Most of us spend the majority of our days on our phones, computers, tablets, and in front of our TVs. We also spend the majority of our days sitting or reclining, whether in our cars, at our desks, or on our couches. Just as humans are not meant to be wired all the time, we are not meant to be sedentary for most of our days. It’s not a coincidence that we are restless, stressed, anxious, and suffer constant back and pains.
Yoga can alleviate the stress, anxiety, and aches and pains that come with the digital age, says Peter Mico, a yoga leader and studio owner in Idaho. One of his specialties is training and teaching students with chronic pain. He is also the operator of Blue Earth Yoga, an institute for yoga, health, and longevity which holds retreats around the world that include Blue Zones principles and education. Some of these retreats are also held in blue zones regions. We recently talked with Peter about yoga, the Blue Zones lifestyle, and the yoga moves you can do anywhere, even at work.
How do you see yoga and Blue Zones research intersecting?
PETER MICO: Yoga is more than just a good workout. Just like some of the daily schedules and habits of the elder inhabitants in blue zones, yoga combines movement and stress relief. It’s about being mindful, being in the body, and being in the moment. In my experiences in the blue zones, the older generation is wonderfully grounded and present. So the practice of yoga helps brings us to a place that these cultures have achieved through their way of life, and one that is very different from our own modern lifestyles of constant distraction and stress.
In our society, it’s common for older people to fall and break a hip. Not so often in the blue zones regions. As Dan Buettner has showed us, centenarians in the world’s blue zones are gardening, weeding, and doing yard work well into their 90’s and 100’s. They haven’t spent their lives sitting in cars and desks, they’re regularly getting up and down from the ground. In this way, it’s as if they are practicing yoga all day and every day, promoting good muscle tone and strong bones with full-body movement.
Also, even though yoga is not a religion, it can be a spiritual practice. Even the practice of learning to breathe slowly and deeply from your diaphragm as you do in yoga is like meditation, besides being invigorating and helping to relieve stress. Blue Zones centenarians had spiritual lives even though they came from different religions, and reaped the benefits of regular prayer, meditation, and spiritual rituals.
Besides stress relief and learning to breathe properly, what are some of the other benefits of yoga?
PM: Driving in cars, sitting in the lounge chair watching TV, or hunched over a computer all day creates multiple problems for the spine. That’s a big reason why probably 80% of Americans suffer from lower back pain. Yoga can be very helpful to people with lower back problems, and as a preventive measure so you don’t develop back problems. Its emphasis on posture and alignment, particularly in the sacral complex, is the perfect remedy for these ailments of pain and discomfort. People come to us with major maladies of herniated disks, scoliosis and chronic muscular pain, and find relief after a steady practice of yoga.
The same is true of ‘mouse arm’ and the effects on the cervical spine, which is a big deal. Allowing the head to hang forward toward the screen, then tilting to look up, then extending the mouse arm forward, and then holding the pose for hours is a recipe for disaster for the cervical spine, especially the C4, C5, and C6 vertebrae. Yoga is a powerful practice for promoting healthy neck care.
Office, Desk, or Cubicle Yoga: 4 Essential Moves to Reverse “Computer Crouch” and “Mouse Arm”
For a typical office job of answering telephones and working at a computer, there are a couple of poses that you should do often.
Every 15 Minutes, Sitting Moves:
1. Elbow Hold:
Put your arms up over your head and hold your opposite elbows. Then move your held elbows in four directions: forward and backwards, from side to side, and in small back and forward bends. Do this for 20-30 seconds every 15 minutes.
2. Arm Twists:
Put your arms straight out to the sides with your thumbs up. Rotate our arms forward and then backwards so your thumbs are moving in a circular motion. Do this 10 times. Then repeat with your arms rotating in opposite directions from each other. Do this 10 times as well.
30 Minutes, Standing Moves:
1. Baby Backbends: Stand up and clasp your hands behind your back. Arch backwards gently as you open your chest and roll your shoulders back and behind you. Then turn your head side to side, 5 times. Then bend your ear towards your shoulder, 5 times on each side.
