Wednesday, March 22, 2017
Tuesday, March 21, 2017
Monday, March 20, 2017
Friday, March 17, 2017
Thursday, March 16, 2017
Algorithms and competition
M. Vestager, here.
"It's true that the idea of automated systems getting together and reaching a meeting of minds is still science fiction (emphasis added)". This excruciatingly reminds me that it has been rather long since I've been back from a refreshing break and that I've still a couple of posts pending...
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Wednesday, March 15, 2017
The Implications of Brexit for Uk Competition Law: Practical Issues and Priorities
The City of London Law Society, here.
Tuesday, March 14, 2017
Monday, March 13, 2017
Sunday, March 12, 2017
Saturday, March 11, 2017
Friday, March 10, 2017
Thursday, March 09, 2017
CJEU: no right to be forgotten in respect of personal data in the companies register
Judgment in Case C-398/15, Press Release here.
Wednesday, March 08, 2017
Crossed Lines: Why the AT&T-Time Warner Merger Demands a New Approach to Antitrust
Roosevelt Institute, here.
Tuesday, March 07, 2017
Age of Algorithms: Data, Democracy and the News
Kavli Conversation, Video here (from 07:12).
('Outrage is the new porn'; 'everyone wants to hand off the responsability for extremely difficult decisions'; apps disentangling algorithms as transparency).
('Outrage is the new porn'; 'everyone wants to hand off the responsability for extremely difficult decisions'; apps disentangling algorithms as transparency).
Monday, March 06, 2017
Tuesday, February 21, 2017
Monday, February 20, 2017
How antitrust enforcement can spur innovation: Bell Labs and the 1956 Consent Decree
M. Watzinger, T. Fackler, M. Nagler, M. Schnitzer, here.
Friday, February 17, 2017
Thursday, February 16, 2017
Wednesday, February 15, 2017
Why Incentives for 'Patent Holdout' Threaten to Dismantle FRAND, and Why it Matters
R. Epstein, K. Noroozi, here.
The Digital Privacy Paradox: Small Money, Small Costs, Small Talk
S. Athey, C. Catalini, C. Tucker, here.
Tuesday, February 14, 2017
When Competition Policy Meets Science Fiction (Part 2)
(Part 1 here)
Further discussions in London focused on a second constellation, characterized
as “Hub and Spoke”, in which competitors do not predetermine the
pricing rules themselves but outsource this function to a third party. The main
differences between this and the “Messenger Scenario” (as described above with reference to the UK poster case) are that
the parties here a) use the same
automated repricing tool and b) the computer programme calculates prices based
on its own blueprint and not directly executing the rules set by the human sellers.
As noted by some of the conference speakers and thoroughly discussed in the book Virtual Competition, the use by competing sellers of automated repricing capabilities
offered by a single provider can lead to some measure of de facto price
alignment. This result is potentially worrisome and competition enforcers
should be prepared to address it in a suitable way. This shouldn’t be too difficult
where the dampening of price competition produced by the automated repricing tool
is intentional on the side of the competitors, meaning that it is the original
reason why they have chosen the same algorithmic tool, or that they are at least
aware that the technology as concretely employed has or could have this effect.
In this case, the automated repricing software jointly employed by the sellers
could be seen as the hub (or "brain") that facilitates collusion by controlling the wheel's spokes.
Also amidst the gales of technological change, therefore, the notion of awareness is likely to remain central to the assessment of collusive behaviour, as recently stressed by the CJEU in Eturas, where the Court applied Art. 101(1) TFEU to an online travel booking system used by 30 travel agencies in Lithuania. The administrator of the booking system posted a notice in the system mailboxes informing the agencies of a technical (and automatic) restriction on the discount rates they could offer their own clients. The first preliminary question addressed to the CJEU by the referral national court asked whether the simple proof of the system notice allows the presumption that the “economic operators were aware, or ought to have been aware, of the system notice introduced into the computerised information system”. According to the CJEU, it is up to national law to decide if proof that a message has been sent to the booking system’s mailboxes is sufficient to prove that the addressees were aware, or ought to have been aware, of its content. The presumption of innocence however precludes the referring court from deducing the undertaking's awareness of the message content from the mere dispatch of the message in the booking system. Instead, a presumption of awareness may be based on ‘other objective and consistent indicia’ that the undertaking tacitly assented to an anticompetitive action (for instance, in this case there had been prior communication between the system administrator and the travel agencies regarding a possible capping of discount rates). If awareness of the content of the message can be demonstrated, the acquiescence in that initiative may be inferred unless the undertaking opposes to it (e.g., by reporting the initiative to the authorities). In a nutshell, the “unusual method of communication” between the undertakings concerned, namely the system notice, is a sufficient basis for the finding of a concerted practice aiming to a discount restriction provided that the travel agencies were aware of the content of the communication. This also means that, as argued by the Advocate General Szpunar, “the mode of communication in itself is not relevant, especially since the participants in collusion may be expected to avail themselves of the possibilities offered by the advance of technology”.
