Shawn Wang: uncertainty

Transcript context

…Thank you for that suggestion. We'll be thinking about how we also help Singaporeans understand the opportunities to be AI engineers, how they can get into it. A lot of governments are trying to do this, right? Like train their citizens and offer opportunities. I have not been in the Singapore workforce my adult career, so I don't really know what's available apart from SkillsFuture. I think that there are a lot of people wanting help and they go for courses, they get certificates. I don't know how we get them over the hump of going into industry and being successful engineers and I fear that we're going to create a whole bunch of certificates that don't mean anything. I don't know if you have any thoughts or responses on that. This idea that you don't want to over-rely on qualifications and credentials is also something that has been recognised in Singapore for some years now. That even includes your academic qualifications. Every now and then you do hear people decide that that's not the path that they're going to take and they're going to experiment and they're going to try different ways. Entrepreneurship could be one of it. For the broad workforce, what we have discovered is that the signal from the employer is usually the most important. As members of the workforce, they are very responsive to what employers are telling them. In the organisational context, like in the case of Grab, Alessio was talking about them shutting down completely for one week so that everyone can pick up generative AI skills. That sends a very strong signal. So quite a lot of the government funding will go to the company and say that it's an initiative you want to undertake. We recognise that it does take up some of your company's resources and we are willing to help with it. These are what we call company-led training programmes. But not everyone works for a company that is progressive. If the company is not ready to introduce an organisation-wide training initiative, then what does an individual do? So we have an alternative to offer. What we've done is to work with knowledgeable industry practitioners to identify for specific sectors, the kinds of technology that will disrupt jobs within the next three to five years. We're not choosing to look at a very long horizon because no one really knows how the future of work will be like in 15, 35 years, except in very broad terms. You can. You can say in very broad terms that you are going to have shorter learning cycles, you are going to have skills atrophy at a much quicker rate. Those broad things we can say. But specifically, the job that I'm doing today, the tasks that I have to perform today, how will I do them differently? I think in three to five years you can say. And you can also be quite specific. If you're in logistics, what kinds of technology will change the way you work? Robotics will be one of them. Robotics isn't as likely to change jobs in financial services, but AI and machine learning will. So if you identify the timeframe and if you identify the specific technologies, then you go to a specific job role and say, here's what you're doing today and here's what you're going to be doing in this new timeframe. Then you have a chance to allow individuals to take ownership of their learning and say then, how do I plug it? So one of the examples I like to give is that if you look at the accounting profession, a lot of the routine work will be replaceable. A lot of the tasks that are currently done by individuals can be done with a good model backing you. Now, then what happens to the individual? They have to be able to use the model. They have to be able to use the AI tools, and then they will have to pivot to doing other things.…

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