Why The Future Is In The Hands Of Individuals, Not Corporations

The power to innovate is falling into the hands of hyper-talented individuals.

Traditionally, the largest and most successful corporations were also the largest employers. Manufacturing and retail businesses required factories, warehouses, logistics and plenty of manpower, all working in harmony to deliver their product or service. Building this capability took years, requiring significant capital investments. Thus, competitors were few and far between, and disruption was painfully slow to make a dent on existing hierarchies.


But with the rise of technology, the model of success has gradually evolved, with businesses requiring fewer and fewer resources and employees to make an impact. Whatsapp is the perfect example; already worth $19bn with only 55 employees. And as we enter the next wave of tech innovation, we’ll increasingly see power transfer away from traditional ‘corporations’ and fall into the hands of smaller groups of highly skilled and hyper-talented individuals.

More, but increasingly complex opportunities

There has never been a more exciting time to be an entrepreneur, with emerging technologies bringing an unprecedented number of opportunities for innovation across platforms and software, with minimal physical resources and infrastructure required. We’re only now beginning to understand the potential of tools such as AI, machine learning, AR, VR, and the Internet of Things, and how they can be combined to create breakthroughs across a whole range of industries and problems.

Yet, identifying and then maximizing these complex and increasingly technical opportunities requires equally specialist knowledge and skills, along with the ability to respond rapidly to new innovations and competition. Understanding and manipulating the most cutting-edge tools requires the best brains, not to mention the drive, resilience and vision to identify the ideas with the most potential. The barriers to entry are rising, placing the power in the hands of those highly capable individuals, who are no longer reliant on building large organizations or physical assets to realize their ambitions.

Size doesn’t equal power

Corporations have always struggled to innovate, lacking the natural agility and flexibility of smaller organizations. However, as we enter this new age of innovation, it is becoming even tougher for the incumbents to keep up with the pace of change and increasing complexity, even with all their manpower and their abundance of cash lying dormant on the balance sheet.

What these big businesses are lacking is the ability to harness the power of the most talented individuals, by providing an environment where they can thrive. Radical change needs mavericks and risk takers who in turn need the freedom and ability to innovate; not be put in a straight-jacket and told to behave and operate according to corporate rules. The most extreme innovators don’t fit into old-fashioned, archaic organizational structures, which means it’s very difficult for big businesses to attract, integrate and retain these individuals.

Investing in these most cutting-edge technologies is also extremely risky, and corporations are too afraid of making mistakes and too busy covering their backs to take a serious punt on ideas that might not build any value. Innovation requires agility and radical thinking, which is impossible in an environment that is paralyzed by politics, an aversion to change and worries of cannibalising its existing revenue streams and product lines. Their only real hopes are spin-offs, joint ventures and acquisitions of the most talented individuals – not in-house innovation.  

Supporting the individual

Those who succeed in the next wave of innovation will be those individuals and small teams with the technical skills and a ‘knack’ for understanding the end vision, along with the freedom and agility to explore the unknown. But to have this freedom, these individuals must be adequately supported with resources, networks and capital to take the necessary risks and follow their instincts.

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Kjartan Rist


I write about the rapidly evolving VC and start-up sector in Europe
What's the Purpose of Companies in the Age of AI?
Recent advances in artificial intelligence (AI) and computer technology are causing us to think again about some really basic questions: what is a firm? What can firms do better than markets? And what are the distinctive qualities of firms in a world of smart contracts and AI?

While there has been a lot of discussion about “what’s left for humans?” as AI improves at exponential rates — the customary answer is that humans need to focus on the things they are uniquely good at, such as creativity, intuition, and personal empathy — I think we now have to ask, “what’s left for firms?”

