It’s time to exert governance over the the Global Tech Leaders!

Tech Governance 2

Nearly 20 years ago, in my research work I and colleagues identified the IT platform companies as implementing a radical new business model that would be profoundly transformational in many dimensions, in terms of potential for astonishing levels of growth, global market share, monopoly and competitive lockout and opportunities for small companies to slingshot their capability onto the global stage.
These things have come to pass. However, what we didn’t foresee was the potential for abuse – specifically the collection and resale of individuals’ data, the profiling and tracking for commercial advantage and more recently for political advantage. Also, the use of the platform for nefarious purposes. Nor did we identify the issue of split responsibility and governance in a platform environment.
All enterprises require some form of governance, internal and external. In the past external governance of corporations has been about ownership, assets and financial probity. More recently there has been some moves to implement more qualitative forms of governance to require corporations to report on issues such as climate change and social responsibility. Clearly, we now need strong governance over the technology companies and their customers use of the platform. I am speaking specifically about Facebook, Twitter and Google as priorities, but I fully anticipate the requirement will be much broader.
Let’s consider a simple model.
1. Establish a global governance board under the aegis of the United Nations. Allow the UN to appoint acknowledged tech sector experts who have unquestioned neutrality to a governance board with a limited term of 3 years. Charter and resource the board to propose and publish policies and monitor and report 6 monthly on key compliance issues.
2. Example policies:
a. Establish limits over individuals’ or enterprises’ use of the social platforms. Require named tech companies to make an account charge of $1 per month for every follower/friend over say 1000.
b. Require platforms to highlight paid adverts and accounts to other users.
c. Require named platforms to provide open standards for interaction between social platforms to reduce monopoly behaviors.
d. Require user ownership of personal data and rights to opt in or out of profiling based messaging and advertising.
e. Require message privacy to be subject to external governance by approved security services.
f. Recommend country level taxation systems that claw back excess profits supplementary to corporate tax regimes.
3. Charter the UN governance board to establish communications with country level governance boards and facilitate coherent implementation of policies at global and country level.
These are simply ideas. The biggest issue will be, how to make it work? Because of course there are no global governance bodies that would see this as their responsibility. Further national governments are restricted by various treaties on cross country taxation. However, we do have examples of global governance. It must be said that climate change is perhaps not a good example to copy. A better example is the Montreal Protocol on Substances that Deplete the Ozone Layer. This is an international treaty designed to protect the ozone layer by phasing out the production of numerous substances that are responsible for ozone depletion. It was agreed on 16 September 1987, and entered into force on 1 January 1989, followed by a first meeting in Helsinki, May 1989. Due to its widespread adoption and implementation it has been hailed as an example of exceptional international co-operation, with Kofi Annan quoted as saying that “perhaps the single most successful international agreement to date has been the Montreal Protocol”.
Further, we might expect that the tech companies in question may be prepared to cooperate in some form of self-governance on key policies that could be implemented very rapidly. Certainly some of the tech leaders have emphasized the importance of moral compass. Google has recently moved from “don’t be evil” to “do the right thing”, and Facebook’s Mark Zuckerberg has made various socially responsible comments including, “give people power”. If the tech companies are smart, and they usually are, they will see they are better off negotiating rather than having governance forced on them.
Very clearly the time has come that we need to be sure political processes cannot be abused, that individuals’ privacy is respected and that profits made by tech companies are taxed appropriately. If demagogues or manipulators can afford to “pay” for the privilege of having 35 million followers, then at least there will be visibility of the cost benefit. These are problems that can and should be fixed, now.

