Image source: Eco Life (https://www.ecolife.zone/)

By Rohit Talwar, Steve Wells, and Alexandra Whittington

Fast Future’s Life in 2025: “Say Hello Say Goodbye” Scenarios were developed in partnership with Huawei Consumer Business Group. This latest scenario explores how a range of exponentially advancing technologies such as AI and big data could transform the way we relate to family and friends.

By 2025, a combination of the power of 5G and a range of immersive and connected technologies should allow us to take part in celebrations with friends and family across the world.

By 2025, technology innovation should enable family members across the planet to work together to create a multisensory immersive birthday experience. Everything from the way we sustain connection, through to how we care for the elderly will be subject to radical change resulting from the rapid pace of advance in these core technologies.

Distance won’t be an issue when it comes to meeting up, with 5G allowing us to spend more time together. Immersive and connected technologies could help us to take part in virtual celebrations with friends and family across the world. Video calls will evolve through AR to allow you to experience multi-sensory communication with family even from thousands of miles away.

Say goodbye to…

• Missing family celebrations – hug grandma on her 80th birthday while you are 12,000KM away, smell the flowers you sent her, and taste the sumptuous birthday dinner.

Using the rapidly advancing developments in brain wave interpretation technologies, our grandparents could recreate multi-sensory experiences from their past to share with younger generations. Combining images and even videos with touch, smell, taste, and emotional sensations, once forgotten experiences can be brought to life. This could be supplemented by AI technology, drawing on internet searches for additional information to fill in the historic context.

Technology could also help bring back the element of surprise around special occasions such as birthdays – rather than giving out wish lists or receiving money. AI located within our devices, might talk to the AI of our friends and family members – sharing what we might like as a gift, based on the AIs knowledge of our current interests and the things we’ve been absorbed by.

Say goodbye to…

• Regifting of unwanted presents – by 2025, all gifts can truly be a surprise because our AI has communicated our desires secretly to our loved ones.

Technologies such as AI might also help increase inter-generational bonds by translating the words, phrases and concepts used by one generation into something the other might understand and relate to.

Visualisations from AR and VR tools might make family histories more interesting to young people and help the elderly deal with memory problems. Storytelling at family events might involve recalling imagery or sounds conjured up with digital technology or smart speakers in real-time.

Say goodbye to…

• Forgotten experiences – the interconnected, smart home of the future may be outfitted to display family photos and videos on demand at all times, perhaps with special holiday settings for family gatherings.

The authors are futurists with Fast Future – a professional foresight firm specializing in delivering keynote speeches, executive education, research, and consulting for global clients on the emerging future and the impacts of change. To arrange a presentation on the Life in 2025 scenarios please contact

To access more of our articles and learn more about our work please visit www.fastfuture.com

You can find summaries of the ten scenarios here https://consumer.huawei.com/uk/campaign/truestories/tech/

Image:https://pixabay.com/illustrations/children-family-network-web-4685126/ by geralt

By Rohit Talwar, Steve Wells, and Alexandra Whittington

Fast Future’s Life in 2025: “Say Hello Say Goodbye” Scenarios were developed in partnership with Huawei Consumer Business Group. This latest scenario explores how a range of exponentially advancing technologies such as AI and big data could transform leisure.

In a world where the demands and temptations of technology are challenging us as we seek to keep up, whilst retaining a sense of control over our time and actions, technology itself may play a vital role in life management. For example, the ability to use digital for work, play, learning, and socialising anywhere and everywhere means the potential for no natural downtime and so, using technology to help us decouple from the digital world is key.

Technology could become a trusted gatekeeper – barring our access to social media so we can sleep and by auto responding to work emails and texts, ensuring that we don’t have to answer them late into the night. This AI technology might also pre-emptively manage our schedule, protect our personal time, and create space for thinking and completing our own tasks alongside the seemingly never-ending demand for meetings.

• Say goodbye to…Unproductive social media scrolling – our smartphones could help direct us to the most interesting content according to our interests, highlight where we’ve missed an important update or event invite from a friend, and give us a gentle nudge to reconnect with those we might have inadvertently lost touch with.

With our friends, the technology will help take over the tasks of arranging nights out, managing event budgets, and organising activities for a group of two or more people. On the night, AI will take care of splitting the bill, so that it is either divided equally or everyone pays their fair share according to their actual consumption – even keeping track down to the amount of wine each person drank.

