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High Impact Future Technologies, Data Trends and Innovation

New technologies, emerging digital innovations and trends in data, data analytics and cybersecurity are developing at a rapid pace. These will shape the future of business, trade, politics, the economy and society. Chief Executive Officers (CEOs), Data Protection Officers (DPOs), Chief Data Officers (CDOs), Chief Information Officers (CIOs), Chief Information Security Officers (CISOs), Boards  and Senior Leaders must understand these developments, assess their competitive advantages, manage  inherent risks and track the evolving governance and security implications. Automation, Artificial Intelligence (AI) Ethics, Blockchain, Data Bias, Differential Privacy, Digital Twins, Edge Computing, the Metaverse, Ransomware and Zero Trust Architecture and Security will increasingly lead the conversations in technology. These are set to grow exponentially, diversify and create lasting impacts. Here are the definitions of these key technologies, innovations and digital trends:  

Automation describes the increased use of sophisticated technologies that minimise or eliminate human input. This includes business process automation (BPA), IT automation, robotics and personal applications such as the automation of private homes and self-driving cars. Automation is driven by a range of technological features and applications of data science, engineering, algorithms, blockchain, machine learning, deep learning, industrialised robotics and artificial intelligence.

Artificial Intelligence (AI) Ethics are a group of values, principles, and techniques that apply widely accepted standards to guide ethical and moral conduct in the development, use and outcomes of AI systems. These disciplines seek to address the individual and societal harms AI systems might cause. AI ethics mitigates these harms by offering leaders, developers, engineers and project teams the values, principles, and techniques needed to produce more ethical, fairer, and safer AI applications.

Blockchain is a decentralised, distributed, and often public, digital ledger made up of records called blocks that are used to record transactions across many computers so that each block cannot be later altered, without changing all other blocks. This allows the participants to verify and audit transactions independently and relatively cheaply. Each block contains a cryptographic hash of the previous block, a timestamp, and transaction data. Blocks contain information about the blocks preceding it, forming a chain, each additional block reinforces the ones before it. A blockchain database is managed autonomously using a peer-to-peer network and a distributed timestamping server. They are authenticated by mass collaboration, powered by collective self-interests. Blockchains are growing in popularity through cryptocurrencies, especially using the Ethereum blockchain, and via the creation, sale, collection and distribution of Non-Fungible Tokens (NFTs).

Data Bias is any trend or deviation from the truth in data collection, data analysis, interpretation and publication which can cause false conclusions. Bias can occur intentionally or unintentionally. A biased dataset, for example in machine learning, does not accurately represent a model’s use case, resulting in skewed outcomes, low accuracy levels, and analytical errors. Types of bias include association bias, exclusion bias, measurement bias, observer (confirmation) bias, recall bias, racial bias, sample bias and sexual (gender) bias.

Differential Privacy is a mathematical technique of adding a degree of controlled randomness to a dataset to prevent the release or extraction of information about individuals in the dataset. This allows researchers and analysts to extract useful insights from datasets containing personal information while also offering stronger data privacy protections.

Digital Twins are digital replicas or representations of physical objects, such as a machine or person, or an intangible system, like a business process, that can be examined, altered and tested without interacting with it in the real world and avoiding negative consequences. The Digital Twin often spans the lifecycle of the object, person or system, is updated from real-time data, and uses simulation, machine learning and reasoning to aid decision-making.

Edge Computing is a distributed computing architecture framework where an organisation’s applications are closer to data sources such as Internet of Things (IoT) devices or local edge servers. The closeness to data at its source can deliver strong business benefits, faster insights, improved response times and better use of bandwidth.

The Metaverse is a unified way for people, data and things to interact in the virtual, physical and spacial environments. It is a collection of systems and interfaces combining computer screens, avatars, virtual reality, augmented reality, internet of things, robotics, artificial intelligence and automation. The term originates from science fiction, specifically from Neal Stephenson in Snow Crash in 1992 and the work of William Gibson.

Ransomware is malicious software, or malware, that stops organisations and computer users from accessing their computer files, systems or networks. This is accompanied by a demand for financial ransom payments to restore access to systems, unencrypt databases or return data. Ransomware can be introduced to a computer or system by users accidentally downloading ransomware by opening email attachments, clicking on advertisements, clicking on hyperlinks or visiting a website that has been deliberately infected with malware. Ransomware attacks can cause significant disruption to IT operations. Critical business information and personal data can be lost. Ransomware attacks can be initiated by state actors and by opportunistic hacktivism. In most cases, ransomware is part of international cybercrime and organised crime.

Zero Trust Architecture and Security uses zero trust principles to plan business, industrial and enterprise infrastructure and workflows. Zero trust architecture is created on the premise “never trust, always verify.” Zero trust assumes there is no implicit trust granted to assets or user accounts based solely on their physical attributes, presence on the network or asset type. Authentication and authorisation of individuals and devices are discrete functions performed continuously before access to an enterprise resource is established. Zero trust is a response to enterprise network trends that include remote users, bring your own device (BYOD), working from home, and cloud-based assets that are not located within an enterprise-owned network boundary. Zero Trust Security is a cybersecurity strategy in which information security policy is applied based on context established through least-privileged access controls and strict user authentication. Trust is not assumed.  A mature best-of-breed zero trust architecture can create a simpler network infrastructure, better user experience, and improved cyber defence.

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