Secrets of Silicon Valley, BBC2

Montreal Protocol

Technology and Society – Problem or Opportunity

 

 

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Terrorism requires new thinking about Technology in Society

Surveillance Image

The abominable attacks in the UK, France and Germany are clearly unacceptable; but the responses of both security services and political leaders are completely inadequate to these types of threat.
Today we hear that one of the London Bridge attackers was well known to the police and media. But “there was insufficient evidence he was part of a plot, so was not actively investigated”. Also, one of the same group of attackers had been hiding in plain sight in Dublin, travelling freely between the UK and the Republic, presumably associating with other similarly radicalised individuals. Perpetrators of the Manchester attack had evidently been identified as radicals by members of the public who informed the police, who evidently didn’t or were unable to respond. And the UK police at last admit they have insufficient resources.
We must sympathize with the police and security services; they have an impossible job; the terrorists can live freely in society and increasingly use everyday artifacts as weapons such as rental vans and trucks and knives. Conventional policing where suspects are tracked involving huge resources is never going to have enough resources.
A conventional response, which was used in times past with the IRA, would be to inter individuals that were clear threats where there was no hard evidence. This was always highly controversial and goes against all our democratic norms. And of course, we could perhaps inter individuals returning from Syria or Iraq who were known to have been involved in those conflicts. But for how long? And what about those that didn’t travel but provided resources, funding and other forms of help?
A modern approach would be to track patterns of behaviour. We are all aware that everything we do is tracked, including telephone calls, emails, social media posts and messages as well as purchases, travel arrangements, border crossings etc. as well as particularly in the UK, CCTV surveillance. Terrorists will have particular behavioural patterns – associations with others who are also suspected, travel to particular locations, use specific web sites, attend specific churches etc. This technology is available and mature; in active use by commercial organizations and tech companies involving sophisticated use of big data and artificial intelligence. But we must assume that the police and security services are not using these systems, at least in any effective manner. Perhaps they are constrained by law?
Strangely I don’t hear or see comment on this aspect of how we should respond. Why? Are we too precious about our democracy? The fact is our democracy is already being undermined by political operators and indeed politicians that have swung and radicalized opinion because of threats to society. It’s time we grasped this challenge and accepted some loss of privacy in order to protect society. It’s way past the time for political leaders to use vague statements of intent; or to focus resourcing as the only solution. We should be using the power of the very latest technology and requiring the tech companies get deeply involved in addressing all the issues that have been talked about for too long and not acted upon. And implement across Europe.
It’s evident the police and security services are simply plodding. They need to be brought into the 21st Century.

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Technology and Society – Problem or Opportunity

