Everyone is talking about AI (Artificial Intelligence) and how it’s going to change our lives. AI is already changing our lives – in ways we might not even realise.
AI is helping us to make better decisions, to automate tasks and to interact with other people more naturally. With AI comes big data, and the ability to analyse this data in ways that were previously impossible. This leads to entirely new research opportunities – but also challenges. Namely, with all these big data tools at our fingertips, how can we ensure that the data we analyse is reliable? And, more importantly, how can we identify the qualities that make up a good analysis?
These are the questions that Digital Knowledge Index (DKI) attempts to answer. For those that are unfamiliar, DKI is an academic research centre that focuses on the quantification, evaluation and management of knowledge in digital environments. As the name would suggest, DKI’s key objective is to provide the means for measuring and comparing knowledge across different organisations and individuals in a digital world. To achieve this, DKI develops and applies novel research methods to investigate the most prevalent issues surrounding knowledge acquisition, storage, and sharing in the digital era.
DKI And The Future Of Work
More and more businesses are moving to a collaborative model where work is distributed across organisations and individuals. This is often referred to as the knowledge economy, and it is changing the way that we will work.
If you’re not yet convinced of the transformative power of AI, consider this – in the next five years, more than half of the jobs currently held will be automated, according to the Forbes Millennials Survey.
In such a climate, it’s important to consider how we can remain competitive – and, indeed, successful.
DKI is focused on developing and applying novel research methods to answer these very questions. By uncovering the methods that proven businesses have used to succeed in this new era, DKI aims to advise businesses regarding how to maximise their potential and how to prepare for the changed landscape that AI is bringing.
DKI And The Evolution Of Knowledge
For centuries, knowledge was primarily acquired through traditional methods – we learned from our peers, we absorbed knowledge through reading books or watching taught lectures, and we imparted knowledge to others via tutorials and expertise. In the digital age, this traditional form of knowledge transfer is being replaced by new methods of knowledge acquisition and storage. In short, we’re learning to get more out of our mobile computers and the internet than we can from a single tutorial.
This has resulted in a flurry of startups, including our own Cloud Knowledge (https://www.youtube.com/c/cloudknowledge.com) that are aiming to make knowledge acquisition and sharing easier and more accessible – with varying degrees of success.
One of Cloud Knowledge’s primary differentiators is the ability to transform the way we search for and consume information. Rather than merely providing access to abstract databases and solutions, Cloud Knowledge provides a meshwork of interlinked data that can be scrolled through in a multifaceted search engine. This means that if we do find a solution we are more likely to find other relevant solutions that can be interlinked, rather than a single flat list of solutions.
Another startup, Memex (https://memex.com), reaches even more broad Areas of Knowledge through the use of big data, machine learning and natural language processing. Using AI to uncover patterns and discover relevant parallel solutions, Memex aims to make knowledge search and navigation as efficient and natural as possible.
The Challenges Of Knowledge Acquisition
Once we have the knowledge, how do we know that we have the right knowledge?
The ability to calculate and predict the behaviour of a particular system is one of the hallmarks of human beings. We can look at the sun and know with near certainty that it will rise in the east and set in the west – we don’t have to witness the sunrise to know this. Similarly, we can look at a map of the United States and know with near certainty that it is an ally of the United Kingdom.
In the world of knowledge, this ability to calculate and predict is known as Verisimilitude. Simply put, the more accurate and up to date the information provided by a knowledge source, the more likely it is to be believed by the user.
For example, if a source claims that a particular product is independently tested and determined to be 90% effective in fighting off foes, but you have never heard of this product before, you’re more than likely to question whether or not it is worth investigating. On the other hand, if the source claims that the product has been certified to be 100% effective, you’re more likely to believe that the product will work for you.
DKI And The Evaluation Of Knowledge
Even if we have the knowledge we need, how do we evaluate and compare this knowledge across different sources?
Knowledge is like any other form of information – it can be updated and improved upon via research, and it can be embellished upon by the interweaving of new data. However, this does not make knowledge easily manipulable or usable.
One of the great achievements of the modern era is the ability to capture and manage these evolving knowledge sources and their content. This is made possible by the use of peer review, which assesses the contents of a knowledge source by comparing it to other sources that are known to be reliable.