In many ways this is an old question, because it takes us back to the arguments of Nobel Laureates Ronald Coase and Oliver Williamson that firms exist to coordinate complex forms of economic activity in an efficient way.  If computer technology has the capacity to simplify and streamline transaction costs, more and more work can be done through these smart-contract arrangements, making traditional human-managed firms obsolete.  For example, when you say to Alexa “order more dog food,” a chain of activities is initiated that leads to the delivery of a fresh supply of Kibble 24 hours later, with little or no human intervention. This work is coordinated by a single firm, Amazon, but it often involves third parties (makers of dog food, delivery companies) whose systems interact seamlessly with Amazon’s.

But is this coordination logic, this ability to internalize transactions to make them more efficient, really the raison d’etre of firms? I would argue that it is just one among many reasons that firms exist. And as computer technology simplifies and reduces transaction costs further, it is these other things that firms do uniquely well that will come more to the forefront. Here are four areas where firms excel.

1. Firms create value by managing tensions between competing priorities. 

In today’s parlance, firms have to exploit their established sources of advantage (to make profits today) while also exploring for new sources of advantage (to ensure their long-term viability).  However, getting the right balance between these two sets of activities is tricky because each one is to a large degree self-reinforcing. Hence the notion of organizational ambidexterity — the capacity to balance exploitation and exploration.

Artificial intelligence is evidently helping many firms to exploit their existing sources of advantage — whether through process automation, improved problem-solving or quality assurance.  Artificial intelligence can also be useful in exploring new sources of advantage: in the famous case of AlphaGo, the winning “strategy” was one that no human player had ever come up with; and computers are increasingly writing new musical scores and painting Picasso-like landscapes.

But AI is not helpful in managing the tension between these activities, i.e. knowing when to do more of one or the other.  Such choices require careful judgment — weighing up qualitative and quantitative factors, being sensitive to context, or bringing emotional or intuitive factors into play. These are the capabilities that lie at the heart of organizational ambidexterity and I don’t believe AI can help us with them at all right now. IBM’s recently-announced Project Debater is a case in point: it showed just how far AI has come in terms of constructing and articulating a point of view, but equally how much better humans are at balancing different points of view.

2. Firms create value by taking a long-term perspective.

As a variant of the first point, firms don’t just manage trade-offs between exploitation and exploration on a day to day basis, they also manage trade-offs over time. My former colleagues Sumantra Ghoshal and Peter Moran wrote a landmark paper arguing that, unlike markets, firms deliberately take resources away from their short-term best use, in order to give themselves the chance to create even more value over the long term.  This “one step back, two steps forward” logic manifests itself in many ways — risky R&D projects, pursuing sustainability goals, paying above-market wages to improve loyalty, and so on. We actually take it for granted that firms will do many of these things, but again they involve judgments that AI is ill equipped to help us with.  AI can devise seemingly-cunning strategies that look prescient (remember AlphaGo) but only when the rules of the game are pre-determined and stable.

An example:  the “Innovator’s Dilemma” is that by the time it’s clear an invasive technology is going to disrupt an incumbent firm’s business model, it’s too late to respond effectively. The incumbent therefore needs to invest in the invasive technology before it is definitively needed. Successful firms, in other words, need to be prepared to commit to new technologies in periods of ambiguity, and to have a “willingness to be misunderstood,” in Jeff Bezos’s terms.  This isn’t an easy concept for AI to get used to.

3. Firms create value through purpose — a moral or spiritual call to action.

There is a second dimension to long-term thinking, and that is its impact on individual and team motivation. We typically use the term purpose here, to describe what Ratan Tata calls a “moral or spiritual call to action” that leads people to put in discretionary effort — to work long hours, and to bring their passion and creativity to the workplace.

This notion that a firm has a social quality — a purpose or identity — that goes beyond its economic raison d’etre is well established in the literature, from March and Simon through to Kogut and Zander.  But it still arouses suspicion among those who think of the firm as a nexus of contracts, and who believe that people are motivated largely through extrinsic rewards.

My view is that you just need to look at charities, open source software movements, and many other not-for-profit organizations to realize that many people actually work harder when money is not involved. And it is the capacity of a leader to articulate a sense of purpose, in a way that creates emotional resonance with followers, that is uniquely human.

