing such a chatbot system is much easier in cities which are in the forefront of urban development, the system could be transferred to cities of developing countries to facilitate the interaction of people with city stakeholders.


%\paragraph{Urban chatbots for citizens}
%\begin{itemize}
%    \item to use human computation to address limitations of current fully automatic chatbots
%    \item to use wikipedia-like approach to add diverse integrations to the chatbot to make it work effectively in open domain
%\end{itemize}



%\paragraph{Urban chatbots for city stake holders}
%\begin{itemize}
%    \item to motivate citizens to collect and report information in a fashion similar to Google Local Guides
%    \item to establish a direct communication between citizens and city stake holders, such that citizens can target responsible employees with their requests and employees could target groups of citizens with their proposed solutions.
%\end{itemize}

\begin{acks}
We thank the participants of the workshop and the personnel of Pakhuis de Zwijger. The research is supported by the Amsterdam Institute for Advanced Metropolitan Solutions  with the \emph{AMS Social Bot} grant.
\end{acks}

\bibliographystyle{ACM-Reference-Format}
\bibliography{sigproc} 

\end{document}

%Conversational recommenders are systems that derive user preferences by conversing with users in natural language \cite{Christakopoulou2016}.

%from the feedback users give interacting with recommendations \cite{Bridge2002}, or

%storytelling and gamification in museums \cite{Boiano16}.
%It is still open research questions are: how to design a chatbot serving recommendations to citizens in a broad set of scenarios, and how to make it an effective communication tool between city stakeholders and citizens.

%While messenger applications are already de-facto standard for brands to communicate with their clients, such medium is less popular in urban context connecting citizens and city stake holders.

%We do not only believe that city stakeholders should consider such communication channel, but we argue that chatbot could as well become a convenient way for both sides to establish such communication at scale. We introduce our vision of using chatbots as conversational recommender systems in urban contexts which will help researchers and practitioners as a framework for their future work.


%\begin{figure}[t]
%\includegraphics[width=6cm]{figures/CitRec-2.pdf}
%\centering
%\caption{Amsterdam chatbot mockup}
%\label{mockup}
%\end{figure}

%\section{Related work}
%McTear et al. give a comprehensive overview of conversational interfaces, along with software solutions using such interfaces - conversational agents - (including chatbots), in their book \cite{McTearCallejasGriol16}.  
%Diversity is considered as a primary selection constraint \cite{McGinty2003}.%, decision support in city governing games \cite{Augello2009b}.


%Challenges and opportunities of conversational agents are discussed in \cite{Zue2000}. 

%Conversational recommender system \cite{McGinty2003}.
CitRec2017.bbl
%%% -*-BibTeX-*-
%%% Do NOT edit. File created by BibTeX with style
%%% ACM-Reference-Format-Journals [18-Jan-2012].

\begin{thebibliography}{00}

%%% ====================================================================
%%% NOTE TO THE USER: you can override these defaults by providing
%%% customized versions of any of these macros before the \bibliography
%%% command.  Each of them MUST provide its own final punctuation,
%%% except for \shownote{}, \showDOI{}, and \showURL{}.  The latter two
%%% do not use final punctuation, in order to avoid confusing it with
%%% the Web address.
%%%
%%% To suppress output of a particular field, define its macro to expand
%%% to an empty string, or better, \unskip, like this:
%%%
%%% \newcommand{\showDOI}[1]{\unskip}   % LaTeX syntax
%%%
%%% \def \showDOI #1{\unskip}           % plain TeX syntax
%%%
%%% ====================================================================

\ifx \showCODEN    \undefined \def \showCODEN     #1{\unskip}     \fi
\ifx \showDOI      \undefined \def \showDOI       #1{#1}\fi
\ifx \showISBNx    \undefined \def \showISBNx     #1{\unskip}     \fi
\ifx \showISBNxiii \undefined \def \showISBNxiii  #1{\unskip}     \fi
\ifx \showISSN     \undefined \def \showISSN      #1{\unskip}     \fi
\ifx \showLCCN     \undefined \def \showLCCN      #1{\unskip}     \fi
\ifx \shownote     \undefined \def \shownote      #1{#1}          \fi
\ifx \showarticletitle \undefined \def \showarticletitle #1{#1}   \fi
\ifx \showURL      \undefined \def \showURL       {\relax}        \fi
% The following commands are used for tagged output and should be
% invisible to TeX
\providecommand\bibfield[2]{#2}
\providecommand\bibinfo[2]{#2}
\providecommand\natexlab[1]{#1}
\providecommand\showeprint[2][]{arXiv:#2}