2.Arm Circles: Put your right hand on your right shoulder. Extend your left arm straight out to the side and bend your wrists so your fingers point towards the floor. Move your left arm around in a circle about 5 times each way. Then repeat this on your right side.
What are some yoga myths that you want to debunk for our readers?
PM: One is that yoga is just for women. Many women have flexibility and come to yoga for strength. Often men come to the studio with some strength, but are seeking or needing flexibility. People seem to think they shouldn’t come to class unless they are flexible. But class is where you get flexible. It would be like saying you won’t go to the gym because you don’t have muscles.
Another myth is that yoga means contortionism. I don’t believe in celebrating just the big crazy poses or the yoga competitiveness of this body-centric society we live in. I once overheard Richard Freeman (a master yogi) tell another teacher that the most beautiful pose he ever saw was an 80-year-old man doing a backbend. No airs, just a simple backbend with mindfulness. Beautiful.
#AIforgood #ethics #leadership #digitaldisruption #digitaltransformation
Enterprises must confront the ethical implications of AI use as they increasingly roll out technology that has the potential to reshape how humans interact with machines
How AI systems can be biased
More human-like bots raise stakes for ethical AI use
Ethical AI is needed for broad AI adoption
#AIforgood #digitaltransformation #techdisruption #sustainabledevelopmentgoals
AI is not a silver bullet, but it could help tackle some of the world’s most challenging social problems.
First: Mapping AI use cases to domains of social good
Equality and inclusion
Health and hunger
Information verification and validation
Public and social-sector management
Security and justice
Second: AI capabilities that can be used for social good
Image classification and object detection are powerful computer-vision capabilities
Structured deep learning also may have social-benefit applications
Advanced analytics can be a more time- and cost-effective solution than AI for some use cases
Third: Overcoming bottlenecks, especially for data and talent
Data needed for social-impact uses may not be easily accessible
The expert AI talent needed to develop and train AI models is in short supply
‘Last-mile’ implementation challenges are also a significant bottleneck for AI deployment for social good
Fourth: Risks to be managed
Breaching the privacy of personal information could cause harm
Safe use and security are essential for societal good uses of AI
Decisions made by complex AI models will need to become more readily explainable
Fifth: Scaling up the use of AI for social good
Improving data accessibility for social-impact cases
Overcoming AI talent shortages is essential for implementing AI-based solutions for social impact
About the author(s)
#futureofwork #digitaltransformation #shiftmindset #leadership
Retraining and reskilling workers in the age of automation
Dec 7, 2017: Weekly Curated Thought-Sharing on Digital Disruption, Applied Neuroscience and Other Interesting Related Matters.
By Vyacheslav Polonski and Jane Zavalishina
Curated by Helena M. Herrero Lamuedra
Today, it is difficult to imagine a technology that is as enthralling and terrifying as machine learning. While media coverage and research papers consistently tout the potential of machine learning to become the biggest driver of positive change in business and society, the lingering question on everyone’s mind is: “Well, what if it all goes terribly wrong?”
For years, experts have warned against the unanticipated effects of general artificial intelligence (AI) on society. Ray Kurzweil predicts that by 2029 intelligent machines will be able to outsmart human beings. Stephen Hawking argues that “once humans develop full AI, it will take off on its own and redesign itself at an ever-increasing rate”. Elon Musk warns that AI may constitute a “fundamental risk to the existence of human civilization”. Alarmist views on the terrifying potential of general AI abound in the media.
More often than not, these dystopian prophecies have been met with calls for a more ethical implementation of AI systems; that somehow engineers should imbue autonomous systems with a sense of ethics. According to some AI experts, we can teach our future robot overlords to tell right from wrong, akin to a “good Samaritan AI” that will always act justly on its own and help humans in distress.
