India is witnessing a paradigm shift into the

India is witnessing a paradigm shift
into the digital age. In the recent years we have witnessed an increase in the
number and usage of search engines, social media platforms, app stores, etc.
which has led to the creation of data-driven markets. Data-driven markets are
the virtual markets created via these electronic platforms who are aiding our
day-to-day lives by serving to our needs in a less chaotic manner. But the
question arises whether these data-driven markets are actually aiding us or are
they manipulating our needs to fulfill their master’s agenda of profit
maximization at the cost of providing free and fair market to the consumers.

These data-driven markets raise many
legal, moral and ethical issues, such as cyber-security threat, risks to our
personal data and information saved voluntarily and involuntarily,
accountability of the companies for their algorithmic actions, anti-competitive
practices by the owners of these virtual platforms and their allied sellers.

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This article aims at bringing out the implications of
data-driven markets with respect to the Competition Laws, what challenges are
before the competition regulatory bodies for providing free and fair markets
and how they can initiate a mechanism to achieve maximum consumer benefit from
these markets without any risks and exploitation.

I.        
Concept
of free and fair market- The Invisible Hand Theory

One of the essential features of any
market economy of a democratic nation governed by the Competition Laws is the
presence of a free and fair market. The Competition Laws of India struggle to
provide a market structure which is fair and equal, there is no illegal bar on
entry of new players in the market, and each is given an equal opportunity to grow.
Goods and services are being sold at a fair market value. The concept of fair
market value is derived from the Invisible Hand Theory.

Invisible Hand Theory (IHT) was
introduced by Adam Smith in his book- ‘An inquiry into the nature and causes of
The Wealth of Nations’, 1776. It is the unobservable market force which helps
the demand and supply of goods in a free market to reach equilibrium
automatically. IHT is characterized by a situation where there is minimal
intervention of government in a free market, and the forces of nature along
with the forces of demand and supply work together in achieving a fair market
value of goods and services. The underlying idea is that individual goal’s of growth
and profit maximization results in growth of the society as a whole1.

But the question arises whether the
IHT still holds good in the present market condition. The answer to it is in
negative. No, the basic concept behind IHT has been lost as the invisible hand has
been replaced by the digital hand.2 What is being observed in
the present economy is that the pre-existing invisible-hand has been replaced
by these online portal regulators who have through their algorithm mechanism
and online databases have formed an invisible hand guiding the process of price
fixation of the product being sold online and thereby exploiting the consumer. Where
IHT aimed at least government interferences so that the natural forces of
market can achieve a fair market and fair market value on their own, the
present scenario is that these digital forces- will and whims of the online
portal owners are distorting the concept of fair market and offering a price
which is far away from the fair market value or the general market price, by
accessing to anti-competitive means of practice. Now, the individual benefit of
these platform owners is serving their profits and growth only, consumers who
should reign the market are being exploited3. Therefore an urgent need
has been felt for the Government to step into and curb out these
anti-competitive practices from the digital market so as to provide a fair
market to the consumers. Our present Competition Laws are inadequate in the
sense that they are able to monitor the anti-competitive practices as long as
they are on the line of price-based competition only. The Indian Competition Act
aims to provide a free and fair market by condemning the acts such as price discrimination,
collusion and cartel formation, abuse of dominant position, predatory pricing, etc.
But this was sufficient when market was limited to brick-and-mortar setup, now
the markets have evolved; concept of virtual marketing is prevailing where these
anti-competitive practices are taking places in the virtual media and our
present Competition Laws lack the mechanism to track the acts such as working
of data-driven algorithms, behavioral discrimination and non-price based discrimination.

The recent example of Price-Fixing
Scheme of Amazon’s marketplace seller is vital for understanding how the
consumers are being fooled by these online platforms through these data
analytics and algorithms. David Topkins, an online poster retailer was the first
e-commerce executive to be prosecuted by the US anti-trust Law. He was charged
with committing the crime of price-fixing, which violates the Sherman Act of
USA. He was charged for fixing the prices of certain posters being sold online
at Amazon, by colluding with other sellers from September 2013-January 2014.
Topkins pleaded guilty of devising an algorithm, which he coded to instruct his
company’s software to set prices of the posters being sold and paid a fine of
twenty thousand dollars for the same4.

Henceforth, let us understand how
these big databases, algorithms and the artificial intelligence are posing a
probable threat to consumers by resorting to anti-competitive practices such as
price discrimination-price fixing and collusion by forming cartels, behavioral
discrimination, frenemy activities to exploit the customers, vertical
integration to remove competition, etc and what mechanism are available with
the competition laws of different countries besides India, and how the Indian
laws should be modified so as to attain the natural market equilibrium in this
data-driven economy of virtual markets.

II.        
Probable
threats of the Digital Market

Digital market or the data-driven
market though is easing our day-to-day lives but is also posing threats such as
tacit-collusion, price-based cartels, price-discrimination, etc5. Let us examine the
negative factors of the data-driven economy under the following heads-

A.    Price
Discrimination

Differential pricing, or what
economists call “price discrimination,” is the practice of charging customers
different prices for the same product6.

