Singapore's lifelong learning efforts need an AI-centred overhaul
The writer says it is important for continuing education and training (CET) to help people thrive in AI-augmented workplaces.
Recent advances in generative AI have prompted much soul-searching among educators on how it will transform teaching and learning in schools as well as in tertiary institutions.
Much of the debate has focused on the relevance of current pedagogies, the skill sets being taught, and the need for new approaches to education.
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Straits Times
5 minutes ago
- Straits Times
AI eroded doctors' ability to spot cancer within months in study
Sign up now: Get ST's newsletters delivered to your inbox A researcher predicted that the effects of de-skilling will 'probably be higher' as AI becomes more powerful. LONDON – Artificial intelligence, touted for its potential to transform medicine, led to some doctors losing skills after just a few months in a new study. AI helped health professionals to better detect pre-cancerous growths in the colon, but when the assistance was removed, their ability to find tumours dropped by about 20 per cent compared with rates before the tool was ever introduced, according to findings published on Aug 13. Health-care systems around the world are embracing AI with a view to boosting patient outcomes and productivity. The UK government in 2025 announced £11 million (S$19.06 million) in funding for a new trial to test how AI can help catch breast cancer earlier. The AI in the study probably prompted doctors to become over-reliant on its recommendations, 'leading to clinicians becoming less motivated, less focused, and less responsible when making cognitive decisions without AI assistance,' the scientists said in the paper. They surveyed four endoscopy centres in Poland and compared detection success rates three months before AI implementation and three months after. Some colonoscopies were performed with AI and some without, at random. The results were published in The Lancet Gastroenterology and Hepatology journal. Professor Yuichi Mori, a researcher at the University of Oslo and one of the scientists involved, predicted that the effects of de-skilling will 'probably be higher' as AI becomes more powerful. What's more, the 19 doctors in the study were highly experienced, having performed more than 2,000 colonoscopies each. The effect on trainees or novices might be starker, said Dr Omer Ahmad, a consultant gastroenterologist at University College Hospital London. 'Although AI continues to offer great promise to enhance clinical outcomes, we must also safeguard against the quiet erosion of fundamental skills required for high-quality endoscopy,' Dr Ahmad, who wasn't involved in the research, wrote a comment alongside the article. A study conducted by MIT in 2025 raised similar concerns after finding that using OpenAI's ChatGPT to write essays led to less brain engagement and cognitive activity. BLOOMBERG
CNA
2 hours ago
- CNA
CoreWeave revenue beats estimates on AI boom but shares fall on bigger loss
CoreWeave easily topped quarterly revenue estimates on Tuesday as the rapid adoption of artificial intelligence tools boosted demand for its cloud services, but a bigger-than-expected net loss sent its shares slumping 10 per cent after the bell. The company currently operates 33 AI data centers across the U.S. and Europe and offers access to backer Nvidia's chips, which are highly coveted by enterprises to train and run large AI models amid intense competition. CoreWeave reported revenue backlog of $30.1 billion as of end of June, compared with $25.9 billion on March 31. "Demand is humming, but it is the cost of growth that tempered the stock down in aftermarket trading," said Michael Ashley Schulman of Running Point Capital Advisors. Operating expenses jumped to $1.19 billion in the second quarter, from $317.7 million a year earlier. The company posted a net loss of $290.5 million, compared with analysts' average estimate of $190.6 million, according to data compiled by LSEG. "We are scaling rapidly as we look to meet the unprecedented demand for AI," CEO Michael Intrator said in the earnings statement. Investors have also focused on the company's reliance on a few big customers. "The backlog surge to $30B+ suggests demand visibility well beyond 2025, but the concentration in mega-customers like OpenAI means those relationships remain both the crown jewel and the single point of failure," said eMarketer analyst Jeremy Goldman. Meanwhile, CoreWeave executives reiterated the benefits of its $9 billion all-stock deal for crypto miner Core Scientific. The deal, announced in July, is facing opposition. Core Scientific's largest shareholder, Two Seas Capital, has said it would vote against the sale. CoreWeave reported second-quarter revenue of $1.21 billion, beating estimates of $1.08 billion. The Livingston, New Jersey-based company raised its annual revenue forecast to be between $5.15 billion and $5.35 billion. It had previously projected annual revenue of $4.9 billion to $5.1 billion.