Although this future is still decades away, today there is much uncertainty as to how, if at all, we will reach this level of general machine intelligence. But what is more crucial, at the moment, is that even the narrow AI applications that exist today require our urgent attention in the ways in which they are making moral decisions in practical day-to-day situations. For example, this is relevant when algorithms make decisions about who gets access to loans or when self-driving cars have to calculate the value of a human life in hazardous situations.
Teaching morality to machines is hard because humans can’t objectively convey morality in measurable metrics that make it easy for a computer to process. In fact, it is even questionable whether we, as humans have a sound understanding of morality at all that we can all agree on. In moral dilemmas, humans tend to rely on gut feeling instead of elaborate cost-benefit calculations. Machines, on the other hand, need explicit and objective metrics that can be clearly measured and optimized. For example, an AI player can excel in games with clear rules and boundaries by learning how to optimize the score through repeated playthroughs.
After its experiments with deep reinforcement learning on Atari video games, Alphabet’s DeepMind was able to beat the best human players of Go. Meanwhile, OpenAI amassed “lifetimes” of experiences to beat the best human players at the Valve Dota 2 tournament, one of the most popular e-sports competitions globally.
But in real-life situations, optimization problems are vastly more complex. For example, how do you teach a machine to algorithmically maximize fairness or to overcome racial and gender biases in its training data? A machine cannot be taught what is fair unless the engineers designing the AI system have a precise conception of what fairness is.
This has led some authors to worry that a naive application of algorithms to everyday problems could amplify structural discrimination and reproduce biases in the data they are based on. In the worst case, algorithms could deny services to minorities, impede people’s employment opportunities or get the wrong political candidate elected.
Based on our experiences in machine learning, we believe there are three ways to begin designing more ethically aligned machines:
1. Define ethical behavior
AI researchers and ethicists need to formulate ethical values as quantifiable parameters. In other words, they need to provide machines with explicit answers and decision rules to any potential ethical dilemmas it might encounter. This would require that humans agree among themselves on the most ethical course of action in any given situation – a challenging but not impossible task. For example, Germany’s Ethics Commission on Automated and Connected Driving has recommended to specifically programme ethical values into self-driving cars to prioritize the protection of human life above all else. In the event of an unavoidable accident, the car should be “prohibited to offset victims against one another”. In other words, a car shouldn’t be able to choose whether to kill one person based on individual features, such as age, gender or physical/mental constitution when a crash is inescapable.
2. Crowdsource our morality
Engineers need to collect enough data on explicit ethical measures to appropriately train AI algorithms. Even after we have defined specific metrics for our ethical values, an AI system might still struggle to pick it up if there is not enough unbiased data to train the models. Getting appropriate data is challenging, because ethical norms cannot be always clearly standardized. Different situations require different ethical approaches, and in some situations there may not be a single ethical course of action at all – just think about lethal autonomous weapons that are currently being developed for military applications. One way of solving this would be to crowdsource potential solutions to moral dilemmas from millions of humans. For instance, MIT’s Moral Machine project shows how crowdsourced data can be used to effectively train machines to make better moral decisions in the context of self-driving cars.
3. Make AI transparent
Policymakers need to implement guidelines that make AI decisions with respect to ethics more transparent, especially with regard to ethical metrics and outcomes. If AI systems make mistakes or have undesired consequences, we cannot accept “the algorithm did it” as an adequate excuse. But we also know that demanding full algorithmic transparency is technically untenable (and, quite frankly, not very useful). Neural networks are simply too complex to be scrutinized by human inspectors. Instead, there should be more transparency on how engineers quantified ethical values before programming them, as well as the outcomes that the AI has produced as a result of these choices. For self-driving cars, for instance, this could imply that detailed logs of all automated decisions are kept at all times to ensure their ethical accountability.
