Collective subconsciouses revealed in work groups 1 February 2018 Noga Chipman-Steinwartz Previous Article Next Article Years ago, I directed a group that discussed bullying among teenagers and how to eradicate the phenomenon. All participants felt very strongly on the subject: senior, involved and professional educators. All were experienced adults accompanying teenagers that were obviously aware to the personal and social price of bullying. By the second meeting I noticed a peculiar behavioral pattern. I gradually realized that two group members are actively participating while not allowing others to speak up and express their opinion. This was done via resentment, teasing and dismissive speech towards both other members and the group director. If anyone did try saying what's on their mind, blunt or tacit sarcastic comments were made to shut them up. Similarly, I worked with a wonderful group of various professionals dealing with socioeconomically challenged sectors. Each participant was far from helpless: professionally acclaimed, highly educated with a fitting income. However, the group as an autonomous entity was as helpless as they come, as it constantly raised heavy doubts regarding its members' ability to influence and change matters; ultimately, the group believed it wasn't even worth a try. There was many a silence, little reaction to products and although objectively financial resources were allocated for the group's work, they nevertheless repeatedly claimed that no resources were available. I felt as if the groups were acting out a part, as in a theatrical drama. The first group took the form of a bullies and victims, popular and shunned while the second group shaped itself as a group marginalized by others. Although this was obviously deterring the groups' work I assumed this phenomenon had its value. In a way, the dynamics the members developed gave a voice to the victims of teenage bullying and the disenfranchised groups in society. However, this position will benefit the groups' progress only if the groups realize what took place and objectively process what they experienced through these "parts". Most current group theories accept the assumption that when individuals work as a group, an array of forces unconsciously activates them and the group as whole. A group cannot be studied solely based on its explicit conduct; beyond its face value façade, every conversation and interaction hides a tacit meaning. Thus, in depth examination at the "here and now" enables us to experience, process and better comprehend the participants' reality in other situations. There is much value of this type of examination as it leads to the development of new knowledge and effective work procedures that wouldn't have been possible if the situations have been merely described by members or via objective in literature. One way to understand the collective subconscious is to examine and process situation through a few questions: Content: what is being discussed? What is the theme? Process: how is the situations evolving? What stages is the group going through? Form: how are the participants talking? Who is talking and who is remaining silent? The "what" and "how" and consideration of the "process" element together create what we directors listen out for: the message. We are especially attentive towards situations that manifest a gap between form and content e.g. a situation in which bullying eradication is being discussed in a manner not unlike bullying, especially during early work stages for conflict development. Another example of a gap between content and form would be a group discussing helpless sectors of society quite helplessly. What do we do with this message? We can derive much value from these situations by reflecting them to the group and examining the different roles together. Try asking: how did it feel to play a certain part? What did you gain/lose? Are there any precursors to the uncomfortable behavior that took place? Was a certain reaction (by either director or member) useful? Which tools inhibit and which promotive? Understanding these dynamics can be translated in future work stages to vital work tools: procedures, checklists and instructions. However, it is vital to be aware of the discomfort group members will probably experience when confronted with the collective subconscious as it appropriates personal experiences and bluntly claims that individuals aren't in full control of their conduct. Directors should present this interpretation as a possible explanation and examine whether it is accepted by them and see whether they view the situation similarly. I wish you success.

KMGN's HacKMthon 2022: Collaborating and Co-creating to Achieve New Learnings and Define Direction for Future Projects 1 October 2022 Dr. Moria Levy Previous Article Next Article For nearly six months, we have planned this HacKMthon- a new yearly peak event of Knowledge Management Global Network , collaborating and co-creating together. 130+ KMers have joined, representing 30 countries worldwide. The majority connected virtually, and in 5 countries, we held physical events, connecting to all the others and working in blended teams. We all worked hard and have achieved new learnings. As for myself, as the 2022 leader of KMGN, I am satisfied; very satisfied. All defined objectives were achieved, and much more: Preparing the scene and direction for 2023 projects (outcomes of the current learnings). Cross-KM collaboration. WOW effect. Engaging KMers in our activities today and giving them a great reason to want to continue participating in future activities such as KM courses, projects, and events such as KM clinics and HacKMthons. What now? Today- We are going to rest. And tomorrow- We will start collecting your feedback to learn as much as possible for our subsequent events and... start working carefully on the outcomes, so together with you, we can prioritize next year's KMGN shared projects. Thank you, Mohamad Faiz Selamat , for leading this project. Thanks to all those who helped to make it happen Vincent Ribiere , Manfred Bornemann , Rajesh Dhillon , Vishal Meena , @Manfred Bornemann, @Olga Smirinov, @Vadim Shraye, Daria, Arthur Shelley , Dr. Randhir Pushpa , Izhar Izhaki , Rudolf D'Souza , Professor Eric Tsui , Stuart French , Madanmohan Rao , Stephanie Barnes , and all the others. Thank you all 130+ who joined and shared their wisdom, energy, and love. We are a great community. We now have new dreams we can fulfill. Together. This post was initially published in LinkedIn