Party planning might be completely stress-free with an AI assistant in charge. Imagine the surprises in store if you were to let a robot plan your birthday celebration. All our special memories and events could be digitally captured to be re-experienced someday in VR. In 2025, we might attend entirely AR-based parties with scavenger hunts, enjoying hired appearances by holograms of celebrity guests (dead or alive), or use the immersive technology to attend live social events virtually.

• Say goodbye to…Boring events – might be eliminated as AI technology can produce endless scenarios for entertainment.
• Absent friends – fewer friends might flake on special events, so that more socialisation, not less, could be the outcome.

The advent of AI powered and 5G enabled AR and VR would allow us to accumulate new experiences while relaxing at home within fully immersive environments, enabling us to explore, interact, learn, and experience things we might never be able or willing to do in the real world. This might also enable us to enjoy truly immersive experiences, virtually connecting us with friends, family, and loved ones when we can’t be together, or even starting relationships with someone we had not physically met.

Technology could increasingly free up leisure time, with AI, drones, and domestic robots taking on more domestic tasks – from cleaning and washing clothes to compiling tax returns and trip planning. That free time could be invested in learning to sing, compose music, develop craft skills, or acquire new languages. These learning experiences would all take place under the careful guidance of an unwaveringly supportive and enthusiastic AI AI tutor with infinite patience.

Since making beautiful things may be easily automated in-home, a future hobby might be producing art with an AI assistant that can write songs or paint. An AI guide could make pastimes like sewing or crafting easier for those who are not artistic but enjoy making unique items – this may also be true for older people whose eyesight or motor skills are in decline.

3D printers might put the power to create beautiful home décor into the hands of more people, even allowing amateur designers to grow their hobby into a side business. We may be enabled to beautify our world and improve our lives in our free time thanks to smart tech at our fingertips.

• Say goodbye to…Mass-produced goods – which may become gauche, as personal design skills expand. Producing things may replace the activity of buying things. For some, ecological considerations and the commitment to recycle would be coupled with the desire to engage in crafts and bring their personal creativity to bear. This could lead to a big rise in the maker movement. We could also see less inclination to shop frivolously for things in the home, with a greater personal meaning behind and investment in the items we create. This might improve the perceived value of the regular things we do own.

The authors are futurists with Fast Future – a professional foresight firm specializing in delivering keynote speeches, executive education, research, and consulting for global clients on the emerging future and the impacts of change. To arrange a presentation on the Life in 2025 scenarios please contact

To access more of our articles and learn more about our work please visit www.fastfuture.com

You can find summaries of the ten scenarios here https://consumer.huawei.com/uk/campaign/truestories/tech/

Image: https://pixabay.com/images/id-1384758/

By Steve Wells

The opportunity to use “21st Century Common Sense” – in this case, Collective Intelligence (CI) – to tackle complex social challenges was considered at Nesta’s event on 16th October. The basic proposition here is that we deploy a fraction of our collective intelligence when addressing society’s biggest challenges, so the event sought to explore how to address such challenges, “through better design, asking how we can tap into the collective wisdom of a place, organisation or market and what new combinations of human and machine intelligence can help us do this at scale.”

What is Collective Intelligence?

Nesta defines collective intelligence as, “something that is created when people work together, often with the help of technology, to mobilise a wider range of information, ideas, and insights to address a challenge,” particularly where the challenge is of a societal nature.

Collective intelligence is the result of a process, data, technology (artificial intelligence, machine learning), and people working toward the resolution of a specific problem

What can Collective Intelligence Achieve for us?

Clearly the basic premise is on bringing together the complimentary capabilities of humans and machines to achieve a better outcome than possible by either going it alone. Despite the rapid progress made in the fields of artificial intelligence (AI) and machine learning (ML), data still needs to be sourced, and sense made of the analysis to support human focused decision making. These are the areas in which humans excel – for now at least.

While the focus with the projects discussed at the event as exemplars of CI in action included public sector engagement both operationally (real time information provision) and consultatively (local government priority setting), CI has applicability in helping to resolve wicked problems more widely and in areas such as participative foresight / futures work.

The notion of “swarm AI” can empower groups with conflicting political views reach satisfactory outcomes where the machine can help participants to reframe challenges and help them find the points of common concern. This raises the future possibility of automating decisions made through democratic processes. (Well, it couldn’t be worse, could it?)