These data-driven markets are
responsible for this anti-competitive act of price discrimination on the
following grounds-

1.      Price Discrimination on the basis of consumer
behavior.

Behavior based discrimination is a
situation where the consumers are being discriminated in terms of price and
market on the basis of their social behavior at these online portals. Behavior
refers to the response consumers portray online.

‘For example, when an Internet user
visits a web site, the owner of the site may place a file called “cookie7” onto the user’s computer,
enabling the site to keep track of information about the user’s interactions
with the site. Over time, cookies can be used to build a long-term picture of
an individual’s Internet browsing history, and that information can be shared
across sites’8.
Besides this, acts such as ‘creating an account’ online or while availing
‘loyalty programs’ consumers not only provide their personal information but
also gives consent to the sellers to track their purchases. Act such as
‘steering9’ also aids in getting to
know the response of a single consumer or a class of consumer towards the
specific product.

Therefore by availing to such
practices as mentioned above, online portals are measuring consumer’s digital
footprint and using their artificial intelligence in form algorithms to exploit
customers.

When these online portals have a
track record of consumer’s behavior towards products they tailor the prices
accordingly. Prices are fixed on the basis of the strategy which involves firms
harvesting our personal data to identify which emotion (or bias) will prompt us
to buy a product, and what’s the most we are willing to pay.  Here
sellers track us and collect data about us in order to tailor their advertising
and marketing to target us at critical moments with the right price and
emotional pitch’10.

Often seller’s are involved in
practice of fooling the consumer, by offering discounts and schemes on their
preferred products, but hidden in those discounts and schemes are the extra
price that the consumer agrees to pay and eventually ends up paying more for
that product than the market price11. These schemes and
discounts are created on the basis of behavioral data of consumers saved with
these platforms, which focuses on giving discounts and schemes in such a way
that the consumer is attracted and compelled to take it.

2.    
Price Discrimination by Tacit-Collusion
and Cartel Formation

As stated by Ariel Ezrachi and Maurice E.
Stucke in their Research Paper12 on-
‘Artificial Intelligence & Collusion: When Computers Inhibit Competition’
there are four13
non-exclusive categories of collusion- the ‘Messenger’,
‘Hub and Spoke’, ‘Predictable Agent’ and ‘Autonomous Machine’.

Let us elaborate each one of them
and their legal implications-

a)     Messenger

To simply state, this practice of
collusion is also known as ‘Computer as a Messenger’, here the computer acts as
a messenger to carry out the instructions of humans or their master’s. Humans
are the masters who map out the cartel, by entering into agreements with others
and the computer algorithms serve as the messenger by carrying out the
instructions of their master’s.

Illustration: ‘in a classic cartel
agreement, executives from rival firms secretly agree to fix prices, allocate
markets or bids, or reduce output14. Here, the executives,
after colluding in secrecy, leave it to their computer algorithms to monitor
and enforce the agreement’15.

Therefore, we may say that this is
the simplest form of collusion observed vis-à-vis algorithms and data
analytics.

Legal Scenario-

In order to track these kinds of
collusive anti-competitive practices, the Regulatory bodies need to focus on
the presence of such ‘anti-competitive agreements’ or ‘illicit agreements’
besides establishing the ‘intent’ or ‘concurrence of wills’ of the humans16. It is important to be
noted that if the computer fails to effectuate the agreement, there is no
effect on the illegality of the agreement. Once the object or intent to distort
the market, has been established in in the agreement, the regulatory bodies can
head against these parties to the agreement in violation of the competition laws.

Presence of a stronger evidence of
anticompetitive agreement will require a lesser intent based evidence for the
purpose of establishing that there was a ‘concurrence of wills’, however
evidence of intent plays a significant role in establishing the crime as intent
merits more detailed considerations. ‘Lower U.S. courts have held that when the
challenged activity is per se illegal under the antitrust laws, the government
in criminal cases need only prove the existence of an agreement and that the
defendant knowingly entered into the alleged agreement or conspiracy17. Defendants’ altruistic
motives are legally irrelevant when the conduct is per se illegal’18.

In 2015, the US Department of
Justice initiated legal proceedings in two cases where restrictive agreements
were implemented and monitored by way of an algorithm. In Topkins case19, a former employee of an
online art retailer was prosecuted for conspiring with competitors to fix the
prices of certain posters sold through Amazon Marketplace. In Aston case20, the US Department of
Justice filed an indictment against a director and his company for a similar
offence. In both cases, a traditional ‘meeting of the minds’ took place whereby
the representatives of the companies involved discussed prices and agreed to
adopt specific pricing algorithms in order to coordinate price changes. Since
the algorithms were merely used to execute a pre-existing agreement among
competitors, there was no difficulty to establish liability under traditional
competition law concepts21.

