The future of readers' advisory: Will technologies usurp this role of libraries?

So I am now back from my social media break and ready to blog again, especially about the interesting things I am reading and discovering on the Web. One such reading that I found interesting this week is the article by Grant (2013) on  Trapit (Siri's relative) and an iPad app that uses natural language processing to recommend content to read. In short, Trapit offers the possibility of readers' advisory, a service that has traditionally been offered by libraries.

For the uninitiated, readers' advisory is a service provided by libraries, whereby librarians, based on an understanding of the reading or information needs and preferences of their users, provide guidance or advice about resources or readings that users should consider reading next.  Reitz (2012) explains that such a service is provided by:

an experienced public services librarian who specializes in the reading needs of the patrons of a public library. A readers' advisor recommends specific titles and/or authors, based on knowledge of the patron's past reading preferences, and may also compile lists of recommended titles and serve as liaison to other education agencies in the community.

While traditionally, reader advisory would be a service offered by libraries, technology is rapidly usurping that role. With Internet developments, such as recommender systems provided by Amazon and Google Books, users do not need to interface with library personnel in order to get suggestions about what to read next. Technology now offers to look at what we have read in the past and our preferences, using these to predict what else may be of interest to us.

Going back to specific app called Trapit, I already see application of this software within large companies with many documents. Grant (2013) suggests that Trapit has the capability to personalize business news and internal reports, for employees to quickly access information relevant to them without searching for it.

Prior to learning about Trapit, I was of the view that artificial intelligent conversational agents (or chatbots) could also play roles as readers' advisors if programmed to ask questions and recommend books based on user responses. However, to explain this, I will need to write an entire technical paper and not just a blog post. Sufficient to say that Rubin, Chen & Thorimbert (2010) have already proposed that libraries use agent for storytelling and for even leading book discussions. Hence, agents can talk about books, though requiring initial and continual human investment in time to update and make them useful. Trapit in contrast, promises to require little or no input from staff, but only end users.

To conclude, the readers' advisory service of libraries seems to be one that will change in the near future. As more persons adopt tablet and other computing devices, our libraries will perhaps play a role in training users to use and customise the technologies for content recommendations, rather than actually engage  in face-to-face dialogue for making recommendations of titles for reading. In fact, such services could also be built automatically in our future (if not present) online catalogues and other electronic systems.


Reference:


Grant, R. (2013, April 3). Content-recommendation app Trapit grows up, enters formidable world of publishing. VentureBeat. Retrieved from http://venturebeat.com/2013/04/03/siris-little-brother-trapit-grows-up-enters-formidable-world-of-publishing/

Reitz, J. M. (2012). ODLIS: Online dictionary for library and information science. Retrieved from http://www.abc-clio.com/ODLIS/searchODLIS.aspx

Rubin, V. L., Chen, Y. & Thorimbert, L. M. (2010). Artificially intelligent conversational agents in libraries Library Hi Tech, 28(4), 496-522.

My latest discoveries on library chatbots: Pixel

This week, I learned through Michael Sauers from #NCompassLive Tech Talk about Pixel, the chatbot at the University of Nebraska– Lincoln Library. You can meet Pixel, the reference library chatbot at http://pixel.unl.edu/ and/or view the YouTube presentation on Pixel:





While listening to the presentation, I learned a couple of new things myself. The presenter DeAnn Allison raises the point that chatbots can flatten one's website, and reduce users from having to navigate to get information. Instead, users can just ask a question and the chatbot could provide the information or even the hyperlink to enable the user to get where they want to go, without having to click through several links. Lorna Dawes, the co-presenter, also made the point that chatbots are very useful for library websites that are very dense. As she made this point, I immediately thought of the  Library of Congress website, which I believe is very dense, yet full of useful information. If there is any library that should get one, in my opinion it is the Library of Congress.

The presentation also gave me an opportunity to reacquaint myself with Artificial Intelligence Markup Language (AIML), the language behind the open source chat bot movement. I also learned about Program-O (Open Source PHP MySQL AIML Chatbot software) http://blog.program-o.com/ as another open source software for creating one's chatbots.


Another thing that I discovered or realized during the presentation was the importance of taxonomies or ontologies in developing chatbots. This I realised as DeAnn Allison discussed how she used Library of Congress Subject headings to inform the AIML of a library chatbot. Allison (2012) also has an article on chatbots in the library if you want to check it out.

Reference:
Allison, D.  (2012). Chatbots in the library: Is it time? Library Hi Tech, (30) 1: 95 - 107.

DOI:	10.1108/07378831211213238

Trickster folkloric characters and my evolving thesis idea

I read an excerpt that I find interesting especially as I consider folkloric characters such as Anansi, Sly Mongoose and Doctorbird as possible options for the AI conversational agent.

"Trickster has particular purposes within cultural stories as educator and teacher. The trickster typically teaches by making mistakes so listeners can hear the stories and learn from the mistakes so they do not have to make them themselves. Trickster typically has some human and some superhuman characteristics and possibly some animal characteristics as well that allow him to get into situations that otherwise would not be possible thus allowing stories to consider complex cultural, emotional, physical, mental, and spiritual domains." (Iseke-Barnes 2009)

Interesting ideas. I never saw it that way. I saw Anasi stories as teaching us the qualities of deception and deceiving other people which I felt ingrained corruption and 'conmanship' in the African diaspora.

My discovery that Native Canadians (or the Indigenous people of Canada) also have trickster stories also makes my thesis idea more relevant to not only Jamaica, but to Canada as well. Hopefully I can establish that AI conversational agents based on one's cultural stories may be effective in the online world in transferring knowledge and information, and in helping people make sense of their activities or world.



Reference:

Iseke-Barnes, J. (2009). Unsettling fictions: Disrupting popular discourses and trickster tales in books for children. Journal of the Canadian Association for Curriculum Studies,

Brief update on my immature thesis idea

Just providing a brief update on my messy thesis concept. Right now it has evolved into the idea of using folkloric artificial intelligent conversational agents for transmitting business information for micro-enterprise owners.

 For the summer, I am hoping to look at literature on folklore being used to convey business information and/or use in online information services. By folklore - I am narrowing down to the use of folkloric storytelling and proverbs as well as the role of natural conversation in using these methods to convey information to micro-enterprise owners.

Also looking for theory to support this perspective. Thoughts, suggestions, or literature welcomed.

Preliminary thoughts on creating a chatbot to answer business questions from Jamaican government online sources

I am currently exploring the process of creating a chatbot for information provision, with view to apply it to my thesis and secondly to discuss its application to libraries in providing a new small business online information service.

So far, I am basing the chatbot as a question answering interface to Government documents for business users. My hope is to create the interface to answer questions by users regarding a Government process. In a sense, this moves into e-governance and the access to e-government information/ or simply the access to information.

So far, one of the issues that I have come across is the issue of updates. When basing the information for a business query on a government online source, in the case that I am doing, the particular Jamaican government agency has had a name change. Since the old/former name is in the document that I am attempting to use to feed my chatbot, one wonders when last the site was updated and how this could be a liability to libraries providing this service.

Stay tuned within the next few weeks for more on this matter.