Chatbots: Can virtual experiences possibly replace reality? 1 September 2017 Revital Elazar Previous Article Next Article Companies are interested in implementing new technologies in order to enable their clients to interact with their brand as they please. Clients usually perform extensive independent research before contacting a company regarding a potential purchase or a service representative. The relationship between brands and their customers is about to undergo a technological revolution resulting in a massive decrease of the scope of human interaction. These changes are derived from the rise of social, digital and portable platforms which in turn led to the public preferring self-service than directly interacting with the brand. Those who follow technological changes and remain updated regarding the latest innovations have probably encountered the term "Chatbot", i.e. a computerized robot that can converse with a human via a chat interface. The Chatbot serves as a virtual assistant available 24/7 that can simultaneously serve numerous inquiries. It can perform various activities by providing a quick and focused response, supporting sales processes, customer service, tech support, etc. Take a quick glance at your Smartphone. What three apps do you use most frequently? The answer probably includes at least one IM application. Over 2.5 Billion people have installed at least one messaging app. In fact, the number of IM apps users has exceeded that of social networking apps' users. In short: you spend a large portion of your time using messaging applications- no wonder businesses and services wish to approach you in this virtual environment. During this past year (since Facebook opened its Messenger to Chatbot developers), more than 34,000 bots have been constructed; tens of thousands are being constructed as you read this review. Throughout the world (including Israel) Bots are presenting a substantial improvement in the relationship between businesses and clients; the Bots also save precious time, enhance marketing performance, increase sales percentages, optimize customer service and generally positively affect customers' level of satisfaction. Many global corporations are beginning to realize the potential of utilizing Chatbots for their businesses, including, for example, American Express, Pizza Hut and Amazon which are all using this technology in order to address customers inquiries, simplify the sales process and attain new advantages in their respective markets. This is applicable to small businesses as well; even a local business can benefit from utilizing a Chatbot. Here are some ways you can enhance you own business using this technology. One example of a successful chatbot is its implementation in the field of tourism. Kayak.com features a chatbot that can assist users in finding relevant flights and hotels by allowing users to send their location and receive authorization. The chatbot then suggests various vacationing location and/or resorts. Once a location is chosen, the chatbot presents the flight price so that you expect it, then follows with a series of questions. Based on your answers, the chatbot will display a number of possible flights, prices, departure dates and details regarding the flight. This will enable you to book the most affordable flight for you via Kayak.com . Of course, there are many more similar examples. So, what exactly are the advantages of utilizing a chatbot? You might be asking what the Chabot can possibly contribute to my business. Well, here are just a few ways this technology can benefit your business: Customer service Chatbot- using AI, Chatbots can easily converse with consumers (they can also comprehend vocal nuances in human speech), offer solutions for various problems and answer standard question Of course, nothing beats human interaction but robots can serve as the first point of interaction between the costumer and your business. If you are looking for new ways to provide excellent customer service, it is well worthwhile to consider using Chatbots. Personal assistant: a chatbot fashioned as a personal assistant can guide your consumers when looking for a certain item according to their personal preferences. Marketing Chatbots: a chatbot can take your order; then suggest paying for it via text message. Snapchat launched Snapchash, a virtual 'wallet' that enables keeping users' credit card details and enables them to send money via a simple message. It is worth noting that a Chatbot can benefit organizational websites and internal portal, raising and improving their response ratio by tens of percentages. Here's something to consider for your own business. I wish you luck.

Holistic User Experience: not a matter of "New Age" 1 January 2018 Michal Blumenfeld Sagi Previous Article Next Article Long before the dawn of the age of "fake news" in which the credibility of all news reports is challenged, prior to post modernism revealing the subjectivity of reality and its dependence on the eye of the beholder, the Gestalt theory claimed that our perception dictates the reality which we experience. Gestalt is German for form, template, pattern. The theory deals with our visual spatial perception and it is natural that Max Wertheimer, the theory's originator, reached his insights via a viewing experience. What he viewed was a sequence of flashing lights near a train junction. What caught his attention was his impression of the light "skipping" from one light to the other (although objectively these lights flashed one after the other). In other words, Wertheimer experienced an illusion of continuous motion between elements though objectively no such motion occurred. This insight still has implications on graphic design. During the 1930s, German psychologists developed this insight into a theory regarding the way in which our brain tends to organize visual elements into groups. According to the theory, our perception process involves holistically disciplining elements by internal order. According to Gestalt, every encounter with the external world involves an initial conciseness template which interprets our sensory input and dictates our perception and interpretation.We search for context, for links between elements (even if such a connection is objectively nonexistent!) because we aspire to experience them as an organized template rather than an assortment of items. To use Wertheimer's student, Kurt Koffka's paraphrase of the Aristotelian phrase "the whole is other than the sum of the parts". A correct understanding of the way we generate these links can assist us when considering UX. A portal is a fine example of a whole comprised of separate elements. These elements do not share design, character, purpose, etc. A document library is totally different from a navigation bar yet together with other elements they comprise a whole. Implementing Gestalt principles in the setup and design process can assist us in creating a whole which provides users with a more efficient and intuitive experience. Minimalistic yet effective design which relies on the users' perceptual links and associations can provide a holistic, even harmonious experience. So, which Gestalt principles may prove useful? Proximity- objects each other tend to be associated one to another. The physical proximity applies a group scheme to them. Elements can be linked by physical location. The association will be made by users intuitively. Similarity- a complimentary principle is the principle of similarity. We tend to group elements that share a characteristic, such as shape or color. If we want to enhance the link between separate elements we can manipulate their proximity and similarity. Continuity- remember Wertheimer's flashing lights? We search for continuity and motion even in its absence; objects directed at the same direction will be perceived as a sequence. Alternating messages will generate a sense of motion. A sequence of 3 or more similar objects assists users in identifying patterns. A dramatic interruption of continuity and sequence may generate confusion and dissonance. Closure- although the contour of some spaces isn't fully closed, users will probably nevertheless close them mentally and complete the "appropriate" shape. We search for distinct boundaries and templates. When organizing an interface, we can form a framework around the elements or organize them in form that might not be complete yet will be completed by users nonetheless. Simplicity- we tend to simplify i.e. search for the simplest possible explanation. We therefore prefer a simple arrangement. Simple is always better. We aspire to attain a harmonious perception; this doesn't imply uniformity and certainly not monochrome dullness. Nevertheless, considering element organization can create a more holistic user experience.

