Artificial Intelligence: Toward a Theory of Minds

One thing that differentiates humans from animals is a concept called “Theory of Mind”. Theory of Mind describes how individuals are able to understand what other humans are thinking and feeling so that they can make an appropriate response. This idea is increasingly important for implementations of artificial intelligence.  Theory of Mind is an understanding of the intellectual and emotional state, motivations, and probable actions of another individual based upon internal hypotheses about how that individual must be thinking. It demands creating a model of another mind. To date, this concept has been considered mainly in the realm of developing humanoid robots, but it has important consequences across all AI.

How is this important? It has two components with different effects. First, it is about developing an AI Theory of Mind to promote more precise interaction with human beings. Intelligent machines will need to anticipate human response to understand the broader context of questions and required actions. Second, it is about having a Theory of Mind for each AI that we, as humans, encounter (Theory of AI Mind). This will become increasingly important for interactions between people and machines.

AI Theory of Minds

AI Theory of Human Mind

The next evolution of an AI will require each AI to have a Theory of Human Mind, and an ability to understand and act according to human characteristics, thought patterns, and biases. This is a part of current developments. It is difficult, however, since it requires machines to understand something that we strain to understand ourselves. Philosophers have struggled endlessly with the lack of capability to externalize human thought or obtain an objective understanding. Still, as with the Turing test, the attribution of a Theory of Mind is proven if the machine is able to anticipate human thoughts, actions, or desires and act upon them in a way that signifies understanding rather than pre-programmed behavior.

Theory of Mind is likely to emerge as a clear differentiator between generations of AI, and an important milestone along the way to true general intelligence. It will also mark the possibility of full collaboration with humans with each side capable of understanding possible actions by the other.

Human Theory of AI Mind

The other side of the coin is the more immediately important human Theory of AI Mind. We are intuitively aware of this when question a digital assistant. Before making a query, we consider the “intelligence” of the machine and its probable response, and frame questions to produce a useful response. We then evaluate the response based on the same model.  If it is a weak or very limited AI, this is taken into account; if it is a strong AI, then questions of capability, bias, focus, and domain come into play. We create a model of AI response. Theory of AI mind is also important in considering responsibility for an action; a concept which will be extremely important for insurance in applications such as autonomous vehicles.

Theory of AI Mind will become increasingly important for user interface in moving toward ubiquitous AI. As machines grow “smarter”, we will expect more of them, and more differences between them. As with understanding of human Theory of Mind and personality, we will hold mental models of specific AI’s and interact with them according to that model.

Implications for Theories of General Intelligence

With further development of both sides of AI Theory of Mind will come a greater understanding of how people interact with other intelligent entities–including other humans. AI provides an intelligent “Other” that is not necessarily subject to biases of human thought. People have inbuilt biases of many types and from many sources including heredity, society, brain function, mental limitations, the conscious/subconscious split, and  innumerable other factors. If we abstract intelligence from this matrix, it becomes more possible to understand the specific things which make human intelligence special. For the first time, we may be able to step aside from human capabilities and reach a broader understanding of intelligence itself.

From a technology perspective, Theory of Mind will become a competitive factor in AI development. Machines of limited intelligence, creativity, or capability will be perceived as such and will have caveats put upon their operation. This is similar to human interactions with animals, which are perceived as having a small intelligence and fixed responses to many stimuli. Competition to meet such perceptual criteria will empower the race toward artificial general intelligence. It will also drive development of intelligence toward more human-like interaction. Some of this is already happening as we move toward intelligent humanoids which are made to appear like rational creatures and satisfy some of the requirements of a theory of mind.


Theory of Mind is likely to become more critical in coming years. In a sense, it provides an evaluative concept for AI which steps beyond the Turing Test. In the Turing test it is possible to create a nebulous interaction which appears on the surface to be somewhat human and somewhat able to fool individuals. But, if a machine is able to interact on an intellectual level and provide the framework for an adequate Theory of Mind ,then it becomes something more than just a machine with interesting and creative responses. Perhaps, a Theory of Mind is the basis for consciousness, or a preliminary step in that direction. But, in any case, this criteria, commonly used to differentiate between humans and animals, must be turned on its head to distinguish between humans and AI.


