© Andrea Danti thinkstock |
Artificial intelligence and machine learning tools are making significant inroads into publishing processes and product development.
Those of us who may be short on time and haven’t been
able to get to that autobiography we’ve been meaning to write need worry no
longer: Artillect Publishing will do the
work for you by scanning your online presence, merging some ancillary
information and producing your sure-to-be best-selling biography. Using artificial intelligence in its production
process, Artillect is just one example of the increasing number of applications
of artificial intelligence (AI) replacing inefficient processes, creating new
products and adding insight to publishing.
News organizations including the Washington
Post and Associated
Press have been using artificial intelligence tools to create news reports
for weather, sports and financial reporting where interpretation of the day’s
(or game’s) activity can be fairly straightforward. As these uses have grown in acceptance and
utility, the use of AI to deliver more complex products is also growing. AI tools can analyze text, images and data
and deliver to a journalist sufficiently structured content around which they
can build articles and stories. AI tools
can do this faster, more comprehensively and with greater accuracy than
traditional research methods. In
analyzing text or images, AI tools can characterize the content: Positive/negative,
liberal/conservative, for example.
Journalists have even used this capability to change editorial content
to match specific political viewpoints, creating liberal, center and/or conservative
versions of the same article.
The accuracy (or veracity) of news content generally
sparks emotions and Knowwhere
is applying AI and ML to the detection of ‘fakenews’. Their process aggregates stories from more
than a thousand different sources of varying political persuasions to create a
“knowledge graph” or database of each news story which is then reviewed by
(human) editors. Mediashift
recently reported that USAToday uses AI to create visual and interactive
content, which they refer to as ‘dynamic editorial’ and hope will improve
attention and raise reader engagement.
Journalism is by no means the only focus for AI and many companies
across the media landscape are using and experimenting with AI tools. In the last few days, for example, journal
publisher Taylor & Francis (T&F) announced two partnerships with AI
companies to add AI tools to their editorial processes. In the first of these, T&F are working
with Katalyst
Technologies to create “contextual copyediting” using AI and natural
language processing to assess and score the language quality of articles
accepted into their journal’s workflow.
This use of AI is designed to make their editorial process more
efficient by identifying and classifying journal submissions. In the second example, the company announced
they are working
with UNSILO which will help T&F subscribers optimize the use of T&F
content by surfacing additional, highly relevant content based on what they are
already reading. T&F expects that
this function will enable users to discover new and pertinent research.
Next month, at the Society of Scholarly
Publishers (SSP) meeting in Chicago, I am hosting a panel discussion on how
publishers are using AI and machine learning (ML) to rethink how they manage
their businesses. On the panel, I will
have executives from Storyfit, Yewno, Unsilo and Molecular Connections. In advance of that meeting, I thought it
would be interesting to explore some of the companies offering their versions
of AI to publishers:
StoryFit: Uses machine learning and data
analysis to predict content marketability, improve discovery and drive sales
for publishers and movie studios.
Yewno: Uses
machine-learning and computational linguistics analyze high-quality content to
extract concepts and discern patterns and relationships to make large volumes
of information more effective.
UNSILO: Provides artificial intelligence tools and solutions for publishers to
grow new business opportunities and improve existing customer experiences and
workflows.
Bibblio: A recommender system that helps content businesses
and publishers deliver more relevant, engaging discovery experiences to their
users.
Iris.ai: Helps researchers build precise
reading lists of research documents across three parameters: Key information extraction (marking
of possible contextually disambiguating information, forming basis for a
document fingerprint); Neural Topic Modeling (clustering
of semantically similar documents, cluster labeling, document fingerprint
update); WISDM (basis for document
fingerprint indexing. Fingerprints are matched using the WISDM document
similarity metric.)
ECHOBOX: Helps
content owners automate their social media presence and “is the best social
media platform for publishers.” Their
solution is the “first artificial intelligence that increases your reach.”
Copyleaks: Detects plagiarized content in scholarly
workflows.
StatReviewer: Uses ML to
generate statistical and methodological reviews for scientific manuscripts to
discern the integrity for scientific manuscripts. Product is currently in private beta.
Webbitz: An
AI-powered video creation platform that leverages patented text-to-video
technology to streamline production of original short-form videos across
multiple platforms. The company works
with more than 400 publishers.
Ross Intelligence:
Using a combination of IBM Watson and proprietary algorithms, ROSS is the
AI-driven successor to tools like LexisNexis and supports both legal discovery
and legal research findings.
ScriptBook: Employs artificial intelligence to analyze
screenplays. The Script2Screen-solution
delivers an objective assessment of a script's commercial and critical success. The company believes their AI-driven process
delivers both objective and fair results.
It treats every screenplay equally with no bias.
Arkadium: An AI product company which has been used by Sports
Illustrated to create infographics.
There is little doubt that AI and ML applications and
tools are here to stay within publishing workflows. But it’s also true that we are only at the
beginning of what will be a fundamental shift in workforce management,
application and roles. The prevailing
concern is that machines will take all the jobs and leave humans with nothing
left to do. Not only is this excessive
hyperbole, the impact of technology on work activities over the last 200 years
points more towards a shift in the role of human work rather than the total replacement
of workers. When ATMs were first rolled
out more than 30 years ago, there was an expectation that brick and mortar
banks and their tellers would disappear.
In fact, the opposite occurred and teller employment increased as banks
focused on building closer customer relationships.
AI will improve publisher workflows but will also help expand the utility and benefits of the products we are producing for customers. Many of the newspapers mentioned above have been able to materially broaden their reporting in a way which would not have been possible without the type of functionality that AI offers. Expect to see many more examples of this technology within the publishing business more broadly.
AI will improve publisher workflows but will also help expand the utility and benefits of the products we are producing for customers. Many of the newspapers mentioned above have been able to materially broaden their reporting in a way which would not have been possible without the type of functionality that AI offers. Expect to see many more examples of this technology within the publishing business more broadly.
No comments:
Post a Comment