Data and Delusion after COVID-19

​The rise of COVID-19 has seen an increase in overall news consumption. This has created a frenzy for “live figures” among members of the public, with each one of us rigorously checking the latest dashboards, graphs and visualisations. These are filled with updates on the COVID-19 numbers in our towns, municipalities, countries and the world.

These were some of the views during the third session of the University of Johannesburg’s (UJ) webinar series that reimagines the world after the pandemic. Held on Wednesday, 27 May 2020, the event was held under the theme Reimagining Data and Delusion after COVID, and in particular how humanity have been misunderstanding the data behind COVID-19 and why data literacy is the make or break skill of our time.

The panel of experts included Dr. Shakir Mohamed (Senior Researcher at DeepMind in London, UK); Professor Charis Harley (an academic in the Faculty of Engineering and the Built Environment at UJ) and Professor Olaf Dammann, (Vice-Chair of Public Health at Tufts University in Boston, US).

Dr Mohamed opened the discussion by focusing on the role of machine learning and artificial intelligence to global challenges. “When we think about advanced technologies in times like these, we must think of it as a coin. One side of the coin (is that) you have very scientific or an engineering field that is trying to address a particular way how data is used, how we build models and how we communicate predictions. On the other side of the coin you have components as networks, systems and stakeholders that are interacting and supporting that field of machine learning & artificial intelligence,” he said.

He added that understanding how data has been collected and how a variable is measured gives us understanding of what that data means. “We need to have ways of sharing data in a safe and systematic way and also look at how we integrate these kinds of predictions and decisions into decision making processes that are being done at political and governmental level. Machine learning has a role in helping us to collect data and can assist in decision making and creating systems that can help us address the four sight tools for thinking about the future.”

Professor Harley focused on models and assumption on data science, saying “When you have too little data, you tend to take whatever facts you have and try and twist them to match whatever you want to theorise.”

“It is well known that the quality of data surrounding Covid19 is not reliable. We know that data is being held by certain agencies and we are aware that there are time lags in the data used and at times there is little data which leads to generalisations that can be dangerous, explained Prof Harley. ”

Prof Dammann echoed the sentiments that all models are wrong, but that some are helpful, even though the helpfulness of the model is limited. “A decision making has to be local and it’s difficult when using global models as they don’t give us what we want.”

In conclusion, however exceptional our situation is now, one thing is clear: we live in a world, where data is not only omnipresent, but more fluid, dynamic and complex than ever before. In this world, it becomes essential for everyone to be able to identify the context of each data point we interpret. The current pandemic will pass, but we are doomed to live in a constant infodemic, surrounded by information manipulations, fake news and panic, if we do not get better at understanding the context of data. Protection of data privacy and the right of individuals to decide on the use of their own data should be high in everyone’s agenda.

Related: Global experts join UJ webinar series in Shaping the Post-COVID World

dr shakir mohamed
Dr Shakir Mohamed
prof olaf dammann
Prof Olaf Dammann
prof charis harley
rof Charis Harley
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