Photo by Patrick Assalé on Unsplash
In 2011, March Andreessen rightly pitched Why Software Is Eating The World. In 2018, I wrote a small note on Hardware Is Running The World. In 2020, algorithms play a crucial role in understanding and thereby catering to the needs of the world for many decades to come.
These smart systems and context-aware algorithms are capable of capturing market trends, which has been made possible due to the amount of data that is generated every day. All these smart systems are also capable of making decisions for others and are often termed as Artificially Intelligent.
During a COVID-19 like pandemic, AI systems could have made decisions in favor of the consumers, enterprise, and businesses. Smart systems catering to manufacturing, logistics, transport, eCommerce, and last-mile delivery would know very well that there is going to be a global demand for essential products based on the data world is sharing (as privacy is dead). That would mean more informed decisions were possible and could have driven the production and delivery of essential goods well in advance.
Example: During COVID-19, a smart algorithm powering manufacturing industry could have projected future outcomes and provided insights to companies to ramp up the production of essential products. Which in turn could have helped adapt logistics and supply chain industry as per the needs of the cities and countries around the globe. This would have also lead to eCommerce to have enough essential products irrespective of the demand, and would have also enabled warehouses and stores to limit how many essential products a consumer is allowed to purchase well before COVID-19 hit the curve. Similar data-driven outbreak predictions can be applied to any industry, not just those producing essential products.
However, instead, it seems there was no projection of crises to come, and thus leading to shortage of essential products.
It can be questioned that outbreak based algorithms are already in place but are accessible only when one pays for it. However, given how every technological discussion is incomplete today without talking about data, isn’t it expected to have such a solution embedded in the data tools for any industry as default feature? Isn’t prediction the key for making smarter decisions?
Focusing on the pandemic, there have been numerous attempts to make data available that could provide insight into coming epidemics:
- Last decade, now-defunct Google Flu Trends was launched based on Detecting Influenza Epidemics Using Search Engine Query Data to enable flu outbreak predictions.
- DHL already has a Resilience360 risk assessment process in place to help logistic companies act before an incident turns into a disruption.
- ATOS and Microsoft already had tools to control and containment of an epidemic outbreak.
- In 2018, Harvard University (Global Health Institute) came up with an extensive report on the Global Monitoring of Disease Outbreak Preparedness.
However, it seems with the COVID-19 crisis such data driven outbreak risk prediction solutions either failed OR were not utilized to full potential.
Post-COVID-19, the data tool war is only going to get more intensive with the major focus on Data-Enabled Outbreak Risk Management. The important question will be whether these AI-Enabled algorithms are capable of making smart human-oriented decisions during crises.
Kira Radinsky’s work on data based prediction is really interesting for anyone looking to read more technical details on prediction algorithms. She apparently wrote about importance of algorithms to predict the next outbreak in 2014.