ISO30401 and KM Excellence 1 September 2021 Dr. Moria Levy Previous Article Next Article ISO30401. Why is so important for the KM'rs that it is implemented? Because it will drive understanding of organizations to the importance of knowledge and to the linkage between knowledge management and business performance, therefore driving more implementation. much more. Why do organizations nowadays consider ISO30401 certification? Some, as they have strong KM teams and they want to excel or to demonstrate their excellence in this field. Others, because they do not have KM, but they are looking for recognition and awards, and the certification is another way to win this honor. A month ago, Khawaja Asif Mushtaq , SPHRi , SHRM-SCP , Lead Auditor from Pakistan suggested we work as a global team to foster ISO30401 implementation. Yesterday we had our first meeting based on KMGN, including Patricia Eng , Arthur Shelley , Ved Prakash , Vincent Ribiere , Khattab Salman , Shreeharsha Gopalakrishna , Lucky Esa. So if you want to join us, or if you know organizations that are ISO30401 certified- please comment or write me in person. This post was initially published in LinkedIn

KM technological trends of 2020 1 May 2020 Elad Piran Previous Article Next Article Knowledge management software and services providers are embracing a fresh wave of technological innovation. It’s necessary because—among both customers and employees—there is a heightened expectation that the right information will be delivered to the right people at the right time." This passage was excerpted from KMWorld's 100 Companies That Matter in Knowledge Management 2020 (For more, click here ). Analyzing the list of the leading companies in this competition- “Companies That Matter in Knowledge Management 2020”, we can learn that KM new trends in the leading organizations include: BI and data analytics projects Smart content management Smart Search AI and cognitive computation Machine Learning RPA – Robot Process Automation These new trends represent a development, albeit a moderate one, compared to previous years. They do not replace classic KM solutions, which continue to be the majority in organizations, rather complement them, suggesting a blended offering. Most solutions are yet enterprise-based, but the leading organizations are slightly starting to move to cloud-based KM services. We believe that COVID 19 will accelerate this trend of cloud services, and as well change the pace of other KM initiatives. We probably have to wait patiently in order to fully learn the long-term effects of what we are experiencing nowadays. Let us all hope for good health, business success and KM prosperity.