But we must be clear about the purpose here, which is to design the process and the technology to extend human capabilities. Artificial intelligence and machine learning can help to provide insight from unstructured data, conduct analysis, and make predictions but it should enable humans to better understand problems, decentralise (leaderless?) participation, and seek real solutions through networked intelligent action.

How do we Start and Enable Successful Collective Intelligence?

For all the talk about AI and ML, what particularly struck me were the required human behaviours. We talk about collaboration and partnership between “man and machine” for effective CI, but – for the time being at least – collaboration and partnership are human traits. Effective real time collaboration / partnership is the result of a process, behaviours, and outcome. So the underpinning human behaviours will remain valid; listening, enquiring, engaging, thinking, sense-making, empathy, suspending assumptions, honesty, mutuality, respect, and valuing differences as well as similarities.

Our process can then focus on ways to support collaborative thinking about how we work with machines, and how we want AI/ML to enable better discussion outcomes. I noted this range of process characteristics:

• Asking the right questions to build understanding and inform AI
• Develop the AI to support human/machine interaction
• Deploy double-loop learning for both machines and humans
• Crowdsource ideas
• Understand how we mobilise data, insight, intelligence, and ideas to help solve problems
• Be clear on issues concerning data ownership, its use, privacy, and the cultural context with which it is gathered and used.

The critical enabling areas are in software development where for many organisations operating in the social space revolves around open source, skills, and cooperation.

Machine learning plays a significant role in teaching the system to interpret the data in the correct way given the problem being addressed. Collaborative working is a dual challenge with both how the software is designed to work with humans and how the humans support their work with each other. Both will need the appropriate skills development through education and training. Skills such as sense-making, systems thinking, contextual sensitivity, collaborative working, working with ambiguity, foresight, and scenario thinking are crucial.

Case Examples

A number of CI case examples were presented at the event that demonstrated a breadth of deployment, approaches, and societal situation. Evidence suggests that CI leads to better engagement, greater satisfaction, and better outcomes in part by machine aggregation and organisation of data gathered by people.

The characteristics and areas of CI deployment included:

• Enabling more consultative democracy
• Analysing socially collected data
• CI at the institution level
• Influencing local service priorities through a consultative exercise to inform politicians
• Creative solutions outside of government – distributed “authority” / crowdsourced “authority”
• Creation of digital platforms for collaborative engagement between people and politicians to improve trust and transparency and encourage engagement
• Support the re-distribution of power through possible citizens assemblies
• Filling crucial data gaps via social media
• Helping to understand how achievement of the UN Sustainable Development goals might be measured to help hold countries to account.

Collective Intelligence Design Playbook (beta)

For more information about Nesta’s work in the field and to help you design and deliver a collective intelligence project you can download the Collective Intelligence Design Playbook here.

Questions

Here are three questions that the event posed for me:

• How do you currently maximise the collective intelligence capability of your organisation/enterprise?
• Which components – process, data, technology (artificial intelligence, machine learning), and people – need further development in your organisation to run a CI project?
• What challenges and opportunities do you face that are best suited to a CI approach?

Image: https://pixabay.com/illustrations/binary-code-privacy-policy-woman-2175285/

By Steve Wells

The challenge of enabling a “fairer future of work” was addressed at Nesta’s event back in October. A world experiencing exponential change as digital and other technologies challenge our perspectives on life, society, business, the world of work, the nature of jobs, and the notion of “fairness” in the context of work – and even “work” itself – is the context.

It’s hard to generalise about employment trends globally but many developed economies are enjoying close to full employment, or low levels of unemployment. Our political and economic systems and processes are geared to creating an environment that seeks to provide full employment. But there is uncertainty about how sustainable that model is, which begs the question, what then?  

The Changing Nature of Work

Based on the analysis of trends in work, the changing nature of work, evolution of new business sectors as old traditional industries die, ideas of how we prepare for new jobs, where the new jobs are created, and how cohorts of existing workers are retrained to allow them to access employment opportunities were the focus of the discussion. The use of new technologies such as artificial intelligence (AI) and Big Data were behind ideas linking candidates’ experiences, skills, and qualifications with job opportunities and training interventions.

