Trends Identified
Digital Identities
Managing identity in an increasingly digital world The digital expression of identity grows increasingly complex every day. Not so long ago, an employee’s entire digital presence belonged almost exclusively to the employer, a practice that culminated in the mainframe ID. As enterprise technology expanded to include new tools and platforms, the number of digital identities grew. Today, many workers must manage a dozen or more user names and passwords across different roles on different systems to do their jobs.
2012
Tech Trends 2012-Elevate IT for digital business
Deloitte
Climate change
Man’s relation to earth is complex. Earth and nature determine the fate of mankind, but in turn mankind determines the fate of earth (nature) through technological advances and the extraction of natural resources, for instance, through large-scale deforestation, leading to less biodiversity and, consequently, desertification and erosion of the soil. Or through dumping plastic in the ocean (the infamous plastic soup). Ever since the seventies of the 20th century there has been a global debate on the limits of growth. Will tomorrow’s population be so large that it will exhaust the earth? Experts believe that climate change (through the greenhouse effect and global warming) will render specific regions on earth uninhabitable [Knox and Marston, 2011]. Weather conditions may become more unstable and more extreme. This will, for instance, increase the risk of large hurricanes and disastrous floods. Extreme heat and lack of water may turn specific parts of the world into deserts. Cities lying on the coast may disappear into the ocean.
2014
Horizon scan 2050
Netherlands, The Netherlands Study Centre for Technology Trends (STT)
The next generation distributed grid
Making distributed energy possible at scale will revolutionise the useability of (and market for) renewables, increase energy efficiency, and disrupt traditional carbon intensive power grids.
2017
Innovation for the Earth - Harnessing technological breakthroughs for people and the planet
PWC
New technologies and principles to develop the component base
Maintaining the rate of growth in the ICT sector globally requires continuous increases in the performance of computer technology. At present, the technological process to manufacture Information and Communication Technology semi-finished products and materials reached the atomic level, which is where the Pauli exclusion principle, the Heisenberg uncertainty principle and other fundamental positions in quantum physics limiting the potential to control elementary particles come into play. So as to avoid a collapse of ICT markets caused by a slowdown in the development of the hardware component, which would result in negative effects for the entire global economy, there needs to be timely industrial development of new technologies and principles to develop the component base. The research priorities in this context should be focused on the areas of nanotechnology (electronics based on graphene, fullerene, etc.), photonics and memrister technologies.
2016
Russia 2030: science and technology foresight
Russia, Ministry of Education and Science of the Russian Federation
Machine / robotics Automating common tasks
Machines and robotics are endowed with AI (programmed algorithms) to ful l set tasks and goals. These generally fall into two key categories: ‘speci c task-based AI’ (e.g. a web search engine or an autonomous vehicle) and ‘general AI’ that aims to replicate aspects of human intelligence (e.g. IBM’s Watson or humanoid robots like Honda’s ASIMO).
2017
Surfing the digital tsunami
Australia, Commonwealth Scientific and Industrial Research Organisation (CSIRO)
Specialized Artificial Intelligence And Machine Learning
Machine-learning driven automation will lead to a wide range of new business opportunities, Evans says, including many companies focused on single-purpose implementations of AI and automation. As well, he says, automation will provide a massive multiplier effect by being able to do the small tasks that thousands of people could do–like look for patterns in images. Kocher says his firm will continue looking for digital health companies with novel ways to reduce costs and improve outcomes. “We continue to look at things that take economic responsibility for the cost and outcomes of care, and use technology and data to make both of those better and more efficient.”
2018
The Most Important Tech Trends Of 2018, According To Top VCs
Fast Company
Machine Learning Coming to Verify Your Identity
Machine learning will come into its own as a technology underpinning digital identity. Identity verification still largely relies on manual processes, bringing documents into the bank. Machine learning maturing as a technology which can carry out suitable verification checks.
2018
Top Tech trends 2018
Juniper Research
Conversational Systems and User Interfaces –Talking to Machines
Machine Learning has reached a state in which conversational systems can have increasingly engaging and human like conversations. These chatbots or digital assistants use mainly natural language processing (NLP) to interact with humans but will use sight, sound, tactile, etc. in the near future as well. Conversational systems can be viewed as a step towards true personal virtual assistants and will replace most common interfaces, simplifying human-machine interactions and replacing less interactive interfaces. The technology will probably merge in part with Immersive technologies and will also leverage the digital network of sensors, appliances, and IoT systems to interact with humans. The chatbot ecosystem is already robust, with many different third-party chatbots, native bots, distribution channels, and enabling technology companies. Messaging platforms such as Facebook Messenger, WhatsApp, Tencent’s WeChat, Google Allo, Apple iMessage, Slack and Kik all use chatbots as well as voice-controlled consumer devices like Amazon’s Alexa, Apple’s Siri, Microsoft’s Cortana, Google Assistant and SAP Co-Pilot. While the focus is on consumer applications right now, especially based on mobile technologies, chatbots will go business very fast, allowing businesses to leverage the inexpensive and wide-reaching technology to engage with more consumers and to support, simplify and speed-up many business processes. Examples are commerce applications as taxi cab ordering (such as Uber), concierge facilities (such as Sephora), B2B contract workfl ows (such as Apttus), food ordering (such as Domino’s Pizza) and others. Use cases for chatbots are helping humans to use technology without the need to know technology like in navigating and exploring, automated customer services, and supporting functions for hand-busy tasks in fi eld service, logistics, maintenance, medicine and others.
2018
Trend Report 2018 - Emerging Technology Trends
SAP
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
On startups built on voice platforms
M.G. Siegler, general partner, Google Ventures. On startups built on voice platforms: I continue to be on the lookout for startups in the audible-computing space. The rise of Amazon’s Alexa and Google Home in 2018 has these devices in millions of homes already, and this holiday season should only accelerate that trend. I would include Apple’s AirPods in this general space as well. These are not niche products. But the jury is still out—people need to learn to use these devices beyond just listening to music or asking for the weather. I believe they will, especially as young people grow up with them integrated into their lives. It will take time, but I think the groundwork can be laid in 2019.
2019
The biggest tech trends of 2019, according to top experts
Fast Company