Strategy of Japanese robot industry

Essay submitted for the class Strategical Management of Technology – Jun 17

An investigative essay about how the government of Japan is shaping the business strategy of national robot manufactures. *The original work submitted has been slightly altered.

Main conclusions of this work

  1. The robot industry of Japan is the largest of the world, however the domestic market is decreasing.
  2. A Robot revolution is articulated by the government via funding, easing regulations and bond buying.
  3. The Bank of Japan is on a program of bonding buying and has a major shareholder position on the robot sector.
  4. It is unclear if the government directly influences the strategy of the robot industry.
  5. The industry has mostly adhered to the Robot revolution plan established by the government, but it demonstrates resistance to incorporate changes related to opening software.

Overview of the Japanese robot industry, market and government management

The Japanese robot industry is the largest of the world. In the last report of the Ministry of Economy, Trade and Industry, Japanese robot industry accounted for 50.2% of a $8.49 bi market. Despite the overall growth, Japan saw a decrease of 25% of the domestic market between 2008 and 2013 [1]. However, the growth of robot use by China, Germany, South Korea and the US led a strong increase of the market size of about 60% between 2008 and 2013. These countries plus Japan account for more than 75% of all robot purchases [2].

To understand the reasons behind the decline in the Japanese domestic market, we can apply the Porter’s five forces analysis (Fig. 1). On one hand, Japanese companies have two main aspects in their favour: suppliers have low bargain power and the threat of new entrants is low/medium. A low threat of the suppliers exists because the semiconductor and electronic supplier industry in Japan is extremely competitive and diversified, making it easy to look for alternative suppliers. More than that, many large companies hold shares on the supplier companies. This strategy model is known as “keiretsu” and helps to stabilize price fluctuations. Two examples are the Sumitomo corporation (owner of Sumitomo bank, NEC, Mazda, among others) and Dai-Ichi Kangyo corporation (owner of Mizuho bank, Fujistsu, Hitachi, among others), which are clients of Trend Micro software company and, at the same time, are indirectly major shareholders of the company via multiple subsidiary fund accounts (Japan Trustee Services Page, subsidiary of Sumitomo Mitsui Trust Holdings and Trust and Custody Services Bank, subsidiary of Mizuho Financial Group)[3].

Figure 1: Main features of the Fiver forces Porter analysis for the domestic scenario of robot industry in Japan.

The other aspect in favor of the Japanese robot industry is the low threat of new entrants. The robot industry requires a set of core competencies which is expensive to develop. As a consequence, only major companies have been able to give continuity to serious robot programs. Additionally, the Japanese corporate market has strong brand loyalty [4] and new companies need high differentiation and focus strategy to be able to place a product. As a result, the robot industry in Japan is composed of previously existing traditional organizations, with research made in national centers and a very modest start-up scenario in comparison with the Europe and North-America. Among the new companies, the one of the most prominent is Cyberdyne, a venture firm which makes robotic suits and exoskeletons. The firm was initially funded with technology developed at Tsukuba University and funded by transfer aids from the Ministry of Economy, trade and industry (METI) and New energy and industrial technology development organization (NEDO) with the purpose of developing robots that can be worn, aiding impaired people to walk or helping to weight heavy lifts (Fig. 2). The company has been valued at about $2.6 bi and had relatively successful penetration in European markets, but, it has been struggling to make profits [5].

On the other hand, the domestic market of Japanese robots face three serious issues: the threat of substitute product, the rivalry among competitors and the bargaining of buyers. One central point is that currently most robots are used for industrial applications [6]. In the case of Japan, it is the country with the second highest incorporation of robots (after South Korea). For each 10,000 employees, there are about 300 robots [2]. But manufacturing jobs have been decreasing according to METI [7] and wages have remained stable in the last 10 years differently from other countries like China, South Korea, US and Germany [8], which have pressure to substitute workers due to rising salaries. As a unique case, the substitute products from Japan is traditional labour, which disfavor further robot incorporation.

Figure 2: Similar robots produced by major Japanese companies.