Successful firms, in other words, institutionalize a sense of identity and purpose that attracts employees and customers. Ironically, even though blockchain technology is — by definition — about building a system that cannot be hacked, or misused by a few opportunists, people still prefer to put their faith in other people.

4. Firms create value by nurturing “unreasonable” behavior.

There are many famous cases of mavericks who succeeded by challenging the rules, such as Steve Jobs, Elon Musk, and Richard Branson. With apologies to George Bernard Shaw, I think of these people as unreasonable — they seek to adapt the world to their view, rather than learn to fit in. And if we want to see progress, to move beyond what is already known and proven, we need more of these types of people in our firms.

Unreasonableness is antithetical to the world of AI. Computers work either through sophisticated algorithms or by inference from prior data, and in both cases the capacity to make an entirely out-of-the-box leap doesn’t exist. Consider the case of investment management, where robo advisors are not just making trades, they are also providing investment advice to investors, and at a fraction of the cost of human financial advisors. But as the Financial Times said last year, “when it comes to investing, human stupidity beats AI.”  In other words, if you want to beat the market, you need to be a contrarian — you need to make investments that go against the perceived wisdom at the time, and you need to accept the risk that your judgment or your timing might be wrong.  Both qualities that — at the moment — are distinctively human.

So one of the distinctive qualities of firms is that they nurture this type of unreasonable behavior.  Of course, many firms do their best to drive out variance, by using tight control systems and punishing failure. My argument is that as AI becomes more influential, though the automation of basic activities and simple contracts, it becomes even more important for firms to push in the other direction — to nurture unorthodox thinking, encourage experimentation, and tolerate failure.

In a recent Fast Company article, Vitalik Buterin described how all the elements of Uber’s ride-sharing service could be provided through Ethereum-based applications that worked seamlessly with one another:  “the whole process is basically as before, but without the middleman [Uber].”  This is may be true, but it doesn’t necessarily follow that a computer-mediated service is the better option.

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Artificial Intelligence can make healthcare more accessible, affordable
Photo: iStockphoto

Most of us approach healthcare with hesitation. There are often several deterrents to seeking medical care (let alone preventive care)—ease of access being a major one. According to the Indian Journal of Public Health (September 2017 edition), India had just 4.8 practicing doctors per 10,000 population. While this is expected to grow to 6.9 doctors per 10,000 people by 2030, the minimum doctor-to-patient ratio recommended by the World Health Organization (WHO) is 1:1000.

Can we have more doctors? That is easier said than done. Even if we can, with our education system focused on quantity over quality, churning out doctors in droves will not guarantee better quality medical services in our country. Besides, with most graduates preferring lucrative urban locations, many Indians still find themselves at great physical or economic distance from quality healthcare.

Essentially, what we need is to fill the gap between the needs of the plenty and the services of the few. In my view, artificial intelligence (AI) has the capability to enable solutions that form the critical middle layer of access—making healthcare accessible and affordable to a large population base at the same quality level irrespective of people’s social standing.

Let us see how AI is set to impact our health in the coming years.

Reactive versus proactive healthcare

The usual attitude towards healthcare is, “I’ll cross that bridge when I come to it”—a reactive rather than proactive approach to seeking medical intervention. However, that has started changing in recent times. Sensors in wearables such as smart watches and Fitbits are already equipped to deliver actionable feedback to apps in our phones and connect to our doctor’s clinic for diagnostic tests and medication prescriptions.

Today, for instance, Apple watches can detect a variety of heart diseases—including diabetes prediction with an 85% match in known cases. All this by using simple, non-invasive tech that is already available.

Interesting AI start-ups like SigTuple (digitized blood analysis), Niramai (thermal scans for breast cancer) and Ten3T (portable, easy-to-use electrocardiograms) are currently developing disruptive diagnostic solutions that will significantly bring down costs, while making physical distance a non-issue. They (and others in this area) do this via cloud-based linkages to hospitals and clinics, chatbots, smart apps and AI-enabled data analytics. This means that sensors, real-time tracking and analytics will enable us to take pre-emptive charge of our own health, helping us to live more aware, healthier, longer lives.

