Trends Identified
Against the Grain
With climate change placing growing strain on the global food system, and with international tensions already heightened, the risk of geopolitically motivated food-supply disruptions increases. Worsening trade wars might spill over into high-stakes threats to disrupt food or agricultural supplies. Conflict affecting supply-chain chokepoints could lead to disruption of domestic and cross-border flows of food. At the extreme, state or non-state actors could target the crops of an adversary state, for example with a clandestine biological attack. In these circumstances, retaliatory dynamics could swiftly take hold. Domestically, rationing might be needed. Hoarding and theft could undermine the social order. Widespread famine risk in recent years suggests that greater hunger and more deaths—in least-developed countries, at any rate—might not trigger a major international reaction. If similar suffering were inflicted on more powerful countries, the responses would be swift and severe. More resilient trade and humanitarian networks would help to limit the impact of food supply disruption. But if trade wars were a contributing factor, then countries might seek greater self-sufficiency in food production and agriculture. In some advanced economies, this might require rebuilding skills that have been allowed to fade in recent decades. Agricultural diversification and the development of more resilient crop variants could bolster national security by reducing countries’ vulnerability.
2019
The Global Risks Report 2019 14th Edition
World Economic Forum (WEF)
Africa and China will tie their fates.
China’s growing investment and presence in Africa over the last several years is undeniable; Xi Jinping just committed another $60 billion to African investment only three years after a similar pledge. “African countries are now fully aware of the huge infrastructure gap they have,” in the $70 billion to $120 billion a year range, and have welcomed Chinese money, says Stephen Yeboah, founder of Commodity Monitor. Meanwhile, China needs arable land to feed its population and raw materials — cobalt from the Democratic Republic of the Congo, copper from Zambia, bauxite from Ghana — to feed its industry. In 2019, public opinion will look at those deals closely, demanding fair terms and quality infrastructure, Yeboah says. Zambia’s loans were so mismanaged it can’t even tell how much it owes, he points out, while countries like Rwanda or Ghana have been able to drive a harder bargain. “Ultimately, each country is sovereign,” he says. “It’s up to African leaders to decide whether they let the Chinese call the shots.”
2018
50 Big Ideas for 2019: What to watch in the year ahead
LinkedIn
Affordable catalysts for green vehicles
Progress is being made on a promising zero-emission technology, the hydrogen-fed fuel cell. Progress to date has been stymied by the high price of catalysts which contain platinum. However, much progress has been made reducing reliance on this rare and expensive metal, and the latest developments involve catalysts that include no platinum, or in some cases no metal at all.
2017
These are the top 10 emerging technologies of 2017
World Economic Forum (WEF)
Advertising: 'All sorts of things will just be sold in plain packages'
If I'd been writing this five years ago, it would have been all about technology: the internet, the fragmentation of media, mobile phones, social tools allowing consumers to regain power at the expense of corporations, all that sort of stuff. And all these things are important and will change how advertising works. But it's becoming clear that what'll really change advertising will be how we relate to it and what we're prepared to let it do. After all, when you look at advertising from the past the basic techniques haven't changed; what seems startlingly alien are the attitudes it was acceptable to portray and the products you were allowed to advertise. In 25 years, I bet there'll be many products we'll be allowed to buy but not see advertised – the things the government will decide we shouldn't be consuming because of their impact on healthcare costs or the environment but that they can't muster the political will to ban outright. So, we'll end up with all sorts of products in plain packaging with the product name in a generic typeface – as the government is currently discussing for cigarettes. But it won't stop there. We'll also be nudged into renegotiating the relationship between society and advertising, because over the next few years we're going to be interrupted by advertising like never before. Video screens are getting so cheap and disposable that they'll be plastered everywhere we go. And they'll have enough intelligence and connectivity that they'll see our faces, do a quick search on Facebook to find out who we are and direct a message at us based on our purchasing history.At least, that'll be the idea. It probably won't work very well and when it does work it'll probably drive us mad. Marketing geniuses are working on this stuff right now, but not all of them recognise that being allowed to do this kind of thing depends on societal consent – push the intrusion too far and people will push back. Society once did a deal accepting advertising because it seemed occasionally useful and interesting and because it paid for lots of journalism and entertainment. It's not necessarily going to pay for those things for much longer so we might start questioning whether we want to live in a Blade Runner world brought to us by Cillit Bang.