Agricultural Robots and AI in Farming; Promises and Concerns

With constant attention given to Industry 4.0, autonomous vehicles and industrial robots, there is one significant area of robotics that is often under-reported—the growing use of autonomous agricultural robots and AI-driven smart systems in agriculture. Although automation has been practiced on the farm for many years, it is not been as widely visible as its cousins on the shop floor. But technology being deployed on farms today is likely to have far reaching consequences.

We are on the edge of an explosion in robotics that will change the face of agriculture around the world, affecting labor markets, society, and the wealth of nations. Moreover, developments today are global in extent, with solutions being created in the undeveloped world as well as in the developed world, stretching across every form of agriculture from massive row crop agribusiness and livestock management, down to precision farming and crop management in market gardens and enclosed spaces.

Agriculture Robots Today

Agriculture is vital to the health of the ever-expanding human population, and to the wide range of interrelated industries that make up the agricultural sector. Processes include everything from planting, seeding, weeding, milking, herding, and gathering, to transportation, processing, logistics, and ultimately to the market—be it the supermarket, or increasing retail online. The UN predicts that world population will rise from 7.3 billion to 9.7 billion in 2050. Robots and intelligent systems will be critical in improving food supplies. Analyst company Tractica estimates shipments of agricultural robots will increase from 32,000 units in 2016 to 594,000 units annually by 2024—when the market is expected to reach $74.1 billion per year.

While automation has been in place for some time and semi-autonomous tractors are increasingly common, farms pose particular problems for robots. Unlike highway travel, which is difficult enough for autonomous vehicles, agricultural robots need to be able to respond to unforeseen events, plus handle and manipulate objects within their environment. AI makes it possible to identify weeds and crops; discern crop health and status; and to be able to take action delicately enough to avoid damage in actions such as picking. At the same time, these robots must navigate irregular surfaces and pathways, find locations on a very fine scale,  and sense specific plant conditions across the terrain.

Agricultural robots using AI technologies are responding to economies in the agricultural sector as well as to rising labor costs and immigration restrictions. The first areas of general impact are in large businesses, since robots have high investment and maintenance costs and there is a lack of skilled operators. Conditions will change as robots become cheaper, more widely available, and capable of performing more diverse tasks. This will require evolution of AI technologies, expansion of collaboration abilities among robots; and man-machine combined operations. The ability of robots to work with humans could be particularly significant due to the wide range of discrimination tasks involved in food safety, quality control, and weed and pest removal. Robots will be guided by human supervisors with skills in agriculture and knowledge of robotic and agricultural systems.

Opportunities and Growth

According to the International Federation of Robotics, agricultural robots are likely to be the fastest growing robotics sector by 2020. Different sectors of agricultural markets will respond differently. Large businesses with row crops are early responders, since they have funds to invest and shrinking margins. For these companies, there are huge benefits in reducing labor costs and instituting more precise farming methods. As picking and weed killing and pest removal systems become more widely available, citrus orchards and difficult-to-pick crops are likely to be next. Robots capable of picking citrus, berries, and other delicate fruit in difficult locations are already starting appear. There are applications in virtually every part of the agricultural sector.

Other uses will appear as robots become more common and less expensive. Robots can make a difference not only in harvesting, but also in precision of water application and fertilizer. In areas where water is contentious, such as California and the Middle East, more efficient watering will make it possible to grow larger crops with greater efficiency and less water, avoiding creation of political and social crises.

In the developing world, opportunities are enormous but individual farmers have fewer resources. For this reason, smaller robots and robot clusters are likely to be more widely used, possibly with emerging Robot-as-a-Service (RaaS) operators providing  labor on a per-usage or rental basis. Robotics will be able to save enormously on chemical costs and water used for irrigation, which will have significant economic impacts, as well as environmental benefits.