We believe that these three recommendations should be seen as a starting point for developing ethically aligned AI systems. Failing to imbue ethics into AI systems, we may be placing ourselves in the dangerous situation of allowing algorithms to decide what’s best for us. For example, in an unavoidable accident situation, self-driving cars will need to make some decision for better or worse. But if the car’s designers fail to specify a set of ethical values that could act as decision guides, the AI system may come up with a solution that causes more harm. This means that we cannot simply refuse to quantify our values. By walking away from this critical ethical discussion, we are making an implicit moral choice. And as machine intelligence becomes increasingly pervasive in society, the price of inaction could be enormous – it could negatively affect the lives of billions of people.
Machines cannot be assumed to be inherently capable of behaving morally. Humans must teach them what morality is, how it can be measured and optimized. For AI engineers, this may seem like a daunting task. After all, defining moral values is a challenge mankind has struggled with throughout its history. Nevertheless, the state of AI research requires us to finally define morality and to quantify it in explicit terms. Engineers cannot build a “good samaritan AI”, as long as they lack a formula for the good samaritan human.
Oct 18, 2017: Weekly Curated Thought-Sharing on Digital Disruption, Applied Neuroscience and Other Interesting Related Matters.
By Dan Clay
Curated by Helena M. Herrero Lamuedra
Meet Dawn. Her T-shirt is connected to the internet, and her tattoo unlocks her car door. She’s never gone shopping, but she gets a package on her doorstep every week. She’s never been lost or late, and she’s never once waited in line. She never goes anywhere without visiting in VR first, and she doesn’t buy anything that wasn’t made just for her.
Dawn is an average 25-year-old in the not-so-distant future. She craves mobility, flexibility, and uniqueness; she spends more on experience than she does on products; she demands speed, transparency, and control; and she has enough choice to avoid any company that doesn’t give her what she wants. We’re in the midst of remarkable change not seen since the Industrial Revolution, and a noticeable gap is growing between what Dawn wants and what traditional retailers provide.
In 2005 Amazon launched free two-day shipping. In 2014 it launched free two-hour shipping. It’s hard to get faster than “Now,” and once immediacy becomes table stakes, competition will move to prediction. By intelligently applying data from our connected devices, smart digital assistants will be able to deliver products before we even acknowledge the need: Imagine a pharmacy that knows you’re about to get sick; an electronics retailer that knows you forgot your charger; an online merchant that knows you’re out of toilet paper; and a subscription service that knows you have a wedding coming up, have a little extra in your bank account, and that you look good in blue. Near-perfect predictions are the future of retail, and it’s up to CX and UX designers to ensure that they are greeted as miraculous time-savers rather than creepy intrusions.
Every product is personalized
While consumers are increasingly wary about how much of their personal data is being tracked, they’re also increasingly willing to trade privacy for more tangible benefits. It then falls on companies to ensure those benefits justify the exchange. In the retail space this increasingly means perfectly tailored products and a more personally relevant experience. Etsy recently acquired an AI startup to make its search experience more relevant and tailored. HelloAva provides customers with personalized skincare product recommendations based on machine learning combined with a few texts and a selfie. Amazon, constantly at the forefront of customer needs, recently acquired a patent for a custom clothing manufacturing system.
Market to the machines
Dawn, our customer of the future, won’t need to customize all of her purchases; for many of her needs, she’ll give her intelligent, IoT-enabled agent (think Alexa with a master’s degree) personalized filters so the agent can buy on her behalf. When Siri is choosing which shoes to rent, the robot almost becomes the customer, and retailers must win over smart AI assistants before they even reach end customers. Netflix already has a team of people working on this new realm of marketing to machines. As CEO Reed Hastings quipped at this year’s Mobile World Congress, “I’m not sure if in 20 to 50 years we are going to be entertaining you, or entertaining AIs.”
Branded, immersive experiences matter more than ever
As online shopping and automation increase, physical retail spaces will have to deliver much more than just a good shopping experience to compel people to visit. This could be through added education (like the expert stylists at Nordstrom’s store without any merchandise) or heightened service personalization (like Asics on-site 3D foot mapping and gait cycle analysis) or constantly evolving entertainment (like Gentle Monster’s Seoul flagship store’s monthly changing “exhibition“).
