The Human Brain: The Final Commodity

“If, then, man’s principal asset and value is his brain and his ability to calculate, he will become an unsaleable commodity in an era when the mechanical operation of reasoning can be done more effectively by machines.”

Technology has always replaced humans

The philosopher, Alan Watts, wrote the above in 1951. The idea that machines will replace humans is not new. The job of sowing seed has become easier and more productive over time with the hoe, the plough and the tractor. The textile industry has seen the same productivity improvements. The spindle, the flying shuttle, the spinning mule and the spinning jenny. Machines continue to replace human manual labour. But technology and innovation has not led to sustained mass unemployment. More productive sectors of the economy create jobs as less productive areas lose jobs. The loss of human jobs to technology has been a feature of human progress since stone tools.

This time it is different

Artificial intelligence tools are arriving at a time of instant global communication and digital distribution. Facebook can make a breakthrough in New York and on the same day Shanghai and Santiago researchers can test the approach. Knowledge can be shared and reviewed with experts on Twitter. Amazon Web Services allows developers to build products faster than ever. Developers can add AI capabilities from IBM Watson with a simple piece of code. The iOS app store and Google Play Store allow apps to reach over 2.6 billion people today, growing to 6.1 billion people in 2020. The Industrial Revolution took around 100 years to transform the global economy. The artificial intelligence revolution will touch almost every person on earth in less than a few decades.

What happens when the jobs run out?

As machines replace the last humans on farms and in factories, the real revolution is coming to offices. The service sector provides jobs in which humans have maintained their competitive advantage: the brain. Digital Genius provides a human-like customer service tool that can replace customer service reps. Ellipse by Thoughtly is a research tool that analyses websites, journals and articles to discover insight. One single research manager with Ellipse can do the job of a team of ten researchers. Products like Guesswork can use AI to qualify, prioritise and route leads reducing the size of the sales team. A machine can complete most data analysis tasks better than a human. Millions of jobs are at threat in every part of the organisation. Data analysis is central to many jobs in marketing, sales, HR & recruitment, customer service, and finance.

What would you do if money were no object?

Over the next 20 years, there will be millions of people around the world that can no longer trade their labour for capital. Retraining programmes may work in some cases and more flexible labour laws may boost employment for a limited time. New technologies like drones, virtual reality and autonomous cars will generate new jobs. But these jobs will be highly-skilled and will need engineering ability. This will leave millions of under-skilled, un-skilled and wrongly skilled workers. Economic growth will no longer create jobs for humans. This is a fundamental break in the engine of capitalism.

A world of worklessness will force society to adapt. One transformative theory that has dismissed before is the Universal Basic Income (UBI). The UBI, first proposed by Thomas Paine in 1795, is not means-tested and every citizen is eligible. High costs and the disincentives to work resulted in the idea being dismissed. The age of worklessness will demand a review. AI applied across the economy will raise productivity levels to unprecedented levels. Healthcare, public transport, and energy will cost less and generate more. The challenge for governments is to ensure AI gains do not amass to a few trillion dollar companies, as millions of citizens cannot earn money. This is already becoming a concern for many governments. UBI will be affordable for most governments if redistribution becomes a policy goal.

If all humans have enough money to meet the majority of their needs, what will people do with their time? Scientists, artists, and designers will be free to pursue their passions without the need for money. Even Thomas Hobbes who described the world as “short, nasty and brutish”, believed leisure to be the mother of Philosophy. Oscar Wilde as always said it best; “cultivated leisure is the aim of man.” All humans may finally be free to pursue leisure and happiness.

What would you do if money was no object?

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The Human Brain: The Final Commodity

Time to Start Taking Artificial Intelligence Seriously

Recent developments in artificial intelligence have been under-appreciated by industry due to a lack of clarity in definitions and a lack of understanding of machine learning. Machine learning, deep learning, neural networks, predictive analytics, big data analytics and artificial intelligence are used interchangeably leading to widespread confusion. In addition, the discussion around artificial intelligence has always been led astray by Hollywood and news media looking for exciting stories. There is nothing more exciting than machines vs humans story, and so important developments in artificial intelligence are lost in the Terminator fantasies. Developments in AI algorithms are often hard to explain, and because the word has been misused over the years, the public associate AI with an human-shaped robot in the future and dismiss stories of incremental progress in AI. This is a huge mistake.

