Challenges of AI in IP & ICT law policy making

Problems and issues to address in this article are as follows-:

Problem / Issue 1 -:

How is AI defined?

For example -: “AI inventions”, AI-generated invention”, “AI-assisted invention”, AI application”) for

the purpose of this questionnaire. A common understanding of these key terms is necessary.

Otherwise, member states will not be sufficiently clear. It might be useful to refer to definitions

that have already been agreed in the context of standardization work. (As there is no standardization of AI and its interpretation as such with any technical and legal accreditation done yet by any organisation).

Problem 2 -:

Patents -: Inventorship and ownership.

Another problem is based on the assumption that “it would now seem clear that inventions can

be autonomously generated by AI”. This premise needs to be clarified and supported, especially

given that the possibility of AI solving problems autonomously was recently considered to be “a

science fiction”. Without a sound understanding of how AI can produce inventions

autonomously and in what way AI-generated inventions differ from AI-assisted inventions (when

humans use AI as a tool to invent), it appears difficult to assess the relevance of questions

regarding inventorship and patent ownership.

Problem 3-:

Inventive Step or Non-Obviousness

When considering the inventive step of inventions containing AI technologies, is there any specific things which should be taken into account? For example, does an invention of mere a systemization of manually-operated tasks using AI involve inventive step?

Problem 4 -:

Patentable Subject Matter and Patentability Guidelines

Computer-assisted inventions and their treatment under patent laws have been the

subject of lengthy discussions in many countries around the world. In the case of AI-generated

or -assisted inventions:

(i) Should the law exclude from patent eligibility inventions that are autonomously

generated by an AI application?

(ii) Should specific provisions be introduced for inventions assisted by AI or should such

inventions be treated in the same way as other computer-assisted inventions?

Problem -: 5

General Policy Considerations for the Patent System

A fundamental objective of the patent system is to encourage the investment of human

and financial resources and the taking of risk in generating inventions that may contribute

positively to the welfare of society. As such, the patent system is a fundamental component of

innovation policy more generally. Does the advent of inventions autonomously generated by AI

applications call for a re-assessment of the relevance of the patent incentive to AI-generated

inventions.

Specifically,

(i) Should consideration be given to a sui generis system of IP rights for AI-generated

inventions in order to adjust innovation incentives for AI?

(ii) Is it too early to consider these questions because the impact of AI on both science

and technology is still unfolding at a rapid rate and there is, at this stage, insufficient

understanding of that impact or of what policy measures, if any, might be appropriate in

the circumstances?

Problem -: 6

COPYRIGHT

Authorship and Ownership

AI applications are capable of producing literary and artistic works autonomously. This

capacity raises major policy questions for the copyright system, which has always been

intimately associated with the human creative spirit and with respect and reward for, and the

encouragement of, the expression of human creativity. The policy positions adopted in relation

to the attribution of copyright to AI-generated works will go to the heart of the social purpose for

which the copyright system exists. If AI-generated works were excluded from eligibility for

copyright protection, the copyright system would be seen as an instrument for encouraging and

favoring the dignity of human creativity over machine creativity. If copyright protection were

accorded to AI-generated works, the copyright system would tend to be seen as an instrument

favoring the availability for the consumer of the largest number of creative works and of placing

an equal value on human and machine creativity.

Specifically,

I. Should copyright be attributed to original literary and artistic works that are

autonomously generated by AI or should a human creator be required?

II. In the event copyright can be attributed to AI-generated works, in whom should the

copyright vest?

III. Should consideration be given to according a legal personality to an AI

application where it creates original works autonomously, so that the copyright would

vest in the personality and the personality could be governed and sold in a manner

similar to a corporation?

Most of the art generated today by AI is based on some previous art work ( Machine learning ) ,

if e.g. AI has created a new Spanish song sung by an English famous artist by using her voice

the credit should also go to the artist whose voice was used.

Due to these reasons - should a separate sui generis system of protection (for example, one

offering a reduced term of protection and other limitations, or one treating AI-generated works

as performances) been visaged for original literary and artistic works autonomously generated

by AI ?

Problem 7-:

Problems in respect to DATA

General Policy Issues

AI is all about data and as data is still easily available to big companies i.e. Google, FB ,MS etc.,

Public institutions must play a role to make data accessible to SMEs and small organizations to

exploit this advanced technology which is much more accessible to these Big players currently.

Further Rights in Relation to Data

whatever is done, it must be sure that data is still available for the development of AI technology

equally without giving unfair advantage to any group. Data should not be free for those who

accumulate it, nor should it be seen as capital.

Data Privacy /Data Protection/ Purpose Limitation

When regulating or non-regulating data, the issues of personal data protection must be taken into account. In this respect, the General Data Protection Regulation GDPR has now set new standards at EU level. With the broad definition of personal data in the GDPR, a distinction between non personal and personal data is problematic. Quite often private users are producers” of the data raw material, especially with their connected devices. Data analytics can de-anonymize previously anonymized personal data.

Problem 8-:

TECHNOLOGY GAP AND CAPACITY BUILDING

The number of countries with expertise and capacity in AI is limited. At the same time, the

technology of AI is advancing at a rapid pace, creating the risk of the existing technology gap being

exacerbated, rather than reduced, with time. In addition, while capacity is confined to a limited

number of countries, the effects of the deployment of AI are not, and will not be, limited only to the

countries that possess capacity in AI.

Problem 9-:

ACCOUNTABILITY FOR IP ADMINISTRATIVE DECISIONS

Accountability for Decisions in IP Administration

It is important to only use AI algorithms in decision making process which could explain the

decision they reached at i.e. which factors contributed to the decision taken by the machine. Also

IPOs should make sure we do not have any data bias in our training data which could discriminate

based on sex, gender, race etc.

Innovative elements (original aspects of the work)

First of all, to take this contrast approach is itself a very unique idea and its very crucial

intersection of law and technology to consider where AI intersects IP & ICT policies and vice

versa.

On the other hand to take the approach of (How these all policies impact on AI & its Technology

applications, development and research in future)

So, this contrast and approach is very innovative itself and I will take all possible aspects with

broader and deeper understanding of its impacts on each other.

Original aspects of work will be-:

1) All present policies and its relations with emerging technologies and balancing of it.

2) Determine the intersection points and defining there standards.

3) To take both approaches with Digital single market, Data economy and comparison

studies of different countries .

4) Determining and defining the scope by considering past cases and future projections.


- By Sahil Tharia


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