Coronavirus Covid-19: A brief look at who is detected in the Apple and Google Mobility Reports

Introduction

As many people know, Google and Apple have published mobility data to help with beating the Covid-19 pandemic.

Google Covid-19 Mobility data is obviously Android users and Apple Coronavirus/Covid-19  mobility data  IOS  users. So  the data is in that sense determined by the type of personality that uses each OS and how they care about privacy.
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Coronavirus Covid-19: Brexit vote determines adherence to lock-down

Introduction

This article will try to answer the question if a regions Brexit vote determines adherence to lock-down. In very simple terms this means if a region has voted for Brexit with a higher percentage does  show more mobility.

Many scientific studies have looked at Brexit.  Reasons listed are:
Sovereignty
Immigration
Age of voters
Education level
Order vs openness
The “left behind”
Britons felt less integrated into the EU
Identity and Change
English national identity
Anti-establishment populism

Since all this research classifies the “classic Brexit voter” as an old, low educated, xenophobic, anti-establishment, English nationalist populist, it would be interesting if these people show a different behaviour to younger, higher educated, inclusive, establishment friendly non English nationalist reasonable voters. Please see the ecological fallacy and Robinson’s paradox.
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Coronavirus Covid-19: Springer releases books of essential textbooks from all disciplines

Introduction

Springer Nature has released 407  free books to help everybody with the knowledge around Coronavirus and Covid-19. This includes many disciplines and 65 books on data science.
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Coronavirus Covid-19: Mobility and Cases, why shopping is more dangerous than going to work.

Introduction to Mobility and Covid-19

This article sets out to analyse Mobility and Covid-19 case numbers, or in more detail, the effect of changes in mobility between different sub-regions of the UK on these  sub-regions’ Covid-19 case loads.

The Coronavirus pandemic has led to many countries introducing lock-downs and restrictions on movements of citizens to reduce interactions between people, so that the SARS-COV-2 virus can not spread. In the United Kingdom this lock-down started on March 23, 2020. This led to a decline in mobility in many regions. Measuring movements on a large scale like this is impossible for single individuals or small companies.
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Coronavirus Covid-19: The fallacy of some simple arguments as to why countries differ

There is a lot of discussion about mortality rates, population factors, population density and health systems around in this coronavirus, Covid-19 pandemic. Doubtlessly some are contributing factors but are they on they exclusively so? Their is a certain fallacy of some simple arguments why countries differ in this pandemic. That they differ is obviously not under question but why they differ is a very complex matter, on which doubtlessly many billions will be spent over the coming decades going to the best connected academics in each country.

Please see this paper for detailed analysis on mobility and influenza.

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Coronavirus Covid-19: What can Benford’s Law tell us about the truthfulness of the reported numbers

Introduction

This article will discuss if there are any rational arguments to distrust any numbers given during the corona virus crisis by individual countries based on Benford’s law.

China is often accused that it forges or manipulates it’s data. That there are possible millions of undetected cases. There are even scientific papers about this (1). But no one seems to look at how other countries fare by this standard. Hence we will have a look at how China’s reporting fares if compared with 6 European countries and the USA via the Newcomb–Benford law.

One can use two data sets to analyse this data, the cumulative data set and the daily reports, not cumulative. The inherent problem with Benford’s law in an ongoing pandemic is WHEN do you take the analysis. The results of the Benford’s analysis can change daily. 

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Coronavirus Covid-19: What will our AI dominated societies look like after the pandemic?

So what will our societies look like after the coronavirus/COVID-19 pandemic when artificial intelligence (AI) is everywhere?

Deleted ethical subroutines
“They deleted my ethical  subroutines”: Star Trek Voyager Series 5 Episode 25 © ® ViacomCBS

Expect more #techlash when more and of the non tech oriented population understands their life is ruled and ruined by algorithms largely based on profiteering.  Additionally enhancing people’s often faulty preferences with recommender systems or looking for conflict and “engaging” subjects like FB will further polarise societies.

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Brexit is stupid. Avoid no deal Brexit!

Brexit is stupid. Avoid no deal Brexit! is AI generated text that shows how screwed up the Brexit debate is. The AI generates the text by putting sentences together it found in the text that it parameters or features were trained on. I used OpenGPT on a local Jupyter notebook to generate the below text. One could of course also use the Google Colab mentioned in  the Medium article to generate text. Overall it seems if the world does not agree on a topic, AI generated text will be diffuse as well and can not hold an argument.

The results of OpenGPT-2 vs GPT are shown in the next image.

Results of opengpt-2 vs GPT-2
Results of opengpt-2 vs GPT-2


This also shows how Brexit will be a disaster as it split the UK in religious factions that threaten world stability and world trade.

Start AI generated text

Brexit is stupid. Avoid no deal Brexit!.

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Data Stuff