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Category: Antitrust

Metadata by TLF: Issue 19

Posted on December 21, 2020December 20, 2020 by Tech Law Forum NALSAR

Welcome to our fortnightly newsletter, where our reporters Harsh Jain and Harshita Lilani put together handpicked stories from the world of tech law! You can find other issues here.

Facebook Oversight Board picks the first batch of cases for review, adds additional matter from India

Facebook’s Oversight Board (OSB), an independent body set up to review moderation decisions by the company, chose 6 cases to review in the first week of December, 2020 from over 20,000 cases that were referred to it following the opening of user appeals in October 20, 2018. Five of the cases being considered by the OSB were referred via user appeals while the sixth arose from a reference by Facebook. A couple of days after announcing the first batch of cases, the OSB added an additional case for consideration from India. It involves a photo posted on a Facebook group with Hindi text describing the drawing a sword from its scabbard in response to “infidels” criticizing the prophet. The photo also included a logo with the words “Indian Muslims” in English. The accompanying text, also in English, includes hashtags calling President Emmanuel Macron of France “the devil” and calling for the boycott of French products.

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Metadata by TLF: Issue 18

Posted on November 18, 2020November 17, 2020 by Tech Law Forum NALSAR

Welcome to our fortnightly newsletter, where our reporters Harsh Jain and Harshita Lilani put together handpicked stories from the world of tech law! You can find other issues here.

Streaming platforms and online news portals brought under the purview of the I&B Ministry

The Cabinet Secretariat issued a notification on November 11, 2020 granting the Ministry of Information and Broadcasting authority over streaming platforms and online news portals. Simply put, this means that platforms such as Netflix, Hotstar, Amazon Prime, etc. will now be under the jurisdiction of the I&B Ministry. While the I&B Ministry cannot regulate these platforms without specific laws being passed towards that end, the notification signals the intent of the government to bring out a regulatory code in the near future. Such a move was expected after Amit Khare, the Secretary of the I&B Ministry, expressed the Ministry’s intent to bring content streamed over OTT platforms under its purview. The online content sector, unlike radio, cinema and television, has till now remained free of censorship. In August 2020, more than a dozen OTT platforms operating in India such as Netflix, Zee5, Voot, Jio, SonyLiv, etc. had signed a self-regulation code aimed at empowering consumers with tools to assist them in making informed choice with regard to viewing decisions for them and their families but the I&B Ministry had refused to support the same.

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Metadata by TLF: Issue 17

Posted on August 19, 2020December 20, 2020 by Tech Law Forum @ NALSAR

Welcome to our fortnightly newsletter, where our reporters Kruttika Lokesh and Dhananjay Dhonchak put together handpicked stories from the world of tech law! You can find other issues here.

SC moves to dismiss PIL implicating Jio’s liability in RCom’s AGR dues

Jio was recently made a party in a matter regarding adjusted gross revenue (AGR case) between companies in India and the Department of the Telecommunications and other telecom companies in India. The issue was regarding investigation into whether telcos like RCom, Videocon and Aircel wanted to evade paying their dues to the DoT by filing for insolvency. The DoT had decided that Jio was to be made liable for the 31000 crore AGR dues that RCom owed to the Department, since Jio was using RCom’s airwaves as evidenced by a 2016 spectrum sharing agreement. Jio sought to prove that the spectrum was simply leased and that they didn’t have any exclusive use of the spectrum. They further argued that spectrum sharing agreements do not assume a sharing of liabilities for DoT’s AGR dues.

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Metadata by TLF: Issue 16

Posted on August 7, 2020December 20, 2020 by Tech Law Forum @ NALSAR

Welcome to our fortnightly newsletter, where our reporters Kruttika Lokesh and Dhananjay Dhonchak put together handpicked stories from the world of tech law! You can find other issues here.

Union Consumer Affairs Minster issues E-Commerce Rules to shift the focus onto consumer protection

In an increasingly globalised world, major retail companies like Amazon have reached even the most inaccessible places. The consumers that are exposed to e-commerce companies can only be protected in the presence of increased accountability. The newly issued E-Commerce Rules set up a Central Consumer Protection Authority to police companies that violate consumer rights. Misleading ads and unfair trade practices are prevented as e-retailers have to mandatorily disclose return, refund, warranty, exchange, guarantee, delivery and grievance redressal details. Henceforth, prices of products cannot be manipulated to produce unreasonable profits for companies. These rules apply to retailers either registered in India or abroad.

