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Stephen Billett discusses the implications of the changes for worklife learning (lifelong learning).

Image courtesy of interviewee. December 6, 2023

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This video video discusses the evolving nature of work due to advancements in electronic technologies and the consequent shift in the skills and knowledge required in various fields. It highlights the transition from manual, sensory-based skills to more abstract, symbolically-based knowledge. This video video change demands that workers not only adapt to new technologies but also deeply understand the underlying systems and processes involved in their work, as illustrated by the Three Mile Island incident.

The narrative then explores how different professions, including airplane pilots and truck drivers, have had to adapt to technological changes that obscure the direct sensory feedback they previously relied on. It identifies that to effectively engage with these new tools, workers need to develop confidence and competence through practical experience.

This video video emphasizes the importance of contextual learning—gaining knowledge in real work settings rather than in isolation—because it enhances cognitive engagement and retention. For example, it cites the practice of junior doctors remembering cases by associating them with patients, thus making it easier to recall related medical knowledge.

Additionally, the implications of new technologies in fields like forensic science, auditing, and healthcare are examined, emphasizing the need for training and transition support for workers to build trust and competence in these technologies.

Ultimately, the text argues that a well-rounded education that combines theoretical knowledge with practical experience is crucial for developing the necessary competencies to thrive in modern work environments. It underscores that both educational settings and workplace experiences are vital in fostering effective learning and adaptation to technological advancements.

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X-TIMESTAMP-MAP:LOCAL=00:00:00.000,MPEGTS=900000

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Increasingly work tasks are being driven

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by electronic technologies, which are based upon functions

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and operations that are quite distinct from some of the

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previous forms of, of how work was undertaken.

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And in particular, the way that we learn these forms

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of knowledge is quite different than tools of the early era.

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And I'm sure many of your listeners would be able to relate

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to tasks that they did, which were based upon manual skills,

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being able to feel and see and smell things.

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And now these, those tasks are done, you know,

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relatively autonomously by different forms of technology.

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Um, so this is then is becoming an increasing element of,

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working life, certainly more so

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for some areas of work than others.

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But most people who are, are engaged

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with computing processes, for instance, encounter this.

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And therefore, there's a need to understand what sits behind

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and, and how you can undertake your, your work.

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I mean, a classical example of this was what happened in

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what is referred to as Three Mile Island, which was the,

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the almost meltdown

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of a nuclear power station in America in the 1980s.

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And that was that the,

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there's something failed within the power station,

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but the people in the control room knew about the controls,

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but they didn't understand

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how the nuclear power station functioned.

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And there, when the information they were getting ceased

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to be informative,

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it wasn't providing them the correct information.

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They didn't have the knowledge to actually make the kind

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of changes, which was to cool down the, the,

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nuclear power cell.

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Um, so they understood the operating system,

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the actual operating screens in front of them,

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but they didn't understand the technologies

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that were running the power station.

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And from the commission, that was a presidential commission

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of the, what was referred to

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as the incident in Three Mile Islands.

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It came out that, you know, workers of this kind need

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to actually understand the processes,

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which they can't get near, can't physically engage

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with, but it's important.

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And we see this across a whole range of work,

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whether we're talking about airline pilots who,

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who now fly planes, you know, on,

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wire based rather than physical contact

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with the Aons and the, the rudders.

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They now use technologies for that.

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And so they can't feel the stress

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and strain that's put on the plane when they make turns.

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So there's been a, you know, this concept

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of haptic technology, which tries to reintroduce the feel

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that comes from the use of these technologies down through,

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for instance, the truck drivers who now drive trucks

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that are controlled by computers, which is very different

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than changing manual gears, clutches and braking systems,

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and even vibrations that come from the engine, which used

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to be the basis by which truck drivers would, would know how

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to manage to drive a very heavy vehicle.

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So these, these, the,

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these considerations are pervading

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contemporary working life.

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And it is, much of it is based upon what is referred to

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as conceptual or symbolic knowledge,

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which is often quite different than knowledge

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that comes from direct field, direct contact, that we

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organize through the sensory systems.

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So that's, that's some of the reasons why this is important.

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And as I said at the beginning, these forms

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of technologies are beginning to pervade all forms

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of, of working life.

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The classical example, and this was a study of the changes

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of metal machinists.

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So these are the people who used to use operate lathes,

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and I dunno about you, but when I was a schoolboy, I did

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what was called manual arts, where you sat on a lathe

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and learned how to use a lathe.

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And these machinists, they would make judgments about

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how they would turn the tool

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to cut the metal based upon the sound

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that the the tool makes.

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Is it screaming because it's too much.

