ACCC takes aim at colluding robots

The ACCC has established an analytics unit to help protect consumers from e-collusion using big data analytics.

The new unit has been deployed in a number of market studies the agency has undertaken and will support the work of its investigation teams and economists, ACCC Chairman Rod Sims said at an address in Sydney yesterday.

While the information revolution and the rise of big data analytics has vast potential to foster data-driven innovation driving many economic advantages, they also bring a range of potential competition issues.

“The ACCC is considering cases where algorithms are deployed as a tool to facilitate conduct which may contravene Australian competition law,” Sims said.

“Within our organisation, we are building the expertise to analyse algorithms [with the new data analytics unit]. And to stay abreast of developments, we are engaging with other competition authorities and practitioners about these issues.”

Through its work the ACCC has identified a number of areas where competition issues may arise, with the most obvious being the market power of online platforms.

In a real-world example, the ACCC last year compelled online travel agents Expedia and Booking.com to remove contractual requirements restricting Australian accommodation providers from offering better rates or different inventories to other online agents or offline channels.

In addition, the regulator plans in future merger reviews to carefully consider acquisitions where both parties are involved in collecting and selling big data to ensure they do not, for example, prevent rivals from acquiring unique data that is essential for them to compete or enter the market.

Another thorny area is the question of whether data-driven innovation increases the risk of collusion, Sims said. While there is a fine line between parallel conduct and collusion, there have already been cases, including at least one investigated by the ACCC, involving retailers having near real-time access to price changes by competitors, reducing competition between the retailers.

“Concern has been raised by some that the way prices are determined, and potentially collusive outcomes are achieved, is changed by machine learning algorithms,” he said.

“It is argued that, in the right market conditions, pricing algorithms may be used to more effectively engage in and sustain collusion, whether ‘tacit’ or not, reducing competition but without contravening competition laws ... To further complicate matters, the development of deep learning and artificial intelligence may mean that companies will not necessarily know how, or why, a machine came to a particular conclusion.”

Sims said the debate over the potential impact of big data analytics on collusion is still taking place, but noted that “in Australia, we take the view that you cannot avoid liability by saying ‘my robot did it’ ... At this stage, the ACCC has not seen any anti-competitive algorithms which require an enforcement response beyond what is now available to the ACCC under Australian law.”

He said the Harper competition reforms introducing provisions further prohibiting misuse of market power are “fit for purpose to prohibit this conduct ... if robots are colluding, this provision will help us stop it”.

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