The Covid-19 pandemic was the perfect moment for AI to, literally, save the world. There was an unprecedented convergence of the need for fast, evidence-based decisions and large-scale problem solving with datasets spilling out of every country in the world. For health care systems facing a brand new, rapidly spreading disease, AI was — in theory — the ideal tool. AI could be deployed to make predictions, enhance efficiencies, and free up staff through automation; it could help rapidly process vast amounts of information and make lifesaving decisions.
Or, that was the idea at least. But what actually happened is that AI mostly failed.
There were scattered successes, no doubt. Adoption of automation picked up in retail warehouses and airports; chatbots took over customer service as workers were in lockdown; AI-aided decisions helped narrow down site selections for vaccine trials or helped speed up border crossings in Greece.
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