Artificial intelligence has been improving software for a long time now, often going by the name of machine learning. Your Google search, Amazon recommendations and your SIRI requests. When an algorithm is successful, it is embedded in software and disappears making the software smarter over time. What then has changed to make AI so important today? The answer is threefold; big data, increased computation and parallel computing.

Vast amounts of data are being collected and stored at ever decreasing costs providing a wealth of training data for training for AI algorithms. With the rise of cloud computing and the continued progress of Moore’s Law, big data can be processed more cheaply and quickly than ever before. Finally, the use of graphical processing units (GPUs) and application specific integrated circuits (ASICs) has provided a more efficient way of running learning algorithms, which tended to be inefficient and ineffective on traditional central processing units (CPUs).

These three trends have provided a cheap innovation platform for developers who are now using artificial intelligence algorithms to make progress across of range of industries. The big internet companies such as Google, Facebook and Amazon have become multi-billion dollar businesses on the back of using AI as a competitive advantage in search, social and retail. These AI techniques are now cheap enough and pervasive enough that they can be applied in any industry. IBM, Google and Microsoft even offer these techniques to any company in a package called ML-as-a-service (MLaaS). The application of AI to meet specific market needs will form the basis on the next billion dollar companies. Already we can see, Uber in Logistics, Airbnb in hospitality and Palantir in data analysis. Human Longevity Inc, for example, are attempting to pull together all genomic, microbiome, metabolome, and physiological data from an individual and run a machine learning algorithm to better understand the human aging process.

The thing about artificial intelligence is that it is an exponential technology. The rate of improvement will continue to double every 18 months, costs of storage and computing will fall, and new neuromorphic chip designs will allow for more efficient machine learning computation. Extrapolating Moore’s Law even further, Ray Kurzweil, Director of Engineering at Google estimates that by 2023 it will cost $1000 for a computer with 20 petaFLOPS, roughly the same processing power as the human brain.

This exponential progress will creep up on businesses not paying attention. This will not be confined to the technology industry, AI will fundamentally reshape every industry. AI is the very definition of a disruptive technology.

Time to Start Taking Artificial Intelligence Seriously

The Internet of Things: Brave New World or Utopia

As William Gibson once said; “The future is already here — it’s just not very evenly distributed”. This is true of the geographic distribution of new technologies, and it is also true of the distribution new technologies across devices. In this case, sensors and connectivity are already in electronic portable devices such as smartphones and tablets, but we are about to see wide distribution across every object, fabric and machine. The next technological revolution will connect the world, quantifying the environment and sharing that data in vast databases. The mattress will know when a body is present, clothing will know when it needs to be washed, and the lights will know when to dim, and the shoe will know what direction to walk. Sensors are now small and cheap enough for this world to be a reality. The natural world is about to be quantified, automated and made more efficient.

Beyond quantifying the external environment, we are beginning to also quantify the human body. We are likely to see huge growth in the smart wristband market as Apple enters and costs of the device decrease. Companies like OMSignal are manufacturing smart clothing and Google and Novartis are working to develop smart contact lenses. Across the board we are seeing the trend of collecting health data such as heart rate and respiratory rate, to glucose levels and galvanic skin response.

The benefits to the individual will be unparalleled; the ability to track and understand their own body and health, as well as share this data with family members, medical professionals and health researchers. For society this offers a unique ability to run clinical trials on a scale never before possible, data is collected and consolidated from millions of individuals, researchers can identify new patterns, new causes, and treatment effectiveness far cheaper and quicker than ever before. All of this has the potential to provide predictive care saving millions of lives every year.

Data is Currency in the IoT Era

The currency of this new era is data. Data from mattresses, data from thermostats, data from fridges, if it is connected then it will be valuable. Service providers will use the data to integrate with other sets such as browsing history, app permissions, location, and camera roll providing personalized services and tailored ads.