In this context, brand is becoming more than a value proposition or signifier—it’s the essential ingredient preventing companies from becoming commoditized by an on-demand, automated world where your car picks its own motor oil. Brands have a vital responsibility to create a community for customers to belong to and believe in.
A mobile world that feels like a single channel experience
Dawn will be increasingly mobile, and she’ll expect retailers to move along with her. She may research dresses on her phone and expect the store associate to know what she’s looked at. It’s no secret that mobile shopping is continuing to grow, but retailers need to think less about developing separate strategies for their channels and more about maintaining a continuous flow with the one channel that matters: the customer channel.
WeChat, for example, China’s largest social media channel, is used for everything from online shopping and paying at supermarkets to ordering a taxi and getting flight updates, creating a seamless “single channel” experience across all interactions. Snapchat’s new Context Cards, allowing users to read location-based reviews, business information and hail rides all within the app, builds towards a similar, single channel experience.
The future promises profound change. Yet perhaps the most pressing challenge for retailers is keeping up with customers’ expectations for immediacy, personalization, innovative experiences, and the other myriad ways technological and societal changes are making Dawn the most demanding customer the retail industry has ever seen. The future is daunting, but it’s also full of opportunity, and the retailers that can anticipate the needs of the customer of the future are well-poised for success in the years to come.
Sep 25, 2017: Weekly Curated Thought-Sharing on Digital Disruption, Applied Neuroscience and Other Interesting Related Matters.
By Klaus Schwab
Curated by Helena M. Herrero Lamuedra
We stand on the brink of a technological revolution that will fundamentally alter the way we live, work, and relate to one another. In its scale, scope, and complexity, the transformation will be unlike anything humankind has experienced before. We do not yet know just how it will unfold, but one thing is clear: the response to it must be integrated and comprehensive, involving all stakeholders of the global polity, from the public and private sectors to academia and civil society.
The First Industrial Revolution used water and steam power to mechanize production. The Second used electric power to create mass production. The Third used electronics and information technology to automate production. Now a Fourth Industrial Revolution is building on the Third, the digital revolution that has been occurring since the middle of the last century. It is characterized by a fusion of technologies that is blurring the lines between the physical, digital, and biological spheres.
There are three reasons why today’s transformations represent not merely a prolongation of the Third Industrial Revolution but rather the arrival of a Fourth and distinct one: velocity, scope, and systems impact. The speed of current breakthroughs has no historical precedent. When compared with previous industrial revolutions, the Fourth is evolving at an exponential rather than a linear pace. Moreover, it is disrupting almost every industry in every country. And the breadth and depth of these changes herald the transformation of entire systems of production, management, and governance.
The possibilities of billions of people connected by mobile devices, with unprecedented processing power, storage capacity, and access to knowledge, are unlimited. And these possibilities will be multiplied by emerging technology breakthroughs in fields such as artificial intelligence, robotics, the Internet of Things, autonomous vehicles, 3-D printing, nanotechnology, biotechnology, materials science, energy storage, and quantum computing.
Already, artificial intelligence is all around us, from self-driving cars and drones to virtual assistants and software that translate or invest. Impressive progress has been made in AI in recent years, driven by exponential increases in computing power and by the availability of vast amounts of data, from software used to discover new drugs to algorithms used to predict our cultural interests. Digital fabrication technologies, meanwhile, are interacting with the biological world on a daily basis. Engineers, designers, and architects are combining computational design, additive manufacturing, materials engineering, and synthetic biology to pioneer a symbiosis between microorganisms, our bodies, the products we consume, and even the buildings we inhabit.
Challenges and opportunities
Like the revolutions that preceded it, the Fourth Industrial Revolution has the potential to raise global income levels and improve the quality of life for populations around the world. To date, those who have gained the most from it have been consumers able to afford and access the digital world; technology has made possible new products and services that increase the efficiency and pleasure of our personal lives. Ordering a cab, booking a flight, buying a product, making a payment, listening to music, watching a film, or playing a game—any of these can now be done remotely.