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They would look at the color

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of the wharf coming off from the tool

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and see if it's looking burnt.

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It's if it's too much pressures being put on.

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And then they would also smell the, the effect

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of the coolant hitting the hot metal.

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And they would feel the vibrations as they turned the,

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the dial to make the, you know,

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the tools go along and shape the metal.

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And they would use, for instance, PIs and, and,

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and to actually determine the, the amounts

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of metal they were cutting from the, the tool.

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But, that all changed when computer

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numerically controlled lasers came in

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and a different set of totally different set

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of skills were required.

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And that is that the computer, a computer would be used

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to be programmed, which would then determine how the,

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the tool cut into the metal.

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And so you went from workers who relied solely on,

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not solely, but largely upon sensory processes through to,

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this symbolic knowledge, which is probably more akin to

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what computer operators, learn to use.

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So that's something is that the classical example of the way

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that this, this knowledge changed,

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and one of the key elements

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of this is the impact it has upon a worker's subjectivity,

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their sense of self.

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So you can imagine these workers who were very,

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very experienced in, in, in what they'd done, all

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of a sudden all

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of the knowledge they had was rendered redundant,

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and instead they needed the skills that they would,

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you know, of, of computer operation.

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Um, so that's,

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and I think a classical example of the kind of changes.

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So it's not just a question of assisting people understand

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the kind of new knowledge they need,

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but also the impact of that knowledge on, on their sense

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of self as, as workers

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and how they then come to know to operate in a,

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in a very different way.

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But what we know now about human cognition is that it's,

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It's greatly enriched when you actually do something which

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provides you with a whole range of clues, cues, and,

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and contributions.

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And this, for instance, is one reason why a lot of knowledge

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that is learned in educational settings doesn't translate

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to, doesn't translate to practice because all those cues

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and cues which are very helpful in assisting people cognate,

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can actually recognize

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and respond to things, aren't in existence.

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So, so one of the qualities

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of workplaces is it provides all

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of this rich contextual knowledge.

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You see half worked examples, you see processes

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and action, you see the outcomes of them,

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and you also get the opportunities to practice.

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So one of the first considerations then is that this kind

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of knowledge, you know, the aspects of it might have

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to be learned in a dedicated training setting,

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but the actual utilization

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and further development of that knowledge is probably likely

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to be required in practice.

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Now, I'm sure you've, at some point in time in your career,

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you've been sent off to do a software program

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and to learn a new, you know, form of technologies

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for journalism work or imageries or whatever.

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But unless you've had the opportunity then

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to go back into the workplace and use that technology

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and use the software on your work task

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and have opportunity to do it frequently,

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it's unlikely you will be, become competent

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or confident in that change.

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Now, one of the things, the important things about change

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for workers is that commitment

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to something comes from confidence within it.

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I mean, nobody would throw themselves out of a plane

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unless they were confident that the parachute

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that they're wearing has been packed appropriately

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and will get them safely to ground.

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And so we know that then commitment

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to something comes from competence in being able to enact it

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and confidence in it.

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So these are the kind of experiences which can best be

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provided in work settings.

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So I guess that's one of the, the, the first point that by

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engaging in these tasks, that the knowledge in,

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in work settings, that the knowledge is made accessible.

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And that is often aided by the,

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the technologies themselves providing those clues

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and cues which are otherwise, which

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otherwise people would've learned

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through physical engagement in tasks.

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So I think a lot of the icons, for instance,

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which are used in digital technologies on the, on the face

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of digital technologies, are very helpful.

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I mean, if you look at a typical computer, the icon

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for saving something, relates to, what used

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to be called a three and a quarter inch floppy disc.

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Now, anybody, anybody, under,

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under 30 probably never dealt with one

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or would hold whatever held one in my hands yet, people know

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that icon and what it means.

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And so these icons are, are helpful even, you know, even,

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you know, the, the idea that,

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They exist. So

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the, and the other thing is that lots

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of these technologies have ways of, of, of,

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projecting what's going on.

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You know, they, they have these digital displays, they have,

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you know, they can demonstrate things

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and show things graphically in a way that is,

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is quite different than other technologies.

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And I think these are the ways in which, that

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that knowledge can become accessible.

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So for instance, one of my PhD graduates,

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studied truck driving

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and the transition from mainly driven trucks to trucks that,

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are operated by computers

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and what the, you know, what the screen

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provided to the driver was a lot of

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important information presented graphically,

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but they needed just the confidence to engage with that,

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understand what it was saying, and then going ahead.

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The other example is what is referred to in in healthcare

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as, wows, which are workstations on wheels.