ChatGPT in a nutshell 1 February 2023 Meirav Barsadeh Previous Article Next Article Artificial intelligence is hardly a new concept to us. Nevertheless, as we are exposed to more and more options and tools, we realize that the relationship between man and machine is becoming complex while also becoming common and conventional. ChatGPT, the latest word in artificial intelligence, is a language processing model developed by OpenAI. It went live in November 2019 and has been continuously updated since then. The goal is to develop a learning model that combines Natural Language Processing and task processing to create a dialogue with a powerful conversation partner who can respond accurately and efficiently. This application, which became a phenomenon in less than a week from the day it was presented to the public at the end of November 2022 and has accumulated a highly impressive number of users, is fed text by users, which it then processes. It can generate conversations that seem more organic than those generated by traditional chatbots. It can be used in various applications such as customer service, virtual personal assistant, and even creative writing. In many ways, this is a revolution. Waze changed how we get from place to place with the accuracy of real-time information, and ChatGPT is likewise changing how we locate and produce content. However, ChatGPT is not designed to serve as a search engine. ChatGPT is a text generator. Many refinements can be applied to the content created by this tool. You can improve phrasing, upgrade language, enrich or simplify phrasing, correct editing errors, or choose a display format. The tool's dynamic nature and ability to respond quickly and efficiently make it an active partner with whom you can continuously converse until a satisfactory product is obtained. Regarding the world of Knowledge Management, this technology has the potential to make a significant difference, dramatically reduce the amount of time and effort required to create knowledge, and assist us in various tasks: Summarizing a long text and presenting it in various formats, such as a table, a bulleted list, or a paragraph. Showing various optional titles for a knowledge segment. In this case, it is best to explicitly state how many ideas you would like to receive, whether there is a word limit, and whether it is a business or instructional format. Suggesting keywords for a text while considering the needs of the audience you are targeting. Assisting in preparing an outline for a new content template, procedure, or presentation on a particular topic. Offering examples of questionnaires for knowledge retention processes, which include a personal appeal to create an emotional connection. Along with its many advantages, this technology also has limitations or drawbacks that cannot be ignored: It depends on updating the version so that it contains current information. As of this moment, ChatGPT only relies on content accumulated until 2021. Errors or fictitious data that necessitate human intervention to prevent the spread of misleading information. Unlike the Google search engine, these tools require registration that includes a verification code sent to a mobile phone. To improve the tool, OpenAI can store sensitive information about users and compromise their privacy. ChatGPT always displays only one answer, unlike search engines that display several options derived from different information sources. In conclusion, we must evaluate and review the products. We must remember that this is an ongoing examination and correction or editing process. The significant value of this process is learning to ask the right question to get an effective and useful answer while also comparing it to our knowledge and experience. We should surely not accept things as they are. It is important to remember that the responsibility for the final product is entirely yours and not ChatGPT's. There is no substitute, at least not yet, for creativity and human intuition as an engine for innovation.

Consequential thought methodology 1 July 2016 Nurit Lin Previous Article Next Article The consequential thought methodology and the logical model are increasingly gaining popularity in many organizations as tools for effectively planning projects, missions or organizational processes. The world of KM is not an exception to this phenomenon. Much has been written and spoken of this model's advantages and simple charm. This article will focus on the other side of the KM project, i.e. the evaluation and assessment stage, and explain how the logical model is of assistance at this stage as well. Generally speaking, consequential thinking (the logical model included) involve reverse thinking. The starting point of this methodology requires understanding the need and as a result- the result we wish to reach (including intermediate objectives). Only after these were clearly defined do we go back and analyze the components required in order to attain this goal: who is the target audience, what are the relevant characteristics of this target audience, what are the activities required in order to achieve the desired result and what are the required resources. The logical method's foundation itself encompasses a contribution that can be utilized when managing a KM project during the evaluation and assessment stage, which is: an in-depth and precise definition of the project's objective. This is unfortunately not a trivial matter. It is not uncommon for one to encounter organizational processes planned and implemented while it is unclear what problem they are intended to solve, to what change that will benefit the workers are they supposed to lead, or what are they meant to achieve at all. Obviously, without knowing the objective it is nearly impossible to evaluate success (since it depends on comparing our "ought" and "is"). It is even more difficult to assess the efficiency and effectiveness of our work method and performance. Yet, the logical model offers even more. In order to plan the project correctly, and in order to be able to able to perform said evaluation process, it is recommended to break the process into interim goals and final goals. For each goal, we will define what is considered success. For example, regarding interim goals success could be considered the target audience becoming aware of the KM solution and its purpose (a goal related to an awareness-oriented change). An example of a "final result success" could be a behavioral change or solving the problem which led to creating/applying this solution in the first place (a goal related to a behavioral change). Furthermore, we must define the means by which we will define said success in attaining our goals. The logical model adds on the ability to evaluate not only the KM solution but the project itself. It also allows us to analyze the different moves made in order to reach each goal and gain the required resources. Some questions that can be useful include: Was the resource X used as planned in terms of time, cost and/or quality? Was activity Y performed as planned in terms of time, cost and/or quality? Did activity Z lead to the desired results? In conclusion, it can be said that the logical model's main advantage regarding the assessment and evaluation stage of a KM project is that it leads to an optimal definition of the projects goals and the means to achieve them, breaks the project evaluation into stages and allows performing changes, alterations or adaptations along the way as well as enables recognizing elements in the process which haven't led to the their designated resulted in a sufficiently efficient manner.