In the future, technological innovation will also lead to a supply-side miracle, with long-term gains in efficiency and productivity. Transportation and communication costs will drop, logistics and global supply chains will become more effective, and the cost of trade will diminish, all of which will open new markets and drive economic growth.
At the same time, as the economists Erik Brynjolfsson and Andrew McAfee have pointed out, the revolution could yield greater inequality, particularly in its potential to disrupt labor markets. As automation substitutes for labor across the entire economy, the net displacement of workers by machines might exacerbate the gap between returns to capital and returns to labor. On the other hand, it is also possible that the displacement of workers by technology will, in aggregate, result in a net increase in safe and rewarding jobs.
We cannot foresee at this point which scenario is likely to emerge, and history suggests that the outcome is likely to be some combination of the two. However, I am convinced of one thing—that in the future, talent, more than capital, will represent the critical factor of production. This will give rise to a job market increasingly segregated into “low-skill/low-pay” and “high-skill/high-pay” segments, which in turn will lead to an increase in social tensions.
In addition to being a key economic concern, inequality represents the greatest societal concern associated with the Fourth Industrial Revolution. The largest beneficiaries of innovation tend to be the providers of intellectual and physical capital—the innovators, shareholders, and investors—which explains the rising gap in wealth between those dependent on capital versus labor. Technology is therefore one of the main reasons why incomes have stagnated, or even decreased, for a majority of the population in high-income countries: the demand for highly skilled workers has increased while the demand for workers with less education and lower skills has decreased. The result is a job market with a strong demand at the high and low ends, but a hollowing out of the middle.
This helps explain why so many workers are disillusioned and fearful that their own real incomes and those of their children will continue to stagnate. It also helps explain why middle classes around the world are increasingly experiencing a pervasive sense of dissatisfaction and unfairness. A winner-takes-all economy that offers only limited access to the middle class is a recipe for democratic malaise and dereliction.
Discontent can also be fueled by the pervasiveness of digital technologies and the dynamics of information sharing typified by social media. More than 30 percent of the global population now uses social media platforms to connect, learn, and share information. In an ideal world, these interactions would provide an opportunity for cross-cultural understanding and cohesion. However, they can also create and propagate unrealistic expectations as to what constitutes success for an individual or a group, as well as offer opportunities for extreme ideas and ideologies to spread.
The impact on business
An underlying theme in my conversations with global CEOs and senior business executives is that the acceleration of innovation and the velocity of disruption are hard to comprehend or anticipate and that these drivers constitute a source of constant surprise, even for the best connected and most well informed. Indeed, across all industries, there is clear evidence that the technologies that underpin the Fourth Industrial Revolution are having a major impact on businesses.
On the supply side, many industries are seeing the introduction of new technologies that create entirely new ways of serving existing needs and significantly disrupt existing industry value chains. Disruption is also flowing from agile, innovative competitors who, thanks to access to global digital platforms for research, development, marketing, sales, and distribution, can oust well-established incumbents faster than ever by improving the quality, speed, or price at which value is delivered.
Major shifts on the demand side are also occurring, as growing transparency, consumer engagement, and new patterns of consumer behavior (increasingly built upon access to mobile networks and data) force companies to adapt the way they design, market, and deliver products and services.
A key trend is the development of technology-enabled platforms that combine both demand and supply to disrupt existing industry structures, such as those we see within the “sharing” or “on demand” economy. These technology platforms, rendered easy to use by the smartphone, convene people, assets, and data—thus creating entirely new ways of consuming goods and services in the process. In addition, they lower the barriers for businesses and individuals to create wealth, altering the personal and professional environments of workers. These new platform businesses are rapidly multiplying into many new services, ranging from laundry to shopping, from chores to parking, from massages to travel.