Progress and Caution

As use of agricultural robots continues to expand, they will take on increasinly complex tasks, and replace a larger portion of agricultural labor–a critical component of global employment. In many countries, particularly in the developing world, this will create shifts in employment which will empower trends such as rural migration to cities, and reduce overall availability of labor–intensive jobs. More training will be needed by more people; this will impact education, socialization, and finance; particularly in countries with large populations.

There are many implications as AI and agricultural robots are deployed. New ideas are blossoming, startups are on the rise, and we can expect a wide range of consequences as  next generation agricultural robotics and AI continue to emerge.


Legacy Modernization: The Video

Digitization is becoming increasingly imporatant as companies attempt to capitalize on new technologies, greater efficiency, and the benefits of cloud, mobile computing, analytics and artificial intelligence. Yet getting to the point where digitization is possible demands modernization of legacy IT. Nowhere is this more apparent than among the huge and expensively maintained government systems. Many large companies also suffer from software modernization issues.

With increasing attention turned to modernization due to Senate passage of the Modernizing Government Technoloyg (MGT) Act, now is a good time to re-examine this issue and consider why modernization is crtical to progress in new technology.  Here are a few videos pointing to modernization issues and possibilities as they are viewed today.

The videos are a mixture of seminars and discussions avaialable under standard YouTube license, with landing page descriptions added. Minor edits have been made where necessary.

New Economics of IT: Modernization (Avanade Inc)

Published on Dec 5, 2016

Critical to achieving a New Economics of IT is modernization. Avanade’s approach to helping organizations modernize is holistic, spanning the entire IT environment and catering for on premises, cloud and hybrid deployment models. Our methodology is underpinned by three key modernization approaches: Application Modernization, Infrastructure Modernization and Workplace Modernization.

Round Tripping & Refactoring (The Software Revolution, Inc. (TSRI))

Published on Aug 20, 2015
 Technology in Transition: IT Modernization (Accenture)

Published on Aug 25, 2017

As government systems age, security risk goes up and cost efficiency goes down.

Chris Howard — IT Modernization Summit (FedScoop)

Published on Apr 20, 2017


Recruiters: Mind Your T’s and Q’s

Finding the right person for the growing range of new technologies can be difficult. There are skills shortages in a number of areas, and there is a rush to fill them with obvious talent. In this rush, however,  it is important to remember that the specific skills are of only transitory value, and requirements will shift as the next new thing comes along.

Digitization is rapidly converging traditionally disparate processes and technologies, creating a need for a new kind of worker. In focusing constantly on specific technical skills, we may be weakening the ability to understand the broader context that must fuel innovation. There needs to be input from the Arts, from global experience, and from the imagination. This demands a different type of learning.

In the late nineties, “T-shaped skills” were introduced, with the vertical bar representing dept of skills and the horizontal bar, the ability to work across disciplines. This was useful in a structured and deterministic world. But we are now in a time of vast changes, shifting skills requirements, and new pressures from robotics and AI. It’s time for a new, and complementary, concept.

Some years ago, I drew a cartoon about recruitment fads ( in reaction to “T-shaped” assumptions. In it, I introduced “Q-shaped” skills as “roundness of knowledge with a squiggly bit underneath.”

Although this was partly in jest, it does raise a significant point. In a converged world, “T-shaped” is no longer enough. Just as Steve Jobs drew from calligraphy for PC invention, exposure to a much wider range of knowledge is increasingly essential for innovation. Imagination and ingenuity are also at a premium.

Certainly, “T-shaped” skills will always continue to be important. But handling the growing possibilities of digital convergence creates a need for the nuanced “Q-shaped” skills that focus upon the big picture and its imaginative possibilities.

We have already seen how over-emphasis upon rote learning and tests can increase “T” and diminish “Q” skills. Companies lacking in the former will have trouble meeting the needs of the moment; companies lacking in the latter will fail to envision  the opportunities of the future.

We need to increase our “Q” skills to create the Total Quality workforce of tomorrow.


