{"id":841,"date":"2020-03-24T23:33:38","date_gmt":"2020-03-24T23:33:38","guid":{"rendered":"http:\/\/wordpress.cs.vt.edu\/cs6724s20\/?p=841"},"modified":"2020-03-24T23:33:38","modified_gmt":"2020-03-24T23:33:38","slug":"03-24-2020-akshita-jha-like-having-a-really-bad-pa-the-gulf-between-user-expectation-and-experience-of-conversational-agents","status":"publish","type":"post","link":"https:\/\/wordpress.cs.vt.edu\/cs6724s20\/2020\/03\/24\/03-24-2020-akshita-jha-like-having-a-really-bad-pa-the-gulf-between-user-expectation-and-experience-of-conversational-agents\/","title":{"rendered":"03\/24\/2020 – Akshita Jha – \u201cLike Having a Really bad PA\u201d: The Gulf between User Expectation and Experience of Conversational Agents"},"content":{"rendered":"

Summary:<\/strong>
\n\u201cLike Having a Really bad PA: The Gulf between User Expectation and Experience of Conversational Agents” by Luger and Sellen talks about conversational agents and the gap between user expectation and the response given by the conversational agent. Conversational agents have been on the rise for quite some time now. All the big and well-known companies like Apple, Microsoft, Google, IBM, etc. have their own proprietary conversational agents. The authors report the findings of interviews with 14 end-users in order to understand the interactional factors affecting everyday use. The findings show that the end-users use conversational agents: (i) as a form of play, (ii) for a hands-free approach, (iii) for formal queries, and (iv) for simple tasks. The authors use “Norman’s \u2018gulfs of execution and evaluation\u2019 and infer the possible implications of their findings for the design of future systems.” The authors found that in the majority of instances the conversational agent was unable to fill the gap between user expectation and how the agent actually operates. It was also found that incorporating playful triggers and trigger responses in the systems increased human engagement.<\/p>\n

Reflection:<\/strong>
\nThis is an interesting work as it talks about the gap between user expectation and the system behavior, especially in the context of conversational agents. The researchers confirm that there is a “gulf” between the expectation and the reality and the end-users continually overestimate the amount of demonstratable intelligence that the system possesses. The authors also emphasized on the importance of the design and interactability of these conversational agents to make them better suited for engaging users. The users expect the chatbot to converse like humans but in reality, AI is far from it. The authors suggest considering ways to (a) to reveal system intelligence (b) to change the interactability to reflect the system’s capability (c) reign in the promises made by the scientists (d) revamp the system feedback given. The limitations of the study are that the sample is the male population from the UK. The findings presented in the paper, therefore, might be skewed. The primary use case for a conversational agent, not surprisingly, was ‘hands-free’ usage for saving time. However, if the conversational agent results in an error, the process becomes more cumbersome and time-consuming than originally typing in the query. The user tolerance in such cases might be low and lead to distrust which can negatively affect the feedback the conversational agents receive. The authors also talk about the different approaches that end-users take to interact with Google Now vs Siri. It would be interesting to see how user behavior changes with different conversational agents.<\/p>\n

Questions<\/strong>:
\n1. What are your views about conversational agents?
\n2. Which conversational agent do you think performs the best? Why?
\n3. As a computer scientist, what can you do to make the end-users more aware of the limitations of conversational agents?
\n4. How can be best incorporate feedback into the system?
\n5. Do you think using multimodal representations of intelligence is the way forward? What challenges do you see in using such a form of representation?<\/p>\n","protected":false},"excerpt":{"rendered":"

Summary: \u201cLike Having a Really bad PA: The Gulf between User Expectation and Experience of Conversational Agents” by Luger and Sellen talks about conversational agents and the gap between user expectation and the response given by the conversational agent. Conversational agents have been on the rise for quite some time now. All the big and […]<\/p>\n","protected":false},"author":295,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[88,87],"class_list":["post-841","post","type-post","status-publish","format-standard","hentry","category-uncategorized","tag-badpa","tag-class10"],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/wordpress.cs.vt.edu\/cs6724s20\/wp-json\/wp\/v2\/posts\/841","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wordpress.cs.vt.edu\/cs6724s20\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wordpress.cs.vt.edu\/cs6724s20\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/cs6724s20\/wp-json\/wp\/v2\/users\/295"}],"replies":[{"embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/cs6724s20\/wp-json\/wp\/v2\/comments?post=841"}],"version-history":[{"count":2,"href":"https:\/\/wordpress.cs.vt.edu\/cs6724s20\/wp-json\/wp\/v2\/posts\/841\/revisions"}],"predecessor-version":[{"id":857,"href":"https:\/\/wordpress.cs.vt.edu\/cs6724s20\/wp-json\/wp\/v2\/posts\/841\/revisions\/857"}],"wp:attachment":[{"href":"https:\/\/wordpress.cs.vt.edu\/cs6724s20\/wp-json\/wp\/v2\/media?parent=841"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/cs6724s20\/wp-json\/wp\/v2\/categories?post=841"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/cs6724s20\/wp-json\/wp\/v2\/tags?post=841"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}