Eliminating human biases

Barring simple ailments, most health consultations and treatments today come with some human bias. Sometimes, there are doubts if doctors’ or pharma companies’ vested interests are pushing certain treatments and medicines. That is why we gravitate towards known doctors. And for serious illnesses and critical care, second opinions are always recommended. In this context, AI-enabled medical care can save time, effort and costs through easy access to unbiased, consistent, good-quality diagnosis and treatment.

The experience of doctors also determines the options they explore. AI makes it possible to access the learnings and data from hundreds of thousands of cases. Oncology, for example, is an area where doctors are continually combining and recombining drugs to treat cancers or overcome resistance to previously successful drugs. Already, AI algorithms are helping doctors analyse a much wider scope of data and predicting—with greater granularity—new drug combinations that are personalized for a patient’s specific need.

Democratizing healthcare for 1.3 billion

Since technology can provide the middle layer bridge, AI-led systems have the potential to take healthcare to people irrespective of their location and affordability. People who live in rural or far-flung locations no longer have to be deprived of the up-to-date care offered at the nerve-centres of medical research. The tech increases the accessibility manifold. We thus have an opportunity to make this world truly equal.

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AI,Chatbot,CMS,CRM,Customer Experience Management,Customer Journey,CX, Digital Experience,IoT,Machine Learning,Marketing Automation,Predictive Advertising

Customer experience is what sets you apart from your competition. A lot of dollars are being invested to analyze customers’ expectations and building technology that can enhance how customers perceive your brand.

There is a lot of action, but there are five technological innovations that are expected to take CX to the next level.

1. Cybernetic CX

AI is at the core of Cybernetic CX – a cyclic process – analyzing, identifying problems, determining solutions, applying them, monitoring, and repeat.

Cybernetic CX will use advanced analytics and AI to detect patterns and identify anomalies. This information will be fed to machine learning algorithms, which will continue to evolve and be able to correlate with a set of outliers to the root cause. As the problems are diagnosed and the remedies applied, machine learning algorithms powered by heuristics will be able to correctly predict remedies, which will be automatically applied to fix the problem.

Better still, it may even anticipate an upcoming issue and take actions to mitigate it.

According to a J.D.Power study, American Express has excelled at customer satisfaction for their credit cards. They seem to be getting their cybernetics right. For instance, a customer doesn’t have to go through multiple hand-offs while connecting to AMEX departments, as their routing system uses advanced analytics, predictive modeling and operational consolidation to route to the correct department.

Though in an embryonic stage, cybernetics can augment your future CX efforts.

2. Digital experience platform

For weaving a seamless customer journey, a customer-centric view and integration of all activities like marketing, sales, operations, customer service etc. have become a mandate. DXPs (digital experience platform) help you centralize and share context and content across your organization, which enables ease of coordination and knowledge sharing across locations, teams and technology platforms.

These platforms generally are armed with analytics, CRM, CMS, and marketing automation tools that help them to:

  • Capture customer information and generate a 360-degree view of a customer
  • Keep track of customer lifecycle for service reps to provide a seamless and consistent experience
  • Glean insights to optimize marketing programs
  • Use analytics to understand customer pain points and attribute CX to marketing efforts and in effect optimize marketing programs
  • Help create personalized content across channels

Also Read: What to do and not-to-do with chatbots

3. Voice of Customer Program

Technological solutions like social media monitoring, cross-channel surveys, speech and text analytics are used to capture and analyze customer preferences, feedback, and expectations. VoC tools can give insights that can aid frontline agents to understand their customers better and help various departments (marketing, sales etc.) to have an in-depth view of the customer journey. VoC helps in:

  • Formulating better campaign messages
  • Creating a unified customer view
  • Uncovering areas of opportunity
  • Identifying areas of customer dissatisfaction
  • Measuring business efficiency and performance

A Voc tool may contain:

  • Ability to collect a large amount of customer feedback and generate reports
  • A holistic view of customer journey like the type of interaction, touchpoints etc.
  • NLP, text analytics, speech recognition, semantic analysis, emotion detection etc. 

