Harnessing the Fourth Industrial Revolution
We are already in the path of the Fourth Industrial Revolution, the one characterised by a merging of the physical, digital and -at least for some- biological world. Personally I tend to limit the characterisation to the merging of physical and digital leaving the merging of the biological to a fifth revolution. At that stage, possibly by middle of this century we will also see the emergence of artificial “consciousness” or Artificial Super/General Intelligence.
Previous industrial revolutions were not contained in the industrial landscape, they affected (and were partly driven) by political vision/framework and of course they changed the social fabric.
This does not change. The Fourth Industrial Revolution will be affected and will affect political systems. The World Economic Forum is actually makinoticsg a call to politicians and Governments to steer this revolution and to take advantage of the forced acceleration created by the pandemic and of the alternative paths opening up in the post pandemic recovery. The call is to look at this crisis as to an opportunity to directi the evolution towards a green, smart and fair future.
The main beacons for this evolution are:
- the shift towards a Digital Economy (this is a quite complex and articulated area as presented in the EIT Digital course developed in conjunction with IEEE FDC) that is not going to kill the whole classical economy but it is most likely to affect all biz in the classical economy, including those that would seem to thrive only in the physical space (as an example, we have just seen how restaurants have been affected by the pandemic and how many had to change their operation first and biz model later to survive and then thrive again);
- the uptake of Industry 4.0 made even more pressing by the need to rethink the supply chains and the need to capture market changes (slow down of demand) and influence upstream processes in real-time. Additionally, the lock-down to contain the pandemic has shown a weakness in scaling of production of goods (like sterilisers, masks…) and the challenge to redirect production to needed goods. This has pointed to the need for a much more flexible organisation of processes and orchestration at micro level (quick hiring, as an example, to manage peak request). At the same time the changing demand showed how much better are digital components at scaling (including support infrastructures, like the Cloud and the Internet/Telecom infrastructure). This latter gives steam to shift as much as possible functionalities to the digital space. Digital Twins are seen as an interesting technology/paradigm to respond to these needs;
- the crucial role of media that to a certain extent failed their mission to provide trusted information. The media space has become so wide and can accommodate so many voices that it is becoming more and more difficult to separate the wheat from the chaff. Uncertainties in understanding the virus spread resulted in confusing and contradicting messages, casting a shadow on science credibility. As media becomes more and more effective in reaching audiences this problem is just getting harder and harder to address. The so called free world did not fare any better than Countries with limited expression freedom. There is a need to regain trust in institutions and to establish effective communications. Interestingly, this aspect was highlighted in many conversation I had in these last two months with several key people in industry. Media are having a direct impact on economy and industry, as shown by the reaction to 5G deployment in several Countries;
- Internet has proved to be extremely resilient, accommodating a doubling of traffic basically with no hiccups. Business and social life, including education and institutions interactions, moved in days from the physical space to the cyberspace. The crucial role of Internet requires an solid Internet Governance;
- the importance of turning to the oceans as a resource. Oceans make up 71% of the Earth surface and 99% of the living space on the planet. They have deep effect on climate and are an immense source of resources, including fresh water that can be extracted using advanced technologies to quench the thirst of agriculture.
If those above are the beacons, there are several factors at play, most likely accelerating the evolution for some and delaying it for others. The understanding of these factors and how they impact a given context (taking into account that any context is not static, it changes as result of internal evolution and external factors, like choices taken by competitors) is crucial in planning for the New World:
- Converging/fusing technologies
Technologies have grown, and keep growing at an amazing pace. Often the issue facing the industry is what to choose, not the lack of choices. Choosing is difficult because of the continuous evolution, technology roadmaps are not sufficient, they have to be considered against market and products roadmaps since they are interacting and affecting one another. Another factor is that products, and products manufacturing processes, are the result of converging technologies and also, we see the fusion of technologies resulting in the advance of performances. A clear example is the growing pervasiveness of Artificial Intelligence, steering evolution of manufacturing processes and leading to enhanced functionality in products. At the same time, this pervasiveness is fostered by the increasing affordability/performance of sensors, creating the data needed by AI, and by increasing processing capability (including new computational architectures). In addition to AI we are seeing the parallel evolution and convergence on products and manufacturing processes of Augmented and Virtual Reality, of 3D printing, of Material Science and Smart Alloys, with Blockchain more and more used in supporting supply and delivery chains. Biotechnology and quantum computations are real but their impact (in general) is limited. They are already important in specific sectors (like prosthetics and pattern matching respectively) but for wider adoption we should probably wait few more years.