Service Centers in crises and emergencies 1 November 2015 Dana Neuman- Rotem Previous Article Next Article I have recently found myself stuck without water and electricity for 36 hours. I became even more frustrated when I realized no one knew when this nightmare was going to end. As customers we expect our service provider to provide us with precise and reliable answers. This expectation is vital when in an emergency. How do we get these service centers to provide us with precise and reliable information even when the company is experiencing a crisis or struggling with an emergency? Send call data: Send data and a response to call representatives as quickly as possible even when the data is partial or might change. Answering a customer incorrectly or with no real response to the actual situation can only make things worse. It is therefore better to supply representatives with data (even if partial) to provide the client with an answer. Short circuits: In times of crisis or emergency, power is diverted towards answering clients. There is therefore hardly any time for long updates. Send short and updated data via pop-up messages, creating a designated space for ongoing updates and writing designated emails. Make sure these information items share a uniform pattern and are sent by one party to avoid an overload of data from multiple parties, which can in turn lead to confusion and disorder. Data overload can also make matters difficult for the call representative. Hotline: open a hotline for questions from the field in order to learn of new situations and the difficulties they pose. Respond to these situations and send updated information to call representatives. Connect to the field: In order to ensure that the data is implemented it is vital to sense the practical reality of the call center; be present at a call center or at least in direct communication with those present to learn of knowledge needs and other needs that are brought up during the shift. Feel the customer: Listen to conversations to understand the customers' needs and how representatives sound during a conversation. Review whether the knowledge the representative is providing matches the organizational messages. Correct any false information and distribute it quickly. Marathon run: In some cases, the crisis takes a while and it is therefore important to maintain the data. If there is no new data, correct mistakes made due to partial messages or gaps between the organizational message and the message customers actually received from the representative. Use various tools such as short frontal tutorials supported by presentations or videos, self-learning from tutorials or short knowledge quizzes as well as gamifying content can help our cause. Learning after the situation was handled: After the crisis is long gone, it is still important to encourage a learning and data-transferring process. IT has been shown that an organization can learn from this situation, utilize the crisis to leverage future opportunities by learning lessons from the event. This process includes summarizing the central events, review the organization's conduct and present conclusions. This is an excellent opportunity to review the knowledge gaps that appeared during the crisis and consider how they can be addressed in order to enhance the call center for future crises. In conclusion, let us hope we don't encounter any more crises or emergencies, yet we can't ignore the fact that they too await around some corner. It is therefore vital to acknowledge them and be as prepared as possible. The crises may catch us unprepared, but we can still manage our data correctly!

Artificial Intelligence - Book review 1 July 2020 Dr. Moria Levy Previous Article Next Article The book "Artificial Intelligence" is a compilation of essays from the Harvard Business Review series, initially published in 2019. It encompasses various crucial aspects related to artificial intelligence, summarized as follows: 1. Definition and Explanation of Artificial Intelligence 2. Main Applications and Uses of AI 3. Practical Guidelines for Implementing AI 4. Controlling AI Systems 5. The Role of Humanity in the Age of AI 6. The Impact of AI on the Labor Market 7. Predictions on the Advancement of AI 8. List of Articles and Authors Undoubtedly, Harvard has effectively presented essential and cutting-edge knowledge in a clear and easily understandable manner. The subject matter holds significant importance, and it is increasingly necessary for managers and knowledgeable employees to begin learning and preparing for AI implementation. Organizations that delay embracing this technology may face severe consequences in terms of competitiveness in the future. In conclusion, this book is highly recommended for those interested in exploring the realm of artificial intelligence and its impact on business and society. Definition and Explanation of Artificial Intelligence Artificial intelligence is defined as the intelligence displayed by machines, as stated in the book "Beginning After..." (Wikipedia definition). Undoubtedly, AI stands out as our era's most significant general technology. Different individuals perceive it in various ways, and each perspective holds some truth: • Managers view AI as a breakthrough technology with disruptive potential. • Employees fear AI because they believe it might jeopardize their ability to work. • Consultants promote AI as a universal remedy for various challenges. • The media portrays AI with a blend of hype and admiration. The term "artificial intelligence," coined in 1956, has undergone various transformations and advancements over the years. Recently, progress has accelerated with a shift towards reliance on neural network algorithms, commonly called "machine learning" or "deep learning." This shift has led to remarkable achievements, such as machines surpassing human capabilities in tasks like face recognition since 2015. It is essential to grasp that the current approach to AI differs from what we have been accustomed to for years. Machines no longer seek to imitate human thought processes; instead, they employ pattern-based learning. These machines examine vast databases, learn from examples, and discern what aligns with the defined objectives (e.g., recognizing a cat). This learning process relies on algorithms, statistics, and databases. AI learns what we already know and uncovers hidden insights, offering a window into unexplored aspects we could never have considered. Today, organizations do not necessarily need to develop everything from scratch. They can adopt pre-existing algorithms from tech giants like Google, Amazon, or Apple and adapt them to address specific business problems. However, despite the enthusiasm surrounding AI, its applicability remains relatively limited and only encompasses some areas of our lives. In this context, human involvement still plays a vital role, which will be discussed further in a separate chapter later in the summary. Main Applications and Uses of AI Artificial intelligence has made significant advancements in various areas in recent years. Some of the main applications include: 1. Comprehension: AI excels in image recognition, natural language analysis, and understanding emotions. 