There are dozens of novels about dystopic robots – our future “overlords” as as they are portrayed.
In the news, there are many stories about robots and artificial intelligence that focus on important business tasks. Those are the tasks that have peopled worried about their future employment prospects. But that stuff is pretty boring if it’s not your own field.
Anyway, while we are only beginning to try to understand the implications of artificial intelligence and robotics, robots are developing rapidly and going beyond those traditional tasks.
Robots are also showing off their fun and increasingly creative side.
Welcome to the age of the “all singing, all dancing” robot. Let’s look at some examples.
Not to be outdone, at the Consumer Electronics Show in Las Vegas, a strip club had a demonstration of robots doing pole dancing. The current staff don’t really have to worry about their jobs just yet, as you can see at https://www.youtube.com/watch?v=EdNQ95nINdc
Music
Jukedeck, a London startup/research project, has been using AI to produce music for a couple of years.
The Flow Machines project in Europe has also been using AI to create music in the style of more famous composers. See, for instance, its DeepBach, “a deep learning tool for automatic generation of chorales in Bach’s style”. https://www.youtube.com/watch?time_continue=2&v=QiBM7-5hA6o
Singing
Then there’s Sophia, Hanson Robotics famous humanoid. While there is controversy about how much intelligence Sophia has – see, for example, this critique from earlier this year – she is nothing if not entertaining. So, the world was treated to Sophia singing at a festival three months ago – https://www.youtube.com/watch?v=cu0hIQfBM-w#t=3m44s
There is even AI that will generate poetry – um, song lyrics.
Marjan Ghazvininejad, Xing Shi, Yejin Choi and Kevin Knight of USC and the University of Washington wrote Hafez and began Generating Topical Poetry on a requested subject, like this one called “Bipolar Disorder”:
Existence enters your entire nation.
A twisted mind reveals becoming manic,
An endless modern ending medication,
Another rotten soul becomes dynamic.
Or under pressure on genetic tests.
Surrounded by controlling my depression,
And only human torture never rests,
Or maybe you expect an easy lesson.
Or something from the cancer heart disease,
And I consider you a friend of mine.
Without a little sign of judgement please,
Deliver me across the borderline.
An altered state of manic episodes,
A journey through the long and winding roads.
Not exactly upbeat, but you could well imagine this being a song too.
A few weeks ago, I wrote about the second chance given to libraries, as Google’s role in the life of web users slowly diminishes. Of course, for at least a few years, one of the responses of librarians to the growth of the digital world has been to re-envision libraries as curators of knowledge, instead of mere collectors of documents. It’s not a bad start in a transition.
Indeed, this idea has also been picked up by all kinds of online sites, not just libraries. Everyone it seems wants to aggregate just the right mix of articles from other sources that might interest you.
But, from my perspective, curation is an inadequate solution to the bigger problem this digital knowledge century has created – we don’t have time to read everything. Filtering out the many things I might not want to read at all doesn’t help me much. I still end up having too much to read.
And we end up in the situation summed up succinctly by the acronym TL;DR, too long, didn’t read. (Or my version in response to getting millions of Google hits – TMI, TLK “too much information, too little knowledge”.)
“How do we find topically relevant, semantically related, timely information in massive amounts of data in diverse languages, formats, and genres? Given the incredible amounts of information available today, merely reducing the size of the haystack is not enough; information professionals … require timely, focused answers to complex questions.”
Like NIST, what I really want – maybe what you want or need too? – is someone to summarize everything out there and create a new body of work that tells me just what I need to know in as few words as possible.
Researchers call this abstractive summarization and this is not an easy problem to solve. But there has been some interesting work going on in various universities and research labs.
At Columbia University, Professor Kathleen McKeown and her research colleagues developed “NewsBlaster” several years ago to organize and summarize the day’s news.
Among other companies, Automated Insights has developed some practical solutions to the overall problem. Their Wordsmith software has been used, for example, by the Associated Press “to transform raw earnings data into thousands of publishable stories, covering hundreds more quarterly earnings stories than previous manual efforts”.
For all their clients, they claim to produce “over 1.5 billion narratives annually”. And these are so well done that the New York Times had an article about it that was titled “If An Algorithm Wrote This, How Would You Even Know?”.
The next step, of course, is to combine many different data sources and generate articles about them for each person interested in that combination of sources.
Just a few months ago, Salesforce’s research team announced a major advance in summarization. Their motivation, by the way, is the same as mine:
“In 2017, the average person is expected to spend 12 hours and 7 minutes every day consuming some form of media and that number will only go up from here… Today the struggle is not getting access to information, it is keeping up with the influx of news, social media, email, and texts. But what if you could get accurate and succinct summaries of the key points…?”
Maluuba, acquired by Microsoft, has been continuing earlier research too. As they describe their research on “information-seeking behaviour”:
“The research at Maluuba is tackling major milestones to create AI agents that can efficiently and autonomously understand the world, look for information, and communicate their findings to humans.”
Librarians have skills that can contribute to the development of this branch of artificial intelligence. While those skills are necessary, they aren’t sufficient and a joint effort between AI researchers and the library world is required.
However, if librarians joined in this adventure, they could also offer the means of delivering this focused knowledge to the public in a more useful way than just dumping it into the Internet.
