Thursday, October 12, 2023

We Cannot Predict What We Cannot Yet Imagine

It is fairly easy to predict that artificial intelligence will affect many--if not most, or all--industries, as the advent of personal computing, smartphones and cloud computing have done. In fact, lots of studies look at the expected AI impact on industries and products that already exist. 


For example, we can predict that we will see:

AI-powered personalized education

AI-driven healthcare

AI-enabled autonomous vehicles

AI-powered creative industries

AI-enabled space exploration

AI-powered cybersecurity

AI-enabled climate change mitigation

AI-driven financial services

AI-enabled legal services

AI-powered manufacturing

AI-enabled agriculture


Likewise, new products will incorporate AI, in forms such as:


AI-powered personal assistants

AI-powered medical devices

AI-enabled self-driving cars and trucks

AI-powered creative tools

AI-powered educational software

AI-powered cybersecurity solutions

AI-powered climate change mitigation technologies

AI-powered financial trading platforms

AI-powered legal research tools

AI-powered manufacturing robots

AI-powered agricultural equipment


Prediction

Study Title

Publication Date

Publication Venue

Personalized education

The Future of Learning: AI and the Next Generation of Education

2023

McKinsey Global Institute

AI-powered healthcare

Artificial Intelligence and the Future of Healthcare: A Report by the National Academy of Medicine

2019

National Academy of Medicine

Self-driving cars and trucks

Self-Driving Cars: The Next Revolution in Transportation

2016

World Economic Forum

AI-powered robots

The Future of Jobs and the Rise of Artificial Intelligence

2017

Pew Research Center

AI-powered customer service

AI and Customer Experience: The Future of Service

2020

Forrester Research

AI-powered legal services

The Future of Law: AI and the Transformation of the Legal Profession

2018

American Bar Association

AI-powered cybersecurity

AI and Cybersecurity: The Next Frontier

2021

Center for Strategic and International Studies

AI-powered financial services

AI and the Future of Finance: A Report by the World Economic Forum

2018

World Economic Forum

AI-powered logistics and supply chain management

AI and the Future of Logistics: A Report by the World Economic Forum

2019

World Economic Forum

AI-powered entertainment and media

AI and the Future of Entertainment: A Report by the World Economic Forum

2020

World Economic Forum


But that’s sort of an imaginative problem. We see ways AI can change or benefit what already exists. We have a really hard time envisioning how AI might create things which do not exist, and the industries and firms that will produce them. 


As former Apple CEO Steve Jobs used to say, one cannot predict consumer interest in a product they have never seen. Nor can we easily imagine what really-new things and industries might arise from AI.


How "Fair Share" Tries to Recreate the Old Closed Network

Sometimes what is important about a report or statement is what is not said. In the case of a report discussing European Union region network infrastructure issues, the European Commission did not issue an explicit decision whether a few large app providers (Netflix, Meta, Google) should be required to pay fair share fees to internet access providers.


Some observers might argue that likely means no action, one way or the other, will be taken in the next year or so. 


Though other issues were noted by the report, including the coming role of network virtualization artificial intelligence, edge computing, a unified EU market and open networks, the immediate battle is over revenue. ISPs and mobile operators say their revenues and profit margins are declining, and the argument is that this is, in large part, because a few large content and app providers benefit from ISP networks without contributing to create the needed capacity of those networks. 


Critics might note that internet domains--including the targeted hyperscale firms--already pay such fees for traffic asymmetry in the form of interconnection payments.