Existing data-driven services have business models that require the collection and storage of vast amounts of personal data. They get this data for free. To charge more to advertisers Facebook, Google, and Twitter need as much data as possible to serve up more relevant ads. Up until now they have had to rely on basic information to tailor ads — search history, friends, browsing habits, etc — in an IoT world, fridge inventory, wake-up times, washing habits, are all extremely valuable signals to feed their machine learning algorithms. As things stand, they will get this data for free.

As we begin to quantify the physical world, data ownership will become the biggest issue for individuals, companies, and governments. People feel uncomfortable sharing home or health data as this is regarded as more sensitive than digital data. The creators of the data and the users of the data have differing incentives — share less vs. collect more.

Trust as Competitive Advantage

The solution to the data privacy challenge will touch almost every business to consumer industry. It is unlikely that ad-supported business models will collapse; they will instead have to become more sensitive to individuals rights and prioritise trust over a land-grab. Individuals will share pretty much all data with trusted service providers as long as the value created is perceived as greater than the cost of sharing the data. Trust is competitive advantage.

Another solution is to create a marketplace for data, bringing together creators of the data (sellers) together with data service providers (buyers). Handshake is a UK-based company that is attempting to do just this. By putting a value on the individual’s personal data, the incentive to give it away for free to Google and Facebook is removed. Some individuals will decide that the value of the internet service provider’s product — instant access to the world’s information, instant connection with all your friends, ability to automatically order groceries — is worth access to their data.

Each individual and family must understand the trade off between sharing data and the privacy implications. It is the most important civic challenges of the digital age; a failure to communicate the loss of privacy associated with new health, home and city services in the internet of things era is to sleepwalk into a world where privacy is completely dead.

The Internet of Things: Brave New World or Utopia

Bionic Eyes: Blending Reality

Last month Google announced that it will partner with Alcon to commercialise smart contact lenses. Contact lenses are today used to correct visual impairments, but with low-power miniaturised chips, smart contact lenses have far greater potential. The miniaturization of integrated circuits will one day lead to implantable and digestible computing, in the meantime, the next frontier is contact lenses.

Contact lenses are in direct contact with tear-film fluid allowing sensors to detect changes in chemical and protein concentrations — data that aids the non-invasive diagnosis of disease. Beyond health monitoring, smart contact lenses also have the potential to include a small display and imaging sensor that will augment vision with digital information.

Disease Diagnosis

The first use case is for contact lenses to measure glucose, but tear-film fluid contains a whole host of proteins and hormones including cholesterol and cortisol. Some of the biomolecules found in tears are as biomarkers for ocular and systemic diseases. Real-time access to biomarkers allows for measurement of levels of concentration. This data enables individuals to regulate their food intake and exercise patterns, as well as acting as an early-warning system for disease.

Initially, smart contact lenses will be an optional diagnostic test alternative for patients; blood tests and even saliva tests will remain more robust in the short term. However, blood and saliva tests need visiting a healthcare professional and cannot be managed in real-time. For low-risk individuals, the benefits of real-time monitoring and the volume of data collected via contact lenses will outweigh the benefits of accuracy. Months of minute-by-minute data used to track various protein concentrations will enable machine-learning algorithms to determine optimal levels for each patient and provide personalized care.

Human/Computer Vision

Contact lenses as a medical diagnostic tool have the potential to fundamentally disrupt the healthcare industry and save millions of lives, but they can do even more. A recent patent filing from Google hints at functionality straight from a sci-fi movie. Google’s report shows a contact lens that includes an embedded circuit, a camera, and a sensor, which when combined, offer the potential to live-stream, take photos directly from the eye, and augment vision with relevant digital information (including advertisements). Babak Amir Parviz, an electrical engineer at the University of Washington, ophthalmologist Tueng Shen, and a group of Finnish optoelectronics researchers have been able to embed a LED display into a contact lens and remotely control it.

These advancements are in the nascent stage and it is unlikely we will have full displays embedded into contact lenses just yet. But the development is an issue of time and investment not physical laws. A tiny LED display could be used as part of a glucose-monitoring system which turns red when blood-glucose falls below the optimal level, making self-regulation easier. A single red light could also alert stress sufferers when their cortisol levels are too high, helping them understand their triggers and avoid unnecessary anxiety.

