5 Important Artificial Intelligence Predictions (For 2019) Everyone Should Read

5 Important AI Predictions
(For 2019)
Everyone Should Read

© 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
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IntroductionIntroduction
Artificial Intelligence – specifically machine learning and deep learning – was
everywhere in 2018 and don’t expect the hype to die down over the next 12
months.
The hype will die eventually of course, and AI will become another consistent
thread in the tapestry of our lives, just like the internet, electricity, and combustion
did in days of yore.
5 Important AI Predictions (For 2019)

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But for at least the next year, and probably longer, expect astonishing
breakthroughs as well as continued excitement and hyperbole from
commentators.
This is because expectations of the changes to business and society which AI
promises (or in some cases threatens) to bring about go beyond anything
dreamed up during previous technological revolutions.
5 Important AI Predictions For 2019

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AI points towards a future where machines not only do all of the physical work, as
they have done since the industrial revolution, but also the “thinking” work –
planning, strategizing and making decisions.
The jury’s still out on whether this will lead to a glorious utopia, with humans free
to spend their lives following more meaningful pursuits, rather than on those
which economic necessity dictates they dedicate their time, or to widespread
unemployment and social unrest.

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We probably won’t arrive at either of those outcomes in 2019, but it’s a topic
which will continue to be hotly debated.
In the meantime, here are five things that we can expect to happen:

AI Increasingly Becomes A Matter Of
International Politics
2018 has seen major world powers increasingly putting up fences to protect
their national interests when it comes to trade and defence. Nowhere has this
been more apparent than in the relationship between the world's two AI
superpowers, the US and China.
In the face of tariffs and export restrictions on goods and services used to
create AI imposed by the US Government, China has stepped up its efforts to
become self-reliant when it comes to research and development.

Chinese tech manufacturer Huawei announced plans to develop its own AI
processing chips, reducing the need for the country’s booming AI industry to
rely on US manufacturers like Intel and Nvidia.
At the same time, Google has faced public criticism for its apparent
willingness to do business with Chinese tech companies (many with links to
the Chinese government) while withdrawing (after pressure from its
employees) from arrangements to work with US government agencies due to
concerns its tech may be militarised.

With nationalist politics enjoying a resurgence, there are two apparent
dangers here.
Firstly, that artificial intelligence technology could be increasingly adopted by
authoritarian regimes to restrict freedoms, such as the rights to privacy or
free speech.
Secondly, that these tensions could compromise the spirit of cooperation
between academic and industrial organizations across the world.

This framework of open collaboration has been instrumental to the rapid
development and deployment of AI technology we see taking place today
and putting up borders around a nation’s AI development is likely to slow
that progress.
In particular, it is expected to slow the development of common standards
around AI and data, which could greatly increase the usefulness of AI.

A Move Towards “Transparent AI”
The adoption of AI across wider society – particularly when it involves dealing
with human data – is hindered by the "black box problem." Mostly, its
workings seem arcane and unfathomable without a thorough understanding
of what it's actually doing.
To achieve its full potential AI needs to be trusted – we need to know what it
is doing with our data, why, and how it makes its decisions when it comes to
issues that affect our lives. This is often difficult to convey – particularly as
what makes AI particularly useful is its ability to draw connections and make
inferences which may not be obvious or may even seem counter-intuitive to
us.

But building trust in AI systems isn’t just about reassuring the public.
Research and business will also benefit from openness which exposes bias in
data or algorithms. Reports have even found that companies are sometimes
holding back from deploying AI due to fears they may face liabilities in the
future if current technology is later judged to be unfair or unethical.
In 2019 we're likely to see an increased emphasis on measures designed to
increase the transparency of AI. This year IBM unveiled technology developed
to improve the traceability of decisions into its AI OpenScale technology.

This concept gives real-time insights into not only what decisions are being
made, but how they are being made, drawing connections between data that
is used, decision weighting and potential for bias in information.
The General Data Protection Regulation, put into action across Europe this
year, gives citizens some protection against decisions which have “legal or
other significant” impact on their lives made solely by machines. While it isn’t
yet a blisteringly hot political potato, its prominence in public discourse is
likely to grow during 2019, further encouraging businesses to work towards
transparency.

AI And Automation Drilling Deeper
Into Every Business
In 2018, companies began to get a firmer grip on the realities of what AI can
and can’t do. After spending the previous few years getting their data in
order and identifying areas where AI could bring quick rewards, or fail fast,
big business is as a whole ready to move ahead with proven initiatives,
moving from piloting and soft-launching to global deployment.
In financial services, vast real-time logs of thousands of transactions per
second are routinely parsed by machine learning algorithms.