4. AR/VR

Augmented and Virtual Reality(AR/VR) are the game changers when it comes to creating awesome customer experiences. Both AR and VR can create engaging customer-brand interactions.

AR is being adopted by retail, financial, healthcare and hospitality industries alike to create immersive and meaningful experiences. For instance, AR in the food and beverage industry enhance guest experiences. AR menus create virtual food with multiple digital renderings and 3D photographs to display accurate representation and portions. Customers can also scan menus or food packages to determine nutritional information.

VR too is increasingly complementing CX because of its life-like experiences and emotional footprint.

5. IoT

Internet of Things is how various devices form a wireless network and communicate with each other using sensors. IoT holds tremendous engaging power and is the key to bring coherence to omnichannel CX strategies. Leveraging IoT, businesses can:

  • Reach customers in real-time: As a loyal customer is nearing your store, using hisgeo-location you can offer to serve him his favorite meal or offer a discount on his favorite order.
  • Make lives convenient: How about reading a grocery list on your customer’s smartphone and automatically creating a cart with the discounted items, and sending an alert to her to hit the buy button, before she runs out of stock?
  • Product health: IoT product can report its health to the customer care, which can proactively act by scheduling a service and fix issues before they become a reality. Read More
By Mark Bergen and Shelly Banjo
August 2, 2018, 3:43 AM EDT Updated on August 2, 2018, 5:11 AM EDT

Google staff awoke on Wednesday to surprising news: Their company is working on a search app tailored, and censored, for China. The project, kept secret from all but select teams and leaders, sparked a furious internal debate.

Yet the move couldn’t have been entirely surprising for Googlers.


Sundar Pichai

Photographer: Simon Dawson/Bloomberg

Sundar Pichai, chief executive officer since 2015, has made no secret of his desire to take the search giant back to mainland China. The executive is more pragmatic about the world’s largest internet market than Google’s founders, who pulled search from the mainland in 2010 over censorship concerns.

Under Pichai, Google has invested in Chinese companies, met with its leaders and made it a priority to spread Google’s artificial intelligence technology across the country. But bringing search back would be Pichai’s boldest move yet and will put his personal stamp firmly on the company.

Co-founders Larry Page and Sergey Brin built Google to “organize the world’s information and make it universally available.” They viewed China as a threat to the company’s stance as a defender of the open web. Pichai, in contrast, sees China as a hotbed of engineering talent and an appealing market. 

Pichai’s new leadership style and priorities haven’t always sat well with the Google rank and file. Within hours of the China search news breaking, several staff privately criticized the plans. Two employees who spoke to Bloomberg News compared it to Project Maven, a Google AI contract with the Pentagon that sparked an internal revolt earlier this year. The company is not renewing that deal. Read More

In 1985, we thought Einstein’s brain wasn’t much different from anyone else’s. We were wrong.

We still don’t completely understand how the brain works and yet we’re building machines to replicate it. Our quest to create artificial intelligence has grown into a near-frenzy as we surge ahead with unprecedented progress. But will we really reach the finishing line?

Any hope of success will depend on our ability to answer one simple question: What exactly is intelligence?

In 1985, American scientist Marian Diamond studied the brain of Albert Einstein and found an answer.

Was Einstein’s brain different?
We’re used to talking about neurons when referring to the brain, but we also have what are called glial cells. In Greek, glia means “glue.” Glial cells were given their name because we thought they did little more than just hold the brain together. One kind of glial cell is the star-shaped astrocyte.