On the whole, there are four main effects that the Fourth Industrial Revolution has on business—on customer expectations, on product enhancement, on collaborative innovation, and on organizational forms. Whether consumers or businesses, customers are increasingly at the epicenter of the economy, which is all about improving how customers are served. Physical products and services, moreover, can now be enhanced with digital capabilities that increase their value. New technologies make assets more durable and resilient, while data and analytics are transforming how they are maintained. A world of customer experiences, data-based services, and asset performance through analytics, meanwhile, requires new forms of collaboration, particularly given the speed at which innovation and disruption are taking place. And the emergence of global platforms and other new business models, finally, means that talent, culture, and organizational forms will have to be rethought.
Overall, the inexorable shift from simple digitization (the Third Industrial Revolution) to innovation based on combinations of technologies (the Fourth Industrial Revolution) is forcing companies to reexamine the way they do business. The bottom line, however, is the same: business leaders and senior executives need to understand their changing environment, challenge the assumptions of their operating teams, and relentlessly and continuously innovate.
The impact on government
As the physical, digital, and biological worlds continue to converge, new technologies and platforms will increasingly enable citizens to engage with governments, voice their opinions, coordinate their efforts, and even circumvent the supervision of public authorities. Simultaneously, governments will gain new technological powers to increase their control over populations, based on pervasive surveillance systems and the ability to control digital infrastructure. On the whole, however, governments will increasingly face pressure to change their current approach to public engagement and policymaking, as their central role of conducting policy diminishes owing to new sources of competition and the redistribution and decentralization of power that new technologies make possible.
Ultimately, the ability of government systems and public authorities to adapt will determine their survival. If they prove capable of embracing a world of disruptive change, subjecting their structures to the levels of transparency and efficiency that will enable them to maintain their competitive edge, they will endure. If they cannot evolve, they will face increasing trouble.
This will be particularly true in the realm of regulation. Current systems of public policy and decision-making evolved alongside the Second Industrial Revolution, when decision-makers had time to study a specific issue and develop the necessary response or appropriate regulatory framework. The whole process was designed to be linear and mechanistic, following a strict “top down” approach.
But such an approach is no longer feasible. Given the Fourth Industrial Revolution’s rapid pace of change and broad impacts, legislators and regulators are being challenged to an unprecedented degree and for the most part are proving unable to cope.
How, then, can they preserve the interest of the consumers and the public at large while continuing to support innovation and technological development? By embracing “agile” governance, just as the private sector has increasingly adopted agile responses to software development and business operations more generally. This means regulators must continuously adapt to a new, fast-changing environment, reinventing themselves so they can truly understand what it is they are regulating. To do so, governments and regulatory agencies will need to collaborate closely with business and civil society.
The Fourth Industrial Revolution will also profoundly impact the nature of national and international security, affecting both the probability and the nature of conflict. The history of warfare and international security is the history of technological innovation, and today is no exception. Modern conflicts involving states are increasingly “hybrid” in nature, combining traditional battlefield techniques with elements previously associated with non-state actors. The distinction between war and peace, combatant and noncombatant, and even violence and nonviolence (think cyberwarfare) is becoming uncomfortably blurry.
As this process takes place and new technologies such as autonomous or biological weapons become easier to use, individuals and small groups will increasingly join states in being capable of causing mass harm. This new vulnerability will lead to new fears. But at the same time, advances in technology will create the potential to reduce the scale or impact of violence, through the development of new modes of protection, for example, or greater precision in targeting.
The impact on people
The Fourth Industrial Revolution, finally, will change not only what we do but also who we are. It will affect our identity and all the issues associated with it: our sense of privacy, our notions of ownership, our consumption patterns, the time we devote to work and leisure, and how we develop our careers, cultivate our skills, meet people, and nurture relationships. It is already changing our health and leading to a “quantified” self, and sooner than we think it may lead to human augmentation. The list is endless because it is bound only by our imagination.