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Metadata by TLF: Issue 14

Posted on July 12, 2020December 20, 2020 by Tech Law Forum @ NALSAR

Welcome to our fortnightly newsletter, where our reporters Kruttika Lokesh and Dhananjay Dhonchak put together handpicked stories from the world of tech law! You can find other issues here.

India bans 59 Chinese Apps including Tik-Tok

The Ministry of Electronics and Information Technology announced in a press release on 29th June that it had invoked its powers under section 69A of the Information Technology Act to ban 59 Chinese applications. The Indian government cited ‘raging concerns on aspects relating to data security and safeguarding the privacy of 130 crore Indians’ as reasons behind the ban. The move comes after a border skirmish with China resulted in the deaths of 20 Indian soldiers. Regardless of the cybersecurity concerns cited in the press release, speculation remains rife over whether the ban was a retaliatory measure in light of the worsening geopolitical situation between India and China. India is a huge market for Chinese apps, particularly for the video-sharing platform Tik-Tok which had previously been banned in February 2019 for encouraging the spread of pornography and ‘cultural degradation’. The ban was ultimately lifted after assurances by Tik-Tok that it had the tools to censor explicit content. The current ban has been called a purely political decision and criticised for its procedural impropriety and its excessive restriction on dissemination of online content.

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Rethinking the Essential Facilities Doctrine In the Context of the Digital Economy

Posted on July 2, 2020November 1, 2020 by Tech Law Forum @ NALSAR

[This post has been authored by Sanchit Khandelwal, a third year student of NALSAR University of Law, Hyderabad.]

The ‘digital economy’ has witnessed remarkable growth and change in the last few decades and promises to continue to do so. Deepened penetration and wider access to the internet has further helped to alter the erstwhile relationship between customers and businesses. The exponential growth of computing power has enabled the upsurge of business models based on the collection and processing of ‘information/data’ exchanged between consumers and business firms.

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Metadata by TLF: Issue 13

Posted on July 1, 2020December 20, 2020 by Tech Law Forum @ NALSAR

Welcome to our fortnightly newsletter, where our reporters Kruttika Lokesh and Dhananjay Dhonchak put together handpicked stories from the world of tech law! You can find other issues here. [Ed Note: This newsletter has been prepared by Dhananjay Dhonchak and Sanchit Khandelwal]

Paytm approaches Delhi HC alleging lack of action by telecom companies against phishing

Paytm has knocked the doors of the Delhi High Court complaining that the telecom operators are not taking action against fraudsters carrying out phishing activities under Paytm’s name. The petitioner has claimed that its users are being duped using unsolicited commercial communications (UCC) in the form of SMS or voice calls made over telecom companies’ networks.

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Metadata by TLF: Issue 11

Posted on May 14, 2020December 20, 2020 by Tech Law Forum @ NALSAR

Welcome to our fortnightly newsletter, where our reporters Kruttika Lokesh and Dhananjay Dhonchak put together handpicked stories from the world of tech law! You can find other issues here.

Private firm blocked from buying “.org” domain

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Algorithms: Can They Collude?

Posted on November 19, 2019December 13, 2019 by Tech Law Forum @ NALSAR

This piece has been authored by Lokesh Vyas, a fourth year law student at Institute of Law, Nirma University, Ahmedabad. Here, he gives a lucid explanation of issues posed by the increasing use of algorithms. 

The Cloak of Algorithms

Unlike the traditional market, the digital economy does not have any geographical limits. Thus, there is fierce competition among all the players. However, due to the unequal availability of resources, it is becoming increasingly difficult for new aspirants to join the market. The use of pricing algorithms, presently adversely  affects the present landscape of online retail.

An algorithm is an established computational procedure that takes a set of values, as input and produces another set of values as output. A catena of algorithms is used in the market to create artificial transparency.[1] These algorithms are called pricing algorithms because competitors in the market use them to set prices after gauging market behavior and competitors. They help competitors to outlive others through optimum pricing. Such a scenario creates artificial algorithmic transparency in the market. However, with an increase in such algorithms in the market, it becomes easy to predict the change in the market. An increase in the accuracy of such predictions, not only strengthens the dominance of certain competitors but also eliminates small competitors altogether, hindering consumer welfare.

Unilateral decision making, the right to make intelligent decisions is a fundamental right of any business, since they aim at maximizing profit. The exercise of such a right effectuates conscious parallelism which is a legitimate and obvious factor in any market. However, the artificial transparency that continues to exist due to algorithms enables competitors to control the market.

Further, the increasing transparency in the market creates interdependency among the competitors, thereby incentivizing collusion. Algorithms create a god’s eye view, enabling competitors to monitor activities in the market in real time. Market players are less likely to deviate because of the instantaneous fear of retaliation.