2. Cognition (Decision Making): AI solves complex business problems, from games like GO to optimizing server room operations for efficient cooling and electricity savings. The current market applications are built upon these capabilities. For instance, self-driving cars rely on AI's ability to perceive and comprehend the surroundings, enabling optimal decision-making regarding speed, turns, stops, and more. Here are some examples of AI applications already in use: 1. Speech recognition for call centers and phone-based personal assistants. 2. AI-powered bots are trading on the stock exchange. 3. Tagging photos. 4. Drug development. 5. Approval of financial requests, such as loans and credit. 6. Fraud detection, particularly in finance and security domains. 7. Intelligent traffic lights to enhance traffic flow. 8. Facial and people recognition in photos. 9. Automated assembly of products like cars. 10. Product design recommendations based on materials, price, and performance. 11. Software project analysis to estimate development costs. 12. Public safety maintenance, identifying crowd movements through cameras. 13. Screening job candidates. 14. Customer service, responding to inquiries, and redirecting complex ones to humans. 15. Casino activity monitoring. 16. Recommendations for machine maintenance based on performance and operation mode. 17. Identification of medical risks based on patient conditions. 18. Wearable AI suggests tailored activities on amusement ships. 19. Wearable intelligence monitoring chronically ill patients (e.g., Parkinson's disease). 20. Personalized recommendations for clothing and fashion items. 21. Emotion-mediating eyeglasses for autistic individuals. 22. Providing support for those experiencing ongoing trauma. These examples illustrate the diverse and ever-expanding range of applications to which AI technology contributes across various industries and aspects of daily life. Practical Guidelines for Implementing AI Initiation: • As an organization, the ideal time to step into the world of artificial intelligence is now, or even yesterday, as suggested by one of the authors. The technologies have matured enough to be harnessed, but it will take time to realize the benefits within the organization and align its structure and processes accordingly. Delaying entry may result in competitors gaining an advantage. • Before commencing, individuals should have a basic understanding of AI, its workings at a high level (without delving into complex mathematical details), areas where successful implementations are evident, and areas where caution is needed (such as those involving complex ethical issues). • Appointing a leader and a supporting team is crucial. Initially, a team for testing and selection (comprising business experts and data-savvy personnel) is needed, followed by a team for full implementation (involving algorithm and computing experts, data scientists, and knowledge engineers). Collaborating with experienced external consultants/partners is also recommended. Planning: • Choosing a pilot project is essential. Opt for 1-2 smaller projects meeting specific criteria: - Enable quick wins - Address problems of moderate complexity related to the organization's core content. - Create value A good starting point is to focus on automating tasks people perform. • Verify compatibility by assessing whether a simple algorithm could provide a viable alternative. Jumping into complex AI solutions solely because they are possible is only sometimes advisable. • Gaining organizational support from managers is vital. Ensuring they understand the potential value created by a successful AI project is essential. Coaching (Machine Learning and Examples): • The machine learning process may start slow but later picks up pace and stabilizes. • It is essential to anticipate failures, as they are part of both the solution development and the machine's learning process. Human supervision is necessary. • Evaluating the machine's success should always be based on whether it aligns with the customer's business goals rather than solely assessing algorithm performance. Operations: • In the operational phase, new and current data are required, distinct from the data used during the training phase. This data is essential for decision-making and continually improving the learning process, as the environment is constantly changing. Control: • A separate chapter deals with control and will be described below. Channeling: • Celebrate successes at the end of the pilot project when significant milestones are achieved during the process. Note: Apart from the technology-specific training phase, the stages of an AI project are similar to those of other subjects, such as knowledge management or machine learning. Controlling AI Systems As previously mentioned, machines are not flawless, and there are three risks associated with their functioning: 1. Machines can exhibit biases based on the content they learned when making decisions initially. These biases might reflect racial, gender, or other ethical considerations. 2. Machines rely on statistics and may struggle to handle edge cases. In critical scenarios, such as nuclear facilities or safety decisions, this poses a risk. 3. Detecting and correcting machine mistakes (which are likely to occur at some point) can be highly challenging. Given the possibility of errors in machine operations, ongoing control measures are necessary, including: • Control of input information, restricting it to validated data. • Testing algorithms for typical biases related to gender, race, age, and other content-based factors. • Proactively searching for potential failure scenarios and devising workarounds. • Having a contingency plan for a less "smart" response in case of system failure. • Establishing a prepared channeling strategy to address failures during the operational phase, including issuing apologies if needed. The Role of Humanity in the Age of AI The book emphasizes the importance of human involvement in the AI process. This role extends beyond algorithm specialists, data scientists, and software workers. People play a crucial role in various aspects: 1. In processes where AI cannot provide a complete solution: - Complex tasks involving diverse functions (e.g., marketing). - Tasks requiring creativity (e.g., brainstorming, sales meetings, system characterization). - Tasks involving emotion-based decision-making (e.g., handling at-risk customers). 