Technology

information & communication technology

“the total decoding and synthesizing of reality”

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A seminal moment in my work came when I saw my first web page on a computer at Montreal’s CRIM in 1994. I finally saw computers as things that connect people around the globe. From here I completed a Master’s degree focusing on how people learn at work with information technology.

The next significant moment arrived with social media. I started blogging and sharing online. When Twitter came along it changed my relationship with hundreds of people. Social media platforms became the great connectors. But now in 2023 we know that much of the web is comprised of surveillance and tracking tools that are designed to influence our behaviour, especially our purchasing behaviour.

In whither Twitter, I wrote that more important than any single platform is our collective ability to seek diversity, think critically, and learn socially. For now I am staying on Twitter and watching the show, muting and blocking with abandon. But we know that platforms like Twitter can undermine democracy and spread disinformation and propaganda. Perhaps that is why Musk bought the company.

I had another seminal moment when I watched The AI Dilemma recorded on 9 March 2023. It shook my understanding about the current state of machine learning, which I thought I sort of understood conceptually. Tristan Harris and Aza Raskin, from The Center for Humane Technology, present on the new force that has been unleashed by several global companies with no regulatory oversight — the Generative Large Language Multi-modal Model (AKA Gollem-class AIs).

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understanding the hype and hope

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I have been keeping an eye on the hype & hope around artificial intelligence (AI), especially:

  • ML — machine learning
  • GPT — generative pre-trained transformers
  • GAI — generative artificial intelligence
  • LLM — large language models

“I’ve long been a fan and found value in AI / ML and its capabilities. Learning and finding patterns and causal patterns that in time can lead to outcomes that are problematic (a large fleet of vehicles with hundreds of sensors feeding and AI / ML to detect early engine, transmission, or other failure to address before more expensive damage or at a human cost). Generative AI from large language models is missing core pieces still and had knock-on effects that are really problematic with its lack of understanding facts (or multitudes of facts and truths), but more problematic is it blunts human learning and cognition.”
—Thomas Vander Wal 2023-03-18

How Technology Influences Social Networks

Stewardship of global collective behavior —2021-06-21

“Human collective dynamics are critical to the well-being of people and ecosystems in the present and will set the stage for how we face global challenges with impacts that will last centuries. There is no reason to suppose natural selection will have endowed us with dynamics that are intrinsically conducive to human well-being or sustainability. The same is true of communication technology, which has largely been developed to solve the needs of individuals or single organizations. Such technology, combined with human population growth, has created a global social network that is larger, denser, and able to transmit higher-fidelity information at greater speed. With the rise of the digital age, this social network is increasingly coupled to algorithms that create unprecedented feedback effects.”

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pilots and copilots

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Simon Terry has a short post on Microsoft’s new Copilot and how we should be careful in fully adopting some of these generative AI tools.

LLMs [large language models] are improvements on past tools but are hardly perfect. In a world where the volume of information means many people scan everything, we need to remain alert for the risks of the models false inferences or patterns gone awry.

In the history of aviation, it became apparent that pilot personal relationships are critical to avoiding dangerous incidents. Authoritarian cultures meant senior pilot mistakes went devastatingly unchallenged. —Microsoft Co-pilot

I mentioned pilot training on a post recently — experience cannot be automated. I concluded that automation, in all fields, forces learning and development out of the comfort zone of course development and into the most complex aspects of human learning and performance. On that post is also a quote by Captain Sully Sullenberger, the famed pilot who safely landed a passenger jet on the Hudson River. A movie was made about this, which included the subsequent safety investigation. Tom Hanks plays Sully and in this sequence of videos we see the difference between human cognition of experienced pilots versus the best software/hardware simulation of the day. There is no comparison.

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capitalism > automation > gpt

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In my last post I covered in detail how ideas become ideology.

“Ideas lead technology. Technology leads organizations. Organizations lead institutions. Then ideology brings up the rear, lagging all the rest — that’s when things really get set in concrete.”—Charles Green (2009)

Today, the underlying ideology is capitalism. It drives the actions of governments, such as claiming that companies are job creators.

“There is no such thing as a ‘job creator’. There are employers, who hire employees, *because they need them*. And then employers pay the employees less than the value they generate. That’s the system. How did we get to the point at which people behave as if the wealthy are giving a gift to working people? I realize it’s not a new attitude, but it remains proudly f’d up.” —Mark Sumner

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how ideas become ideology

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Several times I have referred to this observation about how ideas connect to ideology.