In economics Kondratiev waves (or supercycles) are cycle-like phenomena in the modern world. [1] Initially identified in 1925 as major economic cycles by Nikolai Kondratiev, Joseph Schumpeter suggested in 1939 naming the cycles “Kondratieff waves” in his honor. The theory originally hypothesized the existence of very long-run macroeconomic cycles lasting between 50–54 years. Kondratiev identified three phases in each cycle: expansion, stagnation, and recession. More common today is the division into four phases with a turning point (collapse) between the first and second phases. This latter phase seems very realistic, and is well articulated in the work of Geoffrey Moore in Crossing the Chasm [2].
According to the innovation theory, these waves arise from the clustering of foundational innovations that trigger technological revolutions that in turn create new industries and or commercial markets. However, it is also important to understand that there are also close relationships between technology and economic cycles which may accelerate or reduce adoption and therefore cycle length.
There are several modern versions of the technological cycles. They may be generalized as follows:
• Industrial Revolution—1771
• Steam and Railways—1829
• Steel and Heavy Engineering—1875
• Oil, Electricity, the Automobile and Mass Production—1908
• Information and Telecommunications—1971
And these hypothesised cycles seem to support the cycle duration theory in the range 50 – 60 years. And while we are forever hearing that change gets more and more rapid, we should remind ourselves that the four phases identified by Kondratiev and Schumpeter exert natural constraints on the phase and cycle duration timescale – formation and evolution of foundational R&D, infrastructure, enterprises, markets, and supply chains takes time.
This basic technology cycle model may help us to understand what’s happening in our world today. Some key questions. Are we right now in an Information and Telecommunications cycle? What phase? Is the Internet a phase of this, or is there an Internet cycle? I am minded to say that this phase is reasonably named, and it is in stagnation – that our ability to leverage the foundational information and telecommunications infrastructure is over stretched. And that a new cycle of Artificial Intelligence is in the very early stages of the expansion phase which leverages the essential information and telecoms infrastructure to enable a huge array of application areas in all vertical sectors based on reasoning, decisioning, differentiated user experience, robotics etc.
Let’s examine a little more closely the stresses in information and telecommunications that indicate we are in the recessionary phase. First we can see that technology is having major impacts on society. While social media has an extraordinary and pervasive level of adoption [3] the capabilities are being widely abused. As a result social media is directly impacting on society, facilitating corruption of electoral processes, information integrity and opinion, often creating popular anger and influencing various outcomes in elections, referenda, opinion polls etc. We will all be aware how Donald Trump very effectively uses Twitter to apply pressure in a very public manner. You might conclude that the concepts of big data are being used for unintended purposes.
In response to these obvious flaws the tech companies have responded. But the responses are very tactical, to identify and remove fake news, bullying and criminal behaviors and stop abuse. This is purely tactical; the absence of standards and legislative governance is clearly a major problem, exacerbated by the global nature of the tech industry at a when many countries are rejecting globalism for nationalism, very possibly as a direct result of the abuses. And this chaotic behaviour is only the start. As we move deeper into the Artificial Intelligence technology cycle, the pressures on society will become extreme. Already many are concerned that AI will eliminate many jobs, and not just the mundane and routine, but many skills and disciplines that can be hugely improved using vast stores of knowledge of best practice.
It seems the tech companies are attempting to respond to some of the most pressing symptoms of anarchic data management. But, notwithstanding brave mission statements such as “do no harm”, the tech companies cannot reinvent society themselves. What’s required is a new model for society that provides a backplane for tech innovation. Instead of tech companies innovating simply to make more money in the next 4 quarters, what’s needed is a vision of how tech can support dramatic changes in the way we live, work and play. And in the longer term this approach is likely to deliver a more stable transformation of society into the AI based technology world which attempts to match educational systems with likely resource requirements in the appropriate timeframe. Standards that facilitate integrity, security and privacy, protecting the individual and society.
Of course, there’s a major problem that the greater the level of AI based automation, the greater the probability that we will deliver a big brother like society. And we can observe right now a great fragmentation of society as technology gives more and more people a voice, yet conventional governance systems prevent wide scale involvement apart from voting for individuals or parties every few years. No surprise people feel they are becoming more and more disenfranchised and therefore more marginalized, and are we surprised when radical politicians such as Trump, or radical ideas such as Brexit gain traction; mostly it must be said in protest against the status quo.
So part of the vision and new model needs to facilitate new role and responsibility systems. Many of us will be very familiar with Agile projects. The core idea that small teams, given responsibility and accountability are the ideal way to deliver something useful. Perhaps this is a model that we should be looking to use more widely.. Some examples of decentralization and distribution:
– Back in the 1990s in the UK, many schools were released from local government control; the “grant maintained” schools ran themselves. Albeit with exceptionally strong central governance in the Ofsted system. As the time I will admit I thought it highly improbable that parent based governing committees could rise to the task; but I was proved wrong – in practice and now for decades these independent schools have delivered excellent education with very high levels of local management.
– Recently I noted, again in the UK, a Labour politician was elected as mayor of the Greater Manchester. Whilst Andy was and is a very senior Labour party politician, he rejected most of the central party policies, and ran his campaign specifically on key local issues. In effect he was saying, Greater Manchester is different; we need localized policies that will work for us. He was elected in a landslide.
Consider now, what could we do with tech to facilitate all manner of distributed and decentralized enterprises and projects? Frankly the social media tools today are focused on making money for the tech company and its platform participants. Plainly they do not support collaboration, education, team building and management whether formally or informally. Sure, they can be useful at some level; but consider what could be done if enabling and facilitating meaningful dialogue, higher integrity of all types of data, appropriate levels of AI based governance, coordination of distributed activities encouraging local or distributed groups to form for defined purposes, was at the heart of the platforms? What’s the business model? If governments saw that well organized local groups were a force for good, overcoming some of the most difficult problems in society through concerted action, we might imagine that government funding would be forthcoming. Perhaps governments could even work with tech companies on supporting localized solutions for big national problems that really only have localized solutions.
I accept this is going against the grain of globalization; but globalization and localization should work side by side; small groups collaborating with other small groups to share ideas, practices work products etc. as well as forming standards bodies that provide guidance for wider communities.
The tech companies are at the forefront of societal change. My thesis is that they need to take some responsibility for the outcomes. Many of the tech leaders have made fortunes from their efforts; some have become philanthropists, usually in very different sectors from tech. I suggest it’s time for some of these folks to address their philanthropy to solve the problem that they are handing to society; otherwise we will have a dystopian future of their own making!