Business Times
2 hours ago
- Business Times
Why leaders must learn to see beyond the tech hype
AT THIS year's International Artificial Intelligence (AI) Action Summit in Paris, one thing was evident: the pace of technological change is accelerating, but our ability to make informed, strategic decisions about it is lagging behind. This dissonance is already playing out across organisations. Nearly half of employees who use generative AI at work do so through tools that are officially banned by their companies. It's a paradox that speaks volumes, as leaders remain unsure of how to govern tools their employees find valuable. Yet decision-making around technology is still too often driven by instinct, fear of falling behind, or a fixation on what is new rather than what is necessary. Leaders are encouraged to adopt early, automate more and digitise faster. What they are rarely asked to consider is: Where is the real value being created, and what trade-offs come with it? Recent research conducted by Essec Business School seeks to bring greater structure to this uncertainty. By analysing the impact of six emerging technologies (ranging from generative and descriptive AI to blockchain, quantum computing, robotics, and renewable energy) across 11 key economic sectors, the study introduces a matrix-style framework for understanding where genuine disruption is unfolding. It draws on more than 300 global industry publications, academic papers, patent activity, and the sentiments of 1,000 professionals across industries, offering a data-driven lens to look past the noise. Technologies that drive value Some of the findings are intuitive. Others are deeply revealing. The most striking is the dominance of generative AI, ranked highest in perceived disruption with a score of 89.45 out of 100, reflecting its explosive growth in academic and patent literature as well as industry excitement. But despite its dominance in headlines and boardroom conversations, a closer look reveals that it remains early-stage in implementation. Many firms are still experimenting, and concerns about data governance, content quality and long-term return on investment remain unresolved. By contrast, descriptive AI, encompassing machine learning, analytics, and pattern recognition, received lower disruption scores (49.04 over 100) but is far more integrated into day-to-day operations. It powers logistics, customer segmentation, predictive maintenance and more. Its relative invisibility in public debate belies its foundational role in business value creation. BT in your inbox Start and end each day with the latest news stories and analyses delivered straight to your inbox. Sign Up Sign Up This divergence between attention and adoption invites a more careful reading of what 'disruption' really means. Not all technologies that dominate the conversation are the ones driving value. This becomes even clearer when looking at sectoral variation. Renewable energy and storage, for instance, is championed most strongly not by the energy sector, but by real estate professionals, who view it as both a sustainability imperative and a means of future-proofing asset. An overwhelming 91.1 per cent of real estate professionals express confidence in its value. This enthusiasm is shaped by both external forces – such as sustainability mandates and investor expectations – and internal shifts, such as tenant demand for greener buildings. Other sectors show more ambivalence. The luxury industry, for example, is split on generative AI. Some view it as a creative tool that can extend brand expression; others see it as a threat to authenticity and craftsmanship. Here, the disruption is as much cultural as it is technological. Meanwhile, in automotive, blockchain continues to underwhelm. Despite years of hype around decentralised mobility and supply chain transparency, over 22 per cent of respondents in this sector expressed negative sentiment towards blockchain's potential. Adoption has remained limited, and its strategic relevance is being reassessed. These diverging sectoral responses underscore a crucial truth: no technology is universally applicable. Context is everything. A tool that may be transformative in one sector may be irrelevant or even counterproductive in another. Yet many transformation strategies still rely on blanket thinking, assuming that what works for one industry or geography must work for all. These nuances matter. They show that disruption does not follow a single path. Technologies gain or lose traction based on sector-specific conditions: regulatory frameworks, cost structures, workforce readiness and even consumer psychology. This is why a shift in mindset is needed. Leaders must move beyond digital fluency – being able to talk about technology – towards digital discernment: the ability to evaluate technologies critically, in relation to business needs, strategic goals and sectoral realities. Before asking how a technology works or how fast to deploy it, leaders must first ask why it matters and whether it aligns with what their organisation is trying to achieve. Such thinking is particularly important in economies like that of Singapore, where digital transformation is not just a business priority, but a national agenda. The Smart Nation initiative has placed Singapore at the forefront of global digital experimentation, from mobility to health and finance. But with ambition must come rigour. Calculated investment, guided by both evidence and sectoral insight, will be key to ensuring Singapore's technology ecosystem remains not just advanced, but resilient. Energy: bottleneck to innovation One of the more sobering insights from the Essec research is that energy may soon become a bottleneck to innovation. Many of the most promising technologies, especially those driven by AI and quantum computing, are also among the most resource-intensive. In Singapore's compact, urbanised economy, energy efficiency and infrastructure capacity will play an increasingly central role in determining what kinds of innovation can be scaled sustainably. These are strategic considerations that must be addressed now, not retrofitted later. None of this is to suggest that technology should be approached with fear. On the contrary, innovation holds immense potential to solve the world's most pressing challenges, from climate change to healthcare access and economic inclusion. But realising that potential depends on leadership – not just at the policy level, but within companies, institutions and communities. It calls for decision-makers who are not only open to change, but capable of navigating its complexity with maturity and foresight. Ultimately, the goal is not to win the race for adoption. It is to ensure that the technologies we choose to invest in serve the long-term needs of people, businesses and society. The leaders who will thrive in this new era will not be those chasing the next big thing, but those asking the right questions: questions about purpose, fit, readiness and impact. Understanding what's possible is no longer enough. The future belongs to those who can discern what is truly valuable. Both writers are from the Essec Business School. Jan Ondrus, a professor of information systems, heads the Essec Digital Disruption Chair, and Jeremy Beaufils is the executive director of the Essec Digital Disruption Chair.