As I’ve blogged a few months ago:
Librarians have many skills to add to the task of “organizing the world’s information, and making it universally accessible”. But as non-profit organizations interested in the public good, libraries can also ensure that the next generation of knowledge tools – surpassing Google search – is developed for non-commercial purposes.
So, what comes after everyone has tried curation? Abstractive summarization aided by artificial intelligence software, that’s what!
In our post-industrial, Internet world, an ever increasing percentage
of the population has an ever increasing need for knowledge to make a
living. This is why people have used the Internet’s search engines so
much, despite being frequently frustrated by the volume and irrelevance
of search results. They may also be suspicious of the bias and
commercialism built into the results. Most of all, people intuitively
grasp that search results are not the same thing as the knowledge they
really want.
Thus, if I had to point to a single service that
would dramatically raise the economic importance of libraries in this
century, it would be satisfying this need in a substantive and objective
way.
Yet, if you go to most dictionaries, you’ll find a
definition of a library like this one from the Oxford Dictionary:
“A
building or room containing collections of books, periodicals, and
sometimes films and recorded music for people to read, borrow, or refer
to”.
While few people would say that libraries
shouldn’t provide books, as long as people want them, most librarians
would point to the many services they have provided beyond collecting
printed material.
Nevertheless, the traditional definition
continues to limit the way too many librarians think. Even among those
who object to the narrow definition in the dictionary, these two
traditional assumptions about libraries are usually unquestioned:
Library services are mostly delivered in a library building.
Library services are mostly delivered by human beings.
My
argument here is simple: If libraries are to meet the public needs of a
21st century knowledge economy, librarians must lift these self-imposed
constraints. It is time to free the library and library services!
This
isn’t as radical as it sounds. If we look deeper, more conceptually,
at what has gone on in libraries, libraries services are about the
community’s reserve of knowledge and sharing of information — and
helping members of the community find what they need quickly, accurately
and without bias. I’m proposing nothing different, except expanding
the ways that libraries do this job.
The first of these two
assumptions is the simplest one to abandon. Although the library
building remains the focus for many in the profession, in various ways,
virtual services are available through the web, chat, email or even Skype. (I’ve written
before about the ways that library reference services could become
available anywhere and be much improved through a national
collaboration.)
The second assumption – the necessity for a human librarian at almost all points of service — will be a tougher one to discard.
Consider,
though, one of the most important of the emerging, disruptive
technologies – artificial intelligence and machine learning – which can
supplement and enhance the ability of librarians to deliver information
services well and at a scale appropriate for the large demand.
My hope is that, working with software and artificial intelligence experts, librarians
will start creating machine learning and artificial intelligence
services that will make in-depth, unbiased knowledge guidance and
information reference universally available.
Doing that
successfully as a national project will enable the library as an
institution, if not a building, to reclaim its role as information
central for people of all ages.
During
the last several years, there have been a few experiments in using
artificial intelligence to supplement reference services provided by
human librarians. In the UK, the University of Wolverhampton offers its
“Learning & Information Services Chatbot”.
A few weeks ago, the Knight News Challenge selected the Charlotte Mecklenberg Public Library’s DALE project with IBM Watson and described it as “the first AI enabled search portal within a public library setting.”
In a note that is very much in accord with my argument, they wrote:
“Libraries
are the unsung heroes of the Information Age. In a world where
everyone Googles for the right answer, many are unaware of the wealth of
information that libraries have within their physical and digital
collections.… DALE would be able to analyze the structured and
unstructured data hidden within the public library’s vast collections,
helping both staff and customers locate the information needed within
one search setting.”
Despite the needs of library patrons, so far these examples are still rare for a couple of reasons.
Some
people argue that libraries shouldn’t and maybe can’t compete with the
big corporations, like Apple and Google, in helping people find the
knowledge they need. As I’ve already noted above, many users experience
these commercial services as a poor substitute for what they want.
In
any case, abdicating its own responsibility is a disservice to library
patrons and the public who have looked to libraries for objective,
non-commercial information services for a very long time.
There is
also a fear that wider use of artificial intelligence to help provide
library services might put human librarians out of work. While that is
not a concern that librarians generally discuss publicly, Steven Bell,
Associate University Librarian of Temple University, wrote last month in
Library Journal about this very subject – the potential for artificial
intelligence to diminish the need for librarians. He called it the “Promise and Peril of AI for Academic Librarians”, although the article seemed to focus more on the peril.
This
is the fear of every worker faced with the onslaught of technology and
the resulting prospect of delivering more output in fewer hours. With
artificial intelligence and related robotics, workers in industries
where demand is not accelerating – like cars – may very well have
something to worry about.
But the reality for librarians is
different. The demand for information services is accelerating so that
even in the face of greater productivity per person, employment
prospects shouldn’t diminish.
Indeed, if these library services
become real and gain traction, increasing demand for them and for the
librarians that make them possible will also increase because the
knowledge creates a demand for new knowledge. To use an ungainly and
somewhat distasteful analogy, it is like an arms race.
My concern
is neither about corporate competition nor unemployment. Rather my fear
is that the library profession will not easily abandon its self-imposed
limitations and will not expand its presence and champion new
technology for its services. If those limitations remain, the public –
having been forced to go elsewhere to meet their needs – will in the end
devalue and reduce their support for libraries.
Robots are also showing off their fun and increasingly creative side.
