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        <article-title>Virtual Personal Assistants-A different approach to supporting the end user</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Peter Imrie</string-name>
          <email>peter.imrie@port.ac.uk</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>University of Portsmouth</institution>
        </aff>
      </contrib-group>
      <fpage>106</fpage>
      <lpage>109</lpage>
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      <title>-</title>
      <p>My research is focused on developing a model of a virtual personal
assistant, a technology that interacts with one individual and develops a
personal relationship to provide more contextually relevant outputs to
the user. We are exploring similar technologies that exhibit different
aspects of the model of technology we are describing to evaluate the
usefulness of each component individually, although there is no reason
why in the future they couldn’t all be combined into a new technology.
What these similar technologies lack is the personal feedback loop
between the end user and the technology, where the personal assistant
adapts to the end user and the user learns from the systems outputs.</p>
      <p>
        Supporting technologies are becoming more involved in people’s
lives, both on a personal and professional level. This is in part due to
the rise of new cutting edge technologies that allow these supporting
systems to attempt to be useful in different aspects of a user’s day to
day life. The category of supporting technologies we are interested in
are systems that specifically support the end user [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ]. Examples of these
systems typically have the ability to build metadata from a combination
of inputs and stored data to be able to modify their outputs. An example
of this can be seen with IBM’s Watson, a system that can provide a
medical diagnosis of a patient based upon its understanding of the
symptoms [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ]. Watson learns through analysing medical journals and
comparing that to what it has already learnt from in order to provide the
most logical diagnosis [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ].
      </p>
      <p>
        A number of modern supporting systems are utilizing learning
capabilities to build a relationship with the user in an effort to provide more
refined and useful outputs. A recent example of this is Apple’s Siri,
which provides support to its user in a casual context with
enhancements based upon its knowledge of the user [
        <xref ref-type="bibr" rid="ref4">4</xref>
        ]. Siri learns from its
interactions with the user and categorises the user with other users who
act in a similar fashion, allowing the program to tailor its outputs to a
category of user rather than focusing on the individual [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ]. While this
grouping does help for Apple and Siri to learn about people as a whole,
it loses the personal relationship with its end user.
      </p>
      <p>
        When supporting systems of this type are kept within the context of
the user they are able to develop a personal relationship with the unique
user [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ]. This allows the system to build its metadata in such a way that
it is analysing inputs with the perspective it has built from the unique
user, allowing it to give responses that are within the context of that
user. With its own perspective which is an imitation of the users
perspective, the system is able to analyse and explore uncertain or
ambiguous problem spaces and still provide a relevant and useful discussion
with the user about it. An example of this we have explored is the
concept of a user owned decision support system [
        <xref ref-type="bibr" rid="ref7">7</xref>
        ]. Once the system has
developed a personal relationship with the user it can discuss relevant
options with the user based upon its own perspective which is within
the context of its unique user. The focus isn’t on providing the most
likely option, but to explore alternative options with the user where the
situation may be dealing with unknown variables.
      </p>
      <p>
        When this type of technology is centralized or shared to give other
stakeholders access to the content, some of the usefulness is lost as the
relationship with the personality becomes less personal. Although the
inclusion of other stakeholders into the content control of these systems
can potentially have its benefits, it changes the dynamic of the
relationship and effects the perspective of the system [
        <xref ref-type="bibr" rid="ref8">8</xref>
        ].
      </p>
      <p>
        So what could this mean in the future? Popular media shows us what
its potential is as assistants to explorers (such as in the game Mass
Effect: Andromeda), partners for soldiers (such as in the movie Hunter
Prey) or even as advice givers (such as in the Isaac Asimov book I,
Robot). We are stepping away from the third party support of a system
such as Amazon’s Alexa [
        <xref ref-type="bibr" rid="ref9">9</xref>
        ] and looking at the more personal support
relationship of a system such as Iron man’s Jarvis [
        <xref ref-type="bibr" rid="ref10">10</xref>
        ].
      </p>
      <p>With this in mind, I have formed the hypothesis that end user
supporting technologies that develop a personal relationship with an
individual will have unique benefits that make the system more
useful to the end user. Appendix A Shows a reduced image of the
accompanying poster.</p>
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