There’s clearly a benefit in bringing data sets together to inform faster decisions about the evolving jobs market now. Better data, better information, better insight, better matching of people to jobs to support the development of near term policy and action.

However, there’s a “but”. I understand the benefit of extrapolating from the past to create insights about the evolution of the jobs market and the world of work. I understand the benefit of seeking new data sets, and bringing them together to help generate even more insight. But, will a focus on analysing and extrapolating from the past alone, help us prepare adequately for the future; especially if that future is radically different?

The Future of Work

If we look at the number of studies into the future of work we see a significant range of possibilities from increasing levels of employment through jobs created by new technologies and new industry sectors, the radical redesign of many existing jobs, to potentially many jobs displaced by automation technologies.

So for me, the question is how can we use foresight to pressure test the assumptions we draw from extrapolating trends in jobs, work, and the jobs market? What are the societal options we may need to consider to ensure that people continue to live fulfilling lives? How does the nature of education and training change in a world where we are uncertain about the future of employment? And within the recruitment sector, how do we address the rebalancing of technical skills with softer skills and human experiences?

The event demonstrated a number of valuable partnerships across government (DoE / DWP) and between NGOs and government. These partnerships become increasingly important given the likely change of emphasis in the skills required for the future world of work. For example, if many businesses are using the same automated / AI-enabled systems and products and services have a very similar look and feel, how will we differentiate our offerings to customers and clients? Can we re-align people to study a new portfolio of skills where the balance tips from technical to creative and so called soft skills? Even now, the question of assessing a candidate’s soft skills is increasingly pertinent. Is the recruitment sector truly capable of integrating soft skills into the selection process?

Fairness

The notion of “fairness” is crucial in that access to work and jobs must be made on the ability of the candidate to fulfil a given role and not on the candidate’s ability to access the right technology. So the democratisation of technology through ubiquitous connectivity is one example of how national infrastructure needs significant improvement to support a fairness expansion. Access to skills training enabling more people to use technology as well as access to the technology itself needs to be addressed.

There was discussion about the applicability of some technologies in supporting “fairness” including the effectiveness of facial recognition with darker skin tones. Which begs a question of the development of algorithms and specially the audit of them to ensure they are technically capable of operating without bias.

Preparing People Better for Future Jobs

The question here is, can the effective use of jobs and work data be used to prepare people better for future jobs?

Here, the idea of a “commons data set” accessible widely would allow candidates, employers, recruiters, educators, and policy makers to review evolving business sectors and more effectively match people and jobs – and even provide support where start-ups would have access to the right talent pool.

But the question of how to prepare for the longer term future remains.

At what point, for example, do we need to switch from a technical focused education system to one focused on more human skills; coaching, facilitation, motivation, mind-set and leadership, creativity, collaboration, problem solving, systems thinking etc.

Future job systems also need to factor in attitude as well as technical skills. The labour market of the future is likely to have to become more flexible, resilient, supported by suitable training and retraining, and a much better understanding of the dynamics that will underpin the jobs market in an increasingly digitised society subjected to exponential change.

Questions

Here are four questions that the event posed for me:

• How do organisations effectively assess soft skills and attitudes when recruiting new employees?
• What needs to happen to effectively match workers in the gig economy with work opportunities?
• What role should foresight play in setting the context for future focused education and training policy and design?
• What is the optimal balance between system and process automation and personal interaction in matching people with work opportunities?

Image: Alexas Fotos – https://pixabay.com/photos/figures-professions-work-funny-fun-1372458/

Image: https://pixabay.com/images/id-472496/ by suc

By Rohit Talwar and Helena Calle

How can we tackle gender imbalance in the personalities of AI learning tools?

The Gendering of AI

The expected growth in use of artificial intelligence (AI) in learning applications is raising concerns about both the potential gendering of these tools and the risk that they will display the inherent biases of their developers. Why the concern? Well, to make it easier for us to integrate AI tools and chatbots into our lives, designers often give them human attributes. For example, applications and robots are often given a personality and gender. Unfortunately, in many cases, gender stereotypes are being perpetuated. The type of roles robots are designed to perform usually reflect gendered over generalizations of feminine or masculine attributes.