AI and Risk Management: The Video

Risk Management is growing in importance for all companies interested in survival. It has particular relevance to the financial industries, where risk is at the heart of every investment strategy, and is the basis of insurance.  For other industries, calculating risk and prioritizing options is at the heart of resilience, both within financial and operations areas. It is also tied up with regulatory risk in  Governance, Risk and Compliance (GRC).

As a calculation, Risk would seem an early candidate for AI and Big Data approaches. It has lagged, however, partly due to  inherent conservatism, and partly due to broader questions of prediction that might require an Artificial General Intelligence. There are a lot of niche possibilities in this area, such as fraud detection and portfolio management, and interest seems destined to grow. Risks are growing, regulations are becoming more complex, and data is exploding. Companies need better risk management to improve resilience, and the financial industry would benefit in innumerable ways.

We have assembled a small set of videos on this subject, all with the standard YouTube license, and with descriptions from their landing pages.

Why Automate GRC Management Systems? (360factors)

Published on Oct 26, 2016

Governance, Risk and Compliance (GRC) software based on artificial intelligence technology automates the compliance functions.

 2016-2017 AI trends in Financial Services (Jose Allan Tan)

Published on Jun 13, 2016

Baker & McKenzie partner, Astrid Raetze, believes that financial institutions are looking at the various applications of artificial intelligence from risk management to credit assessment. AI can process an enormous amount of data very quickly. This will enable financial institutions to improve efficiency and customer service.

Applying Robotic Process Automation (RPA) in Finance and Risk (Accenture)

Published on Oct 12, 2016

Accenture Finance & Risk Practice is helping our financial services clients better manage the onslaught of data and regulations with the use of robotic process automation (RPA). Robots can drive cost, time and accuracy efficiency and work 24/7 around key tasks such as anti-money laundering and order-to-cash. Ultimately, this frees up valuable employees to focus on higher value work that only humans can do.

Intelligent Automation for Risk Management, Fraud Prevention, and Security Compliance (Cloud Raxak)

Published on Dec 19, 2016

July 2016 Webinar: Cloud Raxak, Gartner Cool Vendor in IT Automation, hosted a panel discussion on how intelligent automation is enabling regulated industries like financial services to leverage the cloud, while effectively managing risk, fighting digital fraud and money laundering, and maintaining security compliance.

Former executives from Bank of America, JP Morgan Chase, Silicon Valley Bank, and the Canadian Imperial Bank of Commerce provided insights on:
— Banking and finance industry regulatory compliance and fraud management challenges.
— How analytics and machine learning can streamline fraud risk management.
— How automation can reduce the cost and complexity of security compliance.




Digital Transformation, an Evolving Vision: The Video

Digital Transformation is viewed by many companies as a strategic necessity, these days. It can energize a business, build efficiency, reduce cost, and open the way for innovation. As with many concepts, however, it has become diffuse in meaning and marketing strategies tend to focus upon a few simple areas in which digitization can help. What is missing is a greater story of the impact, implications, and the actual consequences of undertaking such a transformative process.

Previous blogs on this subject are: Digital Transformation at the World Economic Forum: The VideoDigital Transformation: The Video, and Guest Blog: Lagging In Digital Transformation? 30% Of Your Senior Executives Are Going To Leave Within A Year.

We have now reached a point where most companies understand that this is coming and have programs in place for digitization of some aspects of their business. Now we need to look more closely at “Digitization 2.0,” where we begin to consider the opportunities and effects that have emerged from the innumerable successes and failures in this realm.

Here we have assembled a few videos on broader aspects of Digital Transformation. Most are standard YouTube licenses with explanation drawn from landing pages. The CEB/Gartner video is a share from the company’s site, with description from that page.

The case for Digital Reinvention (McKinsey & Company)

Published on Feb 28, 2017

Digital technology, despite its seeming ubiquity, has only begun to penetrate industries. As it advances, the implications for revenues, profits, and opportunities will be dramatic. Here we explore the results of our survey into digitization across industries and detail the case for digital reinvention.