Therefore in this ‘Messenger’
category the computer acts as the implementation device of their master’s will
by providing a platform. Challenges faced include ascertaining the proof of
presence of an agreement and establishing the intent to collude.

b)     Hub and
Spoke

Under this, a single algorithm is
devised and used in such a way that it will record the market price charged by
various customers. A Single vertical agreement formed may not be an
anti-competitive practice of distorting the market, unless there are multiple
such agreements amongst the competitors made by the developer of that algorithm
which results in increased prices of products. The developer acts as a hub
using the algorithm, and spokes are the multiple vertical agreements formed
with multiple competitors22. The common algorithm
which traders use as a vertical input leads to horizontal collusion.

Illustration: Possible
anticompetitive effect from hub and spoke collusion practice can be explained
by the pricing algorithm of Uber, which is used to determine contract prices
for taxi services23. ‘That algorithm has been
referred to as ‘algorithmic monopoly’ as it is controlled by Uber and may mimic
a perceived competitive price rather than the true market price24. As more drivers use
Uber’s algorithm, one may wonder what its effect on price may be. Reported
instances in which the algorithm has pushed the price up raise challenging
questions as to the possible manipulation via the algorithm of the perceived
market price. With a growing number of users and providers, the alternative
universe created by the algorithm may provide an opportunity for exploitation
and coordinated price increases25.

Legal Scenario-

In order to track these kinds of
collusive anti-competitive practices, the Regulatory bodies need to focus on
the presence of vertical agreements where the algorithmic based relationship is
formed between the developer of algorithm and the seller, along with the
horizontal agreements between sellers of similar product to use the same
algorithm and the object behind both horizontal and vertical agreements. It is
pertinent to mention that a single vertical agreement between the algorithm
developer and user is not anticompetitive unless there are such multiple
agreements entered into by multiple sellers creating a parallel use of same
algorithm for fixing the prices.

From the perspective of Enforcement
Agencies, this practice is challenging as it requires deviling into the heart
of the algorithm to establish whether it is designed in such a way that would or
may lead to exploitation. Besides getting into the details of algorithms, the
Regulatory bodies are also required to check the intent behind both the
vertical-staged agreements and horizontal-staged agreements.

In evaluating collaboration among competitors,
where the effect of agreements is ambiguous, regulatory bodies must focus on
the ‘intent-based’ evidence which may aid in evaluating the market power, the
likelihood of anticompetitive harm, etc26. ‘Thus in determining
antitrust liability, courts will consider the firms’ intent in using the
algorithms, i.e., whether they (i) intended a clearly illegal result, such as
agreeing to fix prices or (ii) acted with knowledge that illegal results, which
actually occurred, were ‘probable.’27

‘…..different in the context of the complaint28 that
a customer of Uber filed in January 2016 in a US District Court against the
company’s CEO. The complaint alleges that Uber’s vertical agreements with each
individual driver give rise to horizontal coordination due to parallel use of
the same algorithm. In practice, drivers do not compete on price but charge the
fares set by the Uber algorithm. On this ground, Uber is argued to constitute a
so-called ‘hub and spoke’ cartel whereby competitors, in this case the independent
drivers (the spokes), collude with each other through a third party, namely
Uber (the hub). The key issue for determining whether the Uber platform gives
rise to price fixing under EU competition law would be the existence of an
anticompetitive object or of anticompetitive effects. To answer this question,
courts or competition authorities may be required to analyse the working of
Uber’s algorithm to see if it indeed facilitates anticompetitive collusion
among drivers.’29

Therefore, this form of collusion
also raises a question on the effects of vertical agreements formed by and
between the developers of algorithm and the sellers.

Henceforth, the ‘Hub and Spoke’
category involves use of a vertical input to facilitate horizontal collusion.
Challenges faced include technical decoding of the algorithm and documentary
evidence to support the intent. Also, if the crime of collusion is absent then
effects of such network on price, usage and quality of products being offered
should be considered.

c)     Predictable
Agent

‘The use of a Predictable Agent
reflects a scenario where each firm unilaterally uses the computer as part of a
more subtle strategy to enhance market transparency and predict behavior.30’

Humans unilaterally design their
machines through algorithms and data analysis to deliver predictable outcomes
and also set a specific reaction for the changes in market conditions. Each
operator develops its machine unilaterally, with the knowledge of fact of
likely developments of other machines used by its competitors. The
industry-wide adoption of similar algorithms may lead to anti-competitive
effect through the creation of interdependent action. Since, there is absence
of any agreement, the market starts exhibiting conditions for tacit collusion/
conscious parallelism. A tacit collusion is not itself illegal, proof of
‘intent’ to change market dynamics is central in this scenario31, by doing so the markets
are brought closer to the situation of creation tacit collusion/ conscious
parallelism which leads to higher prices.

One may also conclude that since algorithms
can now quickly monitor competitor’s prices and adjust their own prices
accordingly there is an increase in price transparency which instead of
profiting the consumers has ironically end up harming them (increase in
prices). This increase in price is not the result of express collusion but of
the tacit collusion which is not itself illegal32.

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