The Disruption of Cognitive Computing

This is the second of a three-part post on the connection between Artificial Intelligence (AI) and Knowledge Management (KM). In this post I examine those industries that will or are soon to be disrupted by AI and KM, specifically in the form of Cognitive Computing.

Before we look ahead, let’s take a look back. During the time I first became involved in AI (late 80’s), its hype and promise at that time became too much to live up to (a typical phenomenon in software - see Hype Cycle) and its promise faded into the background. Fast forward to 2010 and AI is beginning to become the “next big thing”. AI had already made its presence felt in the automobile industry (robotics), as well as with decision making systems in medicine, logistics, and manufacturing (expert systems and neural networks). Now AI in the form of Cognitive Computing is making its mark on several industries. In a recent CB Insights Newsletter, it was stated that the US Bureau of Labor Statistics indicates that 10.5 million jobs are at risk of automation. Due to the rapid adoption and application of better hardware processing capabilities which facilitate artificial intelligence algorithms use on big data this is leading the change in blue and white collar jobs.

At a recent Harvard University commencement address, Facebook Chief Executive Mark Zuckerberg stated “Our generation will have to deal with tens of millions of jobs replaced by automation like self-driving cars and trucks."

Bill Gates, the founder of Microsoft and Chairman of the Bill and Melinda Gates Foundation in a recent MarketWatch story had this to say “In that movie, old Benjamin Braddock (Dustin Hoffman) was given this very famous piece of advice: 'I just want to say one word to you. Just one word …Plastics.'  And today? That word would likely be 'robots,' and 'artificial intelligence' would have a huge impact."

Although there are many industries where Cognitive Computing will disrupt the way business is conducted including the economics around job loss and future job creation, I have chosen to look at three industries; Legal Services, the Automotive Industry, and Healthcare.

Legal Services

Knowledge Management (KM) is becoming more prevalent within law firms as well as legal departments as the practice of KM has become more mature. AI technologies are also making its way into the practice of law. Ability to reuse internally developed knowledge assets such as precedents, letters, research findings, and case history information is vital to a law firm’s success. Paralegals currently play a critical role in assisting attorneys with discovery. With the use of AI systems attorneys will be able to “mine” more accurately and efficiently the large volumes of documents (i.e., precedents, research findings, and case history information) located in various repositories to aid in decision making and successful client outcomes. This ability will limit the use of paralegals and attorneys currently needed to perform these tasks.

Cognitive computing will enable computers to learn how to complete tasks traditionally done by humans. The focus of cognitive computing is to look for patterns in data, carrying out tests to evaluate the data and finding results. This will provide lawyers with similar capabilities as it provides doctors; an in-depth look into the data that will provide insights that cannot be provided otherwise. According to a 2015 Altman Weil Law Firms in Transition survey 35% of law firm leaders indicate cognitive computing will replace 1st year associates in the next ten (10) years. While 20% of law firm leaders indicate cognitive computing will replace 2nd and 3rd year attorneys as well. In addition, 50% of law firm leaders indicate cognitive computing will replace paralegals altogether. Cognitive computing capability to mine big data is the essential reason lower level research jobs will be replaced by computers. This situation is not just limited to the legal profession.

Automotive Industry

Autonomous Vehicles and Vehicle Insurance

Autonomous vehicles, also known as a driverless car, robot car (here we go with robots again!), and self-driving car can guide themselves without human intervention. This kind of vehicle is paving the way for future cognitive systems where computers take over the art of driving. Autonomous Vehicles are positioned to disrupt the insurance industry. Let’s take a look at what coverages are a part of the typical vehicle insurance policy.

Vehicle insurance typically addresses six coverages. These coverages include:

• Bodily Injury Liability, which typically applies to injuries that you, the designated driver or policyholder, cause to someone else;
• Medical Payments or Personal Injury Protection (PIP), which covers the treatment of injuries to the driver and passengers of the policyholder's vehicle;
• Property Damage Liability, which covers damage you (or someone driving the car with your permission) may cause to someone else's property;
• Collision, which covers damage to your car resulting from a collision with another car, object or and even potholes;
• Comprehensive, which covers you for loss due to theft or damage caused by something other than a collision with another car or object, such as fire, falling objects, etc.;

Uninsured and Underinsured Motorist Coverage reimburses you, a member of your family, or a designated driver if one of you is hit by an uninsured or hit-and-run driver. The way these coverages are applied (or not) to a vehicle policy will be disrupted by the use of autonomous vehicles.