- Agile Technology Governance
A significant number of technologies are creating a sort of backstage to support products manufacturing and usage. Under this category we can find 5G, IoT, blockchain (again), various typed of platforms like FiWare and Mindsphere. Cybersecurity shall also be considered in this category. Notice that all of these require a strategy. It is within this overall Country/company strategy that choices have to be made, knowing that any choice made in this area leads to a sort of lock in (if one chooses FiWare as the platform to accrue data and support applications, this choice leads to the creation of a very specific ecosystem and it will be difficult to change it in a blink of an eye). Yet, all these choices have to be governed, be part of a decision process that is internal to the company and consider global -external- governance. This is why Governments can play a significant role (as an example coordinating with other Government to establish agreed framework, like the one for open data and data protection, privacy rights, standards, emission levels, energy quality/subsidy. The area of energy is particularly important and it is often beyond the control of a single company. Take the example of selecting renewable energy sources. It would seem a no brainer but it is far from it. If selecting a renewable source implies higher manufacturing cost it is an unlikely choice for a company operating in a competitive environment, since other companies selecting fossil fuel would be able to sell at a lower price. This, by the way, is an issue today with the price of oil having it the bottom. Through transnational agreement on energy policy levelling the competition field, Governments can subsidise in various forms the adoption of renewable, clean energy. This is one of the point proposed by the WEF to move for a greener economy.
- Innovation and Productivity
The challenges of innovation and productivity are not new, nor are they characterising the fourth industrial revolution. What may be new is the way to pursue innovation and productivity. More and more innovation can result from an ecosystem wide effort where a company is able to harvest what is good here and now and embed it into its production processes (a big challenge). Hence those companies that have more flexible processes (in supply, manufacturing and customer relations) are the ones that are most likely to reap innovation benefits. Internal innovation is also important and can be a distinguishing/competitive advantage for some companies but again this is more and more the result of attracting the right talent, at the right time on the right goal. These talents not necessarily (see on point 5) have to be “employees”, they may well be freelance willing to share skills and knowledge. Likewise, productivity is no longer a characteristic of a company, rather a characteristic of that company ecosystem. Whilst in the last decades the point of discussion was on offshoring production, vertical manufacturing … in the fourth industrial revolution the point is the optimisation of a flexible distributed manufacturing, extending to the point of sales and in many cases to the user point (as software releases will not just be downloaded by the user (device) but also customised in the user context (this is one of the important aspects of Industry 4.0).
- Business Disruptions
Technology advances and market evolution created business disruptions in the past. Think about the shift to digital music (supported by technology and fostered by users adoption) and the disruption of the music sector. The post pandemic, the need for societal distances and the perception of this need by the market, plus the heavy financing Governments have undertaken to help industry are creating a new landscape where investment may be directed by policy more effectively then ever before. Thin about the forced shift to smart working, the boost to eCommerce, the digitalisation of many physical processes. Add to these a policy towards circular economy, towards green energy, the drive towards shifting “manufacturing” to the cyberspace and support to insourcing to alleviate job losses and you get what the WEF calls the Great Reset, i.e. let’s start from scratch by reinventing the way of doing business. Investment goes to advanced manufacturing (to facilitate/drive insourcing) to softwarization of products and processes by support to data lakes and AI based processing. All this creates, forces a business disruption that may become self sustained. A Country, a company, may elect to go back to business as usual but this might prove impossible if the external context is shifting to the Digital Space and receives funding to foster/sustain that shif
- Disruption of Jobs and skills
The disruption of business as well as the adoption of new manufacturing/business processes and the need to understand and operate with new technologies accelerate what was already an ongoing process of disruption in the job space. New skills are needs and old ones are made obsolete. Interestingly, this creates a push towards the Gig Economy. A given skill can become superfluous here, in this project, but may well be required on a different one run by a different company. Flexibility in the job market provides competitiveness to the whole ecosystem. At the same time, the changing needs stimulates individuals towards continuous education and of course it stimulate the offer for continuous education support. Universities are likely to be transformed by the convergent pressure of offering tele-learning and continuous education. Companies providing customised skill, and knowledge are likely to hit the market. Distributed knowledge is going to become the natural playing field for companies where part of this distributed knowledge resides in machine (AI, Cognitive Digital Twins), part in Companies and part in individuals. The possibility to encapsulate a person skill/knowledge in a machine (in a cognitive digital twin) may lead to a new type of worker, a worker “owned” by a person and instantiated as many times as needed to deliver its services to the market. New frameworks for protection of IP will be needed (see point 8).