In 1985, Diamond’s findings were almost disappointing. Einstein’s brain did not contain more neurons overall than the average person’s. It did, however, contain more astrocytes, in the left inferior parietal area of the brain, a region associated with mathematical thinking.

Since intelligence was assigned to neurons and astrocytes were thought to be little more than “glue,” this finding did not make headline news and was largely ignored.

What did Einstein’s brain actually reveal?
If you insert human astrocytes into the brains of newborn mice, they grow up to be more intelligent. Their learning and memory are significantly sharper. It’s only in the past few years that we’ve come to understand the extraordinary reason why.

We have always assumed that a synapse, the point where two brain cells join to carry information, is made up of two brain cells. We were wrong. A synapse is made of two brain cells — and an astrocyte.

Astrocytes nurture synapses. Not only are they key in synaptic plasticity, but they are plastic themselves. They grow and change. One astrocyte can be in contact with two million synapses, coordinating their activity and plasticity across vast realms of the human brain — and contributing to our intelligence.

How do astrocytes figure in artificial intelligence?
Artificial intelligence researchers from the University of A Coruña in Spain recently improved neural network performance by using an algorithm that included artificial astrocytes. When a neuron’s activity reached a maximum, the astrocyte was activated. It increased the weight of the neuron’s connections with the neurons of the adjacent layer by 25 percent, simulating what might happen in real life.

How do you increase astrocytes?
If Einstein was a genius because of his astrocytes, can we increase our astrocyte numbers and become geniuses too?

As early as 1966, Diamond and her team demonstrated that putting young rats in a stimulating environment rich with challenge and new experiences increased glial cells.

We now know that this even happens in elderly mice. Putting aged mice in an “enriched environment” increases astrocyte numbers and complexity, which correlates with better cognitive performance.

If you’re wondering, the effect is also seen in humans.

A study published this year followed production workers at a factory in Germany for 17 years. The volume of brain regions associated with executive function and motivation was larger in those who had been exposed to recurrent novelty in their work. This was associated with better cognitive performance at middle age.

Plasticity takes energy and effort and our brains are lazy. They don’t want to try to “grow” without good reason. Challenge and novelty tempt the brain with a reason to try.

What this means for you.
During her career as a professor of integrative biology at the University of California, Berkeley, Diamond concluded that five factors were crucial for healthy astrocytes — and for the human brain to thrive at any age: a good diet, exercise, challenge, novelty — and love (she noticed the mice in her lab lived longer and did better when cuddled).

Focusing on these five things can increase stress resilience and keep you mentally sharp. If you’re leading a team, you may not be able to change everyone’s diet and exercise routines or show love, but you can make sure your team has ample opportunities for “newness” and challenge. Minimize repetitiveness and standardization and encourage employees to learn and master new things outside of their skill set.

Astrocytes are one thread in the complex tapestry of intelligence, but our growing knowledge about astrocytes has made intelligence a little less baffling today than it was a few years ago.

When Diamond (who passed away last week) reported her findings in 1985, the overwhelming conclusion was that Einstein’s brain was not much different from anyone else’s. Today, we can confidently say that Einstein’s brain was very different, after all. Read More




Megvii Inc., the Chinese developer of facial recognition system Face++, is said to be raising at least $600 million from investors including Alibaba Group Holding Ltd. and Boyu Capital, according to people familiar with the matter.

The Beijing-based company, which already counts billionaire Jack Ma’s Ant Financial and one of China’s largest state-backed venture funds as investors, will close this round of funding within weeks, the people said, asking not to be named because the matter is private. The company will then seek a second tranche of funding, the people said.

Alibaba is ramping up its investment in China’s largest artificial intelligence startups, hoping to employ the technology across its growing internet and retail empire. Megvii provides face-scanning systems to companies including Lenovo Group Ltd. and Ant Financial, the payments company that underpins Alibaba’s e-commerce platforms. It’s competing with SenseTime, another startup backed by Alibaba, for market share in sectors such as retail, finance and smartphone and public security that could utilize facial recognition. Read More