The New IT Operating Model for Digital (CEB Global – Gartner)

Two-thirds of business leaders believe that their companies must pick up the pace of digitization to remain competitive. The pace and volatility of digitization opportunities, as well as blurred technology responsibility across the enterprise, makes it more difficult for IT leaders to help their organizations exploit emerging digital opportunities.

To meet these challenges head on, progressive IT leaders are changing IT’s operating model. We have identified nine features of the new operating model that will position IT teams for digital success.

The Digital Transformation Playbook (Columbia Business School)

Published on Jun 3, 2016

BRITE founder, author, and Columbia faculty member David Rogers talks at BRITE ’16 about how businesses need to transform by understanding that now: 1) customers are part of a network, 2) competition comes from platforms more than products, 3) data is a strategic asset, 4) innovation is driven by small experiments and scaling, 5) value is dynamic and adaptable. Get further insights and tools to make this transformation by reading his new book, “The Digital Transformation Playbook: Rethink Your Business for the Digital Age.”

The BRITE conference on brands, innovation and technology is hosted by the Center on Global Brand Leadership at Columbia Business School.

Digital Transformation of Society, Business (Gerd Leonhard

Published on Apr 5, 2017

A talk by futurist Gerd Leonhard.

“This is the edited version of my keynote at DST Systems Advance conference in Phoenix Arizona. This talk is about digital transformation (challenges and opportunities) – the next 5 years. You can download the slidedeck use in this talk via this link (PDF)”



Evolving the Cognitive Man-Machine

Human intelligence and artificial intelligence will increasingly interact as we extend the range of mechanical cognition to include sensory interpretation, role playing, and sentiment (Affective Computing, Intersecting Sentiment and AI: The VideoShifting the Boundaries of Human Computer Interaction with AI: The Video). Such advancement will both create new conflicts and increase our understanding of the human mind by providing an objective platform for comparison.

But the cross-pollination of human and machine understanding does not stop there. As digital assistant roles progress, robots will need to understand and influence people. They will need to win negotiations, and devise strategies of engagement. AI will need to become increasingly cognizant of human thought patterns and social characteristics. This will make them a part of the greater “human conversation.”

As cognitive systems are assigned roles in which they must take the lead or suggest actions, AI will be playing a human game with human pieces. Social interaction is a construct: Knowing the rules, anyone can play. This will lead to competition and friction between automata and humans across a wide range of activities.

Even as AI continues to advance, human capabilities will be amplified through integrated advisers, prostheses, and avatars that will vastly increase our ability to process information, remember and assemble concepts, travel to remote locations, and communicate–all at the speed of light.

Robots and mankind are locked in a co-evolution that will ultimately lead to hybridization. We can add new robotic capabilities much faster than we can evolve them on our own. Simple toolmaking was the first step along this path; the final step will be where the intersection of humanity and machine becomes blurred, and finally, almost invisible.

Organisms adapt to fill a niche; when they can no longer adapt, their cousins take over. Evolution is about survival of the fittest, not of the strongest or the largest or even the smartest. Technology is an evolution of tools to fit a world defined by humans, that will continue to be shaped by human thought. Hybridization is inevitable, because it will augment human capability. Technology can evolve and be adapted much quicker than native biology; so further evolution of the species will be based on technology.

At present, we are barely on the doorstep of hybridization. We have clumsy “wearables,” limited but promising smart prostheses; the beginnings of AR concepts from Google Glass to HoLolens; social industrial robots that can work with people; digital assistants that can insert themselves into social settings; and an increasing range of smart devices that bridge the human context and the IoT.

In a somewhat distant future, we will likely view this as simply “making better  tools.” The alarming possibilities we envision today will be the commonplace realities.  As with the unknown Chinese inventor of printing blocks for text, we will ignore revolutionary change and create a narrative in which everything is consistently normal.

Twilight of the Gods? Perhaps. For the present, we are faced with the problem of understanding these changes and applying new technologies in a way that society continues to benefit, and the multitude of interstices are filled. This will create great opportunity, but it will also demand innovation directed specifically toward human-machine interaction.