According to a 2016 Forbes article by Jeff McMahon about 90 percent of car accidents are caused by human error. However, it is estimated that autonomous vehicles will significantly reduce the number of accidents. This will significantly disrupt the insurance revenue model, affecting all six types of coverage identified above. When the risk of accidents drops, the demand for insurance will potentially drop as well (this will not happen unless the states no longer require insurance that covers accidents). So, there will be no doubt that auto insurance companies will change the type of coverage and the language affecting the policies.

Some Unintended Side Effects?

The autonomous vehicle with its multiple sensors has the potential to eliminate accidents due to distractions and drunk driving. This will disrupt the vehicle repair industry by largely eliminating crashes so collision repair shops will lose a huge portion of their business. Indirectly, the decreased demand for new auto parts will hurt vehicle parts manufacturers. According to the U.S. Department of Transportation in 2010 approximately 24 million vehicles were damaged in accidents, which had an economic cost of $76 billion in property damages. The loss of this revenue will put a strain on these manufacturers.

(to be continued)

This is the first of a three (3) part post on the connection between Artificial Intelligence and Knowledge Management.

Artificial Intelligence (AI) has become the latest “buzzword” in the industry today. However, AI has been around for decades. The intent of AI is to enable computers to perform tasks that normally require human intelligence, as such AI will evolve to take many jobs once performed by humans. I studied and developed applications in AI from the mid to late 1980’s through the early 2000’s. AI in the late 1980’s and early 1990’s evolved into a multidisciplinary science which included expert systems, neural networks, robotics, Natural Language Processing (NPL), Speech Recognition and Virtual Reality.

Knowledge Management (KM) is also a multidisciplinary field. KM encompasses psychology, epistemology, and cognitive science. The goals of KM are to enable people and organizations to collaborate, share, create, use and reuse knowledge. Understanding this KM is leveraged to improve performance, increase innovation and expand what we know both from an individual and organizational perspective.

KM and AI at its core is about knowledge. AI provides the mechanisms to enable machines to learn. AI allows machines to acquire, process and use knowledge to perform tasks and to unlock knowledge that can be delivered to humans to improve the decision-making process. I believe that AI and KM are two sides of the same coin. KM allows an understanding of knowledge to occur, while AI provides the capabilities to expand, use, and create knowledge in ways we have not yet imagined.

The connection of KM and AI has lead the way for cognitive computing. Cognitive computing uses computerized models to simulate human thought processes. Cognitive computing involves self/deep learning artificial neural network software that use text/data mining, pattern recognition and natural language processing to mimic the way the human brain works. Cognitive computing is leading the way for future applications involving AI and KM.

In recent years, the ability to mine larger amounts of data, information and knowledge to gain competitive advantage and the importance of data and text analytics to this effort is gaining momentum. As the proliferation of structured and unstructured data continues to grow we will continue to have a need to uncover the knowledge contained within these big data resources. Cognitive computing will be key in extracting knowledge from big data. Strategy, process centric approaches and interorganizational aspects of decision support to research on new technology and academic endeavors in this space will continue to provide insights on how we process big data to enhance decision making.

Cognitive computing is the next evolution of the connection between AI and KM. In future post, I will examine and discuss the industries where cognitive computing is being a disruptive force. This disruption will lead to dramatic changes on how people will work in these industries.

Given the 45th anniversary to of its launch this year, what can we learn about Knowledge Management from Pioneer 10?

Over 9 million miles away from our sun, a solitary spacecraft continues its long journey into interstellar space. Scientific investigations of great value were sent to Earth until March 31st, 1997, the official end of its main mission. Exhausted of all energy, it drifts along the solar winds of space, its last signal having been detected over 13 years ago. Some say that this is when its secondary mission truly began: To act as an ambassador to cosmic civilizations. To accomplish this, a gold-anodized aluminum plaque was attached to Pioneer 10. Carl Sagan and Frank Drake designed the message, with artwork prepared by Linda Salzman Sagan. 

This is the message:

Hydrogen, considered to be the most abundant element in the universe was chosen as it is a universal phenomenon and the hyperfine transition depicted could be used as a base for measuring time and distance, thus decoding the remainder of the plaque. The array of lines and dashes to the center-left of the plaque represent pulsars, which can be used to calculate the position of the sun to the center of the milky way galaxy. They can also be used to calculate when Pioneer 10 was launched. At the bottom of the plaque the solar system is depicted with the home planet of the plaque, and Pioneer 10’s trajectory out of our solar system. 

Lastly, a drawing of a man and a woman, their height able to be calculated based on the hyperfine transition key and a silhouette of Pioneer 10. 

