Author Archives: azurefinops

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About azurefinops

I'm a cloud architect and writer, focused on Azure, Azure cost control, Azure Security and Azure Cognitive Services. Maximizing your cloud investment is the shared responsibility of business and IT but often, there's a disconnect; the teams speak past each other. I act as the bridge, speaking the language of both groups to help organizations achieve their goals and maximize value.

Windows Vista as Neoliberal Instrument

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Synopsis

Last night, before nodding off to sleep, a stray memory flitted across (or through?) my synapses; a posting I made to the Left Business Observer Listserv, titled “Windows Vista as Neoliberal Instrument”. This was, I think, my first attempt to merge my work in information technology with my (always in formation and never complete) Marxian approach to ways of thinking about that industry.

At the time of writing, over a decade ago, February of 2007, the release of Microsoft’s Windows Vista operating system was the source of a lot of debate and frustration. The OS wasn’t performing as hoped and techies were wondering why. It turned out that one of the key reasons was Microsoft’s attempt to enforce copyright via software. This proved to be a rich target for analysis and David Harvey’s ‘A Brief History of Neoliberalism’ provided a powerful analytical framework.  Also, this was a total flex.

Introduction

[content originally posted to LBOTalk February, 2007 some new formatting added]

In his most recent book, “A Brief History of Neoliberalism”, David Harvey analyzes the neoliberal turn that first Western, and later, practically every economy on Earth took to varying degrees of depth over the past 30 or so years. 

Several key features of neoliberalism are dissected:

1.) neoliberalism as a power restoration technique (i.e., restoring to capitalists the margin of power lost during the postwar years of high growth and detente with labor)

2.) neoliberalism as imperfect tool against stagnation and the problems of overproduction

and

3.) neoliberalism as a method for monetizing practices and spaces previously excluded from market concerns and controls

To properly understand the strategic concessions Microsoft made to the entertainment industry — concessions that led MSFT to deploy a software-based version of the Advanced Access Content System (AACS) in Windows Vista — you need to carefully consider that third aspect of neoliberalism.

What is AACS?

Briefly, the Advanced Access Content System is a platform, created at the behest of the entertainment industry, whose sole purpose is to enforce a (it is vainly hoped) completely uncrackable environment for “premium content” to flow through from player — device or software-based — to a display and/or audio output. Of course, the phrase “premium content” is a term of art inasmuch as the actual content might be anything from a slapdash teen sex comedy to the most subtle examples of musical or filmed art.

The motion picture and recording cartels have long been disturbed by the fact that people could record, remix and redistribute “content” at will. Over the years, many copy protection schemes have been tried; all have failed. Advances in computing power and storage capacity — moving in parallel with advances in cryptology — have finally made the old dream of an automated copyright enforcement system achievable.

Achievable, because under the AACS system, ‘intelligent’ hardware is constantly on the lookout for security breaches (for example, interceptions of the content data stream from player to output) and empowered, so to speak, to take action. What action? Well, action like actively preventing component outs from working if the HD-DVD or Blu ray disk you’re trying to view has been flagged as being compromised (or more specifically, if the cryptological “key” associated with the disk has been compromised, leading to your play privileges being ‘revoked’ by the key issuing authority).

All high definition hardware — players, digital sets, audio units — are designed to enforce this automated copyright infrastructure. Your HD-DVD or Blu Ray player will talk to your high def display over what are called High-Bandwidth Digital Content Protection compliant outputs. Together, they’ll ensure that RIAA and MPAA copyright concerns are being addressed wherever and whenever “premium content” is being viewed.

Rent Seeking via Operating System

Microsoft wanted Vista to be marketable as a media platform (and MSFT also wanted to create the de facto standard for software based AACS implementation) so they crafted a complex encryption/decryption methodology within the operating system that obeys — and then some — AACS rules. Doing so gave them negotiating space with the entertainment industry.

As any user of consumer electronics and Microsoft software knows, shit happens. The copyright enforcement, content monitoring and encryption/decryption technologies in next gen players and Vista are always on. This exacts a performance price from the devices (because our CPUs and memory are good, but not so good that they can effortlessly do both content presentation and advanced cryptological functions without exhibiting some problems at least some of the time) and especially from the software, which is very brittle and prone to malfunction.

But beyond the false piracy alarms, stuttering playbacks and other technical annoyances that are already being seen in the wild, there’s an overriding fact to keep in mind: AACS gives the entertainment industry the ability to treat the products you buy as leased objects, which can be (say, in a case of revocation resolution) the source for ever renewable revenue long after they were originally purchased.

It also creates a method for modularizing in unprecedented ways — and therefore monetizing — functions that were previously considered more or less all of a piece, such as playing and therefore viewing the disks you buy.

In order for this system to work as planned, all devices must comply with the AACS standard. The idea is to close all potential areas of escape. Eventually, perhaps after 5 to 15 years, the full magnitude of the lock-in will be in effect as older DVD and audio players are retired.

It’s been rumored that Hollywood and the RIAA are fully aware AACS is, despite all their efforts, eminently hackable, and that the true target of these new constraints are ordinary people who don’t have easy access to workarounds. 