The Google patent proposes an embedded CMOS image sensor allowing users to take photos from their lenses. Such functionality would need the wireless transfer of power or the use of energy harvesting technologies, both of which are not commercially viable today. However, the lenses would not require energy to perform computation, as this can be handed off to a smartphone with the result transmitted back to the lenses. This network allows data-intensive software, including facial recognition and infrared sensing (i.e., extending the visible electromagnetic spectrum), to be completed in real-time and displayed in the user’s field of vision. Enhanced reality software will no doubt expand the processing power of smartphones. Doctors, teachers, police, and armed forces will all benefit from having information available in real-time in their line of vision. As a platform for innovation, visual computing would push the limits of human expression and creativity, driving new and powerful ways of communication and interaction with the world.

Vision as a service

The road to blended reality contact lenses is a long one, and it is unlikely to be commercially viable before 2020. In 2015 we are likely to see the first commercial use of smart contact lenses as glucose monitors for diabetes sufferers. More sensors will be embedded over time and sufferers of other diseases or illnesses will have the option to use contact lenses as part of their remote monitoring treatments. Early adopters will likely consider themselves health customers rather than patients, helping move the public debate from passive patients to engaged customers. A shift of this nature will allow customers take responsibility for their own well-being and improve their health.

Regulatory and societal response will determine the speed at which we see embedded cameras and displays in the mainstream. Advanced vision has important implications for privacy and general human interaction. We will have the ability to know when somebody is lying using iris detection. We will have constant advertising in the real world, and the sum of human knowledge available in the line of sight. These capabilities would mean always knowing the answer to a question, knowing everything about the people around you, and having the ability to reply the day through your own eyes. The benefits to society would be vast, but they would also bring about a fundamental shift in what it means to be human. We are entering the world of bionics and transhumanism. The future is closer than you think.

Bionic Eyes: Blending Reality

The Blended Reality Era

As we start 2015, we are entering the 2nd half of the smartphone era. We’re beginning to see a post-smartphone vision emerge with the smartphone as the centre of a network of sensors. These sensors will be embedded in wristbands, clothing, and everyday items such as locks, lights and thermostats. We are seeing technology brands articulate their vision for their mobile platforms moving beyond smartphones and tablets, into a range of other devices including wearable technologies, cars and household objects. By 2020, a clear picture of the post-smartphone era will have emerged; an era Frost & Sullivan calls the ‘Blended Reality Era’.

Truly ‘smart’ devices

Despite the fevered focus on smartwatches and new wearable devices, the game-changing innovation has already arrived. They are already in smartphones and manufacturers are embedding them in all new products. The sensorization of the world is already happening and the smartphone will be the beating heart of it all.

By 2020, the smartphone will connect with the wristband, fridge and car making the Internet of Things even more valuable to consumers. Sensors will collect data and send it back to a smartphone for visualisation, automation and insight. App-based services will offer automation; if your mattress senses reduced pressure then it will tell the coffee machine to brew a coffee, or if the front door closes, it will turn all lights and appliances onto energy-saving mode. The possibilities are as boundless as the imagination.

From reactive to predictive healthcare

Smartphones, wristbands, and smart clothing will collect real-time healthcare data. The sharing of this data will sit at the core of the privacy-versus-value debate. Sensors will measure glucose levels, blood pressure, and respiratory rate giving a real-time record of personal health. With more data we can expect faster and more accurate diagnosis.  Third-party health and wellness analytics companies, insurance providers and government agencies will want access. If these providers can win the trust of their customers, we will be able to improve personal and societal health outcomes. But if data privacy and security processes are not robust and trust is not gained, society at large will suffer. We have the opportunity to move from a reactive healthcare system to a predictive, preventative, personalised and participatory system. The smart shirt that identifies raised stress levels and plays relaxing music whilst brewing a green tea. The fridge that notifies the user when they are lacking potassium in their diet and suggests a meal of kale and chicken.

Healthcare will not just be something we receive when we are ill. It will be something we take part in daily.

Augmented Reality Eyewear

Augmented reality (AR) is the most exciting use case for an eye-mounted wearable device. The ability to layer digital information on the physical world in real time is unique to a wearable device. An extension of ‘glanceable’ notifications, AR has the potential to be the ‘killer app’ for wearable devices. AR wearables will sit near the eye to be effective, either as with Google Glass or a pair of glasses or with smart contact lenses. The advancements of location-based technologies, display and connectivity technologies will continue to drive adoption.

