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    How Can Blind Spots in AI Help Foster Online Privacy?



    Machine learning application has now made it possible to detect cancer cells and create collision-proof self-driving cars. But, at the same time, it also threatens to turn over our notions of what’s hidden and visible. 

    For instance, it enables the highly accurate facial recognition, sees through the pixelation in photos, and even uses data available on social media to predict sensitive traits like an individual’s political orientation, as was the case seen in the notorious Cambridge Analytica scandal. 

    These same machine learning applications suffer from a peculiar sort of blind spot, which usually humans don’t do. This blind spot is a fixed bug which can make an image classifier mistake a rifle for a jet plane, or create an autonomous and free vehicle by a stop sign. All these misclassifications are known as adversarial examples, have been seen as an irking and severe weakness in several machine learning applications. Only a few small tweaks to an image or some additions of decoy data to a database can easily fool a system to end up entirely wrong conclusions. 

    Researchers have suggested that attackers are increasingly using machine learning to compromise on user’s privacy, as demonstrated by the increasing complexity of cybercrimes, such as phishing ...

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    How Blockchain Proxy-Voting Will Improve Shareholder Engagement



    We live in an increasingly globalised world. Although some world leaders believe that the future belongs to patriots rather than globalists, technology is making the world an ever more integrated and smaller place.

    In fact, we can say that globalisation has gone digital. In the 21st century, globalisation is all about exchanging data. Thanks to the interconnected digital world that we live in, borders are disappearing, and national legislation is increasingly difficult to maintain. In today's world, even a 1-person company can be a multi-national and thanks to blockchain and Security Token Offerings (STOs) organisations can raise funds from anywhere in the world.

    Not only startups can benefit from these new distributed ledger technologies, but also existing public multi-national enterprises (MNEs) can use it to improve, for example, corporate governance. MNEs span multiple jurisdictions and territories, where variables such as technologies, infrastructure, markets, legislation and customer demands are different. In addition, shareholders can be located anywhere in the world, thereby directly affecting corporate governance.

    Corporate Governance and Proxy Voting

    Corporate governance controls how public MNEs behave. The objective of corporate governance is to ensure that the agent (the management of an organisation) behaves as intended by the principal (the shareholders). To achieve that, there ...

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    7 Blockchain Challenges to be Solved before Large-Scale Enterprise Adoption



    When organisations adopt new technologies, the context of that technology plays an important role. How people deal with the material properties of new technology is informed by their previous experience of using or not using similar technologies in the past. Since blockchain is still a new technology, how organisations adopt this technology also depends on how existing and related challenges are resolved. These affect how organisations apply blockchain and smart contracts, and whether the design and decision-making capabilities within will or can change at short notice.

    Currently, many enterprises are experimenting with blockchain, but few have implemented a decentralised solution. According to a 2019 Deloitte report on enterprise blockchain adoption, 53% of the 1386 interviewed executives stated that blockchain had become a critical priority. However, only 23 per cent have actually initiated a blockchain deployment. While blockchain is gaining traction and acceptance in more industries, there are still some challenges left that need to be fixed first before we will see large-scale deployment. Let take a look a seven blockchain challenges that need to be fixed;

    Seven Blockchain Challenges

    1. Scalability

    The first challenge is the technical scalability of blockchain, which is, at least for public blockchains, a hurdle that could limit their ...

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    14 Ways Machine Learning Can Boost Your Marketing Introduction



    Machine learning is an application of artificial intelligence. And it is no secret that this technology is revolutionizing the marketing niche. It enhances a system in a way it that it learns from current and past experiences. It involves the invention and development of computer programs that can read data and use it to influence performance. This, of course, happens without human intervention as the whole process is automated. Exploring technology for gains in business is a practice that has taken ground. More and more companies are employing artificial intelligence in their daily operations, in a bid to perfect customer experience and boost returns. Thanks to the rapid growth in technology, marketing has seen different improvements.

    So, how can machine learning improve your business and affect the flow of clients? This is an argument that has elicited mixed reactions from pundits in the industry. Some argue that this is the way to go for the future, while others are a bit skeptical and reserved. While conventional means of advertising worked efficiently, this may not be the trend throughout. Change is inevitable, and so, you need to shape yourself ready for it, if you’re a participant in this niche. Besides, with the ...

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    The Database of Tomorrow: The Self-Driving, Autonomous Database



    This article is sponsored by Oracle - redefining data management with the world’s first autonomous database. 

    In the coming years, the amount of data we create worldwide will grow to 175 zettabytes of data per year by 2025, up from 33 zettabytes in 2018. Over half of this data will be created by the Internet of Things devices and over 60% of it will be enterprise data. By 2025, 30% of all the data created will be in real-time, offering organisations great opportunities to constantly optimise their business.

    Clearly, the organisation of tomorrow is a data organisation. However, simply collecting vast amounts of data is not enough. You would also need to analyse the data for insights and change your organisational culture to benefit from it. According to McKinsey, data-driven organisations are 23x more likely to acquire customers, 6x more likely to retain customers and 19x more likely to be profitable. Being data-driven is good for business.

    The Importance of Data Governance

    When collecting petabytes of data, it becomes vital that this data is of high-quality. Organisations that focus on high-quality data are better able to deal with changing business environments and achieve strategic objectives. As such, in today’s data-driven world, data governance has ...

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    Cambridge Analytica whistleblower Chris Wylie to headline Big Data LDN 2019 keynote programme



    The UK’s largest data & analytics conference and exhibition,

    Big Data LDN (London), have recently announced Chris Wylie will headline their 2019 keynote programme.

