At the start of the year, I was part of a panel that aimed to offer career guidance to graduating students at a local secondary school in Singapore.
The panel dished out the usual advice about the need to have passion, work hard, and always strive to do better. A student then posed a question that struck a chord: “How can I ensure the skills I learn in school will not be obsolete by the time I enter the workforce?”
These students were no older than 16 or 17 years and, if they took the typical route to university, would not begin life as working adults for at least another five to seven years. With technology changing so rapidly these days, it might very well be possible their course modules would no longer be relevant by the time they graduated.
And with the rise of artificial intelligence (AI), deep learning, and cognitive technologies, jobs that exist today may no longer be available in the near future.
I spoke with Gartner’s research director, Angela McIntyre, this week to discuss the impact of AI in this region and how concerned employees should be about its losing their livelihood.
“Certainly AI could have an impact on jobs,” she acknowledged, adding that such systems could be tapped to perform tedious and routine tasks. For instance, AI systems could scan large amount of videos to identify potential threats to public safety or assess medical images to detect possible tumours. They also could help insurance customers fill out forms and highlight rules and policies relevant to their application.
However, McIntyre said, humans still would be required to answer more complex questions and complete the decision-making process. While an AI system would pick out unusual incidents, security guards would need to make a decision on whether an event required intervention and determine the right course of action. Doctors also had to further evaluate an MRI scan to confirm a tumour had indeed been identified and decide on the next course of treatment.
Ultimately, though, AI would reduce the number of people required to perform that first level of basic tasks.
As a result, companies must think about the roles that could be affected and offer retraining to enable these employees to handle higher skilled tasks, instead of having to resort to layoffs, McIntyre said.
Humans, she added, would always be needed to process more complex issues and create end-products that appealed to consumers. For instance, AI could be useful in interpreting legal codes and regulations, but lawyers would have to step in to handle cases where there were conflicting rules or when there were no legal precedents.
AI systems today still could not sustain a proper human conversation, limiting the effectiveness of virtual personal assistants, for instance. She also pointed to overhyped expectations that autonomous vehicles would soon put people on the roads, eliminating the need to learn how to drive or acquire driving licenses.
She noted that there still were significant challenges to resolve before that became a reality, adding that the necessary laws needed to catch up and the robustness of the technology must first be established.
A Recode report last week revealed that Uber’s self-driving system, comprising 43 test vehicles, required human intervention at every mile of the 20,354 miles covered autonomously.
McIntyre said it could take years before such vehicles proved “infallible enough” to run without humans.
“The concern is that AI can’t feel embarrassed or understand the consequences of their actions,” she said, pointing to how Google Photo’s algorithm in 2015 wrongly tagged two humans as gorillas. “It’s important to have rigorous testing of outcomes and retrain systems multiple times so they can continue learning and improving.”
And when done right, AI technologies could offer significant benefits, enabling organisations to better predict consumer buying habits and pricing structures as well as gain new insights to transform certain aspects of their business.
The emergence of deep learning, coupled with the availability of big data, also could pave the way for new models to be established to help solve business problems, McIntyre added.
According to a global study released by Forbes Insights and Ernst & Young, 66 percent of organisations that had a robust analytics strategy obtained revenue growth of at least 15 percent, while 63 percent saw their operating margins climb by at least 15 percent last year.
Manik Bhandari, Ernst & Young Advisory’s Asean analytics leader, said in the report: “Companies have moved from pilot projects that originated in business units or countries to using data and advanced analytics at an enterprise level to rethink and reimagine their entire business to identify new opportunities.”
Bhandari said Singapore was looking to grow its analytics capabilities, offering opportunities for local companies to nurture their own analytics capabilities, but noted that 47 precent of respondents in the city-state were challenged by the lack of analytics skillsets.
“Singapore is fast building up its analytics talent by embedding analytics curricula in schools and universities, but the local talent pool will likely remain constrained.”
A separate study by Singapore Infocomm Technology Federation (SITF) revealed that, to plug a shortage of ICT skills, 56 percent of local businesses were looking to upgrade their existing workforce so they could handle more work. Another 49 percent said they would deploy technology to reduce their manpower requirements.
The emphasis here needs to be on retraining because, clearly, companies face a severe talent crunch. This should give added impetus for them to invest more efforts in reskilling, so employees can be placed into fields where there are shortfalls in skillsets.
More importantly, AI should be tapped to help human talent generate more value for their organisations–and not as an excuse to replace them.
So how can students ensure their skills remain relevant when they enter the workforce? Perhaps the solution is to work for organisations willing and committed to help them achieve that.