Ultimately, of course, this solves the problem of “the Singularity,” and a robotic Apocalypse. To quote Walt Kelly’s Pogo comic strip, “we have met the enemy and he is us.”


Outsourcing versus Robots: The Video

Business Process Outsourcing (BPO) is currently under threat not only from nativism, job loss, and immigration issues; but also from Artificial Intelligence. Robotic Process Automation (RPA) uses AI to handle a growing range of routine tasks; tasks that have been handled by outsourcing companies since the beginning of this century. Outsourcing firms are struggling to compete with the new technology, while also attempting to move up the value chain. This means that they are becoming more vested in AI,  both to provide RPA as a service, and to help other companies to develop their own automated solutions.

The giant Indian IT outsources are particularly affected. This is already leading to tectonic changes affecting businesses around the globe.

Following is a selection of four videos on this subject featuring presentations and a discussion. One is an embed from Vimeo, and the rest are provided under standard YouTube license, with explanations from their landing pages.

Automation’s Impact on the Economy and the Outsourcing Maretplace ( IRPA AI)

Published on Vimeo. A conversation with Raheem Hasan, IRPA (Instaitue for Robotic Process Automation), Joe Hogan, HCL, and Martin Ford, Author and Futurist

Ford Hogan from IRPA AI on Vimeo.

Approach to Cognitive vs Traditional RPA (EdgeVerve)

Published on Feb 9, 2017

Beyond Robotic Process automation – How AI based systems are ushering the next wave of efficiencies and transformation. Critical process questions before embarking on a RPA journey.

EdgeVerve Systems is a wholly-owned subsidiary of Infosys developing  software offered on-premise or as cloud-hosted business platforms.

Dr. Vishal Sikka, CEO, Infosys, introduces Infosys Nia (Infosys)

Published on Apr 26, 2017

Dr. Vishal Sikka, CEO, Infosys, introduces Infosys Nia, the next-generation artificial intelligence platform from Infosys.

How Robotic Process Automation and Artificial Intelligence Will Change Outsourcing (Mayer Brown)

Published on Jun 14, 2016


Nativism, Technology, Markets, and You

As we ponder the effects of global trends which brought us the recent US election and Brexit, the theme of nativism continues to play strongly. Nativism is the urge to reject external influences, such as immigration, and focus upon one’s own country in a zero-sum game. The world is viewed as a continuous competition, in which only one “side” can ever win. It can lead to isolationism and aggression, creating mirroring responses throughout the globe.

Nativism in the US is powerful and influential with the current administration, but it has an important context. The world is changing rapidly and we are in the throes of an extraordinary technological revolution. Many of the reasons for the growth of nativism are related to adaptation issues with technology.

The Internet has blown the human conversation into a million shards of conflicting opinions and information with varying degrees of truth. Simultaneously, education and affluence have grown in countries around the world, particularly in India and China. While technology makes it possible to conduct business across vast distances, it also enables companies to move swiftly between countries for tax benefit, or to create overseas research capabilities.

These changes will be felt most particularly in technology markets themselves, as companies struggle to meet the demands of changing geopolitical influence and new business clusters emerge around the world.

For the IT sector, we can see:

  • Increased movement to cloud computing and digitization, fueled by the need to provide mobility and instant access to information, processes, and resources in locations around the globe.
  • Accelerating repatriation of Indian and Chinese technologists to their native countries, in response to anti-immigration policies and regulatory constraints (Baidu Adds xPerception to its AI/VR Stockpile). This is aided by improving home country conditions.
  • A continued rise in development of virtual and remote enablement technologies such as collaboration tools. This will lead to greater interest in AI, mixed with VR to perform the mechanics underlying real time conferencing across national borders (On the Intersection of AI and Augmented Reality).
  • Development of new re-headquartering protocols as companies hedge their bets and realize that they can now move more easily to tax havens such as Ireland or toward closer proximity to markets in Asia which are growing at a faster rate than markets in the West.
  • An increasing geopolitical benefit to countries which avoid nativism and embrace immigration, particularly with the huge numbers of engineers that are coming of age in China, India, and the European Union.
  • Development of overseas resources and research hubs for all international firms to hedge against immigration policies, as we have already seen with Intel and its recent MobilEye acquisition (Car Wars: Intel Bags Mobileye), which takes AI research to Israel.
  • An increase in automation and further support of AI and robotics in the workplace as US companies attempt to retain operations in America, where the cost of a human workforce remains high.
  • A growing uncertainty over markets in the US, leading to a wide range of effects overseas. The locus of innovation could move, and the structure of international finance could change due to the combination of Brexit and Trump.

