Examination’ contain specific advice
about how AI and ML-related patent
applications should be assessed by
the EPO. This guidance has introduced
greater clarity and will make it easier
for innovators and their IP advisors
to secure the commercial protection
required when preparing to bring
inventions to market.
In the past, a lack of certainty
surrounding the EPO’s approach to
the examination of AI and ML-related
applications may have discouraged
some innovators from seeking patent
protection.
Based on the new guidance
however, it is now clear that as long
as innovators can demonstrate that
their invention provides a technical
solution to a technical problem, it will
be assessed and examined in the
same way as other inventions. This
means that the valuable commercial
protection that accompanies a granted
patent is within their grasp.
One of the areas where the
guidance has brought greater clarity
is the description of how an AI or
ML-related invention might make
a technical contribution. They can
achieve this either through their
end use or by demonstrating that
the underlying technology makes a
technical contribution in its own right.
The guidance takes the example of
a neural network, which might qualify
for patent protection when used to
operate a heart-monitoring device
RESEARCH & DEVELOPMENT IP
capable of detecting an irregular
heartbeat as this use demonstrates
a technical contribution. Alternatively,
a neural network could also achieve
patent protection without reference
to any real-world application, as long
as its architecture is considered
inventive and solves a technical
problem.
Whilst the increased clarity
surrounding the EPO’s approach to
assessment will certainly help, the
success or failure of individual patent
applications in this field of R&D is
likely to be determined by the way in
which they have been drafted. For this
reason, innovators should continue
to take care to provide detailed
evidence of their invention’s technical
contribution. A good test to apply
to every patent application is ‘is it
inventive?’ Or in other words, ‘is this
more than a routine development of
the sector?’ Ultimately, the decision
to grant the patent or not will rest on
its ability to answer this question.
When preparing a patent
application for a new algorithm for
example, it is important to describe
it in sufficient detail, so that a skilled
person could implement it based
on the information provided in the
patent specification and standard
sector knowledge otherwise known
as ‘common general knowledge’.
Meeting this ‘sufficiency’ test is
obviously more challenging when
talking about algorithms and
computational methods and it is
important for the innovator to invest
time in ensuring their patent attorney
fully understands the technology at
the outset.
Innovators should also consider
the best approach to securing
commercial protection. A granted
patent automatically gives them a 20-
year period of exclusivity in which to
leverage their invention to the full and
build up a market for their product.
Other strategies are sometimes
considered e.g. keeping the invention
a trade secret. However, it is
important that innovators understand
the commercial risks they are taking.
A ‘trade secret’ is not an
enforceable right in the same way
as a patent, as no monopoly is
provided, and a business would
not be able to sue a competitor for
infringement if the invention leaked
to the marketplace. It is also entirely
possible that a competitor develops
the same invention at the same time
and if they apply for patent protection
first, this could block your route to
market altogether.
In summary, there is a tremendous
opportunity for innovators operating
in the field of machine learning and
the full potential of these inventions
is only just being realised. With the
right intellectual property strategy and
commercial understanding, innovators
can secure a stake in this rapidly
evolving marketplace.
Harry Strange
Author details:
Karl Barnfather
and Harry Strange
are attorneys
at European
intellectual
property firm,
Withers & Rogers
www.newelectronics.co.uk 14 January 2020 31
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