On a slightly different note, it should also to be highlighted that future cases are likely to be substantially more challenging than the one considered by the CJEU in Eturas, which had some rather rudimentary technology at its core. Thus, the provider of a jointly employed, big data-fueled repricing tool like for instance Feedvisor could work out profit maximization strategies for the benefit of its high-paying clients that are much more sophisticated (and opaque) than a bare price alignment, based on rich and complex sources of market data, the ranking criteria (algorithms) employed by the marketplaces, the flow of information coming from the sellers, in-depth consumer data, etc. Among the many tactics creatively employed by the automated repricing tool, only a few – difficult to spot, and for intermittent periods of time – could possibly be considered price dampening by way of horizontal collusion.
Also amidst the gales of technological change, therefore, the notion of awareness is likely to remain central to the assessment of collusive behaviour, as recently stressed by the CJEU in Eturas, where the Court applied Art. 101(1) TFEU to an online travel booking system used by 30 travel agencies in Lithuania. The administrator of the booking system posted a notice in the system mailboxes informing the agencies of a technical (and automatic) restriction on the discount rates they could offer their own clients. The first preliminary question addressed to the CJEU by the referral national court asked whether the simple proof of the system notice allows the presumption that the “economic operators were aware, or ought to have been aware, of the system notice introduced into the computerised information system”. According to the CJEU, it is up to national law to decide if proof that a message has been sent to the booking system’s mailboxes is sufficient to prove that the addressees were aware, or ought to have been aware, of its content. The presumption of innocence however precludes the referring court from deducing the undertaking's awareness of the message content from the mere dispatch of the message in the booking system. Instead, a presumption of awareness may be based on ‘other objective and consistent indicia’ that the undertaking tacitly assented to an anticompetitive action (for instance, in this case there had been prior communication between the system administrator and the travel agencies regarding a possible capping of discount rates). If awareness of the content of the message can be demonstrated, the acquiescence in that initiative may be inferred unless the undertaking opposes to it (e.g., by reporting the initiative to the authorities). In a nutshell, the “unusual method of communication” between the undertakings concerned, namely the system notice, is a sufficient basis for the finding of a concerted practice aiming to a discount restriction provided that the travel agencies were aware of the content of the communication. This also means that, as argued by the Advocate General Szpunar, “the mode of communication in itself is not relevant, especially since the participants in collusion may be expected to avail themselves of the possibilities offered by the advance of technology”.
On a slightly different note, it should also to be highlighted that future cases are likely to be substantially more challenging than the one considered by the CJEU in Eturas, which had some rather rudimentary technology at its core. Thus, the provider of a jointly employed, big data-fueled repricing tool like for instance Feedvisor could work out profit maximization strategies for the benefit of its high-paying clients that are much more sophisticated (and opaque) than a bare price alignment, based on rich and complex sources of market data, the ranking criteria (algorithms) employed by the marketplaces, the flow of information coming from the sellers, in-depth consumer data, etc. Among the many tactics creatively employed by the automated repricing tool, only a few – difficult to spot, and for intermittent periods of time – could possibly be considered price dampening by way of horizontal collusion.
Also discussed as at least tangentially part of the “Hub and
Spoke Scenario” was the so called Uber Dilemma. By joining the car service platform,
the driver agrees to charge her riding services according to the fares worked
out by Uber’s algorithm. This is a simple, middling vertical agreement between
the platform and the driver. Once the platform acquires market power, other drivers could become aware that
by joining the platform they would feast on supracompetitive prices (higher
fares and, subsequently, higher commissions earned by the platform). At this point, that is likely to materialize after the platform has already tipped into dominance, competition enforcers
could detect the familiar scent of horizontal collusion in the market, possibly
by way of hub-and-spoke conspiracy. But as soberly intimated by one distinguished competition
enforcer and keynote speaker at the conference, “intervening after tipping may be futile”.
(Part 3 never followed, c'est la vie, folks!).