First, let us go over what is “wrong” in the message: 

• The frequency of one of the pulsars is calculated incorrectly. That error was made by Sagan and Drake because the pulsar could not be calculated as precisely in the 70s as it can be now.
• The solar system is depicted incorrectly. We now consider our solar system to have 8 planets and 5 dwarf planets. Additionally, the arrow showing Earth and Pioneer 10’s trajectory may not be understood by aliens who did not “grow up” in a hunter-gatherer society. Lastly, Saturn has a dash through it, which was meant to signify its rings. A dash, based on the plaque and binary could be misinterpreted to mean the planet does not exist anymore or that some calamity occurred. 
• The male and female portrayed are the most debated on the plaque. The major issue back in the 70s was that both were depicted without clothing. The drawings of both were meant to depict all races but many viewed them as Caucasian. The female was also perceived as being subservient to the male.
• Lastly, the hand raised was considered a sign of greeting but aliens could consider this to mean “stop” or anything else for that matter.  

The “right” in the message:

• Despite the change in our understanding of what we consider a planet, 8 of the largest bodies are represented. A small version of Pioneer 10 was depicted travelling from Earth outwards so it truly was the best representation at the time for its origin (and still is).   
• The hand raised by the male had an additional use and that was to show the opposable thumb, which many consider to be one of the largest leaps in our evolution. If the female raised her hand too, it could be depicted that we all walked around that way, for the same reason her stance was a little different from her counterpart. 
• It was simple and concise and could be interpreted by cultures at both ends of the technical spectrum. 

What does this have to do with Knowledge Management? 

• When writing any type of Knowledge Base Article, keep things as simple as possible as even the simplest pieces could be interpreted differently. Wording should be concise and should “stick to the facts.” Do not create an article for the sake of creating it – the article must serve a purpose. 
• Maintenance of Knowledge. Takes steps to ensure whatever is created can be maintained by having a process to do so. A Knowledge Base Article is a living thing. 
• Your Knowledge Base Article will be there even if you are not. Only because one person created it does not mean that person “owns” it. Knowledge is for the betterment of all and not for a select few. 
• Your Knowledge Base Article is an Ambassador for your company. Use spelling and grammar check and most importantly be professional in your writing.
• Technology. While it is not the main force behind Knowledge Management, we cannot discount its power, so invest in the tools proven to increase successes. When writing an article, think about how a quick video, diagram, and other multimedia may help to supplement the document. The Voyager probes contained images and recordings while the New Horizons probe went all digital. 

In our last blog post, our featured author discussed how "knowledge change is not a technology project."  This week our author presents the case for the use of tech tools especially in dealing with issues of employee retention.  Endorsement of specific vendors by KMI should not be implied.

Implemented in organizations with high employee turnover, knowledge management tools are not only to facilitate knowledge accumulation and transfer but also to stimulate employees’ engagement and retention. Here how it works. 

According to the 2016 BenchmarkPro survey, the average employee turnover rate in the USA equals 18.1%. While the highest rates are characteristic of the states with a lower median household income such as Montana (23.0%), Oklahoma (22.1%), Idaho (21.5%) and New Mexico (21.5%), turnover rates in the richest US states are also above the ‘healthy’ 10-15% - Maryland (19.1%), Massachusetts (17.1%), California (16.8%), New Jersey (16.4%). High employee turnover is a true headache in such industries as retail, healthcare, banking and financial services, as well as the IT sector where employees rarely stay with a company longer than a year.

How high employee turnover impacts organizational knowledge

In terms of knowledge management, high turnover rates mean that companies can face multiple knowledge-related challenges, including:

• lost knowledge if employees leave and don’t transfer their valuable knowledge in any form
• knowledge leaks if employees leave and reuse acquired knowledge at their new workplace
• knowledge transfer and constant learning required any time to introduce newcomers to their work
• knowledge gaps that (re)appear in different knowledge domains, and more

If left unaddressed, these challenges can lead to discontinued business processes and cause serious mistakes that will end up with lost money and damaged reputation.

Why turn to a knowledge management system?

With so many knowledge-related risks, organizations with high employee turnover can do nothing but turn to knowledge management to achieve the following goals:

• Make the turnover less painful and hire new employees with the needed knowledge level quicker
• Facilitate regular employees’ work in an unstable environment and reduce their efforts on transferring knowledge to newcomers
• Support productive teamwork
• Minimize newcomers’ mistakes and eliminate knowledge gaps
• Create incentives to retain employees

Now, let’s analyze how companies can achieve these goals through relevant knowledge management tools and techniques.