I am a great enthusiast and early adopter of technology, but sometimes I wonder whether the inexorable integration of technology in our lives could diminish some of our quintessential human capacities, such as compassion and cooperation. Our relationship with our smartphones is a case in point. Constant connection may deprive us of one of life’s most important assets: the time to pause, reflect, and engage in meaningful conversation.
One of the greatest individual challenges posed by new information technologies is privacy. We instinctively understand why it is so essential, yet the tracking and sharing of information about us is a crucial part of the new connectivity. Debates about fundamental issues such as the impact on our inner lives of the loss of control over our data will only intensify in the years ahead. Similarly, the revolutions occurring in biotechnology and AI, which are redefining what it means to be human by pushing back the current thresholds of life span, health, cognition, and capabilities, will compel us to redefine our moral and ethical boundaries.
Shaping the future
Neither technology nor the disruption that comes with it is an exogenous force over which humans have no control. All of us are responsible for guiding its evolution, in the decisions we make on a daily basis as citizens, consumers, and investors. We should thus grasp the opportunity and power we have to shape the Fourth Industrial Revolution and direct it toward a future that reflects our common objectives and values.
To do this, however, we must develop a comprehensive and globally shared view of how technology is affecting our lives and reshaping our economic, social, cultural, and human environments. There has never been a time of greater promise, or one of greater potential peril. Today’s decision-makers, however, are too often trapped in traditional, linear thinking, or too absorbed by the multiple crises demanding their attention, to think strategically about the forces of disruption and innovation shaping our future.
In the end, it all comes down to people and values. We need to shape a future that works for all of us by putting people first and empowering them. In its most pessimistic, dehumanized form, the Fourth Industrial Revolution may indeed have the potential to “robotize” humanity and thus to deprive us of our heart and soul. But as a complement to the best parts of human nature—creativity, empathy, stewardship—it can also lift humanity into a new collective and moral consciousness based on a shared sense of destiny. It is incumbent on us all to make sure the latter prevails
Aug 24, 2017: Weekly Curated Thought-Sharing on Digital Disruption, Applied Neuroscience and Other Interesting Related Matters.
By Niall McKeown
Curated by Helena M. Herrero Lamuedra
“If we understand what the technology is capable of, we will be in a better place to tell you how our organisation can leverage it” – says one business leader.
“This is what we want the business to achieve and how we’re going to get there. Go find technology that helps make this happen” – says another.
So which comes first? Do we start with understanding what technology is capable of and devising a strategy to leverage it? Or do we define our strategy and then use technology to deliver it? Should leadership strategy push the business or should the rapid adoption of new technologies pull the business? Perhaps it’s a hybrid of strategy push and technology pull?
CIO.co.uk (an online magazine for Chief Innovation Officers) suggests that IT supports the business strategy. They argue that organisations should have an agile IT function capable of exploiting new technologies that facilitate delivery of the organisation’s strategic vision.
Harvard Business Review, as far back as 1980 have been suggesting that strategy pushes the business and technology is required as a support function. MIT Sloan doesn’t sit on the fence either. They suggest that Strategy – not Technology Drives Digital Transformation.
Times, however, are changing. Most of these thought leadership articles were written pre-artificial Intelligence. The explosion of new technologies and its rapid adoption by industry and consumers is creating massive opportunities for businesses that are technically informed, agile, opportunistic and innovative. Few modern businesses can claim to be all four unless their leadership has at least studied formal frameworks for digital transformation and upgraded their leadership thinking in new data driven decision making strategy planning and leadership techniques.
My own experience would suggest that the most advantaged leaders create strategy influenced by what is possible. They leverage new technologies as well as the assets that have always delivered competitive advantage to their business. They don’t abandon what makes them great, they augment it, enhance it, upgrade it. Transformation, however, is where they aim for step change not marginal gain. If I were to put a number on it, the most successfully transformed businesses are 80% strategy-pushed and 20% opportunistically technology-pulled.