Futures – Scenarios, Options and Agency – Preliminary Results

A wide range of methodologies are available for predicting the future such as foresight. Such approaches have been widely deployed by organisations and governments to explore potential developments for purposes of planning, resilience, mitigation and adaptation. The differing methods employ a range of qualitative, quantitative and mixed methodology research tools. The future is subject to dynamic intervention as embodied in innovation and the phrase that ‘if you wish to know the future, design it’. The advent of widespread use of artificial intelligence, robotics, neurotechnology and continuous advance in each of the domains is impacting many if not all aspects of society. This review uses diverse methodologies to explore developments within a defined time horizon, a generation taken as approximately 25 years, focussed on 2050, across a range of domains and topics subject to multi, cross, inter and transdisciplinary practice. Although all domains are considered along with major influences on society, a focus is given to eight domains, medicine, robotics, photonics, materials, AI, space, physics and behavioural science, in particular, as representative examples of changes expected. Major societal and behavioural drivers identified in this presentation of preliminary data from the study include well-being, authenticity and sustainability, the steady influence of established philosophy and religion, emerging social media influences, thinking and developments arising from transcending our planetary boundaries, and the impact of disciplinary boundary morphing approaches on innovation in both established and emerging domains.

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Publication Details

Journal
Design for Augmented Humanity
Published
2026-03-12
DOI
https://doi.org/10.1177/29776481261426495
Primary Topic
Innovation, Sustainability, Human-Machine Systems
Type
article
Field-Weighted Citation Impact
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article

Futures – Scenarios, Options and Agency – Preliminary Results

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Design for Augmented Humanity
Innovation, Sustainability, Human-Machine Systems
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Futures – Scenarios, Options and Agency – Preliminary Results

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article en

Abstract

A wide range of methodologies are available for predicting the future such as foresight. Such approaches have been widely deployed by organisations and governments to explore potential developments for purposes of planning, resilience, mitigation and adaptation. The differing methods employ a range of qualitative, quantitative and mixed methodology research tools. The future is subject to dynamic intervention as embodied in innovation and the phrase that ‘if you wish to know the future, design it’. The advent of widespread use of artificial intelligence, robotics, neurotechnology and continuous advance in each of the domains is impacting many if not all aspects of society. This review uses diverse methodologies to explore developments within a defined time horizon, a generation taken as approximately 25 years, focussed on 2050, across a range of domains and topics subject to multi, cross, inter and transdisciplinary practice. Although all domains are considered along with major influences on society, a focus is given to eight domains, medicine, robotics, photonics, materials, AI, space, physics and behavioural science, in particular, as representative examples of changes expected. Major societal and behavioural drivers identified in this presentation of preliminary data from the study include well-being, authenticity and sustainability, the steady influence of established philosophy and religion, emerging social media influences, thinking and developments arising from transcending our planetary boundaries, and the impact of disciplinary boundary morphing approaches on innovation in both established and emerging domains.

Design for Augmented Humanity
Guangdong University of Technology (CN), Cornell University (US), University of Cambridge (GB), Imperial College London (GB), Delft University of Technology (NL), Tsinghua University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 29%
Innovation, Sustainability, Human-Machine Systems
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