Hyperscale App Provider

ISP

Interconnection Payment

Netflix

Comcast

$1 billion

Netflix

Verizon

$750 million

Amazon Web Services

Comcast

$1.2 billion

Amazon Web Services

Verizon

$900 million

Microsoft Azure

Comcast

$1 billion

Microsoft Azure

Verizon

$750 million

Google Cloud

Comcast

$800 million

Google Cloud

Verizon

$600 million

Microsoft Azure

AT&T

$75 million per year

Alphabet

Charter

$100 million per year

Amazon

AT&T

$150 million per year

Microsoft

Charter

$75 million per year

Google

AT&T

$125 million per year

Meta

Charter

$50 million per year

Meta

AT&T

$75 million per year

Alphabet

China Telecom

$150 million per year

Amazon

NTT

$125 million per year

Microsoft

Deutsche Telekom

$100 million per year

Google

Telefónica

$75 million per year

Meta

Singtel

$50 million per year

Meta

Orange

$75 million per year


In addition, one can clearly argue that ISPs charge their own customers for internet access service, and can set those fees at levels that support their own customers’ data consumption. Already, some heavier users pay more than lighter users, and that is a business decision any ISP is free to make. 


In other businesses, when the cost of a product goes up, so does the retail price. In other words, if their own consumers are consuming more capacity than present retail prices recover, raise prices. 


The other angle is that, traditionally, traffic imbalances between domains were assumed to be created by the initiating party. For example, the party placing an international call pays for the call. The party sending a text message pays for it. 


The claimed traffic imbalance ISPs complain about is created by requests from their own customers for app providers to send data. 


That noted, in the past it was the telcos themselves that created interconnection payments for traffic asymmetries. Even in the internet era, where the hyperscale app providers often create their own end-to-end networks, traffic imbalances result only when a customer on one ISP network requests content from a firm on another ISP’s network. 


In other words, interconnection obligations happen when one party invokes the use of another party on a different network. At a retail level, the initiating customer creates a session that generates revenue for the initiating and terminating networks. At a wholesale level, imbalances between networks and domains are resolved either by settlement-free peering or true-ups at the end of a year. 


This is arguably more complicated than in the past, in part because internet sessions are based on nailing up circuits for finite periods of time easy to measure. Also, the locations of requesting and fulfilling parties is not set. 


The party requesting content can be on the same ISP network as the requesting party, in which case no inter-domain traffic is invoked. The requesting party can be on network A, while the fulfilling party is on network B, but, on balance, requesting and fulfilling parties exist--in many cases--on both neworks A and B. 


At a high level, traffic might roughly balance over a year’s time, especially in cases where ISPs A and B have hyperscale data centers as customers “on their own networks,” as well as retail customers invoking delivery of content from firms at those data centers, both on networks A and B. 


At one level, one might argue that peering makes more sense on transit and wide area networks since the actual path any packet might take is indeterminate. Any WAN provider might be able to cite the total number of packets flowing over the network, but be unable to identify which originating networks were involved in creating the traffic. 


On any access network, in contrast, the use of network resources is definite. No matter what path packets might take across the interconnected wide area networks, they use only one physical path at the receiving party’s location on the local access network. 


But again, one might ask: is the “cause” of traffic imbalance the originator or the fulfiller of a session? Is it the ISP customer asking for streaming of a Netflix movie the traffic initiator, or is it Netflix fulfilling the request? 


Beyond that, is it the ISP supporting Netflix content delivery that is “creating the traffic asymmetry” or is it Neflix or the Netflix customer on the ISP network that asks for the content?


Without question, domain interconnection, what constitutes a “session” and “who initiated the session?” are different questions in the internet era than was the case in the voice era. 


But the issues are bigger than that. In the internet era, transport and access service providers have lost their “closed” networks and the ability to control the presence of every app that uses the network, by and large. 


In a “permissionless” era, where no app creator needs a formal business relationship with a capacity provider to reach a customer, ISPs also have lost the ability to monetize their traffic as owners of such third-party apps. 


In a real sense, the proposed “fair share” payments from a few hyperscale app providers to ISPs is an effort to recreate that revenue mechanism. 


Or, in other words, “fair share” is an effort by ISPs to participate in the revenue earned by a few hyperscale app providers, as would have been the case in the older world of “closed” networks, where all apps needed permission from the network owner to operate.


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