There are likely to be a wide range of additional repercussions. The progress of these issues will remain obscured since technology is evolving swiftly, and creating so many fault lines and subordinate processes that it will be impossible to gauge the mid-term result.

We can expect an acceleration of global change. Just as nativism is in itself a result of disruption brought about by technology, it also tends to increase these effects. Political repercussions will inevitably follow. As countries withdraw from international cooperation to seek independent advancement, reaction will include political and military adventures, with uncertain economic results.

Ultimately, this could force even greater globalization and move technical concentrations around the globe. This will create in a flowering of technological innovation in diverse locations, with particularly interesting possibilities in China–which already leads the world in patents. Forcing China to be more self-reliant plays into its traditional strengths and can create surprises as Chinese technological firms develop in stealth mode and come into confrontation with Western firms.

Nativism is likely to increase in ferocity in the coming years, though it is faced with a strong resistance which could prevail as people react to negative effects on security and jobs. There is a tectonic shift underway that will create major changes; uncertainty is likely to emerge as a dominant theme. As with the age of Gutenberg, technology has outpaced the capacity to predict the future.

For businesses, it will be increasingly important to act locally but plan globally. National trends must be respected, but the context needs to be understood. Global markets and technology trends will persist. During this readjustment, maintaining balance between local and global demands will be critical.


Blockchain Meets the IoT: the Video

Blockchain, the secure ledger system behind the Bitcoin cryptocurrency, is becoming increasingly important in key usage cases throughout business and industry. It provides a persistent, unalterable record system that is becoming increasingly important to security. And secure transactions are of critical importance in sensitive areas such as finance and health. But one of the most important areas that is now emerging is the connection with the Internet of Things (IoT). The surprising benefits of incorporating blockchain concepts in IoT development are creating intense interest as companies grapple with the needs of new infrastructure.

In these videos, we provide several discussions on the intersection of blockchain and the IoT. The videos are under standard YouTube license, and the description provided is from each video’s landing page (with minor edits).

Blockchain and the Internet of Things explained (IBM Internet of Things)

Published on Nov 2, 2016

A blockchain ledger can create a tamper-resistant record when information needs to be shared among business partners without setting up a costly centralized IT infrastructure. Let’s look at how supply chains benefit when data is shared through a private blockchain.

Next Generation IoT Technologies Using The Block Chain (Samsung Developer Connection)

Published on Dec 1, 2014

Talk by Gurvinder Ahluwalia

An overview of how Samsung and IBM are thinking about the next generation of IoT infrastructure, and why they are using Blockchain. This presents an approach to address the problems of cost, privacy and longevity of smart devices on the Internet Things.

Key Use Cases Intersecting Blockchain and IoT (IBM Internet of Things)

Published on Dec 9, 2016

Jerry Cuomo (Vice President Blockchain Technologies, IBM), Mika Lammi (Head of IoT Business Development, Kouvola Innovation), and James Murphy (Offering Manager, IBM Watson IoT Platform – Risk Management & Security) talk about the trends in business that are driving the pairing of Blockchain and IoT.

Blockchains for the Internet of Things – Solving the IoTs Most Critical Problems (

Published on Jul 7, 2016

Blockchains are poised to revolutionize the Industrial Internet of Things (IIoT) by providing security, peer-to-peer device communications and new functionality via smart properties. Andre De Castro CEO of Blockchain of Things, Inc. discusses why blockchains make sense for the IIoT