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“Success in creating AI would be the biggest event in human
history. Unfortunately, it might also be the last, unless we learn
how to avoid the risks.” — Stephen Hawking1.

Billions of dollars are being raised and spent in developing new
products and services based on AI. Even though AI has started
impacting our lives e.g., through data analytics that can predict
our likes, dislikes, buying behaviour, etc, however the technology
is still in its infancy. Exciting products like driverless cars or
new ways of diagnosing and treating illnesses are being

In the midst of these revolutionary changes, some very senior
industry leaders have raised the issue of regulating AI. It is seen
as a technology with immense benefits and risks. Frequent
comparisons with nuclear energy and nukes brings out the
apprehensions. Fears have been expressed that AI guiding weapon
systems can be scary. Similarly, other ways of abusing the
technology will have disastrous consequences. However, there are no
proposals in the public domain about the regulatory agenda from the
developers of AI, especially the large tech companies.

Some players have articulated key principles to be kept in view
while designing AI systems, in a way, a type of a self-regulation.
Principles include fairness, transparency, inclusiveness,
reliability, safety, privacy, security, etc.

Can the Governments strike the right balance between their
roles of promoting and policing Artificial Intelligence

It is widely believed that adoption of digital technologies has
improved the standard and quality of life across the globe. Some
countries have reaped greater benefits by becoming home to some of
world’s most successful digital companies and also creating an
economic eco-system that positions them for further growth and
dominance. This is reflected in the recent paper on Artificial
Intelligence published by EU, where status of development in EU has
been compared with China and United States.

Some commentators have said that the internet’s growth has
come from it being open and free. This has incentivisied and
encouraged entrepreneurs and innovators to invest, take risks, and
develop products and services for consumers. One point of view is
that a good way of ensuring that AI grows is by not regulating

While the application and challenges from AI development are
global in nature, however the regulatory approaches taken by
countries vary.. As an example, EU took the lead in formulating and
enacting a detailed regulation on data usage and privacy in the
world. In contrast US is seen as a country that follows the
principle of light touch regulation.

Some countries are in the process of designing guidance
documents as general principles of governance. The other
alternative to this is to adopt a more ex post reactionary approach
and develop regulation on the go as responses to practical
interactions. The trade-off is between addressing the potential
harms vs possibly stifling development of these technologies.

The current debate of facial recognition software reflects the
dilemma. Money and time have been spent in developing and deploying
these technologies. However, there are concerns about the purpose
and safety of its usage. Some cities have banned the use of facial
recognition software.

The question is – What would make more sense from both a public
trust and a business predictability point of view ?.

Attribution of Liability

The challenges imposed by machines and robots are to a large
extent the same as those by humans, for which regulatory frameworks
are already in place. As an example, under consumer protection laws
manufacturers, distributors, suppliers and retailers are held
responsible for any harm that the products may cause. In some
jurisdictions, manufacturers may be liable for damage (death,
personal injury or damage caused to private property) in case a
product or any of its component parts are found to be defective.
Possibly, some of the existing laws and regulations on liability
could be used with or without suitable modifications to mitigate
any apprehensions/ risks from the implementation of AI.

Under consumer protection laws, one of the circumstances under
which the manufacturers are often not held liable are when the
defect did not exist at the time of the product being put under
circulation. Related to that is the issue as to whether the defect
is to do with the way a product was designed or the way it has been

This raises the issue of attribution of liability in case of a
harm by an AI system. This ideally should be the same as what would
be expected of a human being. e.g. a driver causes an accident, he
will be liable for this. In the same manner, a driverless car
causing an accident should also attribute liability for accidents
that were unforeseeable. The additional issues here would be:

distribution of this liability amidst: the developer of
technology, the owner of the car and any third party user/

affording a legal personality status to machines and robots
akin to human beings in the law

Legal personality for AI applications

Unpredictability of AI applications is probably perceived as the
biggest challenge in regulating AI. It stems from the
unpredictability of automation. It is possible that AI application
takes decisions or leads to outcomes that are outside the purview
of the design or the instruction of the operator of the

Therefore a question that has been raised is whether some types
of AI application have a legal personality that is distinct from
its creator or operator. Such a principle has been used in creating
companies that own assets and take liabilities distinct from its
owners, managers and employees. This structure has facilitated
greater economic risk taking and thereby higher levels of economic

However, it may be kept in view that in case a company indulges
in criminal conduct, then often its employees and directors are
held accountable for that. Even if AI were to have an independent
legal personality, some of the liabilities especially on account of
criminal action would need to travel back to human beings involved
in its design and deployment. There is a slight distinction that
exists here as well because where companies are fictitiously
independent, AI may be fully autonomous. Closely linked to this is
the ability of AI to enforce contractual relationships. Existing
contract laws and IT laws would have to be brought up to speed here
to incorporate such type of contracts. Then there are issues like
nationality to be given to a robot, if a distinct legal personality
were to be defined. Sophia, the Saudi Arabian humanoid comes to
mind here. As of the time of writing this paper, there are no
serious proposals on the table on providing a distinct legal
identity to AI applications In the alternative, it may be possible
to navigate existing consumer protection, contracts, and IT laws to
arrive at best possible solutions for AI functions.

Promoting AI

The recent paper on AI by EU argues that data would be the raw
material for development and operation of AI applications.
Asymmetry in current access and title to data to all potential
developers of AI has been identified as a key issue. This is in a
way a competition issue and the question is whether significant
barriers to entry exist for developing some of the applications and
how this would be overcome. Comments to the same effect have been
made in the draft E-commerce policy published by the Indian

Similarly, there are issues around IP rights for various
algorithms that are developed and how the stance of regulators
while considering IP applications impact the ability of small
players to develop applications and scale up. Again such issues
could be potentially addressed through IP laws in how they would
apply to patenting of algorithms, grant inventorship and address
relevant issues

To conclude this discussion, it seems that an AI regulatory
agenda need not warrant re-inventing the regulatory wheel. Instead,
it should incorporate two elements:

the same gamut of regulations that would apply to a human being
performing the same or a similar function. Some modifications may
be made to current legislations or proposals at an advanced stage,
so that AI can be addressed through them.

additional regulations that would address and manage the risks
posed by AI that are inherently unique to such systems and
distinguish them from the rest.

Rajnish Gupta – Associate Partner, Tax and Economic
Policy, Ernst & Young, India.Natasha Nayak – Senior Manager, Tax and Economic Policy,
Ernst & Young, India.



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