[1] Kondratiev wave

[2] Crossing the Chasm

[3] Number of social media users worldwide from 2010 to 2020 (in billions)

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Optimizing User Experience AND Customer Satisfaction with AI?

Let me tell you a true story. A couple of weeks ago I received an email reminding me to renew my motor (auto) insurance. I wasn’t best pleased as the premium had increased considerably. So I called the insurance company. Speaking to the agent he offered me 5% discount, as if it was a personal favour he was doing for me. I said, “that’s exactly what happened last year. Why don’t you just build that discount into the rate for long term customers?” And I continued, “But more importantly, even with the 5% off the top, the premium has now increased by over 20% in two years!” The agent said basically, “take it or leave it.” I asked for the case to be escalated on the basis of being a long standing customer, but he became just a little stressed. So I wrote an email to the firm, stating my case; and after two days I received a standard reply saying, sorry nothing doing. You might be thinking, why didn’t you look around – and I did, but I have several policies with this firm and I want to keep the multi-policy discounts.

At this stage the renewal is coming within 7 days, and the very next day I receive an email making me some amazing offers if I renewed; would you believe a €200 holiday voucher, or a three month cinema pass, or fully funded family fun day, or a round of gold on a leading course. Now none of these would really cost the insurance company €200, but they would still involve serious cost, even if the uptake rate post renewal was low.

So I called the company again and spoke to another agent, “why not just cut the cost of my premium by say half of what the special offer would cost?” Predictably the answer was in the negative. Oh just not possible. Nor was it possible to talk to someone who might just be interested in what a customer had to say!

I make no apologies for the shaggy dog story because it highlights an essential truth about how large businesses operate. They fail to coordinate marketing and operations in both cost and policy. So when business analysts talk about cross channel user experience are they simply figuring out the mechanics? Do they ignore the policy separation and customer behavioral impact? Clearly that’s what happens in this big insurance company, and I would bet they are typical. They take a view that they will lose a certain percentage of their base on renewal each year and work on new business strategies to compensate. As opposed to looking at the overall problem from the customer behavioral perspective!

What’s this got to do with AI? Well you might say that your AI based system is only as good as your policy set and your ability to drive policies and strategy from an understanding of customer behavior. We have all complained down the years about the literally terrible call center agent experience; but very often this is not down to skills, it’s down to policy implementation, not allowing the agent to operate as a human by taking responsibility for some discretion. So in an AI context the question is with what sort of intelligence will you aim to replace your agents? And how much do you really understand about your customer behaviors so you can implement customer responsive policies?

To conclude, user experience (UX) must be more than just the mechanics of allowing the customer to renew a policy, place  an order, manage a process etc. It’s got to respond to real customer needs in a manner that improves the business performance and customer satisfaction. And this won’t happen without major change in the way you track customer needs and develop policy. And surprise, surprise, this will lead to AI getting a bad name, not just for destroying jobs but also being totally unresponsive as more and more barriers are put in place between the organization and it’s customers.

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Remembering Lawrence Wilkes – SOA Pioneer

I am deeply saddened to report that my long-time business partner and friend Lawrence Wilkes has passed away after a short illness.