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And so these days when a patient is being treated in a

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hospital, there's often a computer,

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a workstation on wheels brought at the side of the bed.

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And the, the, you'll find

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that the doctors spend far more time looking at the

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information on the screen than the patient,

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which can be a problem.

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But the point is they're getting a lot

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of information digitally

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and it's presented graphically so they can follow,

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things in, in rich ways.

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So there's great potential from this technology

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to make the kind

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of knowledge which is important, accessible.

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This is the point that it's not just like the one-off

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training, regime,

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but rather it is embedded in work practice.

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It's also embedded when workers need to engage

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with particular tasks and make sense of them.

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And what we know, for instance, from medical studies,

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that the best way that people remember things are when

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things are done in context.

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So a typical practice within healthcare, for instance, is

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that junior doctors are told instead of trying

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to memorize the, you know, the conditions

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of something like pneumonia, just remember the patient

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that you first encountered it in.

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So remember Mr. Smith,

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and in remembering Mr. Smith, that brings back all

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of those conditions or symptoms that Mr. Smith showed.

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And so these examples are richly contextual,

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and we know then that that kind of cognition,

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that's which is referred to as a assimilations

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are powerful ways in which we bring together information

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and can remember and recall it.

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So, so that there's some of the qualities

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that why it's important to,

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to have those kind of experiences.

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Well, I mean, it's this issue that's,

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these are major challenges to, work a sense of self.

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So in a project I was involved with, with,

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forensic science, which is the, the where bodies are

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cadavers when people die

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and they're subject to coronial inquests,

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the standard process of engaging

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with 'em traditionally has been a full postmortem.

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And believe me, nobody, you know, you would like to go

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through a full postmortem

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unless it's a hundred percent necessary.

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But with the advent of cd scanners, they're now able

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to often, determine the cause

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of death without doing a postmortem.

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Um, and as such, this then is better

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because the body isn't desecrated.

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Um, they're able to get information that they

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otherwise wouldn't be able to get.

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For instance, they can get a, a jawline

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and make it straight

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so they can examine the teeth in a particular way.

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They can follow through, for instance, the trajectory

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of bullets through a body to be determined, the entry

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and exit point of a bullet from a body,

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which is very important in cases of murder.

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You know, whether the person, which direction the person was

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shot in, you know, all those things.

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Now they can do that with technologies.

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Now, some forensic, pathologists have moved very quickly

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to, embrace this,

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but others, are are uncertain about it

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because they don't trust it currently.

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Uh, well, recently, I should say,

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I was doing a study in Singapore that involved auditors

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and they're using artificial intelligence

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to do the auditor task.

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Now, auditors have to sign off to on a document to say

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that they've audited the books

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and many of them are, are, are still not certain

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that about the way that the AI works,

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and they are the ones that have to sign off on it.

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So they're, you know, using the, you know,

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the proverbial example, they're the ones

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that have been asked to throw themselves out the plane,

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but they're not quite sure whether their parachutes going

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to work for them.

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So these are important ways of introducing the technology,

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but building the confidence of people to,

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engage with them.

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Now, many, many years ago, I used

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to work in garment manufacturing.

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I was trained in Britain

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and I worked in Gart manufacturing in,

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in Britain and Australia.

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And I was there when we first started using

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automatic sewing machines.

13:52.625 --> 13:56.005
And the machinists were quite nervous about this new

13:56.005 --> 13:57.365
technology because up until

13:57.365 --> 13:59.805
that point it had only been their skills with their feet

13:59.805 --> 14:01.565
that would manipulate the machine.

14:02.585 --> 14:04.765
And so it took some persuasion,

14:04.785 --> 14:07.485
but it was quite easily achieved once

14:08.025 --> 14:10.885
the machinists had been given some sample pieces to work on.

14:11.185 --> 14:14.165
And they realized that this technology then increased their

14:14.165 --> 14:17.365
productivity, which then increased their potential

14:17.865 --> 14:18.885
for earning more money

14:18.885 --> 14:22.565
because you get bonuses when you work over, you know,

14:22.565 --> 14:24.205
your required work.

14:25.025 --> 14:28.365
Um, so I, I've actually experienced that, you know,

14:28.575 --> 14:31.205
these kind of changes, but there has to be a process

14:31.385 --> 14:34.045
to help people understand these new technologies.

14:34.145 --> 14:37.325
And so they become confident, in them.

14:37.465 --> 14:40.565
And then, you know, from that derives, competence,

14:40.835 --> 14:44.045
this is the point that I think there's great potential in

14:44.455 --> 14:47.045
these new technologies to display knowledge, which

14:47.045 --> 14:49.005
otherwise, because it's abstracted,

14:49.005 --> 14:52.525
because it's conceptual, you, it, it, we now have ways

14:52.545 --> 14:55.125
of understanding that now just, remember what occurred

14:55.125 --> 14:58.805
during the, the, the, the, the covid pandemic.