The government is trying to change this situation with a plan for a Robot revolution [9], which aims to turn Japan into a “robot superpower” and is part of the plan devised by the government to revitalize Japan’s economy [10], which we synthesized in a PEST graph (Political, Economical, Social, Technological points of view of the Japanese government about the robot industry 3). The main idea is that robots will be incorporated in areas not saturated by robot use, such as healthcare, food and agriculture. The plan also contains a set of actions to be taken by the government to stimulate the robot industry and to position it on the international market. The government hopes that the Robot revolution will help at the same time to solve the problem of aging population in Japan and of the escalating healthcare costs, which are estimated to increase by about 1 trillion yen per year [11].


Figure 3: PEST analysis of the robot industry in Japan according to the Robot revolution planned by the Japanese government.


Companies have apparently complied with the government plan, which led to the development of very similar products such as in Fig. 2 by major Japanese companies. Although each products claims differentiations and niche markets, there is clear competition, since they were designed with a general purpose in mind. Most seriously, although the Robot revolution plan has been a well defined set of actions to tackle serious problems of Japan, the market for consumer robots such as in Fig. 2 has not been fully deployed, which means large R&D projects have to be conducted with the perspective of a potential market without actual profits. According to Minoru Asada from Osaka University, “Japan has been a technology leader, especially in hardware, but when it comes to strategies for making robots more available to society at large, we are behind” (via The Financial Times) [12]. As a consequence, customers who are unsure if they need or want a certain product have higher purchase power and are part of a smaller market, which increases the rivalry and competition between similar products.

As METI recognized, “Should Japan lag behind such trend in terms of ideas about robot development or perspectives of business models, Japan will be isolated from the rest of the world in the field of robotics as well and be eyed as Galapagos which will draw more concerns over the situation in Japan where craftsmanship enjoys a victory but business suffers a defeat.” [13]. The analogy to Galapagos is a reference to the isolated island in the Pacific ocean where animals evolved unique characteristics due to the lack of competition and predators and means that it is not necessary only for Japan to have the best robots, but also to find profitable business models. At the moment, the market for consumer robots in Japan is promising, but elusive.

Paradoxically, both the most relevant strengths and weakness of the industry lie in the idiosyncrasies of the Japanese domestic robot market. If we do the SWOT analysis of the robot industry in Japan (Strength, Weakness, Opportunities, Threat), it becomes clearer that Japan is in a very unique position. One main strength of the Japanese robot industry is the advanced hardware industry which has been developed trough decades of R&D in related technology sectors and has allowed high incorporation of robots in the industry, most notably in the automotive sector [14]. A second main strength is related to the openness of Japanese people to robots as part of society. That means that even if consumer robots have not yet become a hit product, Japanese society is more comfortable interacting with humanoid robots than people from western cultures [15]. And it may as well not be a choice, given the aging population in Japan. Japan currently has the highest ratio of dependents/working force in the world and it is set to increase significantly by 2030 [16]. Prime minister Shinzo Abe said “Japan’s demography, paradoxically, is not an onus, but a bonus.” [17]. In that sense, the urgency to solve the aging problem and the low productivity rates of Japan is an incentive to the robot industry translated in government financing and regulatory support. $100 bi yen have been reserved for the Robot revolution project [13] and the robot regulations have been eased. According to Reuters, “The trade ministry has convinced health ministry officials to relax certification procedures for medical devices and introduce affordable robots to nursing homes on a trial basis.” and cites Kiyoshi Sawaki, head of the trade ministry’s industrial machinery division: “The approval process is being simplified. […] So companies can’t use the same excuses that they did before.” [18].

Figure 4: SWOT analysis of the robot industry in Japan in an international scenario.

The incentives given by the government try to overcome the high risks associated with the emerging market of robots for consumers. That is probably necessary given that major Japanese companies tend to be risk averse [4], which can be a weakness in a fast changing market. Another reported weakness of the Japanese robot industry is over-engineering, a gap between what engineers envision and the minimum product required, causing delays in releases and increase in the price and complexity of the product [19]. Naturally, many of the robots developed by the companies such as depicted in Fig. 2 are made to develop competencies for future projects, but Bruno Maisonnier, CEO of the french company Aldebaran, which developed the robot Pepper for Softbank points: “Honda makes an impressive robot [Asimo], but where can I buy it?”.

