This is my own reflection after studying in the “Gestion des connaissances” class, UOKM Winter 2017, with my modern, cosmopolitan and inquisitive professor, Pierre Levy
Parujee Akarasewi (Writer)
@plevy (Twitter) – University of Ottawa
Before I wrote this work, a memory of having to buy a new external drive last December at Best Buy popped into my mind. I honestly had ZERO knowledge about data and knowledge management at that time, and almost bought a 5Tb drive for my catalogue of 5,000 selfies. Seriously! Fortunately, at that time I was able to consult some IT-savvy friends to give me advice, complete with all the technical language and explanations that that left me without a clue as to what he was talking about. All I know is that 1 Tb is enough for my narcissistic collection of 5,000 selfies.
Once I started to take in the material of the Knowledge Management class with Professor Pierre Levy, I was exposed to many types and techniques of knowledge and data management on many platforms using many types of storage… I realized that we can save and manage data in more ways than just a USB flash drive or saving it to external storage.
In class, I learned to save, manage and share the knowledge that we have learnt during class through the class’s accounts using the #UOKM hashtag on the Twitter and Facebook social networks, complete with emojis, videos and links to articles. Frankly, this is a creative, intellectual way to use social networks, better than just clicking “Like”, and scrolling up and down to see pictures from friends.
My curiosity went into overdrive from the beginning of the class in January until the last class. I came to know that data curation is the key to Google’s management of massive quantities of data, “Big Data”, organized and put into different categories.
We cannot deny that we are all now in the Cyberspace Era, which has come into existence through multiple technologies. It requires collective intelligence and a community effort to help individuals towards a better and uniform understanding of new technologies like Bitcoin (a new E-currency for investments) and Blockchain (security for banks and money transfers) through well thought-out innovations in education, such as the use of social media, teach-back design, crowdsourcing, learning approaches through videogames, formative analysis, future learning, translanguaging, data journalism, open science, and so forth.
In fact, from what we learned in class, knowledge management, or KM, has many definitions: it is the whole process dealing with knowledge that is established in an organization in order to create, capture, manage, share and apply this knowledge in order to carry out the strategy to achieve the organization’s objectives; or the process of multi-disciplinary management by regrouping initiatives, methods and techniques that allow the perception, analysis, organization, addition to institutional memory and sharing of this knowledge by members of an organization. The knowledge can be the product of the organization itself, or learnt from external organizations in order to achieve its business goals.
At the organizational level, the behaviors, processes and technologies are filled in
- to allow personnel to understand each of these things individually and know how they apply to everyone, and
- see the big picture that applies to the entire organization, in order to be able to adjust, so that
- the organization can find out what they do not know and what they can apply for.
Humans can think, communicate and present things that are hard to present, but they can also create knowledge and, using symbols for better communication, transfer it from generation to generation.
I used to contradict my father, telling him that mathematics are not important…
I have since come to realize that I was wrong, because mathematics now run the world. In order to manage the data at the foundation of knowledge, they have become the tools of statistics and analysis.
Imagine Big Data as a wizard: he must be a powerful and brilliant one. He can predict the future, identify phenomena, and create statistical models of the results. He can also identify causes for phenomena through statistical analysis and the application of the wonderful magic tricks of algorithms. This wizard will interpret all the data, and will always play an important role in verifying hypotheses and scientific models, and communicating the results to others. We cannot refuse this great wizard control over us in the cyberworld.
On the other hand, the advance of technology has been retarded in many companies: they have blindfolded themselves, which is why their evolution will inevitably be found to be lacking in enormous opportunities for the future, and even for the present.
None of this should scare us, because Big Data, with its statistics and algorithms, is still a million years from replacing the intelligence of human analysis, the experience of scientists, peer validation, the evolutionary comparison of data, etc.
In the book “Free Culture”, Lawrence Lessig defends “free culture” as freedom balanced with control. He sees culture as the growth of creativity when built upon permission when using the intellectual property of others.
He defines “piracy” in two ways: stealing for one’s own benefit, cutting into the income of creators; and striking a balance between the interests of IP owners and society to create a new business model. He makes a compelling case for the balance between owners and society so that we may have freely available culture that encourages new creation.
The author’s intention in making this book freely available and accessible to everyone was to create, to “kick start”, so to speak, a culture of freedom in copyright law so that tomorrow’s culture may grow without hindrance out of today’s.
When we take into account Big Data, though, the law might not be able to protect any intellectual creations in the cyber world, because of sharing and the wizard algorithms that I will explain in a later section.
This fancy expression is a new term and new method applied in modern technology and social media when saving data, information and knowledge. We can find old data, qualify it, and keep the right or favorite content for all time with tools like Scoop.it, Evernote, etc. We use hashtags and emoji to express our feelings toward the content we read. (For example, when I posted in the class Facebook page that I would be late due to the traffic my bus was facing, the professor commented on my post with an angry face emoji. That prodded me to run to class after I got off the bus, to try not to be that late. Ha-ha+) *** But please note: according to my KM-savvy Prof. Levy, Facebook, Twitter and other social media type are information platforms, not the sources of knowledge: the content that we post and repost is the real source. The more we share, the more data is stored on the platform, which is why those wizardly mathematical algorithms know what we like and keep sending us what we want to see on our page.
Data curation can manage all the data in the data schema through tags that categorize the data as a model. It comprises collective and artificial intelligence in order to make the data accessible and systematic.
Collective intelligence is intelligence distributed everywhere using everyone, constantly valued, and coordinated in real time, which results in an effective mobilization of skills, the aim being to channel knowledge to think together, according to the book that professor Levy assigned to me, “The Knowledge-creating Company” by our kind Japanese “grandpa”, Ikujiro Nonaka. In short, in this book I found that a person acquires implicit knowledge (procedural or understanding) through her efforts in research and development (R&D) for new product development.
Nonaka also stated that “organizational knowledge creation is like a ‘derivative’ of new product development.” Or in other words, knowledge is created in the interactions between frontline employees and so forth. This book helped me to realize that the next generation of wars will be fought with data, not harmful weapons. The more data we have, the more chance to win, as happened in the Japanese revolution.
Finally, What is Artificial intelligence? Artificial intelligent is the simulation of human intelligence processes by computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions), and self-correction.
All in all, a semester tackling knowledge management with a scholar such as Professor Levy is tremendously valuable for my future professional and daily life. I hope my readers can learn as much as I have, and see the importance of knowledge management for the future, because the future war is a war of knowledge, not of weapons…