    The New Yorker calls him “a pink-haired, nose-ringed oracle sent from the future”. Best known for his role in setting up – and then taking down – the cyberwarfare firm Cambridge Analytica, Chris has been listed in TIME100 Most Influential People in the World, Forbes’ 30 Under 30, Politico’s 50 Most Influential People in Politics and Business Insider’s 100 Coolest People in Tech.

    Named as “the millennials’ first great whistleblower,” his revelations exposing the rampant misuse of data rocked Silicon Valley and forced numerous Fortune 500 companies to overhaul cybersecurity and user privacy practices. Congress held its first-ever hearings on the impact of social media on democracy and Facebook experienced the largest single-day share value drop in American corporate history – twice.

    His evidence also exposed the deep links between the Alt-Right and Russian intelligence networks, leading to major ongoing FBI and NCA investigations in the US and UK.

    With his neon hair and brutally honest candour, Chris engages audiences around the world and makes AI understandable, disturbing – and yet somehow compelling. When Chris speaks out about the future of ...

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    Artificial Intelligence in Future and Present



    One of the most cherished dreams — and fears — of today is penetration of Artificial Intelligence in all aspects of our life. Books and movies about wars with robots, artificial masterminds and the forever changed Earth emerge every year to stir our imagination. The reality is far less thrilling: in his famous article Andrew NG, one of the most influential figures in the AI field, admits that the most recent progress is through one type, in which some input data (A) is used to quickly generate some simple response (B). Let’s sketch what AI might do and what it can actually do in various industries:

    Artificial Intelligence and Medicine

    Artificial Intelligence and Education

    Artificial Intelligence and Finance

    Artificial Intelligence and Manufacturing

    Artificial Intelligence and Media & Entertainment

    Artificial Intelligence and Everyday Life

    It is true that our perception of Artificial Intelligence is formed under the influence of mass culture with all its dreams and fears. Of course, AI plays an increasingly important role in our life and we’ll see tremendous improvements in technology in the following years, but in its essence, AI is a tool. It helps us to enhance our abilities, just like normal computers, or calculators, or a pen and a paper that improve our memory. So, we ...

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    The Token Sales Mechanics



    Creating tokens in an ICO was one thing, but figuring out how many to create, how much to sell, the early round bonuses, the inflation rate and everything else relating to the mechanics of the tokens was (and still is) a challenging task.  

    Although there is no right or wrong way to create tokens and market it, a lot of parallels can be drawn from the issuance of regular shares in a company served with a side of economic incentives, a sprinkling of game theory, and a dust of creative marketing. In this article, we will look at the all-important supply and distribution of an ICO. 

    This article is an excerpt from the book Tokenomics by Sean Au and Thomas Power. This book is a deep-dive into the economics and technology of tokens, and how this will lead to a new tokenized economy.  

    Token Supply & Distribution 

    Looking at the number of tokens created, there is generally no rhyme nor reason for the values chosen. The standard default in the early days seemed to be 100 million tokens which was a nice round number. Others preferred 1 billion as a round number. The supply ranged from 2.6 million to 2.7 quadrillion. 

    ICO  

    Amount 

    Counterparty 

    2.6 million 

    Factom 

    8.8 million 

    Gnosis 

    10 million 

    Augur 

    11 ...

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    Statistical Methods and Machine Learning Algorithms for Data Scientists



    The mining of useful data from big data sets is done by professional big data analysts. There are statistical methods and machine learning algorithms for data scientists which help them provide training to computers to find information with minimum programming. This also makes predictions on the basis of big data. 

     Because of this, it’s essential that you don’t confuse data science with big data analytics.

    Machine learning practice involves the use of algorithms to understand data and predict possible trends. The traditional software has a predictive and statistical analysis that helps in finding the patterns and getting the hidden information based on the perceived data. 

    The term data science is vast and caters several disciplines, machine learning works within data science. There are numerous techniques available and applied in machine learning, including supervised clustering and regression.

    How does Data Science differ from Machine Learning?

    But the data that is used in data science may not have come from a machine or any mechanical process. The most significant difference is that data science covers a broader spectrum and doesn’t just focus on statistics and algorithms but will also look at the entire data processing system.

     It’s obvious to ask how the latest criteria for causation could be ...

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    A Distributed Future: Where Blockchain Technology Meets Organisation Design and Decision-making



    Blockchain technology records and forever maintains data that cannot be changed. It also involves ‘smart contracts’ and consensus mechanisms that govern processes of automation, as well as the development, evaluation and execution of decisions. Blockchain technology has the potential to transform organisation design due to its decentralised and distributed characteristics. To understand how blockchain will change organisation design and decision-making, let’s first dive into the history of organisation design before investigating the impact of this fundamental technology on organising activity.

    History of Organisation Design

    The theory and practice of organisation design have evolved significantly over the past 100 years. At the beginning of the twentieth century, organisations were mostly viewed as closed bureaucracies. Involving a strict hierarchy of authority and power, these organisations were rational entities and assessed purely on economic performance criteria. It was called the ‘bureaucratic model’, as it captured standardised, authoritative, decision-making procedures, rational discipline and strict separation of planning and execution1. This meant that only managers had access to information and were solely responsible for strategic decision-making therein. Trust was based on controlling conformity with the organisational rules and technology, which was predominantly manufacturing technology, with very predictable effects on how organisations were designed to perform.2-4

    Natural Systems Perspective

    In ...

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