Hence, the algorithms become a cloak to escape liabilities under competition law. Such tacit collusion has not been considered not barred by the law.

Challenges

The primary question is, does traditional competition law accommodate the recent trends in the market such as pricing algorithms and if so, how? The challenge before competition law authorities is to detect whether tacit collusion exists among competitors, and whether it negatively impacts consumer welfare.

Additionally, questions about communication and liability arise. The absence of explicit communication is a major issue when considering collusion, because in order to prove collusion, there must be an existence of communication. Algorithms have enabled companies to escape the necessity of explicit communication.

Another issue associated with such algorithms is that of liability, because there is no human intervention which facilitates such tacit collusion. Thus, it becomes difficult for authorities to ascertain the liability of the final wrongdoer. The three possible assertions with respect to liability are; the liability of the person who invents such algorithms; the liability of the person who deploys them; the liability of the person who gains from such algorithms.[2]

None of the above acts are explicitly prohibited by law unless a mala fide intention [intentional cartelization] to cause harm is proved. Competition law only outlaws bilateral or multilateral decision making by the competitors because it implies the existence of cartelization. By contrast, the adoption of pricing algorithms through undertakings merely enables them to attain dynamic pricing. The issue arises when competitors maximize their profit by colluding with each other, by entering into automatized virtual agreements. As per the current debate on algorithmic collusion, algorithms are used to facilitate an existing price agreement between the competitors. They simply act as intermediaries, as an extension of the human will. Alternatively, the algorithms are designed to result in a tacitly collusive result. Here, unilaterally designed algorithms learn to tacitly understand each other due to limited market characteristics. Presently, two scenarios emerge when considering algorithms that could cause collusion.

The first is the ‘messenger scenario’, since here algorithms acts as an instrument of collusion, including the implementation of agreed price adjustments as well as the monitoring of such agreements. An example of this is the US Department of Justice and UK Competition and Markets Authority’s proceedings regarding the distribution of posters through the Amazon Marketplace. Here, the companies involved initially agreed via e-mail that they would not underbid each other. After an attempt at the manual adjustment of prices had proved too complex, both companies used (different) repricing software. Pertinently, this software made it possible to monitor competitors’ prices and dynamically adjust one’s own prices according to those of competitors. The software was set so that the products were offered at the same price as long as no third (uninvolved) dealer with a lower price was active on the market.

In the second scenario, a collusive market comes about because the behavior of companies is canonically harmonized by using similar algorithms or by using algorithms which adapt to change in the others. Such agreements do not come under the general definition agreement, however there exists a tacit ‘meeting of mind’ among the competitors. Hence, the traditional definition of a contract under competition law needs to revisited in order to include such collusion. Notably, the definitions of an anti-competitive agreement under Section 3 of the Competition Act, 2002, Section 1 of the Sherman Antitrust Act, 1890, and Article 101 of the Treaty on the Functioning of the European Union do not cover mere ‘meeting of mind’ which exists due to such virtual agreements.

The use of algorithms in the market cannot be curbed altogether, since it would tremble the pillar of the digital economy. However, there is a need for regulatory policies to accommodate for the status quo. Pertinently, mutual price monitoring—the crux of tacit collusion which is not prohibited by Competition Law—must be addressed again.

The meaning of communication, a pre-requisite for constituting anti-competitive behavior also needs to be revisited to prevent ‘algorithm driven cartelization’. Pricing algorithms create a barrier for new entrants which in the long run affects market efficiency. Such a barrier is likely to impede the innovation in the market, which has direct nexus with consumer welfare.

Information Technology Act, 2000

There have been a lot of cases where e-commerce platforms and social media websites have been cleped as intermediaries, however, it is largely connected with the content uploading. Similarly, Section 2 of the recent Motor Vehicles (Amendment) Act, 2019 defined aggregators such as Uber and Ola as digital intermediaries or marketplaces which can be used by passengers to connect with  cabs. The question of intermediary liability primarily deals with content uploading or verification, and attracts the applicability of IP laws or other criminal laws.

However, the competition in the market is so fierce today, that independent firms like Feedvisor and Intelligence Node have started offering algorithmic pricing as a service. Here, the question arises whether such firms are intermediaries under section 2(w) of Information Technology Act, 2000 and do not attract liability (see Section 79 of the Act) because they are a link that collects the information of various competitors and compares them to produce the best results for a third party. Thus, the applicability of the safe harbor provision on algorithm deploying companies also needs to be considered, since they are aware about the effects and utilization of these algorithms.