The goal then, is to have a lever that can be pulled at any time to extract more income from “consumers”.

Links —-

A Brief History of Neoliberalism

https://global.oup.com/academic/product/a-brief-history-of-neoliberalism-9780199283279?cc=nl&lang=en&

High-Bandwidth Digital Content Protection

http://en.wikipedia.org/wiki/High-Bandwidth_Digital_Content_Protection

Advanced Access Content System

http://en.wikipedia.org/wiki/Advanced_Access_Content_System

A Cost Analysis of Windows Vista Content Protection

http://www.cs.auckland.ac.nz/~pgut001/pubs/vista_cost.html

Techno-Skepticism: A Tactical Skill

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Techno-skepticism is a vital and necessary response to a world awash in self-promoting boosterism and the capitalist utilized ideologies of techno-optimism and techno-determinism.

To define terms, techno-optimism is the belief any proposed technology is possible and good. Optimists look to past examples of things that were once impossible which became possible – such as machine flight – and infer this tendency is universal.

Techno-determinism (which can be considered a species of determinism) builds on tech-optimism’s ideological framework by asserting not just possibility, but inevitability.

For example, a techno-optimist views a development such as ‘robot’ kitchens as being both positive and possible as presented – determinists assert there’s nothing to stop such a development: it’s inevitable and beyond resistance, like gravity.

Robotic Chef Marketing Video

Skepticism, correctly practiced, isn’t the denial of technological change or the reality of, or potential for, benefits from such change. Skepticism is remembering to ask three questions:

  • How does this work? A technical inspection
  • Is it possible as described? A feasibility interrogation

Consider, for example, Amazon’s failed drone delivery service, which Cory Doctorow analyzed here – As Doctorow describes, this idea was inexplicably taken seriously:

“When Amazon announced “Prime Air,” a forthcoming drone delivery service, in 2016, there was a curious willingness on the part of the press – even the tech press – to take the promise of a sky full of delivery drones at face value.

This despite the obvious problems with such a scheme: the consequences of midair collisions, short battery life, overhead congestion, regulatory hurdles and more. Also despite the fact that delivery drones, like jetpacks, are really only practical as sfx in an sf movie.”

At the time this proposed service was announced, I read detailed analyses and excited Tweet threads about the supposed meaning of a bold new age of drone delivery. I noticed however, that simple questions regarding feasibility were rarely asked – optimism and determinism (with a good amount of self-interested boosterism in the mix) prevented a skeptical response

When you read about a technological system, such as delivery via drone, remembering to ask questions about function (the how), benefit (who’s promoting this and why) and feasibility (can this be done at all or as the promoters describe?) is a reliable way to avoid being fooled and knocked from delusion to delusion.

Pointillistic But Useful: A Machine Learning Object Lesson

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I devote a lot of time to understanding, critiquing and criticizing the AI Industrial Complex. Although much – perhaps most- of this sector’s output is absurd, or dangerous (AI reading emotions and automated benefits fraud determination being two such examples) there are examples of uses that are neither which we can learn from.

This post briefly reviews one such case.

During dinner with friends a few weeks ago, the topic of AI came up. No, it wasn’t shoehorned into an otherwise tech-free situation; one of the guests works with large-scale engineering systems and had some intriguing things to say about solid, real world, non-harmful uses for algorithmic ‘learning’ methods.

Specifically, he mentioned Siemens’ use of machine vision to automate the inspection of wind turbine blades via a platform called Hermes. This was a project he was significantly involved in and justifiably proud of. It provides an object lesson for the types of applications which can benefit people, rather than making life more difficult through algorithm.

You can view a (fluffy, but still informative) video about the system below:

Hermes System Promotional Video

A Productive Use of Machine Learning

The solution Siemens employed has several features which make it an ideal object lesson:

1.) It applies a ‘learning’ algorithm to a bounded problem

Siemens engineers know what a safely operating blade looks like; this provides a baseline against which variances can be found.

2.) It applies algorithms to a bounded problem area that generates a stream of dynamic, inbound data

The type of problem is within the narrow limits of what an algorithmic system can reasonably and safely handle and benefits from a robust stream of training data that can improve performance

3.) It’s modest in its goal but nonetheless important

Blade inspection is a critical task and very time consuming and tedious. Utilizing automation to increase accuracy and offload repeatable tasks is a perfect scenario.

How Is This Different from AI Hype?

AI hype is used to convince customers – and society as a whole – that algorithmic systems match, or exceed the capabilities of humans and other animals. Attempts to proctor students via machine vision to flag cheating, predict emotions or fully automate driving are examples of overreach (and the use of ‘AI’ as a behavioral control tool). I use ‘overreach‘ because current systems are, to quote Gary Marcus in his paper ‘The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence‘, “pointillistic” – often quite good in narrow or ‘bounded’ situations (such as playing chess) but brittle and untrustworthy when applied to completely unbounded, real world circumstances such as driving, which is a series of ‘edge cases’.

Visualization of Marcus’ Critique of Current AI Systems

The Siemens example provides us with some of the building blocks of a solid doctrine to use when evaluating ‘AI’ systems (and claims about those systems) and a lesson that can be transferred to non-corporate uses.