Everybody is talking about Artificial Intelligence (AI) right
from Google, Facebook, Amazon
to small companies. There are many tech startups
trying to solve industry challenges through AI solutions. Most of these
companies are acquired by the big companies to scale up their AI capabilities
and use the solutions to solve their own challenges or innovate new products.
What is AI? In the simplest
terms, AI is the part of computing that gathers information from us, from the
online world, and importantly learns from the information collected. Most of
the AI solutions available in the market, study the data collected from our daily
information consumption and give us recommendations to suit our convenience.
Sounds simple but behind the scenes, there is a complicated algorithm that runs
and displays the desired results. This may sound familiar if you are using apps
like Siri, Ok Google and Netflix.
AI technology has been in
existence for quite some time. Amazon and other big retailers
have been using
AI to learn individual purchase history and recommend other products,
similarly, Netflix suggests videos and shows based on the individual’s past
viewing history.
So, we have been consuming AI technologies, we need to just
figure out how these use
cases can be used for the publishing industry.
AI and its technologies are hot
buzzwords today, everybody is talking about it without understanding the true
meaning and its power. Artificial Intelligence, Machine Learning, Natural
Language Processing are often interchangeably used. There are fundamental
differences between each and it is important to understand them before you plan
to work on them.
For all the publishers with
limited technology background, let the techies not take you for a ride, here
are a few basics for you to keep you engaged in the technical conversation.
Artificial Intelligence (AI) helps in building systems that can
do intelligent things.
Subset of AI are:
- Machine Learning (ML) helps in building systems that can learn from experience.
- Natural Language Processing (NLP) helps in building systems that can understand language.
- When NLP and ML are used together, it helps in building systems that can learn how to understand language.
Search
Most of the publishers have gone online with user focused digital platform. Many open search technologies like Solr, ElasticSearch, LucidWorks, OpenSearch and so on are already being used by the publishers. AI or to be more specific machine learning algorithms if used for search can help your end users get the right information within few seconds. The key would be to build machine learning algorithms that learn from user behavior and provide information in various formats including text, pdfs, images, videos and other digital assets.This is a sure shot winner to increase customer experience and to earn your brand loyalty.
Most of the publishers have gone online with user focused digital platform. Many open search technologies like Solr, ElasticSearch, LucidWorks, OpenSearch and so on are already being used by the publishers. AI or to be more specific machine learning algorithms if used for search can help your end users get the right information within few seconds. The key would be to build machine learning algorithms that learn from user behavior and provide information in various formats including text, pdfs, images, videos and other digital assets.This is a sure shot winner to increase customer experience and to earn your brand loyalty.
Smart
recommendations
Considering the same
use case from Netflix, AI can be used by publishers to recommend
articles,
research papers and other relevant resources to the user based on their search
or
past usage history. Combine this with semantics and the users can get
exactly what they
have been looking for.
Personalization
Machine Learning
algorithms can learn the behavioural patterns of the users and
personalize the
content to deliver the right message to the right audiences. For instance,
some
users may like the information in the form of graphs, numbers or visuals rather
than
long text, the algorithms can learn the user pattern and personalize their
content
consumption showcasing the desired format at the top.
Short reviews and
summaries
The attention span for
an individual has further reduced to 8 seconds. This is all we have to
grab the
user’s attention and make him stay longer on the website. Especially in the
case of
journals, chapters, research papers, academics or stories, a short
review or summaries
could help the user decide and stay longer. Using Natural
Language Processing (NLP),
coherent and accurate snippets of text could be
produced from longer pieces.
Customer Service
The AI chatbots, voice
search or AI assisted human agents are improving quality of the
customer
service. Be it a researcher, editor, librarian or a student, the enquiries
would differ
based on the user and other demographics. With the help of deep
learning ML and NLP,
algorithms can be developed to provide the right answers
in no time. Combine this with text
analysis and computational linguistics, you
can take a step forward with sentiment analysis
to decipher your user’s mood
and react accordingly.
Use of Social
Media
Leverage the power of
machine learning to optimize social media channels, identify the right
target
audience, personalise the content and timing for your post. Use NLP to
understand
and analyse the social behaviour and with the combination of both
the technologies,
manage your reputation before it gets out of hand.
Automate internal
processes
Publishing workflow
includes all teams – Publishers, Editors, Production, Legal, Developers,
and
Marketing. Each team has their own internal workflows and processes. Replacing
some
of the manual processes with automation can reduce time to market. For
example, an
algorithm to peer review the research papers, or conduct a
copyright test or do a reference
check can reduce the workload of the teams and
time taken to do the tedious manual job.
Security
Let’s not forget
security. Ransomware, Sci-hub and other hacking attempts are a result of
some
vulnerabilities that have been ignored on our digital platform. Machine
Learning
algorithms can focus on prediction and easily detect a known attack
learnt from earlier data.
There may be many more
AI uses cases publishers may be working on, but this is an easy
start. However,
just understanding AI its use cases are not going to move the boat forward.
You
need to build a proper infrastructure and a conducive environment to build AI
solutions.
You need the right skills, software technologies, hardware
technologies with a strong vision
to build AI solutions. It needs time,
patience, efforts and commitment to be a forerunner in
technology and ahead of
the competition.
Putting
these jigsaw pieces together, many companies are embracing AI technologies to
accelerate their digital journey. AI becomes meaningful and impactful when it
has access to
large amounts of high-quality data and is integrated into
automated work processes. AI is
not a shortcut to these digital foundations but
is a strong powerful extension of them.
A
platform that is inscribed with all the above mentioned attributes is PLAiTO –
Learning
Personalized.
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