Security has always been important and as better way to provide/ensure security were found, more critical situations arose, as the overall ecosystem became more complex. Security has become part of the design and this is no longer sufficient. It has to become part of the ecosystem and this requires the existence of framework and testing at the design level. I was speaking recently with a person of Mevea, discussing digital twins, and he pointed out that a new role for digital twins is to participate in the testing of features and interactions to discover weaknesses and to act as supervisors through the lifetime of a process/product/service to detect any security threats. I don’t fool myself into believing this can be the solution, but it surely shows a continuous effort in upscaling technology to face the upscaling challenges in system wide security. Technologies like drones, IoT, neuroscience can be at the same time source of threats and countermeasures. International cooperation detecting global risks as well as agile governance for fast response are more and more needed.
As mentioned, different Countries will have different policies and result (or as result of) different cultures and this may lead to inequality in business opportunities. Gender inequalities (level of instruction, salary, access to leading position) will translate in lesser competitivity, as fewer resources will be available. Part of these issues on Gender Inequality are addressed in a Roundtable today at Melecon 2020. The GDP may become more and more dependent on the actual Happiness/Wellbeing index. So far, (even worse in the past centuries) that has not been the case. Robert Kennedy famous statement “GDP measures everything in short, except that which makes life worthwhile” is very true (although one may object that a well distributed GDP provides the material resources that contribute to make life better…). Some countries, like Bhutan Gross National Happiness, are trying to use a different metrics to measure the wellbeing of citizens and plan to increase those metrics. Inequality plays a role across Countries as well, different taxation rules lead to shift of business (companies) towards more favourable environment. Sustainability measures may play both ways and it is important to reach agreement on the broader possible scale to ensure market viability.
I have been addressing the various factors that make up a fourth industrial revolution plan in order from technology upwards, in a way from the enabling factors to the system wide consequences, noting that the interplay goes both way. At the peak, if you want, we have the ethical aspect. Ethics is context and time dependent. We have, of course, declarations of human rights and we like to call these universal values but if we look back just a couple hundred years these “universal rights” were quite different. Even today, different cultures sustain different sets of rights. We like to think we have reach the point of absolute care in human rights and we consider those Countries that have a different set as “lagging behind” (just consider the different stance on death penalty, youth work/education, gender parity, LGBT parity). Same goes, with different nuances for different (religious) belief. The truth is that two hundred years from now our offsprings will look at us as a generation with low perception of human rights. The fourth industrial revolution will bring along challenges to our belief on rights. What about the rights of intelligent machines? How should an intelligent machine behave in case it finds the possibility of an autonomous action resulting in the loss of a human life as well as in the preservation of several others? Or in the preservation of resources? During the Covid-19 healthcare institutions had to take decision on allocation of resources that resulted in some cases in choosing who should be assisted. Some of these decisions were taken based on clinical data resulting from machine/AI analyses. The dividing line between machines and humans is getting fuzzier. What about autonomous cognitive digital twins that could replace a person’s cognition? What about responsibility, as well as accountability and ownership? Difficult questions awaiting for discussion.