The Democratic Quality Vector and
the New Social Agreement

A Brief History of Fake News

When the knowledge that is handed down is combined with errors. As soon as anybody belongs to a certain narrow creed in science, eerie unprejudiced and true perception is gone”


Humanity has passed the industrial age and is well into the information age. Data has become the lifeblood of our society and our economy. Like it or not, we are all interconnected by a vast network of information arteries that allows instantaneous communication. In recent years, self-organized mass social events such as the Occupy Movement, the Arab Spring, the Yellow Jackets, and the Zimbabwe uprising have seen a game of citizens using social media as a powerful democratic organizational tool. It is so powerful that governments sometimes respond by shuttering the internet or social media. Such is the power of the internet and real-time mass information flow.

Today the internet is about to enter a new era. With the dawn of IoT (Internet of Things), Blockchain and AI, machines are going to join this network in a way that will result in massive step change in the internet and data landscape. IoT is expected to reach 75.44 billion units worldwide by 2025 (, eclipsing computer sales. The microscale implications of this seismic macro-scale shift will be profound. As explained before, technology that moves this rapidly brings huge socioeconomic-ecological changes, both beneficial and harmful. It is a power that is transforming lives, but it comes at a price.

If information is the currency of modernity, then decision-making is how we spend it. So, the question is: are we spending wisely? The explosion of technology is generating reams of data, but all the information in the world is of no use to us if we cannot sort through it, make sense of it or trust it. These massive mounds of unusable information are the digital equivalent of a hoarder. How many of us have emails that have never been pruned, with useless messages, spam or outdated information sitting somewhere in the cloud? How much unused data are companies collecting through social media data analytics and

machine to machine systems? Here are some sobering facts about our growing data mountains, published by Forbes magazine in 2015:

• 90% of the world’s data has been generated in the past two years (Sintef, 2013)

• By 2020, we will have 6.1 billion smartphone users globally and 50 billion smart connected devices

• Google uses 1,000 computers to answer a single search query, taking no longer than 0.2 seconds to complete (with 3.5 billion searches a day in 2019, this is a major reason why IT is becoming a serious power hog)

• A typical Fortune 1000 company will generate $65 million of additional revenue by increasing data accessibility by 10%

• Retailers who leverage margins by up to 60% big data can increase operating

• 73% of organizations have already invested or plan to invest in big data in 2016

• Only 0.5% of all data has been analyzed and used

The first problem we will have to contend with is how to deal with the sheer volume of data. The unintended consequences of this mountain of data reach into many dimensions. For instance, the findings of Swedish researcher Anders Andrae shows that all of this data traffic could have a profound impact on total electricity usage and subsequently and carbon emissions.

If there are no interventions, this amount of data usage could consume a fifth of humanities’ electricity supply by as early as 2025. For organizations, inexpensive digital technology, high bandwidth internet, and the coming of IoT, A.I., and blockchain will create more data than we can deal with. How will we manage and make sense of all this data? This is important because it won’t be of much value to us if we can’t. As the above graph shows, we could be wasting vast physical resources if that data is not used effectively. We have to develop super-efficient hardware, data-miserly software, and data habits to apply whole new fields such as big data science, data analytics, and machine learning efficiently. This will produce valuable policy, business, and personal insights to support effective decision-making.

The second problem is information quality. With so much data coming from so many sources, data quality is rapidly becoming a significant issue. One of the most apparent data quality issues is the rapid emergence of the phenomena of fake news, a term which has become part of the lexicon of modernity. It reflects the ease with which anyone can use commonly available digital tools to create false information. The power of digital media tools now allows anyone with a bit of skill to manufacture any news, image, or video, and distribute it through a fake social media account. While anyone can fabricate a deception on the internet, it becomes problematic when the lie is state sponsored. What is even more disturbing is that after being exposed, state actors deny the accusations with plausible deniability. As a result, those bad actors hiding in the shadow areas of the dark web are actively shaping the information that vulnerable consumers digest, and advancing a narrative that aligns to their ulterior political motives.

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