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IP Issues in the Era of Artificial Intelligence
Prof. Joseph Straus, Munich
3rd EU China IP Academic Forum
Shanghai, November 22, 2018

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Points to Consider
? The Fourth Industrial Revolution
? Artificial Intelligence (AI) – Evolutionary Technology
? Investments in AI Technologies
? AI "Products"
? AI – Challenges for standard patent law concepts
? Lessons to Learn

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Navigating the Next Industrial Revolution
Source: World Economic Forum

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The Fourth Industrial Revolution
? The advent of cyber-physical systems – involving entirely new capabilities
for people and machines
[N. Davis, WEF, ]
? The marriage of physical and advanced digital technologies, such as
– analytics, artificial intelligence, cloud computing and the internet of
things
[Forbes Insights with Deloitte]

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Artificial Intelligence (AI)
? "The science and engineering of making intelligent machines"
[John McCarthy, 1955]
? A machine's adaptation of cognitive functions that are associated with the
human mind – such as understanding of language, problem solving, and
learning
[https://www.techpats.com/artificial-intelligence-potential-implications-patents/]
? In the sense of patent law: Mathematical algorithms allowing computers to
simulate intelligent human behavior
European Patent Office

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Artificial Narrow Intelligence (ANI)
? Specialized in a specific area – e.g. IBM's Deep Blue? Super Computer (Chess), or
China's Tianhe-II – 34 quadrillion calculations per second!
? Can solve complex problems extremely fast – but have no perception of things
other than the information provided to them by the creators
? Examples: Intelligent thermometers (Nest?), Apple's "Sirr"?, video games, search
engines, etc.
? Cannot imitate thought process outside the scope of their pre-determined operation
? Efforts on the way on creating an AI processing information with software based on
human physical, biological and chemical thought process; electronic neural
networks, cognitive computing algorithm and artificial neo-cortex through software.
[Gurkaynak, Yilmaz, Haksever, 2016]

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Artificial General Intelligence (AGI)
? Represents "Human-level AIs", computers as smart as humans – in every
aspect and capable of performing all intellectual tasks humans can
? Performing tasks involving complex calculations requiring substantial effort,
time dedication for humans – very simple for AIs
? AI by now succeeded in doing essentially everything that requires "thinking" but
has failed to do most of what people and animals do "without thinking"
? May be reached around 2030

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Artificial Super Intelligence (ASI)
? Represents AIs "much smarter than the best human brains in practically
every field, including scientific creativity, general wisdom and social skills"
? It is expected that AGI once established it will evolve itself into an ASI very
quickly – as a result of an exponential growth (phenomenon of
"intelligence explosion" or "singularity)
? ASI major forms: speed super intelligence, collective super intelligence
and quality super intelligence – anyone of the three capable of creating the
other two

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Artificial Intelligence Explosion
Hutson, Science 18 May 2008

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Some Technical Foundation of AI
? Tools that can process vast amounts of data, detect and interpret
patterns – previously impossible to calculate, identify or even imagine
? They enable machine prediction, diagnoses, modeling and risk analysis
? AI – an essential element enabling effective use of large data volumes –
not manageable manually – and algorithms no longer efficiently
reprogrammed by hand

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Machine Learning – An Important AI Tool
? A method of data analysis that automates analytical model building
? Uses algorithms that iteratively learn from data
? Allows computer to find hidden insights without being explicitly
programmed where to look
? Google's "AlphaGo" – masters Go – "Deep learning is killing every
problem in AI"
[J. Schaefer, 2016]

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Investments in AI Technologies
? China – US $ 2.1 billion on an AI industrial park
? EU - € 1.5 billion to AI research through 2020
? France - € 1.5 billion to AI research through 2022
? US Government – hesitant to engage

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Q4 2017 TOP 10 Deals of VC Investments Split
Between China and US in AI

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Comparison United States - China
[Data: Astamuse; Linkedin; Mckinsey Global Institute]
United States China
Years experience of the
nation’s data scientists
More than half have more than
10 years.
Forty percent have less
than 5 years.
AI patent applications,
2010–2014
15,317 (First in world) 8410 (Second)
Number of workers in AI
positions
850,000 (First) 50,000 (Seventh)
Percent of private AI
investment (2016)
66% (First) 17% (Second)

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Comparison United States - China
? "For traditional scientific fields, Chinese [scientists] have a long way
to go to compete with the U.S. or Europe. But for computer science,
it's a relatively new thing. Young people can compete. Chinese can
compete."
? "China played no role in launching the AI revolution, but is making
breathtaking progress catching up."
[Eric Lander, President of the Broad Institute in Cambridge, Mass.]

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AI-Powered Drug Discovery Captures Pharma Interest
Source: Nature Biotechnology, Vol. 35, No. 7, July 2017

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Machine Learning Classifies Cancer
Source: Nature, 22 March 2018
Tumour classification using a machine-
learning approach. Capper et al.1 used a
machine-learning approach to classify brain
tumours on the basis of genome-wide
patterns of a type of DNA alteration called
methylation. The computer was trained using
methylation data for tumour samples that had
been diagnosed by pathologists using
standard microscopy-based analysis or
analysis of selected genes. After training, the
computer was given 1,104 test cases. The
authors compared the diagnoses made by the
computer and by the pathologists. Although
the machine was unable to diagnose all
specimens, of the specimens that it classified,
the machine-based diagnosis was more
accurate or could assign tumours to more-
specific subcategories than the classifications
made by the pathologists.

