Adam Smith introduced the theory of ‘invisible hand’ meaning, ‘free market economy left to their own devices will produce results more beneficial than can be realized by intervening in the markets’.

Globally, the key focus of competition law and policy is to encourage and sustain fair, free competition by regulating the process of competition and prohibiting anti-competitive behavior, such as abuse of dominant position, cartels, price fixing, collusion, unfair trade practices etc. Competition policy strives to achieve ‘level-playing field’ and aims to remove ‘entry barriers’ for all players, which will help markets to be competitive. Fair and effective competition in turn will promote economic growth and development, greater innovation, operational efficiency, better quality of products and services at lower prices and overall consumer welfare. As such, competition is a central driver for productivity and growth in the economy.

In the last few decades, rightly termed as fourth industrial revolution, technology has and still keeps evolving at an incredible speed and continues to disrupt conventional markets and competitive practices. The exponential growth of digital landscape - online marketplace platforms, e-Commerce companies and search engines are taking the competition online from conventional brick and mortar industries.

While, the competition landscape is shifting to a more dynamic and complex digital environment, which is controlled by algorithms, the following questions arise–

1.Does technology encourage competition or facilitate monopoly?
2.Are the existing competition law and policies, still hold good and relevant in regulating digital markets?
3.How effective are the regulations where the competition is driven not by humans but by bots?

AI & Big Data
Big data, algorithms, and artificial intelligence are not inherently good or bad but largely depends on how the use.

Data as such has no intrinsic value, however through intelligent analysis of large chunk of data using AI, which helps in solving complex problems with accurate answers, drive innovation, improve productivity and efficiency, data can be turned into a goldmine. Big data is termed as fuel of the future. This data advantage has tilted competition significantly in favor of online market players as opposed to traditional organisations.

According to International Telecommunication Union, (ITU) more than 50 percent of the world population is using internet. Digital landscape has transformed the way people communicate socilaise, work, shop, trade, travel, invest, spend, access information and read news. This super connectivity has made us feel the world is truly our oyster! The online content and pricing is customized to suit user preference.

Constant tracking of user behavior online accurately and processing the data by engaging AI powered bots and intelligent algorithms, search engines, e-Commerce and marketplace organisations makes this kind of highly personalised user experience possible. Using big data

analytics, organisations are able to profile individual users precisely and deliver a customised content including products, services as well as dynamic pricing.

It’s true that big data analytics has benefited immensely certain fields such as medical research, access to quality health care, improved treatments etc. When it comes to commercial purpose, big data gives an edge to some organisations in the digital space to target millions of people with customized advertisements, dynamic pricing for products and services giving them undue advantage over their brick and mortar rivals.

Algorithmic collusion & pricing bots
Traditionally, competition law regimes viewed any form of cartel, collusion of organisations to fix prices, agreement not to compete against one another, exclusive agreements, territorial restrictions or any such monopolistic practices, as anti-competitive, and penalized, such organisations for engaging in such practices. However if this kind of collusion happens not between humans but between AI powered algorithms, which decide pricing without human intervention, which are programed to avoid competition or price war automatically, will it be treated as anti-competitive by antitrust authorities? Algorithms can be programed to track the behavior of numerous rivals and anticipate and react to competitive threats, avoid price war and tacitly collude.

Fair and effective competition in turn will promote economic growth and development, greater innovation, operational efficiency, better quality of products and services at lower prices and overall consumer welfare

Potentially, these autonomous pricing algorithms may without human intervention, and without explicit human command, independently discover that to make the highest possible profit, there should be no price war. The algorithms may learn to tacitly collude even if they have not been specifically instructed to do so and even if they do not communicate with one another. With no express illegal agreement, no anti-competitive agreement, no explicit cartel or price fixing, and no human interference, it may be difficult to prosecute and fix liability in such cases.

Antitrust Enforcement Challenges
At present, while explicit collusions is illegal, tacit collusion falls outside the purview of competition law. EU and other major competition law regulations do not cover this kind of tacit collusion. This could potentially create an enforcement gap. Algorithm driven marketplace, search engine are exempt from many legal and regulatory compliance requirements. Therefore, antitrust regulators are faced with the following challenge in fixing responsibility and taking enforcement actions-

Is this even a competition law problem?
How to ensure fair competition in a digital market where there is tacit collusion of algorithms?
If the bots and algorithms decide pricing and constantly change it depending on user profile, is competitive pricing an illusion?
Can antitrust liability be established when business decisions are made by machines rather than by human beings?

Similar to ‘lifting corporate veil’, the antitrust regulators should be able to bring the programmer(s) who designed such algorithms to support tacit collusion or the organisations that use that algorithms and make them accountable for distortion of competition.