As a result, while Japanese industrial robots thrive, there has been a grey area for assistant robots such as in Fig. 2. Critics say one of the causes of the delay in the market deployment is the resistance of Japanese companies to open the software and allow outside programmers to develop software. Japan robot industry is regarded as a hardware power, but software has lagged behind [12]. The government pointed in the Robot revolution plan that this issue must be addressed choosing robots with open software for the companies to work together, but major Japanese companies usually do not have experience in handling open software and this seems to be one of the few aspect of the government guidelines which were ignored.

This poses a great threat from other robot exporters which have experience in managing open software like Germany, France and the US. On the case of China and South Korea, the threat arises from the geographical proximity: a report from Moody’s shows that most of the robot trade is inter-regional. Therefore, in order to Japan to establish its position as a robot superpower, it is not enough to do well on a global scale but to surpass regional competitors China and South Korea, which are heavily investing to achieve the same position (China 1.9% of GDP and South Korea 4%) [2].

This raises the question: are Japanese companies heading further away from a blue ocean? This seems to be happening not only because of fierce international competition, but also but also because of the domestic compliance to the Robot revolution, which comes with advantages – financing, easing of regulations – and burdens – heavy R&D expenditure, development of low profit products, risk taking. By itself, it is remarkable that the government was able to engage the companies in this policy. Traditionally, Asian companies prefer to keep good relations with the government while western companies don’t mind being disruptive, but there might be another another aspect that could be considered.

In the last years, the Bank of Japan has become the major buyer in the stock Japanese stock market and is now the a Top 5 owner of 81 companies listed and on course to become major shareholder of 55 companies. The mass purchase is said to be done to help to achieve the 2% inflation rate established by “Abenomics” policy and reinforced by the Bank of Japan [20]. According to prime minster Shinzo Abe, “The government and the BOJ will work as one in close coordination to accelerate ’Abenomics’”. These purchases are distributed along strategical sector of the Japanese economy, including robotics, as shown in Table 1. There is no evidence that the Bank of Japan or the government indirectly influences the strategy of these companies, but it would be odd if a government shareholder would oppose the plan established by the government. So, Table 1 suggests there is another factor to account on the reasons the robot industry is following the Robot revolution plan and reveals also a collateral way the government can support the industry with higher security and stable price of suppliers. These actions are consistent with the ambitions of the Robot revolution plan, however, they might help to steer companies away from a blue ocean towards a common goal and they make the sphere of influence of the government unclear.


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Original PDF file: RobotStrategy_masukawa

Coding into cracks – How inherent flaws of law can be exploited by artificial intelligence

Essay submitted for the 47th Saint Gallen Symposium.

For more than 50 years, researchers have been developing the theoretical foundations to use Artificial Intelligence (A.I.) in law. But, only recently, the first A.I.’s made their way into big law companies. For now, A.I. systems act as assistants, however, it is expected that their responsibilities grow in the next years. As they do so, computers will face the complicated challenge of understanding human language and, more specifically, law. But could it be that they also do that better than us? A common opinion is ”yes, because laws are sets of logical hierarchical rules, which computers can handle well” and, conversely, ”no, because computers follow fixed instructions and therefore can’t reason”. We will know the answer in the foreseeable future, but both justifications are wrong. In this essay, we will try to show why laws can not be interpreted as simple mathematical statements and how computers are able to cope with it, possibly posing a challenge to the judiciary system procedures and helping us to see flaws in today’s making and amendment of laws.

The cracks

It is often believed that law is a logic and consistent set of rules or, more modestly, that the inconsistencies in legislation compose a small set among the vast universe of laws discussed and written by a parliamentary institution based on democratic principles and constantly under review. However, this is not strictly true. Holmes, an associate justice from the USA supreme court in the early XX century, famously wrote: ”The life of the law has not been logic; it has been  experience”.