I first met Lawrence 30 years ago when I joined James Martin Associates (JMA) in Wimbledon. Lawrence was in pre-sales and we collaborated intermittently on tool demos and sales to my consulting customers. In the early 90s (then part of Texas Instruments) I moved into marketing as product manager and as Lawrence was marketing manager he and I forged a close partnership that would last for nearly 25 years.

When I set up the company in 1997 that was eventually to become the CBDI Forum Lawrence joined me without hesitation, and together we became well known as highly influential technology evangelists and methodologists in Service Oriented Architecture (SOA). At that time we went where other analysts and consultants couldn’t go – providing practice level guidance on the use of the rapidly emerging service technologies. Initially we guided big tech vendors like Intel, IBM, Microsoft, Sun etc and rapidly evolved to support major corporations including banks, insurance companies, oil majors, retailers etc. It’s no exaggeration to say we were flying right at the leading edge of best practice and we made up a lot of the guidance as we went. And here Lawrence’s skills as a problem solver and communicator were extraordinary, creating structure around our ideas that provided a coherent and practical framework.

Soon we were joined by others particularly John Dodd and Richard Veryard and we forged a high performing team that ran forum meetings all around the world, providing consultancy and developing education products and documenting our thinking in the monthly CBDI journal. We didn’t call it an Agile process in those days, but that’s what it was, moving incredibly rapidly, constantly delivering useful products to market and evolving the products in a continuous stream of guidance for our architect practitioner customers.
We really believed in what we were doing. Some would say we continued the JMA ethic, breaking new ground and finding that customers came with us because they adopted our belief system along with the methodology. A vital part of this was communications and Lawrence drove the delivery of the knowledge base, without which we would have been just another disorganized consulting shop. And he combined that role with problem solving, developing better methods and education delivery platforms.
After we teamed up with Everware our products evolved rapidly as we actually delivered services.

At this point and for the last few years Lawrence was highly instrumental in the architecture and development of what I believe should be viewed as our most valuable contribution to service oriented computer science – the specification portal. This capability enables the comprehensive specification of services independent of technology, and through pattern based code generation implements a platform approach to service delivery and evolution that massively improves quality and productivity. But even more important automates governance over the code that ensures ongoing architecture integrity. Now it’s true to say that the product that Lawrence and the team worked on is more than a little industrial; it’s nowhere near a mass market user experience. But customers that have used it have enthusiastically embraced it because they understand the business value it delivers – a business level specification that governs architecture and code.
This is what we should remember Lawrence for – he articulated the vision of service architecture realized through business specifications independent of design and technology, and worked on realizing the vision – delivering on the goals of “diagrams to code” in a practical manner. Lawrence was writing and speaking about that opportunity very early on and he had the persistence to see it through. While the current spec portal product is not widely used, I fully expect these ideas will not be lost; they will in time become pervasive best practice for delivery of enterprise level services.
I remember back in the early days, the marketing communications people we worked with would often get exasperated with Lawrence; they would say to me, “We’ve got deadlines to meet, can you hurry him up?” What they didn’t realize was that Lawrence was using his lateral thinking capabilities to come up with great ideas, new concepts and ways of thinking; and that takes time. And I would say, “don’t worry, he will deliver.” He always did. Over the years he demonstrated time and time again the ability to translate and communicate difficult problems into solutions; to help others deliver better solutions. He will be remembered and missed.

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H-1B Fracas Could be the Trigger for Distributed Teaming

It’s widely reported that Donald Trump is about to go after skilled guest worker programs, particularly the H-1B, with an executive order aimed at ensuring American workers take precedence and that guest workers are genuinely highly skilled. However, like all of Trump’s executive orders issued in the past few days, this one will also cause chaos because there’s many different use cases and the devil’s in the details.