In 2020 eyewear will be standard equipment for soldiers, surgeons, police and customer service reps. The ability to live-stream and layer on relevant information in real-time such as a patient’s health record, a criminal record, or purchasing history is valuable. Eyewear further reduces the friction of using digital information and will save hours of labour-intensive work.

By 2020, the smartphone will be the central hub in the personal internet of things, connecting with wearables, household objects, and vehicles. Sensors will quantify, and mobile and cloud apps will automate everyday tasks. Sensors, displays and augmented reality services will bring a digital layer to the physical world, quantifying it for efficiency and optimisation. We are in the very early stages of making our environment intelligent. The media coverage may focus on new phones and watches, but the real advances are happening quietly behind the scenes in software. Computing is moving from something that we do, to something that just happens around us. Innovation is continuing unabated in the technology industry. It has just moved from tangible shiny consumer electronics to intangible pieces of code. We are at the very early stages of the Blended Reality Era, by the end of it computing power will be as ubiquitous as electric power. Electric power fundamentally reshaped the global economy. Ubiquitous computing will do the same.

The Blended Reality Era

Why Apple bought Beats

The Next Episode: Why Apple Wants to Buy Beats

With 2014 being the year of crazy tech acquisitions, Apple obviously doesn’t want to miss out. When Google buys Titan Aerospace or Nest, and Facebook acquires WhatsApp or Oculus VR, they are making bets on the future. Whether it’s drones, the internet of things, mobile messaging or virtual reality, each of these domains are clearly part of the future in some way and the value of buying early is not to be disrupted later. It makes at least some sense. The music business is anything but future technology. Music is no longer the key battleground, Apple won out with iTunes and has dominated the industry ever since. Music is no longer a lock-in service as music streaming services are platform-agnostic, meaning Beats would provide almost zero ecosystem value for Apple. This feels like more of a bet on the past, and at US$3.2 billion (the largest ever acquisition for Apple), a big bet. So what is this all about?

“They say rap’s changed, they want to know how I feel about it”

The pricing model for music is changing. iTunes unbundled the album and its a la carte model of selling music won out. There are signs that the subscription model is now overtaking a la carte. Music subscription revenue increased 50 per cent to US$1.1 billion in 2013, whilst downloads declined by two per cent in the same period, for the first time since the iTunes store launched. But Beats Music only had 111,000 subscribers as of March 2014, the paid-for figure is likely to be considerably lower if you strip out the 90-day free promotional trial offered by AT&T. Spotify has over six million paying users and Deezer has over four million. Beats Music, despite being newer, has a very long way to go. The key differentiator for Beat Music is its curated experience. Quality content discovery is still too complicated for most users and curation solves the “what to listen to” problem. Apple’s defines itself by its simplicity and user focus. Beats would certainly be more interesting to Apple than a Spotify or Deezer and a lot cheaper to boot.

“Got my red Dre Beats on, tryna put my peeps on”

With 64 per cent market share of the premium headphone market in North America, Beats was on track to record revenues of US$1.4 billion in 2013. Beyond market share, the most valuable part of Beats is the brand. Much like Apple products, serious professionals bemoan the poor quality specs and dismiss Beats as poor quality. That misses the point. Headphones are now for more than just listening to music; they are a piece of clothing, an item that can reflect personality. Brand, not sound, is key. Beats headphones are now ubiquitous, worn by football players, pop stars and actors; they are cool. Even cooler than Apple’s white headphones in the iPod era. That cool factor translates its revenues, as customers flock to pay a huge premium. Cool, premium and high margins; the business sounds a lot like Apple.

The Message

The proposed purchase is a music subscription play first and foremost. Apple needs to move to a subscription model and must feel that the iTunes organisation is not capable of changing the business model. The curated product and ease of discovery fits with the Apple ethos, and it has plenty of runway for growth especially if bundled with an iPhone contract in the future. Second, they get a profitable US$1.4 billion business, a strong brand, and a team that has intimate knowledge of designing products customers want to wear. All of which seems like an awful lot for a US$3.2 billion price tag.

Why Apple bought Beats