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AI Designs Organic Synthesis
- A System in Which an AI Program Learns the Rules for Itself -
Source: Nature, 29 March 2018
Retrosynthetic Analysis

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Multibillion Investments in AI & Resulting Products and Processes
- Require Efficient Patent Protection –
Patent Eligible
? EPO, JPO, SIPO & USPTO – by and large – apply same standards as for
"traditional" computer implemented inventions
? Patents available for inventions where computer programs [i.e. algorithm-
related inventions] make a technical contribution, e.g. in the fields of:
? medical devices; the automotive sector; industrial control;
communication/media technology; automated natural language
translation; voice recognition and video compression;
computers/processes itself

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US Patent No. US 8,126,832 B2 of February 28, 2012 for
"Artificial Intelligence System" of Cognitive Code Corp.
"The present invention extracts concepts from text and/or speech and
utilizes numeric representations of concepts and their relationships. The
extraction of concepts allows expression in various patterns to be
understood by the system. The processes allow the system to bypass
human language constraints in order to think in concepts. The present
system may also dynamically construct output so that it can generate
intelligent responses in a number of grammatically correct ways. Because
the system utilizes numeric representations of concepts and their
relationships, the system is language independent and may even function
with a plurality of languages."

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AI-Related Patent Publications

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China is Catching Up With the US in AI

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Number
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Development of Families with Applications in AI
Source: EPO

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US-AI Patent Champions
? IBM: 2012-2017 – 5.600 AI patents (in 2017 more than 1.400)
? IBM's Watson - a cloud based AI product – provides Application Program
Interfaces (APIs) that can understand all forms of data to reveal business
critical insights "harnessing" the power of cognitive computing –
organized into various products for building cognitive search
? Google: 2012-2017 - ~ 4.500 AI patents
? Google's neural machine translation system developed its own internal
language to represent the concepts it uses to translate other languages

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AI Challenges of Traditional Patent Law Concepts
? Currently applied approaches overlook/ignore [?] that AI technology itself
creates its own technology & applications, i.e. inventions – solutions of
technical problems with technical means
? This requires, inter alia, new assessments of:
– the notion "invention" [identifying a problem, then solved by AI?]
– [non]patentability of mathematical algorithms – the "self-evolving"
core of AI
– who is the inventor – can a legal person be an inventor?
– the notion of the “person” skilled in the art – decisive for assessing
inventive step

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Challenges for the IP System Digital Inventor?
Source: Siemens AG 2018

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Deep Dream Image Example
Works of Art?

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Inventorship in the context of AI
? Does the inventor have to be a natural person?
? Although not explicitly mentioned in EPC, the inventor can only be a
natural person according to the current legal interpretation (Articles 60,
62 and 81 EPC)
The inventor is the one who is the author of the claimed invention, i.e.
who has recognised the idea of the invention and has developed it into a
technical instruction in creative activity. Only a human being is capable
of a creative activity in this sense. (Benkard EP?, 2. edition, Article 60,
points 9-10)
Source: EPO

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Inventions generated by AI
? In the context of machine inventions, various levels of human
participations are possible
? Although the technical solution can be developed to a large extent by a
machine, the human being is currently not completely eliminated from
the process
? The human being triggering the process of inventing through creative
ideas and/or combining the results delivered by a machine remains the
inventor
Source: EPO

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Could AI be designated as inventor?
? Current situation
– if the applicant designates AI (e.g. a computer) as the inventor, the
requirements of Article 81 and Rule 19 EPC are not met
– if no valid designation of the inventor is filed, the application will be
refused (Article 90(5) EPC)
Source: EPO

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Designation of AI as inventor
? Should inventions be generated solely by AI, it could become necessary
to clarify whether AI could be considered as the inventor
? The role of the inventor and the interpretation of the term inventor would
have to be adapted
? Also the right to a patent in the sense of Article 60(1) EPC would have to
be clarified by the legislator
Source: EPO

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Effect of AI on the skilled person
? If the use of particular creative software becomes common in a certain
field of technology, it may be presumed that the skilled person would use
such software
? Inventions involving AI or machine learning may therefore raise the skills
and knowledge of the skilled person
? This would have an impact on the afore-mentioned requirements of
disclosure and inventive step
Source: EPO

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The UK/Irish Copyright Solution – A Viable Model?
? The copyright in "works generated by a computer in circumstances such
that there is no human author"
? Vested in "the person by whom the arrangement necessary for the
creation of the work are undertaken"
[Copyright, Designs and Patents Act, 1988, c48, § 178 (UK)
Copyright and Related Rights Act, 2000, part 5, § 2 Art. No. 28/2000 (IV)]
? Computer-generated works – not the works of an AI
? Is "non-human" copyright ownership possible? If so – to whom it should
belong?

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Lessons to Learn
? Over centuries the IP-system – by adapting itself to ever evolving challenges of
technological and scientific developments – also those of the 1st, 2nd and 3rd
industrial revolution – have served the public's well-being well
? The IP-system should develop further – to meet the needs of the 4th industrial
revolution in general and that of AI specifically – internationally harmonized &
rational & consistent approach necessary!!
? Those challenges may/will have an entirely new quality – thereby the evolving
AI technology will help humans in solving problems beyond known paradigms

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Thank you
for your attention!
谢谢大家听我的发言！

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