\bibitem[\protect\citeauthoryear{Augello, Pilato, and Gaglio}{Augello
  et~al\mbox{.}}{2009}]%
        {Augello2009}
\bibfield{author}{\bibinfo{person}{Agnese Augello}, \bibinfo{person}{Giovanni
  Pilato}, {and} \bibinfo{person}{Salvatore Gaglio}.}
  \bibinfo{year}{2009}\natexlab{}.
\newblock \showarticletitle{An Intelligent Agent to Support City Policies
  Decisions}. In \bibinfo{booktitle}{{\em Conference on Neural Nets WIRN09}}.
  \bibinfo{publisher}{IOS Press}, \bibinfo{address}{Amsterdam},
  \bibinfo{pages}{163--168}.
\newblock


\bibitem[\protect\citeauthoryear{Boden, Fischer, Herbig, and Spierling}{Boden
  et~al\mbox{.}}{2006}]%
        {Boden2006}
\bibfield{author}{\bibinfo{person}{Cordula Boden}, \bibinfo{person}{Jessika
  Fischer}, \bibinfo{person}{Kathrin Herbig}, {and} \bibinfo{person}{Ulrike
  Spierling}.} \bibinfo{year}{2006}\natexlab{}.
\newblock \bibinfo{booktitle}{{\em CitizenTalk: Application of Chatbot
  Infotainment to E-Democracy}}.
\newblock \bibinfo{publisher}{Springer Berlin Heidelberg},
  \bibinfo{address}{Berlin, Heidelberg}, \bibinfo{pages}{370--381}.
\newblock
\showISBNx{978-3-540-49935-0}


\bibitem[\protect\citeauthoryear{Christakopoulou, Radlinski, and
  Hofmann}{Christakopoulou et~al\mbox{.}}{2016}]%
        {Christakopoulou2016}
\bibfield{author}{\bibinfo{person}{Konstantina Christakopoulou},
  \bibinfo{person}{Filip Radlinski}, {and} \bibinfo{person}{Katja Hofmann}.}
  \bibinfo{year}{2016}\natexlab{}.
\newblock \showarticletitle{Towards Conversational Recommender Systems}. In
  \bibinfo{booktitle}{{\em Proceedings of the 2016 International Conference on
  Knowledge Discovery and Data Mining}} {\em (\bibinfo{series}{KDD '16})}.
  \bibinfo{publisher}{ACM}, \bibinfo{address}{New York, NY, USA},
  \bibinfo{pages}{815--824}.
\newblock
\showISBNx{978-1-4503-4232-2}


\bibitem[\protect\citeauthoryear{Insider}{Insider}{2015}]%
        {BIIntelligence}
\bibfield{author}{\bibinfo{person}{Business Insider}.}
  \bibinfo{year}{2015}\natexlab{}.
\newblock \bibinfo{booktitle}{{\em Messaging apps are now bigger than social
  networks}}.
\newblock
\newblock
\shownote{\url{http://www.businessinsider.com/the-messaging-app-report-2015-11}.}


\bibitem[\protect\citeauthoryear{Janarthanam, Lemon, Liu, Bartie, Mackaness,
  and Dalmas}{Janarthanam et~al\mbox{.}}{2013}]%
        {Janarthanam2013}
\bibfield{author}{\bibinfo{person}{Srinivasan Janarthanam},
  \bibinfo{person}{Oliver Lemon}, \bibinfo{person}{X. Liu},
  \bibinfo{person}{Philip Bartie}, \bibinfo{person}{William Mackaness}, {and}
  \bibinfo{person}{Tiphaine Dalmas}.} \bibinfo{year}{2013}\natexlab{}.
\newblock \bibinfo{booktitle}{{\em A Multithreaded Conversational Interface for
  Pedestrian Navigation and Question Answering}}.
\newblock


\bibitem[\protect\citeauthoryear{Kashioka, Misu, Mizukami, Shiga, Kayama, Hori,
  and Kawai}{Kashioka et~al\mbox{.}}{2011}]%
        {Kashioka2011}
\bibfield{author}{\bibinfo{person}{Hideki Kashioka}, \bibinfo{person}{Teruhisa
  Misu}, \bibinfo{person}{Etsuo Mizukami}, \bibinfo{person}{Yoshinori Shiga},
  \bibinfo{person}{Kentaro Kayama}, \bibinfo{person}{Chiori Hori}, {and}
  \bibinfo{person}{Hisashi Kawai}.} \bibinfo{year}{2011}\natexlab{}.
\newblock \bibinfo{booktitle}{{\em Multimodal Dialog System for Kyoto
  Sightseeing Guide}}.
\newblock


\bibitem[\protect\citeauthoryear{McTear, Callejas, and Griol}{McTear
  et~al\mbox{.}}{2016}]%
        {McTearCallejasGriol16}
\bibfield{author}{\bibinfo{person}{Michael McTear}, \bibinfo{person}{Zoraida
  Callejas}, {and} \bibinfo{person}{David Griol}.}
  \bibinfo{year}{2016}\natexlab{}.
\newblock \bibinfo{booktitle}{{\em The Conversational Interface: Talking to
  Smart Devices}}.
\newblock \bibinfo{publisher}{Springer}, \bibinfo{address}{Cham}.
\newblock


\end{thebibliography}