Good news for those who already use SharePoint: turning to SharePoint consultants or developers, they can adapt the platform to knowledge management needs.

Outlining workforce gaps with a knowledge map

Usually, organizations create a knowledge map to structure corporate knowledge and understand if its current level is enough to cover particular business needs. Besides that, companies can use their knowledge map to smartly and timely find new employees. By identifying key knowledge areas essential to business processes, organizations can mark out risky areas and relevant knowledge owners. Guided by the map, HR managers can form and support a base of candidates suiting critical knowledge areas and find employees with specific knowledge faster.

Automating knowledge transfer

Constant staff changes disturb regular employees. That’s a real nightmare for experts who should transfer their knowledge to newcomers over and over again. With this in mind, it’s reasonable to automate knowledge transfer to key knowledge owners’ relief. For example, an organization can create a dedicated knowledge center for newcomers to access the working materials prepared by experts and study them. To check up their knowledge, newcomers can take relevant tests right in the KM system. Test results will be then presented to a line manager and an expert. If results are unsatisfactory, a knowledge owner can schedule individual training. This way, an initial knowledge transfer can be fully automated or coupled with only a few one-to-one consultations, which reduces experts’ involvement substantially.

Storing team knowledge on collaboration sites

The value of collaboration sites at companies with high employee turnover increases dramatically. When team collaboration takes place in a single collaboration hub (these can be dedicated SharePoint team sites), a new team member will be able to learn the collaboration history, view project-related documents, get consultations of teammates and dive into the working process much easier.

Eliminating mistakes due to knowledge gaps

To minimize mistakes made regularly by newcomers, companies can use at least two knowledge management tools. First of all, a centralized knowledge base with well-structured instructions and recommendations can guide newcomers throughout their working process. Secondly, newcomers can use a knowledge map to quickly identify knowledge owners and connect them in order to ask for a piece of advice and solve problematic or complex tasks successfully.

Reducing employee turnover with a knowledge management system

Unfavorable corporate culture, boring or unimportant work and the lack of recognition are constantly on the list of popular reasons to quit a job. To change this, companies can use their knowledge management system to create comfortable working conditions that will stimulate employee retention.

Recognizing employees’ contribution and ensuring personal growth

A knowledge management system can include a system of points attributed to employees who regularly contribute to the development of organizational knowledge (develop a particular knowledge domain, organize a community of practice, make research work, etc.). ‘Knowledge’ points can be included in a personal development plan so that employees could see their professional advance, as well as into employees’ general rating for line managers to reward top contributors with relevant incentives.

Turning off stress and enabling a supportive working environment

Employees are always afraid to make a mistake especially if they don’t have the needed knowledge and can’t find it anywhere. Provided with strong search capabilities, a knowledge management solution will allow employees to find relevant pieces of knowledge or knowledge owners who can assist a newcomer in solving a particular task. With the possibility to contact experts and teammates, employees will feel more comfortable at work, which increases employees’ satisfaction and confidence.

Creating extra opportunities

Companies can also think about giving extra opportunities to their staff. For example, employees can share their ideas and store them in a bank of ideas located in the knowledge management system. Best insights will be then discussed with line managers and experts and turned into real projects. This is how employees will get a chance to implement their own project and advance in their career.

Even one KM activity can bring several outcomes

Obviously, companies struggling with high employee turnover are focused on replacing employees and keeping business processes uninterrupted. Due to impressive investments into HR management, they can cut other corporate investments, especially the ones into such activities as knowledge management. However, it’s not always right.

High employee turnover is an exceptional situation when even scattered KM activities can be of a great value. Companies can adopt at least one of the described solutions to get multiple outcomes at once. For example, having a knowledge map on their hands, companies can simplify the hiring process and invigorate the connection between newcomers and experts, while collaboration sites will support knowledge transfer, uninterrupted teamwork and the introduction of newcomers to the working process.

This article is referencing concepts and terminology common in “Knowledge Management” (“KM”) and “Adoption & Change Management” (“ACM”) and assumes that the reader has at least some experiences in one or the other. It also references the use of SW solutions and “collaboration tools” as a means to realizing organizational benefits, and value, of KM concepts.

I have inserted links to articles explaining some of the concepts where appropriate.

I have touched upon this topic in a few of my earlier posts, how we often mistake a Knowledge Management, or a Collaboration tool project, for being a technology project. I will go out on a limb here and be Boolean:  It is not.