Feminine personalities in AI tools such as chatbots and consumer devices like Amazon’s Alexa are often designed to have sympathetic features and perform tasks related to care giving, assistantship, or service. Many of these applications have been created to work as personal assistants, in customer service or teaching. Examples include Emma the floor cleaning robot and Apple’s Siri your personal iPhone assistant. Conversely, male robots are usually designed as strong, intelligent and able to perform “dirty jobs”. They typically work in analytical roles, logistics, and security. Examples include Ross the legal researcher, Stan the robotic parking valet and Leo the airport luggage porter.

Gendering of technology is problematic because it perpetuates stereotypes and struggles present in society today. It can also help reinforce the inequality of opportunities between genders. These stereotypes aren´t beneficial for either males or females as they can limit a person´s possibilities and polarize personalities with artificial boundaries.

Response Strategies

We propose four strategies to help tackle this issue at different stages of the problem:

• Mix it up – Developers of AI learning solutions can experiment with allocating different genders and personality traits to their tools.
• Gender based testing – New tools can be tested on different audience to assess the impact of say a quantum mechanics teaching aide with a female voice but quite masculine persona.
• Incentives for women in technology – By the time we reach developer stage the biases may have set in. So, given the likely growth in demand for AI based applications in learning and other domains, organizations and universities could sponsor women to undertake technology degrees and qualifications which emphasize a more gender balanced approach across all that they do from the make-up of faculty to the language used.
• Gender neutral schooling – The challenge here is to provide gender neutral experiences from the start, as the early stages experiences offered to children usually perpetuate stereotypes. How many opportunities do boys have to play with dolls at school without being bullied? Teachers’ interactions are crucial in role modeling and addressing “appropriate” or “inappropriate behavior”. For example, some studies show teachers give boys more opportunities to expand ideas orally and are more rewarded to do so than girls. Conversely girls can be punished more severely for the use of bad language.

A version of this article originally appeared in Training Journal.

Image: https://pixabay.com/images/id-3950719/ by john hain

By Rohit Talwar, Steve Wells, Alexandra Whittington, April Koury, and Helena Calle

On the first day of Christmas in 2019, my true love sent to me: An AI gift-giver assistant on my smartphone to help me pick the best presents for my loved ones.

On the first day of Christmas in 2020, my true love sent to me: A smart Christmas card that changes its shape and greeting on each of the 12 days of Christmas.

On the first day of Christmas in 2021, my true love sent to me: A Cooking robot who prepared our Christmas dinner, including a 3D printed Christmas pudding.

On the first day of Christmas in 2022, my true love sent to me: My family arriving in autonomous cars and personal drones, robot Christmas carolers, and an augmented reality Santa who delivers every present.

On the first day of Christmas in 2023, my true love sent to me: A live holographic representation of my extended family from across the world, sat around our dinner table.

On the first day of Christmas in 2024, my true love sent to me: My first nutritionally customized laboratory -grown turkey with all of the vegetables sourced from a local vertical farm.

On the first day of Christmas in 2025, my true love sent to me: A fully immersive physical and visual experience of Charles Dickens’ A Christmas Carol, including experiencing the smells and sounds of walking through London’s cold, misty streets.

This article was published in FutureScapes. To subscribe, click here.

Image: https://pixabay.com/images/id-4699007/ by dp792

By Rohit Talwar

Life in the digital age is raising fundamental questions about the future of business and employment and hence the strategies, skills, and abilities we need to develop to survive in the next economy. This article explores two key changes that we need to start developing a core of capabilities for – namely the quest for exponential growth and the growing use of corporate venturing.

Why are these becoming important? Well, technology and the thinking it enables are driving new ideas and experiments on commercial strategies, the shape and structure of organisations, business models, and the relationship with extended ecosystems of partners. Both strategies are seen as options to drive growth and accelerate the realisation of market opportunities.

Exponential thinking is seen as a fast track approach to driving business innovation and growth. We are used to the idea of exponential growth in many fields of science and technology. For example, Moore’s Law in information technology tells us that the amount of computer power we can buy for £1,000 doubles every 18-24 months. This has inspired digital innovators to try and grow their business at the same pace or faster than the underlying technologies. The broader business world is taking notice. The stellar rates of development and growth we are witnessing for some exponential businesses in the digital domain are encouraging many organisations across literally every sector from banking to aviation to try and apply similar thinking to some or all of their activities.