Seminal work of philosophers Jacques Derrida, Niklas Luhmann and Rudolf Wiethölter originally discussed the fact that law is ridden with inconsistencies[1], even though civilian instinct may insist that the laws are subject to strict logical reasoning and so are accepted and legitimated. Although there are many examples of such contradictions, which can be sourced from the discussions on the book ”Paradoxes and Inconsistencies in the Law”[2], we would like to avoid the interpretation that flaws are due to a specific law or country or political inclination and will discuss law on the broadest sense possible.

Some reasons why laws contain inconsistencies are, for instance, because legislation adapts in reaction to the historical/social context and usually there isn’t extended thought before laws have to be changed. This is directly related to the fact that there are close ties between law and traditions. Such relation is concomitantly cause and palliative solution for inconsistencies: at the same time laws have no compromise to mathematical rigour, they are subject to further judgment, review and iteration that makes them adequate and legitimate. And, most importantly for this essay, laws contain inconsistencies because they are almost always made and interpreted using classical logic [3], which can not be used in systems with paradoxical definitions. As a surprise to many people, there are other logic systems, some of which can handle inconsistencies better such as paraconsistent [4] and defeasible logic [5].

But the stated reasons on why laws are flawed are by no means nihilistic and do not implicate that laws should be disregarded. In a context in which law is made by humans and interpreted by humans, the vagueness is what allows laws to conform [6]. Furthermore, in order to make sense of the legislation, it becomes necessary to have an extensive knowledge not only of laws, but also of the current political situation and human reasoning and nature. This knowledge is cumulative and, because of that, so extensive, that it takes years to train a lawyer to be able to reason a complex law case and, most importantly, to express her or his own reasoning understandably and convincingly. For the complexity and importance of this job, the lawyer profession has been for many centuries praised and subject of much esteem. Fairness and persuasion were commodities that few could offer, let alone computers. But this was to change in this decade.

The code

The attempts to automatize the activities related to law date back to the 70’s [7, 8, 9]. But, until recently, researchers could not tell whether or not computers would abide unable to do tasks such as collecting evidence, ordering data by relevance, synthesizing unstructured text and image, interacting with lawyers, sensing political and public moods, creating and supporting thesis and conveniently exposing the summary in a human understandable way. Computer still don’t excel at some of this tasks, but not long ago many researchers from the A.I. field believed it would be impossible for computers to execute such tasks even on a basic level [7, 10, 11].

As consequence, the practical use of A.I. until the 90’s was limited to simple tasks such as counting the frequency of words, simple word context guessing and matching short text excerpts to input keywords [7, 12]. The technology at this time was highly experimental and it took a 50 years hiatus until A.I.  software and humans shared tasks in big companies.

Ross, for example, is a modern software lawyer already employed in law companies to do the same job as junior lawyers. Ross searches relevant cases and is able to extract facts and conclusions from documents [13]. And it can only do so because it uses multiple techniques of natural language processing, information retrieval, machine learning, computational linguistics, knowledge representation and knowledge reasoning [14]. Theoretical studies on these areas are relatively recent and this is the first reasons why A.I. software felt short of expectations until now. The second reason is that the computational power needed for such intensive tasks was not available a couple of years ago.

So, what would be a scenario in which A.I. is completely integrated with law and used in the judiciary system? Prof. Richard Susskind, from University of Oxford and one of the earliest promoters of use of A.I. in law, suggests that in the beginning, two parallel processes will occur: the use of A.I. as assistants and the progressive increase in A.I. autonomy in judiciary tasks [15]. At the moment, the first seems to be true as Ross is already used with this purpose, but Susskind proposes that soon people will use A.I. online platforms as consultants and that the role of A.I. in law will be to democratize access to law advice. This scenario is optimistic but feasible, since many technology companies today adopt a business model of democratic access to technology. But a much less discussed aspect of this scenario is how our laws and public workers will cope
with it.