The EU, acting on its own, may conclude the Marrakesh Treaty
Court of Justice of the European Union, Opinion C-3/15, here.
(And shame on those EU States still opposing the conclusion of the Treaty.)
(And shame on those EU States still opposing the conclusion of the Treaty.)
Monday, February 13, 2017
Sunday, February 12, 2017
Saturday, February 11, 2017
Friday, February 10, 2017
Thursday, February 09, 2017
Premier bilan d'étape concernant les engagements pris par Booking.com
Autorité de la concurrence, ici.
When Competition Policy Meets Science Fiction (Part 1)
The algorithmic economy is the new digital economy, in case you hadn’t noticed. Companies use the outcome of sophisticated data analytics in order to enhance internal monitoring, better tailor marketing strategies, cut processing costs, deploy new or refurbished products and services, and determine sale prices. On their side, consumers have been embracing algorithm-based services such as search engines (e.g., Google and Bing), aggregators (Booking.com and Amazon Marketplace), rating services (e.g., Tripadvisor and Yelp), recommender systems (e.g., Deezer and Spotify) and bidding agents (e.g., eBay’s ) to help them navigate the web and make purchase decisions, both online and offline. Moreover, recent advances in the area of artificial intelligence (AI), combined with Gargantuan strides in computing storage and processing power, open new opportunities to employ algorithms along the economic value chain and to further automate market transactions. Parallel developments in the so called Internet of Things (IOT) are likely to intensify these trends. IOT devices and personal digital assistants fed by artificial intelligence and big data troves are deployed to make purchase and other decisions on the consumer’s behalf by directly communicating with other systems through the internet and, possibly, with decreasing amounts of human involvement. Sergey Brin, Google’s co-founder, recently envisaged a possible future in which automation will alleviate “some of the more mundane tasks”, allowing people to “find more and more creative and meaningful ways to spend their time.”
A recent event organized by Concurrences in London (available slides here) gathered an impressive quantum of human intelligence in order to, among other things, have a good look at the algorithmic economy through the lens of competition policy. By rooting still rather futuristic technologies in the more familiar framework of markets and economic power, the excellent conference speakers painted some vivid scenarios in which potential issues could play out. At the creepier end of the spectrum, discussions even hinted at questions reminiscent of the most intriguing sci-fi books and movies, such as whether AI-enabled, increasingly autonomous market tools could “address” the profit maximizing objective differently from how (even hyperintelligent) human agents would do.
The underlying script of at least two conference panels was largely provided
by the bedside book (in the sense of livre de chevet) “Virtual Competition”, recently written by Ariel Ezrachi
and Maurice Stucke, two of the distinguished conference speakers. While keeping abreast of fast-moving technological developments should never
be an afterthought, the Authors convincingly argue that there is a responsibility
on competition enforcers and other stakeholders to up their game in order to
meet the challenges posed by increasingly algorithm-based markets and protect consumers.
New digital technologies hold innumerable promises, but they can also present some perils, such as when firms selling online employ algorithmic tools that prevent consumers from enjoying truly competitive prices. To start with, competition authorities in the UK and in the US, in two separate investigations, found out that online sellers of posters (or wall décor) implemented anticompetitive arrangements restricting price competition by the use of automated repricing software. Between the two online sellers investigated by the CMA there was clear agreement to facilitate price coordination, with ample evidence that they aimed not to undercut each other’s prices. As to the chosen tools for ensuring price co-ordination, these were software packages offered by different providers. As explained in the Decision, the software employed by one of the sellers could be configured in such a way (“rule 55”) that her prices would match the price of the other seller (identified by the Amazon Merchant ID number) provided that a) there was no cheaper third party seller on Amazon UK and b) the price did not go below the seller’s unilaterally set minimum price. Where the price fixing arrangement did not apply, the software was configured to undercut competing products on Amazon UK Marketplace. The automated repricing software employed by the second seller was programmed in such a way that the usual undercutting rule (“compete rules”) did not apply to the first seller (“ignore list”). What Ariel Ezrachi and Maurice Stucke in their book call the "Messenger Scenario" was unanimously considered a "no-brainer" by the conference speakers. In fact, in the poster cases mentioned above, as well as in previous instances in which the collusion was facilitated and monitored by computers, human market actors are clearly liable for the restriction of competition.
