Across the globe, AI and machine learning are being pressed into action to combat Covid-19. Supercomputers are engaged not just in a war to wipe out the virus, they’re also being used to mitigate its effects on many struggling sectors.
If and when the pandemic recedes or is beaten, the ‘new normal’ that is described by politicians, business leaders and senior officials the world over may be led by AI in ways we couldn’t even contemplate just a few short months ago.
Ultimately, that could be good news for AI practitioners who have been trying to convince skeptical populations that use of powerful data can be a force for good. And that will be a boon for brands.
Take a step back, and it’s easy to see why the public in particular is reticent about the nascent power of AI and machine learning. Following the Facebook / Cambridge Analytica scandal a couple of years ago, the UK Parliament’s House of Lords called for greater regulation over AI. The report’s authors want to see the creation of tools that can be used to identify algorithmic bias and make it easier for people to understand how AI systems reach their decisions.
This view was echoed more recently by the Government’s advisory body, the Centre for Data Ethics & Innovation, when it stated new legislation was needed to tighten up the use of algorithms that drive content on social media – including advertising, videos and posts – and hand back control to consumers.
The debate rages on, as does discussion around the use of personal data not just for marketing, but also more specific purposes that are important at present, like the information required for the UK Government’s embryonic “Test, track and trace” program as it bids to control Covid-19.
Yet the current crisis is also being hailed as an opportunity to right the previous wrongs of AI deployment and prove its benefits to entire industries and nations, not just individuals. For example, tracking and forecasting are the very core of data science. But this approach can also be applied to many other sectors in a bid to build preventative measures that help minimize the negative economic effects of Coronavirus.
Supercomputers are currently leading the race to find a vaccine, with large engines running complex calculations and determining model solutions. Their processing is many levels above normal computer or human processing.
There are myriad examples of AI and machine learning at work right and now. These are just a few[1]:
- machine learning-enabled chatbots are being used in several countries for a contactless screening of Covid-19 symptoms and to answer questions from the public
- agri-tech start-up Mantle Labs is offering AI-driven crop-monitoring to retailers free of charge to assess satellite images of crops, and flag potential issues to farmers and retailers early so they can better manage supply, procurement and inventory
- BlueDot, a Canadian start-up that uses AI to detect disease outbreaks, was among the first to raise the alarm about Coronavirus in Wuhan, China. The algorithm sifts through news reports in 65 languages, along with airline data and animal disease networks, to detect outbreaks. Results can be reviewed by epidemiologists to anticipate and manage risk
- CORD-19 Search, a new website powered by machine learning, helps researchers quickly and easily seek analysis papers. It is built on the Allen Institute for AI’s CORD-19 open research datasetof more than 128,000 research papers, and other materials and extracts, deciphering relevant medical information from unstructured text, accelerating disease response.
This all appears to be a solid foundation for the positive use of AI in the future.
In marketing, CMOs are aware of the importance of ethical data use for their profession. The issue was highlighted this month (June) in a report from the World Federation of Advertisers. In the organization’s survey of nearly 150 senior marketers, 74% said data ethics will be more important to their roles in the next five years.
Overall, there is a keen understanding that AI and machine learning will soon underpin marketing operations. Some 79% of senior European marketers believe the technology will be in place across their organization’s marketing stack in the near future.
Meanwhile, a staggering 82% would consider leaving an employer if they felt the approach to data was not ethical, while up to a quarter have already felt uneasy about data use at some point.
The guide, Data Ethics – The Rise of Morality in Technology, states: “Brands must be transparent and work towards more open and honest data practices, particularly as AI and machine learning approaches start to automate decisions.”
In a further development, the Advertising Standards Authority announced recently it is installing an in-house data team that will harness AI to monitor and regulate online ads.
It’s clear the multi-dimensional nature and true power of AI and data science are being thoroughly unleashed – for good or ill. From supercomputers working tirelessly to produce a vaccine to drones delivering medical supplies to those in need, or monitoring lockdown measures in major cities, the need for AI and data science is unprecedented.
AI has received a hostile reception in many countries, mostly because of its seemingly opaque decision making. However, post-pandemic, we could see a shift towards a more normalized use of AI in everyday life, proven by the monumental benefit it can have in times of need.
If, as hoped, AI and machine learning help health and research experts make vital breakthroughs against Coronavirus, reducing infection rates and even finding a vaccine, it could cement the positive side of AI’s use in the public’s consciousness. That will make a huge difference to its deployment in better times as well as crises.
And for marketers, that would also mean the use of AI to improve customer experience and sell products will no longer be a novelty – it will be commonplace.
[1] https://www.weforum.org/agenda/2020/05/how-ai-and-machine-learning-are-helping-to-fight-covid-19/