2011
20 predictions for the next 25 years
The Guardian
Adversarial Machine Learning Becomes Key for Security & Fraud Prevention
Machine learning has had its advantage in effectively delivering rapid prediction of trends and establishing robust risk management and inference. Much investment, time and focus by organisations has been dedicated to programming and training machine learning algorithms to fulfil these functions. However, if these algorithms become compromised, they will be prone to attacks from threats and viruses. The chaotic damage that permeating cyberattacks have inflicted in algorithms can dangerously result in the misclassification/alteration of information within them; in effect an organisation’s entire system’s security can be at stake. Cybercriminals constantly seek to successfully exploit weaknesses of learning algorithms of highly valued organisations. Fraudsters are responding to the enhanced detection capabilities for transaction fraud and account fraud offered by fraud detection and prevention service providers. In some instances, they are also using machine learning algorithms to uncover weaknesses in fraud detection systems, in a type of machine learning chess match. It is here that the choice of FDP vendor becomes important, in terms of how its machine learning solution is implemented. Is a static model used, or does the vendor employ an adversarial model that adapts to changing conditions? Fraudsters will have very little knowledge of the precise algorithms being used to detect fraud. As a result, time, effort and funding must be sourced to identify weaknesses, which may then be applied or replicated across other merchants assumed to be using similar algorithms. Sectors (healthcare, industrial, advertising) where protection of huge amounts and types of sensitive data (e.g. consumer/public data) is a high priority – will be the drivers here. Spend on Fraud Detection & Prevention software in the financial sector, ie for eCommerce transactions including ticketing, money transfer and payments, will reach $10 billion by 2022. These sectors recognise the value of determining and containing susceptibilities (e.g. to detect unauthorised access points, weak security infrastructures, etc.) in machine learning approaches within adversarial circumstances. They will prioritise increasing their understanding of these vulnerabilities in machine learning algorithms. They’ll also engage with machine learning specialists to design and implement effective action steps to address these vulnerabilities. Juniper Research believes, moving forward into 2019 and beyond, that adversarial machine learning will be required by numerous industries to: · Identify weaknesses of machine learning algorithms during the learning and identification process · Enforce the protection and integrity and validity of data in these systems · Action steps in response to specific threats · Assess the potential damage of these threats · Programme algorithms to enhance their resistance to viruses · Eliminate the presence of opaque ‘black boxes’ · Grant adequate time to algorithm developers to invest into ‘breaking’ the efforts of cybercriminals to infect data Related Research: Online Payment Fraud: Emerging Threats, Segment Analysis & Market Forecasts 2018-2023.
2019
Top Tech trends 2019
Juniper Research
Advances in Simulation
Advances in social science, behavioural science and mathematical modelling will combine, leading to more informed decision making. Advanced processing techniques and computational power will permit a more comprehensive level of modelling, potentially enabling more effective pattern recognition. This is likely to improve the identification, representation and explanation of systems and processes. As a result, simulation will become an increasingly powerful tool to aid policy and decision makers. Simulation will also blur the line between virtual and real environments.
2010
Global strategic trends - out to 2040
UK, Ministry of Defence
Advances in Material Science
The design and manufacture of materials at the molecular level will result in ‘designer’ materials, with in-built capabilities to sense and modify their behaviour or functionality, introducing a new manufacturing paradigm. Most advances are likely to occur where material science combines with, or adopts, principles employed with other innovative disciplines including electronics, nanotechnology and biology.
2010
Global strategic trends - out to 2040
UK, Ministry of Defence
Advanced Robotics – The Rise of the Super Machine
Advanced robots are featured in many science fiction films and are probably 10-15 years away from mainstream, with new materials, fuel cells, motors, algorithms, sensors and designs. They would feature many aspects of true AI, like working fully autonomously, sensing the environment, recognizing and solving problems and learning from their environment and from humans. Some of the advanced robots may have humanoid appearances but the majority will probably have special functions and look more like machines or will merge into the background. Most of the advanced robots will interact with humans using voice, gesture, face/emotional recognition and neurolinks. We expect many smart robots to work collaboratively with humans and the upcoming of transhumanism, i.e. the merging of man and machine into cyborgs. Applications for advanced robots would be extensive, going beyond the first wave of automation and optimization, into an economy operated in large parts by machines and/or human-machine units. We would either have solved the ethical questions by setting up robot laws or the questions that we see around contemporary machine learning and robotics would be even more pressing, such as the borders between humans and machines: do we allow robots to control humans, how can we guard us against robot mistakes, if we will allow smart robots to design and build themselves and how we would stay in control.
2018
Trend Report 2018 - Emerging Technology Trends
SAP
Advanced robotics
Increasingly capable robots with enhanced senses, dexterity, and intelligence used to automate tasks or augment humans
2013
Disruptive technologies: Advances that will transform life, business, and the global economy
McKinsey
Advanced oil and gas exploration and recovery
Exploration and recovery techniques that make extraction of unconventional oil and gas economical
2013
Disruptive technologies: Advances that will transform life, business, and the global economy
McKinsey