While this is certainly true, and further scenarios such as the "Predictable Agent" and the "Digital Eye" pose a number of unequivocal challenges to competition enforcers (more on them later), how powerful online intermediaries are continuously reshaping competition dynamics in the digital economy is also worth the attention of many a conference panel. As marketplaces offer customers the possibility to easily compare prices of products without incurring significant cost, sellers’ pricing decisions become increasingly crucial. At the click of a mouse, sellers employing algorithmic tools can choose with whom to compete and with whom not to compete in the marketplace. Thus, for instance, a seller may decide that it is not worth competing with sellers shipping from distant regions, as many of her potential customers are likely to prefer a faster shipping time. Prices displayed on the marketplace go up and down, also many times in a single day, fluctuating according to highly inscrutable parameters. In many instances, these fluctuations are the likely result of strategic sellers trying to “game” their competitors pricing tactics (both algorithmic and non-algorithmic), but also trying to acquire higher ranking and product visibility on the platform (e.g., being featured in Amazon’s Buy Box, “the most valuable small button on the Internet today”, as more than 80% of sales on Amazon go through it). Moreover, the poster cases have shown that sellers could employ algorithmic pricing in order to achieve anticompetitive results and that, rather alarmingly, collusion can literally be one click away. For these and other reasons, there is the pressing need to better understand the behaviour of algorithmic sellers in specific competitive scenarios such as marketplaces, where the rules of the game are largely decided by the platform (“Truman Show”).
Wednesday, February 08, 2017
Tuesday, February 07, 2017
Rapport d'information: "les objets connectés"
Commission des affaires économiques, Assemblée Nationale, ici.
Australia: Apple “Banks use digital wallets as a revenue source”
CompetitionPolicyInternational, here.
Monday, February 06, 2017
Sunday, February 05, 2017
Saturday, February 04, 2017
Thursday, February 02, 2017
Recap and Analysis: Responsible Art Market Initiative Launched in Geneva
Sullivan & Worcester, here.
Wednesday, February 01, 2017
Tuesday, January 31, 2017
Monday, January 30, 2017
Thursday, January 26, 2017
Wednesday, January 25, 2017
Tuesday, January 24, 2017
Competition Law and Big Data: Do Competition Authorities Know How To Do It?
A. Lamadrid, S. Villiers, here.
Monday, January 23, 2017
Sunday, January 22, 2017
Privacy in our Digital Lives: Protecting Individuals and Promoting Innovation
Former US President Barak Obama, here.
Friday, January 20, 2017
Thursday, January 19, 2017
Artificial Intelligence at WEF17
"the market is not the right way to make certain decisions"
"most engineers don't even know why governments exist"
"a corporation is a kind of AI, already "
Wednesday, January 18, 2017
Tuesday, January 17, 2017
Monday, January 16, 2017
Trump’s vision for behavioral science in the White House is anyone’s guess
NewYorker, here.
"The President-elect, it turned out, had a gift for the behavioral arts. He intuitively grasped “loss aversion” (our tendency to give more weight to the threat of losses than to potential gains), and perpetually maximized “nostalgia bias” (our tendency to remember the past as being better than it was). He made frequent subconscious appeals to “cultural tightness” (whereby groups that have experienced threats to their safety tend to desire strong rules and the punishment of deviance), and, perhaps most striking, his approach tapped into what psychologists call “cognitive fluency” (the more easily we can mentally process an idea, such as “Make America great again” or “Lock her up!,” the more we’re prone to retain it). Even his Twitter game was sticky: “Crooked Hillary!” “build the wall.”
"The President-elect, it turned out, had a gift for the behavioral arts. He intuitively grasped “loss aversion” (our tendency to give more weight to the threat of losses than to potential gains), and perpetually maximized “nostalgia bias” (our tendency to remember the past as being better than it was). He made frequent subconscious appeals to “cultural tightness” (whereby groups that have experienced threats to their safety tend to desire strong rules and the punishment of deviance), and, perhaps most striking, his approach tapped into what psychologists call “cognitive fluency” (the more easily we can mentally process an idea, such as “Make America great again” or “Lock her up!,” the more we’re prone to retain it). Even his Twitter game was sticky: “Crooked Hillary!” “build the wall.”
Saturday, January 14, 2017
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Centre for a Digital Society , Video here . These are my very rough talking points on pay or okay in full length (more than I actually had...
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Arstechnica.co.uk, here .
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LG Frankfurt am Main, 2-06 O 172/09 (verkündet am 13.05.2009). Lesenswertes aus der Begründung (meine Hervorhebungen): "Vorstellbare ...
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Public Knowledge, here .
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TechCrunch, here .
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Here (thanks to Netzpolitik).
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J. Morrison, here .
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Gigaom.com, here .