Anyone who has worked in larger US corporations’ offices like I have over the past few years will have observed the huge shift to employment of Indian IT staff on contract via organizations such as Wipro, Infosys or TCS.  In some cases it’s obvious that local staff have been made redundant to make way for cheaper, very average resources. However my experience is this is the exception. Many of the Indians are really very highly skilled and frequently are as or more effective and skilled than indigenous staff. And it’s the latter point – better skilled. It’s very common that permanent staff are employed on legacy systems and technologies and contractors are employed on new development. This reflects reality that core systems usually run on mainframes and many of the permanent staff are expert in these; but more importantly they are often older and well versed in older languages such as COBOL or PL1, and technologies such as CICS. Or older proprietary package languages such as ABAP. In contrast the contractors are younger and highly skilled in Java and C++ and all the open source frameworks. Obviously this isn’t universally true, but it is a significant trend.

Whilst cost may be a factor, there’s also a real issue with transferring skills from older mainframe environments to the modern frameworks. It’s not just about language, it’s a real paradigm shift from procedural to object oriented design and many people find that very hard indeed. It’s also about process, moving from waterfall projects to Agile development environments that are small, empowered, multi-skilled teams. And again making that shift can also be hard.

So issuing an edict that makes it harder to deploy contractors on H-1B visas is a very simplistic solution. The root problem is skills availability, skills development and resource flexibility both in the educational system and within the corporate environment. And this isn’t a problem for which there’s an instant fix. It will take years.

If the Trump administration goes ahead with visa restrictions in some form, it seems more likely that the tech industry will innovate, as they always do, by finding solutions that address the core blockers. I would predict a return of offshoring models but with a 21st century twist based on use of better telecommunications including telepresence, desktop sharing, remote pair programming tools, and massively improved life cycle automation that dramatically simplifies Agile project management and dependency. And maybe it should be referred to as “distributed Agile teaming” which allows skills to be more easily deployed wherever they are, in domestic USA, India, China or Australia.

This isn’t such a large step; we already have all the technology and process building blocks in place. Corporate employers have maybe been lazy, insisting on all staff being “onsite”. However I and many others like me have been working cross time zone and continent effectively for years, and necessity will be the mother of invention in this situation. In fact my experience is that remote working demands better discipline and governance and therefore brings real benefits as well as potential for reduced costs and round the clock working for faster delivery.

Whether Trump and co bring in their restrictions or not, I would encourage the tech  industry and its customers to be actively embracing distributed working for resource flexibility. Why wait to be told?

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Artificial Intelligence – Fake News or Alternative Facts?

One of the most worrying developments in 2016 was the rise of fake news. And from the outset of 2017 it appears distortion of reality will become the norm. Perhaps we shouldn’t be so surprised; the marketing industry has always been about changing perceptions, and the technology industry in particular is notorious for generating hype. There are countless examples of hyperbole about new technologies that in the end fail to realize the optimistic predictions. The latest new kid on the block is AI, the development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making and language translation which of course also encompasses the whole field of robotics. The rise of robotics and AI has provided copy writers with great material. A Japanese life insurance firm recently announced it is laying off 34 office workers by the end of March as a result of the implementation of an AI based claims adjudication system based on IBM’s Watson Explorer. The system is described as reading tens of thousands of medical certificates, factors in length of hospital stay, medical history and procedures before calculating payouts. This experience clearly supports the 2016 Nomura Research Institute report which forecast that nearly half of all jobs in Japan could be performed by robots by 2035.

Sean Welsh, researcher in robot ethics at the University of Canterbury, New Zealand goes even further making the prediction that robots will replace many humans: perhaps most humans in the workplace. Oxford Business School writers Carl Frey and Michael Osborne predict massive technological unemployment over the next 20 to 30 years. Something like half to three-quarters of existing human jobs are “vulnerable to automation” they say. Martin Ford, author of a popular best-selling book, The Rise of the Robots, predicts an explosion in robotics; his rationale is based on the emergence of the open source robot operating system (ROS) conceived by the Stanford University’s Artificial Intelligence Laboratory, will make the technology ubiquitous.
Last year Professor Stephen Hawkin, one of Britain’s outstanding scientists told the BBC that, “The development of full artificial intelligence could spell the end of the human race.” This view has been supported by Microsoft founder Bill Gates and SpaceX and Tesla founder Elon Musk.
And these examples are a very small selection of the vast amount of media coverage of this technology. With a basic message that is unmistakably threatening peoples jobs and livelihood, many people are not surprisingly very concerned and this reinforces the widespread public opinion in the USA and United Kingdom that in 2016 pushed back against the inevitability of globalization.