  • Algo 1- Algorithm P
  • Algo 2- Algorithm P

[The above diagram demonstrates a scenario where a common algorithm (Algo P) is used by two different business entities(Firm A & Firm B).]

Conclusion and Suggestions

There have been four approaches to solving the above problems so far:-

  1. To broaden the interpretation of competition laws;
  2. To insert new provisions in the existing legislation;
  3. To use more rigorous alternative methods of dispute resolution; and
  4. To act in a way that parallel consciousness would not happen.

The underlying assumption of all the above approaches is that algorithms are inherently perilous to the market and pose threats to the fair competition in markets. The heart of the entire pricing algorithms debate revolves around the term ‘contract’ which needs to be revisited and interpreted. The term contract/agreement connotes ‘meeting of mind’ and the meeting of mind suggest the intention of the parties to agree on something. The most strenuous task before the competition law agencies is to ascertain such intention even when such explicit agreement is lacking.In order to curb the above challenges, the intervention can either be in the form of making big legal changes (e.g. Expanding the scope of major offenses like cartelization and abuse of dominant position) or to come up with small interventions (such putting a cap on the price change for more than a certain number of times in a day).

Therefore, competition law authorities can retaliate to such changes by bringing enforcement algorithms which can detect deviant or anomalous behavior in the market and thwart them timely.

[1] See Virtual Competition by Ariel Ezrachi and Maurice E. Stucke.

[2] See Virtual Competition by Ariel Ezrachi and Maurice E. Stucke.

Figure taken from here.

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‘Search Bias’ Under Indian Competition Law

Posted on August 6, 2019March 16, 2023 by Tech Law Forum @ NALSAR

The following post has been authored by Vishakha Singh Deshwal, an LLM candidate at the West Bengal National University of Juridical Studies (WBNUJS), Kolkata. Here she analyses an emerging issue at the intersection of technology and competition law.

 

Every enterprise wants its Uniform Resource Locator (URL) to appear among the top links on search engines because these links get the most clicks. Research reveals that the 10 highest-ranking generic search results on the first page together generally received approximately 95% of all clicks on generic search results.[1] While some enterprises pay huge advertisement costs to ensure that their links appear at the top (paid links), others resort to Search Engine Optimization (“SEO”) from a service like the SEO services in Provo
to acquire top spots among unpaid links. SEO may include regularly uploading quality content to the website, creating a user-friendly browsing experience, ensuring that the website is compatible with computers and hand-held devices, engaging in social media marketing, etc.

As a large part of the market has shifted to online platforms (e-commerce platforms), it becomes important to understand the interface between the working of Search Engines and Competition Law. This post seeks to explain the concept of “abuse of dominance” in the context of search engines. First things first, let us look at Google Search Shopping case to understand the relevance of Search Neutrality.

Until 2010, Google, which is the most used search engine, misused its dominant position to place certain links above others. In 2010, European Union’s Commissioner for Competition began investigating Google’s conduct and held it liable for abuse of dominance. In 2017, the biggest fine ever imposed by an antitrust regulator was slapped on Google (Google Search Shopping Decision). After this, Google corrected the bias advertised and sponsored links were distinctly marked and search order was based on relevance, popularity, design and so on.

Search Neutrality

The principle of Search Neutrality requires that search engines should have no editorial policies other than that their results be comprehensive, impartial and based solely on “relevance”. For instance, Google Search uses certain algorithms to rank web pages based on their relevance. For e.g., PageRank that works by counting the number and quality of links to a page to determine a rough estimate of how important the website is. Moreover, several updates (like Panda) are also used to improve the user experience by identifying and demoting low-quality sites that do not provide useful original content or otherwise add much value.

Search Bias

Any manipulation of the organic/natural order of the links in search results amounts to a search bias. Such bias is inbuilt in the very business model of the search engines. As per the founders of Google: “ . . . we expect that advertising funded search engines will be inherently biased towards the advertisers and away from the needs of the consumers”.[2] So, the pertinent question is – what is the basis of such bias?

Relevance as the basis of Bias

In the domain of search engines, neutrality does not mean equal treatment regardless of the content. As mentioned earlier, search engines try to push up more relevant and quality links for a better user experience. Therefore, some amount of bias is inherent. Relevance is used as the basis of refining search results; it is defined in the search engine, so that the results are subject to the user’s preferences and the user is satisfied.

For example, a search for “Flights from Delhi to Mumbai”, would show several links. Some would be advertisements and sponsored links, while others would be unpaid links of travel gateways like MakeMyTrip, Goibibo, etc. Additionally, some other links for travel blogs, news items, maps, etc. would show up . Here, the search engine uses various algorithms to ensure that the most relevant links appear at the top. However, as relevance is subjective, bias based on relevance is contentious. At times, search engines tweak the algorithm to place their own or associated links higher up in the order to limit or eliminate competition.