Hence, it is now common to see businesses pursue a vision of doubling of revenues within three to four years and a achieving a 2-20X or more improvement in other aspects of the business. For purely digital entities, their business models are predicated on using network effects to drive exponential growth or better in user numbers and revenues. Some suggest that to embrace the exponential model, businesses must reject defined end goals and step-by-step plans in favour of such ambitious visions and develop a high tolerance of uncertainty. Typically, the exponential growth initiatives are driven through a combination of iterative task specific ‘sprints’ to define, test, refine, and deliver business changes that could result in massive performance improvements in specific areas of the business.

At the overall business level, exponential revenue growth is a function of trying a variety of experiments to take current and possible new offerings to existing and potential customers, trialling different pricing models and routes to market, and engaging ideally the whole firm in the search for new opportunities. The aim is to try a portfolio of experiments, each of which delivers a 1-2% annual improvement in revenues. The process, if repeated annually, can lead to exponential growth within a relatively short timeframe. The critical learning enablers for both exponential approaches are curiosity and the relinquishing of restraining assumptions, learning how to work at speed, a willingness to experiment, training of staff to help them become opportunity spotters and creators, and effective portfolio management.

Corporate venturing and intrapreneuring are seen as ways of buying ourselves faster learning and growth. As organisations wrestle with finding the right path to the future, we can expect a growing focus on the use of corporate venturing, or corporate venture capital. This is basically the investment of funds in external start-up companies. Typically, this is either focused on investments in firms that could enhance the core business, enterprises in adjacent sectors, or ventures that could potentially disrupt and compete with the existing entity.

This business model may become increasingly popular as firms look to these startups to help speed up knowledge acquisition, learn about new technologies, accelerate entry to new markets, or access critical skills and resources. Core to the success of such models are intrapreneurs and venture managers who can help the ventures gain the support they need from the core business without the imposition of unnecessary central processes and controls. Alongside these venture management skills, success requires internal leaders and functional heads to have the ability to collaborate with new ventures which might threaten their existing business.

We are on an uncertain path through an almost unknowable future. Experiments to test such new strategic innovation approaches are only likely to increase as the pace of change accelerates. This creates an exciting opportunity for learning and development to get ahead of the game and identify the skills we might need to drive the next waves of experimentation and change.

This article was published in FutureScapes. To subscribe, click here.

A version of this article originally appeared in Training Journal.

Image: https://pixabay.com/images/id-2133976/ by Javier-Rodriguez

By Rohit Talwar

How will learning and development cope with the growing trend of humans augmenting their basic capabilities with chemical, electronic, physical, and genetic enhancements?

We’ve been entertained by a never ending stream of Marvel and DC Comics characters with super powers ranging from x-ray vision to mind control. Many of us have also spent time fantasising about the additional capabilities we’d like to help see us through the day. But what happens when those boundaries blur between science fantasy and everyday reality?

The practice of human enhancement or augmentation is a phenomena well underway across society – although the concept may be new to many of us. Over the next 25 years, the integration of information and communications technologies (ICTs), cognitive science, new materials, and bio-medicine could fundamentally improve the human condition and greatly enhance human intellectual, physical, and psychological capacities. As a result, the notion of the “transhuman” could emerge. For example, we are well underway with the process of augmenting human beings’ cognitive and intellectual abilities through technological implants, such as memory storage. These enhancements mean humans could achieve heightened senses and biological capabilities that are largely the prerogative of other species (e.g. speed, resistance, adaptation to extreme conditions, etc.).

The speed of development is truly mind blowing. Advances in cognitive enhancement drugs and “nootropic” supplements, electronic brain stimulation techniques, genetic modification, age extension treatments, 3D printed limbs and organs, and body worn exoskeletons, have given rise to the notion of enhancing the human brain and body well beyond the limits of natural evolutionary processes. Indeed, many leaders in the field of AI are fierce advocates of Transhumanism as the next stage of human evolution—arguing that if humans want to keep up with AI, we ourselves will have to become machines—embedding technology in our brains and bodies to give us similar levels of processing power.

There is already evidence of the growing use of ADHD and sleep disorder drugs like Ritalin, Adderall, and Modafinil to enhance concentration and mental agility in the workplace and by students of all ages. So how do we cater for the learning needs of a workforce which is enhancing its capacity to learn and retain information at speed and perform better at manual tasks?

We are still in the early stages of addressing the enhancement challenge, but here are five practical guidelines for L&D.