Suppose a litigation whose parts use both human and A.I. lawyers and which is arbitrated by a judge who also uses a A.I. aid. Now, it is not uncommon that very complex scenarios develop, which are further painted by the parts. As a consequence, it can happen that there are not clear precedents. The plaintiff and her or his A.I. colleague would be able to bring a statically chosen set of previous legislation and metadata (information that describes information) to be presented by the lawyer. This metadata, which will guide the lawyer on how to make the case, is not only about the law itself, but it will take into account the expertise of the judge and the defense lawyer, making accurate guesses on the probability of winning the case. For example, a software from the University of Liverpool developed by the group led by Prof. Katie Atkinson was able to guess the correct result of 31 out of 32 cases of real law cases sampled [16].

And, fairly, the judge and defendant lawyer will have the same awareness. In a case regarding a long standing law, the plaintiff will be able to find a few hundred related precedents/legislation, with a couple being more relevant. Only to find out those are themselves contradictory to other laws as indicated by the defense lawyer. In the end, the infinite loop will be inevitably terminated by a verdict. But the main problem is that all of this discussion will be added to the pile, increasing the risk of making the whole set of laws even more inconsistent.

One useful analogy to understand this situation is the Socratic method. Socrates would walk in the street market of Athens talking to different people. As soon as an interlocutor made an assertion, Socrates would ask what are the premises, usually 4 or 5 would suffice. Then, Socrates would show that based on these premises the thesis of the interlocutor does not hold. And the point is, the more promises one adds or the more original promises one changes from the beliefs the  interlocutor started with, the less likely it will untangle the inconsistencies pointed by Socrates. Back to the court case, if we imagine that we are trying to make the laws sound like one consistent system and courts decisions are the answer to Socrates’ questions, we would have one remarkable difference. Instead of a handful of premises, the law system of every country deals with literally dozens of millions of premises, which, in our analogy, encompass legislation and precedents. And one point that may have passed unnoticed in this anecdote is that computers played the role of Socrates.

The same way Socrates fostered his interlocutors to think critically by realizing inconsistencies, we might be forced to see by the use of A.I. that our law systems may in the long term not reflect what we expect from it. Maybe Socrates himself reached this conclusion before being ordered to poison himself by a jury in Athens 399 B.C. The point being, how will we react to the realization that law may become cumulatively less intuitive? And why would we hear computers if philosophers and jurists already pointed that?One of the reasons is that the use of A.I. will allow us to look at law in a broader scale rather than self-contained and, with that, inconsistencies will become much clearer and quantifiable. For example, a team from Griffith University, Australia, now seeks to work with the Australian Taxation Office on the detection of loopholes in taxation laws and regulations [5]. Now, as we said before, inconsistencies are often not a source from serious grieve due to the consensus that law should be interpreted and that those interpretations should be made hierarchical, archived and used for posterity. Therefore, the point is not the sole existence of inconsistencies, but their abundance in a way that inconsistencies can be criminally exploited and undermine public confidence in the law.

At the same time this may help to bring light on the romantic view on the fairness of law, it might diminish the confidence on it below the threshold required for legitimacy of the institutions, giving the feeling that as long as the law in old enough or complex enough and the chances of inconsistencies have been introduced are high, A.I. can be used as a tool to revert and postpone decisions. We may find a harsh way to realize that the same way a fruitful discussion requires common knowledge, consensus requires common ignorance. However, this seems-to-be-dystopian reality assumes the way we make and interpret law remains the same for the coming years.

Concluding remarks

In the book Artificial legal intelligence by Pamela Grey, it reads ”There is now an opportunity to review legal intelligence and consciously determinate any evolutionary leap in the form of codification [17]”. The author suggests that the challenging advance of A.I. in law is in fact an opportunity to reform the law system. Big changes on law systems are indeed rare and have only happened a few times in history in reaction to moments of huge turmoil. However, if it becomes imminent that reforms are made due to the use of A.I., it will be an advantage that we had thought beforehand on the implications of modifying our current law model. At this point, resistance should be expected from an institution which is largely based in tradition. In order to aid any transition, it is a requirement that world leaders, law makers and judiciary are acquainted with the ongoing changes of the use of A.I. in law and that population has a minimum degree of programming literacy to understand and concur. To have an uneducated opinion on this matter is willingly assuming the risk of choosing a sub-optimal solution when changes in what is law and how we do law become increasingly imperative.


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