Search Bias and Abuse of Dominant Position under Competition Act, 2002

Search Bias may become anti-competitive when it violates Section 4 of Competition Act, 2002. Section 4(1) prohibits abuse of dominant position. The explanation to Section 4(2)(b) defines “dominant position” as a position of strength, enjoyed by an enterprise, in the relevant market, in India, which enables it to- (i) operate independently of competitive forces prevailing in the relevant market; or (ii) affect its competitors or consumers or the relevant market in its favor.

Further, clauses (c) and (e) of Section 4(2) prohibit practices resulting in denial of market access and use of dominant position in one relevant market to enter into or protect other relevant market. In case of search engines, the peculiar feature of the sector is that there are a few enterprises that enjoy a dominant position in relevant markets (e.g. Google, Amazon, etc.) and such position may be abused.

To understand the interface of these provisions with search bias, let’s take a look at the Competition Commission of India’s (“CCI”) ruling on Google (2018).

In 2012, two cases were filed against Google alleging contravention of Section 4 of the Act. It was alleged that while conducting the core business of search and advertising, Google had been manipulating the search results and favoring its own services and partners, such as Google Video, YouTube, Google Maps, etc. Pages in the search results did not appear solely according to their relevance, popularity, etc. It was further averred that Google is widely recognized as enjoying a dominant status in the search advertisement market because of its market share, size, resources, reputation etc. Therefore, its search bias amounts to abuse of its dominant position.

Decision

The CCI confirmed that Google is a dominant enterprise with respect to the relevant markets of Online General Web Search Services and Online Search Advertising in India based on factors such as size and resources, economic power and commercial advantages, entry barriers, etc.

The CCI held that Google violated Section 4 by extending and preserving its dominance through:

  • Wrong and unfair display of the search results prior to 2010 in pre-determined/fixed positions instead of ranking them in order of relevance.
  • Embedding only its specialized services in ‘more results’ link. Further, by abusing its dominance, Google did not merely limit market access of its competitors, but it also accessed large volumes of user data and thereby, indirectly deteriorated the ability of the competitors to further innovate on their products and sustain and survive in the market.

Approach

The decision did not deal with the question of effect-based versus form-based approaches to determine abuse of dominance. The dissent order indirectly referred to the latter approach as it emphasized the need for greater economic evidence and its implications for competition and consumers to consider an alleged conduct as abusive. The form-based approach is the traditional approach to look at the abuse of dominance where perfect competition is the goal. Whereas, the effect-based approach aims at weighing the pro-competitive and anti-competitive effects of a firm’s action keeping in mind special considerations for an industry, rather than simply protecting competition. It recognizes that firms continuously look for new opportunities to maximize their profits through innovation. For this, a firm may adopt strategies that enhance its market power or eliminate a competitor, however, its actions may result in more efficient processes and enhanced consumer welfare (E.g. Reliance Jio case).

Thus, the argument of improving quality of search results cannot be disregarded, as it ultimately benefits the users. However, we must not overlook the implications of bias e-commerce platforms such as Amazon, Grofers, Nykaa, etc. where products that are not necessarily better in quality appear high up in the search result to the disadvantage of third-party sellers. For instance, if products sold by Cloudtail (in which Amazon has a substantial stake) on Amazon appeared higher in the search result not on the basis of relevance but as part of the strategy to push Cloudtail’s products, that would be an anti-competitive practice. The provisions under Section 4 of Competition Act could be invoked in these cases as well.

Way Forward

CCI’s decision demonstrates the ability of the Indian law to deal with new forms of abuse. Further, the Competition Law jurisprudence is to evolve with changing times including the propounding of the effects-based approach by the CCI. However, the effect of Search bias is not just limited to the visibility of business enterprises, but it has an over-arching impact in shaping public opinion and even affecting political outcomes (e.g. Cambridge Analytica Case). Today, when more people have access to the internet than ever before, it is important that search engines ensure transparency in their bias. It will ensure that the rights of all stakeholders such as consumers, business enterprises and citizens in general are protected. Relevance as the basis has stood the test of time, but other markers like popularity, design, quality etc. used by search engines may also affect search neutrality. Therefore, there is a need for an informed debate over the most appropriate basis of bias that keeps a check on the abuse of dominance in the market as well as suppression of information in the society in general.

 

[1] https://www.epw.in/engage/article/should-google-search-engine-be

[2] The Anatomy of a Large-Scale Hypertextual Web Search Engine (1998)

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