2. In processes where AI offers a partial solution, human-machine collaboration is vital: - Processes comprising mechanized and delicate tasks (e.g., assembling luxury cars). - Processes involving routine responses by machines, with exceptions handled by humans (e.g., customer service). 3. In processes fully leveraging AI, people are required for various critical functions: - Defining the business problem and solution. - Making decisions regarding data usage. - Defining data requirements and ensuring data quality. - Providing initial guidance and understanding of desired goals. - Training the AI system. - Explaining AI-generated outputs in especially crucial fields like law and medicine where explanations are essential. - Monitoring mechanized activity. - Addressing issues when failures occur. To facilitate optimal integration between people and machines, organizations are advised to follow these recommendations: 1. Redefine organizational processes with a focus on long-term goals and aspirations. 2. Involve employees extensively, drawing on their expertise to determine what will be effective. 3. Formulate a clear AI strategy for the organization. 4. Define clear responsibilities for data collection. 5. Redesign work processes to incorporate AI capabilities alongside employee skills seamlessly. By following these guidelines, organizations can harness the potential of AI while ensuring that human contributions remain an essential and strategic component of their operations. The Impact of AI on the Labor Market Predictions labor market vary, and five possible scenarios are presented: 1. The labor market will become a battleground between machines and humans, with machines eventually emerging victorious. 2. Intelligent machines will gradually take on more tasks, leading to overall economic well-being but reduced demand for human labor. 3. Machines will enhance labor productivity, resulting in economic growth, but the benefits will be unevenly distributed. People will need to focus on continuous education and invest in technology. 4. Despite the advanced capabilities of machines, productivity improvement will be only marginal. 5. Productivity gains will occur in specific sectors and successful companies while new professions emerge. However, manual workers may face challenges transitioning to these new roles. Research and planning are required to address this issue. Recommendations for managers to prepare for the future labor market include: 1. Leveraging technologies to automate routine tasks and achieve cost savings. Redefining the organization's operating model is essential. 2. Identifying opportunities for redefining roles by determining which tasks can be automated, integrated, or performed solely by humans. The organizational structure should be adapted accordingly. 3. Engaging employees as partners in intelligent enterprise planning, involving them in decision-making processes related to integrating AI and automation. Predictions on the Advancement of AI Despite the exciting AI capabilities already in use, laboratories are actively working on the next generation of solutions, which will encompass: 1. Emotions: Advancing AI to recognize, process, and even imitate human expressions. 2. Accuracy: Continuing efforts to enhance predictive accuracy in understanding people's desires and preferences, leading to innovative sales business models (e.g., shipping items deemed desirable to your home and avoiding unwanted ones). 3. Data: Developing AI that can achieve comparable results using less data, reducing costs, and expanding the application of AI to various business problems and other domains. 4. Conceptual comprehension: Improving AI's ability to comprehend concepts, facilitating more advanced learning stages. 5. Handling edge cases and exceptions: Addressing challenges from unusual situations or circumstances. 6. Common sense: Enhancing AI's capability to apply logical reasoning to objects, places, and actors, including humans. 7. Improved assessment: Enabling better decision-making under conditions of uncertainty. The reality of AI's progress surprises us repeatedly, and its continuous advancement is indeed admirable! (M.L.)

Useful video editing software for beginners 1 February 2019 Moran Maravi Previous Article Next Article My previous pieces on video content discussed combining video and Knowledge Management (click here ), tips for writing a script for your short video (click here ), tips for video filming (click here ), platforms designed for video management in organizations (click here ), reviewed different ways to leverage video as a learning channel (click here ) and discussed the importance of leveraging video as an intra-organizational strategic channel (click here ). Incorporating video content as a complementary tool for organizational Knowledge Management processes can enhance the effectiveness of organizational knowledge implementation. For example, incorporating short video segments of workers sharing their personal experience of using insights managed in the database can add a personal quality. Furthermore, it can both assist in clarifying the necessity of these insights and encouraging others to make use of them. Videos can also be used as a tool for distributing knowledge to workers spread out across the country or globe. This serves as a quick and easy way for workers to access knowledge, compared to reading a new procedure or frontal tutorial. Plus, it saves time and money while raising the chances the information will be implemented. Before we review useful video-editing software, let's review some statistics concerning video content on the internet: 82% of Twitter users consume video content via Twitter YouTube has more than a billion users, which are nearly a third of all internet users. 45% of internet users watch approximately an hour of video each week (via Facebook/YouTube). 72 hours of video content are uploaded to YouTube every 60 seconds Marketers that make use of video content to promote their product have grown 49% more than those that do not. I will not tire you with more statistics. I will however state that the forecast for 2019 is that 80% of all internet traffic will be dedicated to video watching. So, if your KM strategy for this coming year doesn't involve any video elements, now is the time to consider introducing this medium to your toolbox. This might not seem an issue worth a substantial investment compared to more pressing and important areas of your business/organization. That is a legitimate concern. You can, however, start off with making some video content using simple editing software for beginners. iMovie by Apple: designed for Mac users yet available for iPhone or iPad users (via a designated app). This software's main advantage is that one can film a video with their iPhone/iPad and transfer it to their Mac to be edited, using Apple's Airdrop function. If it's simplicity and elegance you seek, iMovie is for you. One of its prominent features is the "green