“Ideas lead technology. Technology leads organizations. Organizations lead institutions. Then ideology brings up the rear, lagging all the rest — that’s when things really get set in concrete.”—Charles Green (2009)

Here are some examples of these shifts.

Ideas lead technology

Hedy Lamarr invented spread spectrum technology in 1941 but its value as a technology accelerated half a century later as it would, “galvanize the digital communications boom, forming the technical backbone that makes cellular phones, fax machines and other wireless operations possible.”

Peter Senge’s book, The Fifth Discipline, ushered in the idea of the learning organization but it was only recently that organizations had the Web 2.0 technologies to enable distributed team learning or share systems-thinking across the enterprise.

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watch the machines

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I wrote the next two paragraphs in a blog post last year — we have met the enemy.

A long time ago — pre-pandemic and pre-9/11 — I was flying on a commercial passenger aircraft. The flight was over-booked and as I was wearing my Army uniform, I was offered to sit in the jump seat, just behind the pilots. Yes, these things happened in the ‘before times’.

It was a short flight but I had a chance to speak with the pilots. The captain told me that many civilian pilots had a military background but their training and experience resulted in some differences. He mentioned that if there was an observed incident on take-off, most of the civilian-trained pilots would make small adjustments to the throttle speed, aware that fuel costs money for the company. On the other hand, many of the military-trained pilots might react to an incident by slamming the throttles forward and getting out the situation and in the air as fast as possible. This of course costs more fuel, but from a military operational perspective would probably be the best default action.

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auto-tuning work

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Are we moving into a post-job economy? Can the concept of the job continue to be the primary way that people work? Building ways to constantly change roles can be one way to get rid of the standardized job, which has decreasing usefulness in a creative, networked AI-assisted economy. We should be preempting automation by identifying what routine work should be automated as quickly as possible, so that people can focus on what machines cannot do — being curious, creative, empathetic, passionate, and humourous.

One area of dwindling jobs is at the entry level. This creates a challenge for career development. It is difficult to start as a highly skilled worker, especially since our academic institutions focus on knowledge acquisition and provide very little skill development. Standardized curricula are useless in developing those skills listed above that machines cannot do. Standardization is the enemy of creativity.

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it’s not not about the technology

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Writing my essays at university was always a painful process. We were still allowed to write them, though more professors were requiring essays to be submitted typed. My essays were never good because I often left them to the last minute and hand-writing a better version was just too much time and effort. As much as I loved reading and new ideas, I was not a good writer.

A decade later I went to graduate school and word processors were widely available. I still could not type but at least I could peck away at several versions of an essay before submitting it. My writing got a bit better. David Weinberger recounts the impact of the word processor on his writing.

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stepping in

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In the book, Only Humans Need Apply (2016), the authors identify five ways that people can work with machines. They call it ‘stepping’. We are seeing an increasing need to do what they call ‘stepping in’ or using machines [and software] to augment work. In GPT-3 through a glass darkly I used the McLuhans’ media tetrad to examine this form of machine learning, which is all over the media today.

GPT-3

  • Extends each voice & mimics creativity
  • Obsolesces copy-writing and essays so that human insight becomes a luxury
  • Retrieves the polymaths of the European Renaissance so that the best writers must be multi-talented to earn a living
  • Reverses into mass deception and provides answers without real questions behind themsee quote below

We may be in a ‘golden age’ of AI, as many have claimed. But we are also in a golden age of grifters and Potemkin inventions and aphoristic nincompoops posing as techno-oracles. —Derek Thompson, The Atlantic, 2022-12-01

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platform collapse

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The robber barons of the 21st century are the platform owners. They have combined the power of network effects with a 20th century corporate capitalist, winner-takes-all approach. Amazon is choking the book publishing industry, Google is dominating advertising, and telecommunications companies are using their control of the pipes to directly compete with service providers. Now Uber is going after the taxi and car rental industries, getting to be larger than established rental car brands, with none of the overhead. All of these companies provide initially good services to customers. But over time their monopolistic tendencies kill competition and the entire ecosystem of innovation.

I wrote the above paragraph is 2014, not mentioning Twitter, which until recently was where journalists, institutions, and governments shared what was happening and fed the algorithms that showed what was trending. In some ways Twitter was the pulse of the world and helped drive the Arab Spring, Black Lives Matter, and many other causes. It was the main source of visitors to this blog when I deleted Google Analytics several years ago, as a way to ignore vanity metrics.

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