DIY software development, digitized workplaces, union and employee resources, Cybersecurity professional shortfalls
Welcome to WORK:LIFE. The weekly update to navigate technology driven transformations and broader trends shaping the future of work.
This issue is 864 words, 3 mins reading time.
If you have feedback, or future of work interests you’d like me to address in an upcoming issue, do get in touch at worklife@edaith.com
Tina
This week:
🗒 The multi-generational ‘perennial’ workplace
🗒 Jobs reviewing AI-generated material
🗒 DIY software development
🗒 Digitized workplaces: Union and employee resources
🔍 Education-job mismatch
➡️ Cybersecurity professional shortfalls
🗒 The multi-generational ‘perennial’ workplace
At its plant near Munich with about 8,000 workers, BMW is showcasing its multi-generational workplace:
“..where as many as five generations of people collaborate and bring to the table their unique skills and perspectives. They have redesigned factories and the various sections within them so that several generations of workers feel comfortable toiling together, leading to productivity increases and higher job satisfaction.”
🗒 Jobs reviewing AI-generated material
Contrary to the positive spin this story takes, jobs annotating data used to train AI systems, and jobs reviewing AI generated outputs are not aspirational. They are low paid contract positions whereby reviewers are sometimes subjected to the worst of humanity’s content to inform the fine tuning of the model before it is released to the public (e.g. Work:life 11.09.23 Human labour behind AI).
🗒 DIY software development
Using Microsoft’s Power Platform, a no code and low code environment for creating business apps, data analysis and automations, a former cleaner was able to transition to the IT department of a university.
The author of this article ponders that large language model’s capabilities in coding may end up having a much bigger impact than the natural language component that has captured most of the public attention. From my experience at the National AI centre, many businesses just need simple apps and systems automations, rather than building from scratch or complex development. So basic applications through a no code platform, or the skills to plug into and utilise finished solutions provided by platform service providers, will achieve the ends needed.
I’m constantly testing the natural language capabilities of the main chatbot offerings for research assistance and first drafts of text and have not found them to (yet) be of the quality or reliability necessary for lightening the load in my day-to-day work. I’ve also read about software developers being of a similar opinion in terms of using LLMs with software development tasks. So I’m sceptical about the possibilities to develop anything past basic solutions with no code tools, even those powered by AI.
🗒 Digitized workplaces: Union and employee resources
The authors argue that unions and workers need to understand what’s happening in digitized workplaces: what AI systems are being used in workplaces and what data has been used to train those systems; what data is being extracted from employees, and how it affects employment decisions.
Tools to help workers and unions include:
Public Services International’s (PSI) Digital Bargaining Hub - to help unions prepare to bargain over employees’ digital rights.
Why Not Lab’s Governance of Algorithmic Systems Guide - a checklist for unions to effectively talk to management about digital products used in the workplace and the use of workers’ data.
Why Not Lab’s Data Lifecycle at Work - to help unions grasp how data is collected and used by employers.
As a result of lobbying in this space, the Australian Public Service enterprise agreement will soon include a set of clauses to allow workers to blow the whistle on the unethical use of algorithms.
🔗 Building Union Power to Rein in the AI Boss (Stanford Social Innovation Review)
🔍 Education-job mismatch
Based on analysis of 100 million people in 18 global economies the World Economic Forum estimates that a staggering 49% of individuals work in roles unrelated to their formal education.
If you’ve got a soon to be university entrant around, the research on mismatches for Spanish graduates might be of interest. Not in terms of selecting a degree to study (find/follow interests!), but in terms of setting expectations and planning accordingly regarding the amount of time post-graduation it generally takes some degrees to land a ‘matched’ job. The broader the degrees oft
en take a few roles, and are at higher of risk of not being linked to employment in the longer term.
Skills career entrants are likely to benefit from in their education:
Negotiating
Networking
Speaking confidently in front of crowds
Working long hours
Resolving work conflicts
Being managed by another person
Although we could probably all benefit from upskilling in couple of those realms (or is it just me?!)
🔗 Education-job mismatch (Edaith blog)
➡️ Cybersecurity professional shortfalls
“Global cybersecurity job vacancies grew by 350 percent, from one million openings in 2013 to 3.5 million in 2021, according to Cybersecurity Ventures. The number of unfilled jobs levelled off in 2022, and remains at 3.5 million in 2023, with more than 750,000 of those positions in the U.S.”
For Australian readers, current National Skills Commission data shows there is a skills shortage for cyber security professionals in every state across the following occupations:
Cyber security engineer
Cyber security advice and assessment specialist
Cyber security analyst
Cyber security architect
Cyber security operations coordinator
🔗 On the Cybersecurity Jobs Shortage (Schneier on Security)
Future ready?
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