Episode 37 of the Big Tech Little Tech podcast got off to a good start. Our opening chitchat was fun, the news was short and sweet, and before long we arrived at the main topic. The initial episode schedule had a few discussion guides, like so: The impact of AI on the future of work– automation, job displacement, new opportunities, responsible AI, and trust.
As with all good conversations, Rick and I diverged, following paths that sounded the same, but were in essence quite different. Despite having done research around acknowledging the significant influence of established AI, such as automation, I let Rick guide the direction. His focus was on generative AI – a topic we talk about quite often: common, comfortable ground for both of us. It did mean I couldn't fall back on my notes, playing it by ear instead.
My preparation for episode 37 makes me wonder two things: Is it a good idea to have a pre-show discussion, to ensure we talk about the same themes; or is it good for the show to go off-piste, even though it may be a blind alley for one of us? Either way, it's these interesting dynamics that make for a good partnership. The element of surprise may catch one of us out, but that can often make a great show for listeners. We should be wary of doing it too often, which might eventually make for a poor listening experience, too!
So, what else did we talk about? I was quite taken by the M4 Morphobot, while Rick enjoyed the story about the headteacher at Cottesmore School (Tom Rogerson) who's working with Abigail Bailey, an AI assistant! We also mention the lawyer who used ChatGPT in a US courtroom, and CNET's AI-written articles, where it was called out for plagiarism.
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The impact of AI on work so far
"I’d like to begin with how AI has affected work so far, Rick. For instance, automation has had a big impact on particular industry tasks such as in manufacturing, customer service and data entry. Automation has helped many companies streamline their operations by handling repetitive tasks."
I worked with Aito for a while, which is an intelligent automation specialist. Among the use cases ripe for automation disruption were customer operations such as IT support tickets. It meant technical issues were solved faster, which led to happier, loyal customers. You could match support tickets with the right department using automation, and when you add machine learning, the process becomes more efficient and accurate. The AI makes predictions based on what it has learned so far. Data simply gets better, and there's so much of it around these days!
PwC research says that, by the mid-2030s, a third of all employment will be at risk of being automated, and those most likely to be affected will have a low level of education.
Did you know that CNET apparently jumped on the AI bandwagon quickly? According to Forbes, CNET published dozens of articles written by ChatGPT when it first came out. It's hardly a repetitive task – more like a cost-cutting strategy, which I think is disrespectful to its audience. I read that plagiarism was a problem, so someone had to correct the articles anyway!
What about the American writers’ strike? Can AI replace scriptwriters yet? Perhaps talk shows and shopping channel nonsense, but what about film and TV scripts?
What job opportunities does AI present?
Statistic: Jobs requiring AI or machine-learning skills are expected to increase by 71% in the next five years.
Statistic: The US Bureau of Labor Statistics expects computer science and information technology employment to grow 11% from 2019 to 2029, adding about 531,200 new jobs in the industry.
Jobs: AI product manager, AI research scientist, Big data engineer, Business intelligence, developer, Computer vision engineer, Data scientist, Machine learning engineer, Natural language processing engineer, Deep learning engineer, AI consultant.
create AI systems that are efficient and compatible with regulations
ensure that development processes consider all the ethical, legal, and societal implications of AI
track and mitigate bias in AI models
build trust in AI
prevent or minimise negative effects of AI; and
get rid of ambiguity about “whose fault it is” if something in AI goes wrong.
I'm positive about the effects of artificial intelligence on the future of employment. As Rick says in the show, revolutions happen at the expense of something else, which history often demonstrates. There's much to think about. Rick also said a few episodes ago that his advice is to learn as much as you can about AI, and make an effort to not fall behind. We are both past our fifties, yet we are hungry about this stuff.
Until next time, stay safe, keep smiling and enjoy the details.
