Trends Identified
Emergence of Disruptive Technology
Disruptive technologies will continue to evolve in the coming decades. Hence, it is in the hands of policy makers, entrepreneurs, business leaders and citizens to maximise application of these technologies while dealing with the challenges.
2017
Science & Technology Foresight Malaysia
Malaysia, Academy of Sciences Malaysia
Emergent artificial intelligence
Artificial intelligence (AI) is, in simple terms, the science of doing by computer the things that people can do. Over recent years, AI has advanced significantly: most of us now use smartphones that can recognize human speech, or have travelled through an airport immigration queue using image-recognition technology. Self-driving cars and automated flying drones are now in the testing stage before anticipated widespread use, while for certain learning and memory tasks, machines now outperform humans. Watson, an artificially intelligent computer system, beat the best human candidates at the quiz game Jeopardy. Artificial intelligence, in contrast to normal hardware and software, enables a machine to perceive and respond to its changing environment. Emergent AI takes this a step further, with progress arising from machines that learn automatically by assimilating large volumes of information. An example is NELL, the Never-Ending Language Learning project from Carnegie Mellon University, a computer system that not only reads facts by crawling through hundreds of millions of web pages, but attempts to improve its reading and understanding competence in the process in order to perform better in the future. Like next-generation robotics, improved AI will lead to significant productivity advances as machines take over – and even perform better – at certain tasks than humans. There is substantial evidence that self-driving cars will reduce collisions, and resulting deaths and injuries, from road transport, as machines avoid human errors, lapses in concentration and defects in sight, among other problems. Intelligent machines, having faster access to a much larger store of information, and able to respond without human emotional biases, might also perform better than medical professionals in diagnosing diseases. The Watson system is now being deployed in oncology to assist in diagnosis and personalized, evidence-based treatment options for cancer patients. Long the stuff of dystopian sci-fi nightmares, AI clearly comes with risks – the most obvious being that super-intelligent machines might one day overcome and enslave humans. This risk, while still decades away, is taken increasingly seriously by experts, many of whom signed an open letter coordinated by the Future of Life Institute in January 2015 to direct the future of AI away from potential pitfalls. More prosaically, economic changes prompted by intelligent computers replacing human workers may exacerbate social inequalities and threaten existing jobs. For example, automated drones may replace most human delivery drivers, and self-driven short-hire vehicles could make taxis increasingly redundant.On the other hand, emergent AI may make attributes that are still exclusively human – creativity, emotions, interpersonal relationships – more clearly valued. As machines grow in human intelligence, this technology will increasingly challenge our view of what it means to be human, as well as the risks and benefits posed by the rapidly closing gap between man and machine.
2015
Top 10 emerging technologies of 2015
World Economic Forum (WEF)
Emerging market and/or non-traditional competitors
21% of the respondents view this as a negative trend.
2019
4Q 2018 KPMG Global Insights Pulse Survey Report
KPMG
Emerging market and/or nontraditional competitors
27% of the respondents view this as a negative trend
2017
Adoption of intelligent automation does not equal success. 4Q 2017 KPMG Global Insights Pulse Survey Report.
KPMG
Emerging market competitors
27% of KPMG member firm advisors answered that this trend has a large negative impact for the user organizations.
2015
Top trends and predictions for 2015 and beyond
KPMG
Emerging markets increase their global power
Today, emerging markets serve as the world’s economic growth engine, and the far-reaching effects of their spectacular rise continue to play out. But their risks are often downplayed. Therefore, taking advantage of emerging-market opportunities requires careful planning.
2011
Tracking global trends - How six key developments are shaping the business world
EY
Emerging service and knowledge economies
Coming out of the mining boom, Australia continues to grow the service sector and knowledge economy. The labour upskilling trends across Australian industries provides evidence of the rise of the knowledge economy1. At the same time, service industries are growing faster.
2017
Surfing the digital tsunami
Australia, Commonwealth Scientific and Industrial Research Organisation (CSIRO)
Emotional Disruption
As the intertwining of technology with human life deepens, “affective computing”—the use of algorithms that can read human emotions or predict our emotional responses— is likely to become increasingly prevalent. In time, the advent of artificial intelligence (AI) “woebots” and similar tools could transform the delivery of emotional and psychological care—analogous to heart monitors and step counters. But the adverse consequences, either accidental or intentional, of emotionally “intelligent” code could be profound. Consider the various disruptions the digital revolution has already triggered—what would be the affective-computing equivalent of echo chambers or fake news? Of electoral interference or the micro-targeting of advertisements? New possibilities for radicalization would also open up, with machine learning used to identify emotionally receptive individuals and the specific triggers that might push them toward violence. Oppressive governments could deploy affective computing to exert control or whip up angry divisions. To help mitigate these risks, research into potential direct and indirect impacts of these technologies could be encouraged. Mandatory standards could be introduced, placing ethical limits on research and development. Developers could be required to provide individuals with “opt-out” rights. And greater education about potential risks—both for people working in this field and for the general population—would also help.
2019
The Global Risks Report 2019 14th Edition
World Economic Forum (WEF)
Emotionally aware machines
Example of Organizationsactive in the area: IBM (US), Toyota (Japan), Mimosys (Japan), Persado (US), Joy AI (US).
2018
Table of disruptive technologies
Imperial College London
Employers will make room for neurodiversity.
Neurodiversity refers to the inclusion of people with all sorts of cognitive abilities and patterns, from ADHD and dyslexia to people on the autism spectrum. It is coming to workplaces as the chronological consequence of a cultural and scientific shift in the 1990s; conditions once seen as pathologies to be medicalized became differences society should embrace. “You have a whole generation of people who were much more rigorously diagnosed entering the workforce now,” says Ed Thompson, founder of Uptimize, an organization that helps employers attract, hire and retain neurodivergent talent. Add to that a “chronic war for talent,” he says, which is prompting recruiters to look beyond their usual demographics, and neurodiversity is “becoming a category of workplace [diversity and inclusion] that a lot of people are talking about in a way that wasn’t true even a year ago.”
2018
50 Big Ideas for 2019: What to watch in the year ahead
LinkedIn