1. Encourage employees to make clear if they are pursuing any form of enhancement so L&D solutions can be tailored
2. Encourage those employees to find their own learning resources that best fit their enhanced capabilities and use simulation and self-managed tools that allow learners to cover the materials at their own pace
3. Recognise and plan for the disruption that can take place when enhanced participants are sharing the same classrooms and workshops as standard issue Humans 1.0
4. Work with the enhanced individuals to develop alternative learning materials that allow for their augmented capabilities to be used to the full
5. Work with HR and corporate leadership to establish clear policies around the organisation’s approach to enhancement.

Whatever we may think personally, the practice of enhancement is well on the way to becoming an observable and growing trend in society, getting ahead of the curve here is critical if we don’t want to find ourselves unable to cater for the emerging Storm (or Dr Strange).

This article was published in FutureScapes. To subscribe, click here.

Image: https://pixabay.com/images/id-2127669/ by EliasSch

By Rohit Talwar

We’re at a fascinating point in the discourse around artificial intelligence (AI) and all things “smart”. At one level, we may be reaching “peak hype”, with breathless claims and counter claims about potential society impacts of disruptive technologies. Everywhere we look, there’s earnest discussion of AI and its exponentially advancing sisters – blockchain, sensors, the Internet of Things (IoT), big data, cloud computing, 3D / 4D printing, and hyperconnectivity. At another level, for many, it is worrying to hear politicians and business leaders talking with confidence about the transformative potential and societal benefits of these technologies in application ranging from smart homes and cities to intelligent energy and transport infrastructures.

Why the concern? Well, these same leaders seem helpless to deal with any kind of adverse weather incident, ground 70,000 passengers worldwide with no communication because someone flicked the wrong switch, and rush between Brexit crisis meetings while pretending they have a coherent strategy. Hence, there’s growing concern that we’ll see genuine stupidity in the choices made about how we deploy ever more powerful smart technologies across our infrastructure for society’s benefit. So, what intelligent choices could ensure that intelligent tools genuinely serve humanity’s best future interests.

Firstly, we are becoming a society of connected things with appalling connectivity. Literally every street lamp, road sign, car component, object we own, and item of clothing we wear could be carrying a sensor in the next five to ten years. With a trillion plus connected objects throwing off a continuous stream of information – we are talking about a shift from big to humungous data. The challenge is how we’ll transport that information? For Britain to realise its smart nation goals and attract the industries of tomorrow in the post-Brexit world, it seems imperative that we have broadband speeds that puts us amongst the five fastest nations on the planet. This doesn’t appear to be part of the current plan.

The second issue is governance of smart infrastructure. If we want to be driverless pioneers, then we need to lead on thinking around the ethical frameworks that govern autonomous vehicle decision making. This means defining clear rules around liability and choice making on who to hit in accident. Facial recognition technology allows identification of most potential victims and vehicles could calculate instantly our current and potential societal contribution. The information is available, what will we choose to do with it? Similarly, when smart traffic infrastructures know who is driving, and drones can allow individualised navigation, how will we use their information in traffic management choices? In a traffic jam, who will be allowed onto the hard shoulder? Will we prioritise doctors on emergency calls, executives of major employers, or school teachers educating our young?

At the physical level, globally we see experiments with innovations such as solar roadways, and self-monitoring, self-repairing surfaces. We can of course wait until these technologies are proven, commercialised, and expensive. Or, we can recognise the market opportunity of piloting such innovations, accelerate the development of the ventures that are commercialising them, deliver genuinely smarter infrastructure in advance, of many competitor nations, and create leadership opportunities in these new global markets.

The final issue I’d like to highlight is that of speed. Global construction firms are delivering 57 storey buildings in 19 days and completing roadways in China and Dubai at three to four times the speed of the UK. The capabilities exist, the potential for exponential cost and time savings are evident. We can continue to find genuinely stupid reasons not to innovate or give ourselves permission to experiment with these new techniques. Again, the results would be enhanced infrastructure provision to UK society whilst at the same creating globally exportable capabilities.

As we look to the future, it will become increasingly apparent that the payoff from smart infrastructure will be even more dependent on the intelligence of our decision making than on the applications and technologies we deploy.

This article was published in FutureScapes. To subscribe, click here.

Image: https://pixabay.com/images/id-2564057/ by Stock Snap