screen", which allows you to display characters on a background of your choice. You can also import songs and/or recordings via iTunes or GarageBand. Once the editing process is complete, you can immediately share it on Facebook or iMessage. Cost- free for Apple customers. For further details, click here . Nero Video- a low cost video-editing software that is surprisingly full of features and effects. It presents the user with basic editing tools that are quite simple and less professional than Filmore (described below). It enables you to edit video easily using a Drag & Drop which is very comfortable for beginners. Its main advantage is its immense amount of video templates (more than a thousand!), which can simplify the editing process, especially for first-timers. For further details, click here Corel VideoStudio- a software which features, beside all the properties described above, a 4K or VR360 advanced editing option. Furthermore, it enables access to more than 2,000 filters and effects, including premium effects used by leading figures in the video industry. Its great advantage is that it allows the editor to 'follow' characters throughout a certain shot and thus add a certain element to it: an arrow above it, amusing attire, or simply blur its face for discretion purposes. Its main disadvantage is that it is slow compared to other software. For further details, click here Filmora- a simple yet high-quality video-editing software, Filmore offers a free version. I use this version and highly recommend it. Its design is very intuitive and user-friendly. The software comes with many filters, layers and movement elements coupled with a limited pick of royalty-free music. Furthermore, it allows you to create cool titles on par with more professional software. Its greatest advantage is that it features an "easy-editing" mode, specially designed for beginners. This mode allows users to edit videos by dragging &dropping. Selecting music and choosing a title for your video. The full version, available for pay, features further functions for advanced editors. For further details, click here . Shotcut- a totally free, open source software that can serve you in your first steps in video-editing. The software supports a wide variety of formats, the intuitive and simply operated interface. The Drag & Drop feature simplifies the editing process for beginners. For further details, click here . Windows 10 Photos App- the official substitute to Windows Movie Maker. This software is installed on computers with a Windows 10 operation system and is somewhat hidden, since anyone who searches for video editing tools in this operation system might not find it. A Google search, however, reveals its location. Why Microsoft chose to do this is a mystery. This software is a simple editing tool, quite similar in its functionality to its previous version perfect for a video editor uninterested in investing money and downloading software. The tool allows users to edit videos using a number of premade templates. In other words, the user chooses a video/picture file and the tool does the rest of the work for me, choosing apparats, music and transitions according to the selected template. This tool's advantage is its (quite surprising) 3D effects features. For further details, click here . Windows Movie Maker- The first software I ever used, an entire decade ago. I've left it for last, as I have a special affinity to it and also since it is supported only by previous versions of Windows (up to the Windows 7 operation system), meaning that if you own a Windows 10 computer you won't be able to make any use of it. It is the simplest software I know and doesn't feature many functions and effects. You simply drag picture/video files, incorporate background music and subtitles and- voila, a video is ready in minutes. You can also add some effects from the limited array the tool offers. For further details, click here . In conclusion, this review was meant to enable readers to select one of various simple and user-friendly editing tools. If you are making your very first steps, I recommend Windows Movie Maker or Photos App. For a more professional tool, I recommend using Filmora. I wish to welcome all newcomers to the world of video editing. I fell in love with it and am sure you will too. References: The 12 Best Video Editing Software for Beginners in 2023 75 Staggering Video Marketing Statistics

Dr. Moria Levy Dr. Moria Levy is one of the foremost thought leaders driving the knowledge management discipline forward. In 1998, Dr. Levy established ROM Knowledgeware, a firm specializing in KM. ROM turned out to be one of the biggest KM firms worldwide, nowadays with 40 employees daily serving KM organizations worldwide. ​ Moria didn’t settle for owning and leading a big KM firm, exceptional in its size in this evolving market. She pushed forward to develop new methodologies addressing intranets, lessons learned, knowledge retention, collaborative knowledge development, and more. These methodologies, based on fieldwork, were later the basis for her research papers and books, having nowadays over 1,000 citations. In 2017 Moria Levy was included in the Journal Impact Factor of Thomson Reuters. ​ Dr. Levy led the first worldwide initiative of a KM standard: the Israeli KM standard SII25006. This standard was published In 2012 and was the foundation on which KM in Israel later developed. In 2015 she was chosen by the International Standards Organization (ISO) to lead a global experts team in developing a KM standard. This resulted in “ISO30401 – Knowledge management systems” an agreed upon comprehensive compass for knowledge management excellence. Dr. Levy led the first initiative worldwide for high school studies specializing in knowledge management as part of information and data sciences studies, a program running in Israel for over a decade. ​ Since the beginning of the Covid pandemic, Dr. Levy was focused on pushing the KM discipline forward, with the vision of utilizing it to bring prosperity to organizations and to the community. As the Israeli KM forum chair, she joined KMGN, the KM global network, turning her personal vision into the organization’s. She led. in KMGN, the development of two innovative KM courses, one focused on AI and KM, and the other on advanced KM methodologies. These courses were very successful, offering experienced KMers around the globe new ideas on better implementing KM. During her 2022 tenure as KMGN chairperson, the organization doubled from 12 to 25 involved countries and networks. This period saw KMers all over the world better acting together, looking for shared KM challenges and running specific projects to tackle these challenges. ​ Nowadays, Dr. Levy continues to lead the “Designing the Future for KM” committee in KMGN, and continues to take part in leading KMGN working on setting a shared KM week worldwide.