So what’s the reality. Will artificial intelligence really eliminate millions of human jobs? Let’s look in just a little more depth at the case study of the Japanese life insurance company and its use of IBM’s AI technology. Over the past few years many insurance companies have been modernizing their claims adjudication systems. For many the trigger for change has been that the existing claims systems are based on mainframe technology, often decades old, and that once elegant software systems have become impossibly complicated by constant change of regulations, change of health and insurance industry standards, new product and plan introductions and the continual mergers and acquisitions that involve systems rationalization. The result is the firms’ ability to respond in a timely manner at reasonable cost to continuing change is dramatically reduced. And just to make the situation even worse, the technology used to build the systems is decades out of date, and the original support staff are now retiring, and younger personnel are not interested in using the older technologies.

The way AI system works is that it searches for similar patterns that have occurred in the past and compares current cases, and where they are common can recommend decisions with minimal or no human intervention. But the AI system requires a vocabulary that describes the claims business policies – and in most firms this is locked into the existing software system, all muddled up with design and computer language specifics. In larger insurance firms it typically requires teams of business analysts working for multiple years to reconstruct the complexity of the firm’s claims policy in a well-structured manner that can be used to guide claims adjudication.

For most insurance firms therefore this requires a significant modernization project. The systems often need to be redeveloped to use the rationalized policy base and AI based decisions. From this description it will be seen that there’s a massive amount of work going on to make all this happen. Existing systems development personnel are typically not skilled in the new development or AI technologies, but they are expert in the existing claims business policy and are commonly employed in developing and managing the business rules base. Similarly claims adjudicators are commonly subject matter experts and play a critical role in these tasks as well as quality assurance, systems testing and governance. The reality is that when the business rules knowledgebase and AI system are operational and mature the number of human adjudicators actually making decisions on claims will reduce. But there are many new roles in the redevelopment and subsequent operational phases that mitigate the overall reduction in headcount.

So returning to the Japanese case study we might speculate why the press release focused on job losses. First industry experience is that modernization efforts like this are undertaken to reduce and govern claim pay-outs. Labour costs of the operational system are less important. Also, while the press release concentrated on the AI element of the adjudication system, it is quite likely that the company would have been involved in a major effort such as described here, at least to rationalize the business rules involving many people over multiple years to re-establish the existing claims system, and retraining of staff to establish the business knowledge bases and preserve the deep skills and expertise. The case study reported increased productivity of 30%, ROI in two years, cost savings of £1m per year all set against a system cost of £1.4m. These costs seem trivial compared to the real cost of development that most firms in this situation would need to spend.

I note IBM CEO Ginni Rometty spoke last week at Davos, and delivered a clear message to business and political leaders that artificial intelligence will not lead to mass redundancies any time soon. Similarly, in an interview last week Microsoft Chief Executive Officer Satya Nadella said, “Microsoft Corp. and its competitors should eschew artificial intelligence systems that replace people instead of maximizing their time.”

New technologies always cause change in skills and roles. This is entirely natural. However, experience shows that as roles evolve and disappear, new roles emerge. In the early stages of any new technology it’s often difficult to envisage what those new roles will be. However, as discussed experience to date shows that the new technologies always require massive efforts to realize. And skills development and lifelong learning is going to be even more important than it is today. Clearly leaders in some tech companies have got the message that it’s not a good idea to promote their technology as job elimination. Let’s hope the media will reflect that message.

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