14:59.145 --> 15:01.285
Now none of us would ever be able to see

15:01.315 --> 15:03.245
what a covid thing looks like,

15:03.745 --> 15:05.005
but what we were confronted

15:05.005 --> 15:08.645
with the on the news was every night, this, this, this,

15:09.145 --> 15:11.485
symbol that this, this depiction of

15:11.485 --> 15:14.925
what the covid virus looked like and the spurs on it,

15:14.945 --> 15:17.885
and the, the conversations then around the importance

15:17.885 --> 15:20.005
of those spurs and what you're able to do.

15:20.445 --> 15:22.085
I think they were called spurs,

15:22.425 --> 15:24.885
to inhibit its ability to spread.

15:25.425 --> 15:28.005
So I think something like that, which is you can't see,

15:28.225 --> 15:29.725
you know, you can't see it,

15:29.985 --> 15:33.565
but that representation allowed people to understand what,

15:33.715 --> 15:36.765
what, what something was that you can't see visually

15:36.765 --> 15:37.765
because it's so small.

15:38.425 --> 15:41.725
And then from that, then you could understand why certain

15:41.725 --> 15:42.765
things had to happen.

15:43.185 --> 15:44.645
So I think there's great potential,

15:44.665 --> 15:47.405
and of course there's animations and all sorts of things,

15:47.865 --> 15:51.405
but the, the use of these needs to be done quite intent

15:51.625 --> 15:52.725
and quite intentionally.

15:52.785 --> 15:56.125
So then workers can, can come to make that,

15:56.125 --> 15:58.445
that transitions, come to understand these things

15:58.505 --> 16:01.525
and use them, use them effectively.

16:01.665 --> 16:04.965
The first thing is we need to understand with any form

16:04.965 --> 16:08.085
of knowledge how people can access it and learn it.

16:08.785 --> 16:11.165
Um, and so we have to make a decision about

16:11.385 --> 16:12.565
how best that can occur.

16:13.025 --> 16:15.605
Now, some of it can occur within training situations

16:15.705 --> 16:17.725
or educational settings,

16:17.725 --> 16:21.045
and that's important for things that you will not learn,

16:21.785 --> 16:24.925
in the workplace because it's, it's simply not accessible.

16:25.225 --> 16:28.085
And that's very helpful. But we also must be aware

16:28.085 --> 16:31.245
that probably a lot of rich learning comes from when we

16:31.255 --> 16:33.685
apply these, these forms of knowledge in practice.

16:34.285 --> 16:37.925
'cause that gives us the basis to understand, to remember

16:38.265 --> 16:40.925
to bring together their contributions

16:41.185 --> 16:45.845
and to actually be able to, recall and reuse them later.

16:46.185 --> 16:48.325
So to come to, so it's really the, the,

16:48.385 --> 16:51.125
the standard problem, the standard issue perhaps

16:51.195 --> 16:54.005
with education, which is we need to understand what kind

16:54.005 --> 16:56.245
of experiences are best at developing

16:56.245 --> 16:57.285
these forms of knowledge.

16:57.505 --> 17:00.005
And in this case, there's things which the artifact

17:00.025 --> 17:01.165
itself can provide.

17:01.705 --> 17:04.005
And then there's the thing, there's the need for it

17:04.005 --> 17:05.845
to engage it and have experiences,

17:06.185 --> 17:09.805
but there's also going to be the need for specialized,

17:10.075 --> 17:13.245
education, to understand the fundamentals

17:13.385 --> 17:14.605
of these sorts of things.

17:15.385 --> 17:17.325
So for instance, it's best perhaps

17:17.355 --> 17:20.405
that medical students learn, you know, the basics

17:20.405 --> 17:21.725
of physiology in a,

17:22.065 --> 17:24.245
in the way they do within educational settings.

17:24.585 --> 17:27.405
But then it's important then that they have the opportunity

17:27.585 --> 17:30.765
to, take histories of, of patients

17:30.865 --> 17:33.525
and come up with diagnosis of their circumstances

17:34.065 --> 17:36.965
and then predict the kind of, regime

17:36.965 --> 17:38.125
of treatment they need.

17:38.385 --> 17:40.605
And that brings the two sets of body bodies

17:40.625 --> 17:44.005
of knowledge together, one without the other, I suspect,

17:44.425 --> 17:45.765
is, is where we have problems.

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