I am also intentionally calling it “Knowledge Change” as opposed to “Knowledge Management”, because when we try to implement a new KM process, solution or Collaboration tool, we are inevitably facing a Change Management effort. Not a “system implementation” effort or “adoption” effort. Perhaps in the rare exception, if an organization is already fully embracing KM principles, have defined and successfully implemented a knowledge-centric business model and managed to create and nurture a truly collaborative culture, they could possibly be doing a 1:1 replacement of one KM platform to another. I think anyone who’s been involved in any KM/Collaboration effort would agree with me when I say that is a close-to utopian scenario.

So, let’s focus on the large majority, rather than the rare exceptions.

Most of us work in organisations that truly wish to embrace a collaborative culture and leverage the collective knowledge of the organization to achieve more. Pretty much common sense in any knowledge worker organization, isn’t it? But it is a lot easier said than done as many of us also work in organisations that have a long(ish) history of engineering-driven, development-centric and traditional organisational structures. In this case I am thinking of organisations that quite typically are hierarchical and organized around geography and/or functions, rather than organized around capabilities or knowledge areas.

There are probably a fair number of barriers as well, in the shape of policies and processes, that prevents knowledge from flowing freely and effectively between those functions and/or geographies. And in some cases, there may even be barriers in-between levels within the hierarchies, in terms of roles and seniority.

Finally, the demographics of the work force will also likely, yet inadvertently, create additional barriers based off what kind of moral values and/or academic principles we were exposed to in our formative years. Someone born in the 50’s or 60’s for example may have a much higher focus on “perfecting before sharing” than someone born in the 80’s or 90’s. I believe that nationality/culture also plays a role in that area.

Does any of this sound familiar?

In those cases, implementing a new Knowledge Collaboration platform or Collaboration solution, is so much more complex than process change or a tools implementation project, because it immediately becomes a project to change culture and behaviours.

Here are a few things that are at the top of my mind, that I think you may find useful to consider.

• To change culture, you must change individual behavior
• To change behaviour, you must undo existing habits
• Undoing habits takes leadership, dedication and patience

I am making an assumption here that everyone has a good understanding of what we mean by [Organisational] Culture, are familiar with Peter Drucker’s statement that “Culture eats strategy for breakfast”[1] etc., so I will not delve into defining “culture”.

A second assumption I am making is that most of you are familiar with Adoption and Change Management fundamentals and know Prosci’s ADKAR or Kotter’s 8-step Change Model, so I will not go into those but skip right into the more challenging parts associated with those: Sponsorship, leadership and perseverance.

Culture is more than Vision, Mission and Values

So it takes more than a few strategy sessions, or management consultants to change it. Culture is the collective values, actions and behaviours of the company employees, so if we want to change it, we need to change the mind-sets and behaviours of everyone who works there. From top to bottom. Having active and visible (Executive) sponsorship is fundamental but it is not enough. We must avoid falling into the trap that so many of us have fallen into and forget about the middle management layers. They are crucial to drive any sustainable change because they are the people who manages the majority of the work force and if they do not ask for the change, it will most likely not happen. It matters a lot less what my CEO says, in practice, than what my direct manager and perhaps his/her manager says, doesn’t it? “Middle management” is the key change agent that can make the difference between failure and success.

Acquiring new habits would be a lot easier if we did not have to get rid of existing ones

Just think about your last New Year’s resolution – how many days did you last on that diet, or going to that gym 3 days a week, once you got passed Jan 1st? All of us have habits. Good ones and bad ones and they are all hard to change but most difficult to change are the bad ones. Then add to that the dimension of having previously been rewarded for one type of behaviour (“the bad habit”), now being asked to do something different (“the good habit”). It will be hard for everyone and it will be even harder for people with tenure. Therefore, rewards and recognition are key, but they are not a silver bullet.

Patience is a virtue that very few of us possess

Learning anything new takes patience and practice for most of us, as well as perseverance. But it does become a little bit easier if the people we look up to and respect are leading by example, or if there is a reward at the end. But carrots and sticks alone won’t do it either. It will take repetition, consistency and alignment between the spoken and the acted messages, and role models that repeatedly demonstrate the desired behaviours. In addition to awareness, readiness, knowledge etc., which are the Change Management 101’s, we need to walk the talk. We need to stick with the program and keep pushing the same message over and over in various ways, shapes and forms.

There are of course many more challenges, opportunities and aspects of driving cultural change in the context of KM (as in any context!) but I am going to leave you with these three and I hope that this article will spark some healthy conversations and generate some knowledge sharing. This is a big topic and there is a lot we can all learn from each other.

[1] Some argue he never said this, but it is most often attributed to him, so let’s go with that for now.