Into Every Business
Retailers are proficient at grabbing data through till receipts and loyalty
programmes and feeding it into AI engines to work out how to get better at
selling us things. Manufacturers use predictive technology to know precisely
what stresses machinery can be put under and when it is likely to break down
or fail.
In 2019 we’ll see growing confidence that this smart, predictive technology,
bolstered by learnings it has picked up in its initial deployments, can be
rolled out wholesale across all of a business’s operations.

Into Every Business
AI will branch out into support functions such as HR or optimizing supply
chains, where decisions around logistics, as well as hiring and firing, will
become increasingly informed by automation. AI solutions for managing
compliance and legal issues are also likely to be increasingly adopted.
As these tools will often be fit-for-purpose across a number of organizations,
they will increasingly be offered as-a-service, offering smaller businesses a
bite of the AI cherry, too.

Into Every Business
We’re also likely to see an increase in businesses using their data to generate
new revenue streams. Building up big databases of transactions and
customer activity within its industry essentially lets any sufficiently data-savvy
business begin to “Googlify” itself.
Becoming a source of data-as-a-service has been transformational for
businesses such as John Deere, which offers analytics based on agricultural
data to help farmers grow crops more efficiently.
In 2019 more companies will adopt this strategy as they come to understand
the value of the information they own.

More Jobs Will Be Created By AI
Than Will Be Lost To It
As I mentioned in my introduction to this post, in the long-term its uncertain
if the rise of the machines will lead to human unemployment and social strife,
a utopian workless future, or (probably more realistically) something in
between.
For the next year, at least, though, it seems it isn’t going to be immediately
problematic in this regard. Gartner predicts that by the end of 2019, AI will be
creating more jobs than it is taking.

While 1.8 million jobs will be lost to automation – with manufacturing in
particular singled out as likely to take a hit – 2.3 million will be created. In
particular, Gartner's report finds, these could be focused on education,
healthcare, and the public sector.
A likely driver for this disparity is the emphasis placed on rolling out AI in an
"augmenting" capacity when it comes to deploying it in non-manual jobs.
Warehouse workers and retail cashiers have often been replaced wholesale
by automated technology.

But when it comes to doctors and lawyers, AI service providers have made
concerted effort to present their technology as something which can work
alongside human professionals, assisting them with repetitive tasks while
leaving the "final say" to them.
This means those industries benefit from the growth in human jobs on the
technical side – those needed to deploy the technology and train the
workforce on using it – while retaining the professionals who carry out the
actual work.

For the financial services, the outlook is perhaps slightly grimmer. Some
estimates, such as those made by former Citigroup CEO Vikram Pandit in
2017, predict that the sector's human workforce could be 30% smaller within
five years.
With back-office functions increasingly being managed by machines, we
could be well on our way to seeing that come true by the end of next year.

AI Assistants Will Become
Truly Useful
AI is genuinely interwoven into our lives now, to the point that most people
don't give a second thought to the fact that when they search Google, shop
at Amazon or watch Netflix, highly precise, AI-driven predictions are at work
to make the experience flow.
A slightly more apparent sense of engagement with robotic intelligence
comes about when we interact with AI assistants – Siri, Alexa, or Google
Assistant, for example – to help us make sense of the myriad of data sources
available to us in the modern world.

Truly Useful
In 2019, more of us than ever will use an AI assistant to arrange our
calendars, plan our journeys and order a pizza. These services will become
increasingly useful as they learn to anticipate our behaviors better and
understand our habits.
Data gathered from users allows application designers to understand exactly
which features are providing value, and which are underused, perhaps
consuming valuable resources (through bandwidth or reporting) which could
be better used elsewhere.

Truly Useful
As a result, functions which we do want to use AI for – such as ordering taxis
and food deliveries, and choosing restaurants to visit – are becoming
increasingly streamlined and accessible.
On top of this, AI assistants are designed to become increasingly efficient at
understanding their human users, as the natural language algorithms used to
encode speech into computer-readable data, and vice versa, is exposed to
more and more information about how we communicate.

Truly Useful
It's evident that conversations between Alexa or Google Assistant and us can
seem very stilted today. However, the rapid acceleration of understanding in
this field means that, by the end of 2019, we will be getting used to far more
natural and flowing discourse with the machines we share our lives with.

© 2017 Bernard Marr , Bernard Marr & Co. All rights reserved
Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website
© 2017 Bernard Marr , Bernard Marr & Co. All rights reserved
Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website

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5 Important Artificial Intelligence Predictions (For 2019) Everyone Should Read

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