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The 4 Top Artificial Intelligence Trends For 2021

Bernard MarrContributorEnterprise Tech

Source: https://www.forbes.com/sites/bernardmarr/2020/09/21/the-4-top-artificial-intelligence-trends-for-2021/#79521c041c2a

Before the global pandemic struck in 2020 and the world was turned on its head, artificial intelligence (AI), and specifically the branch of AI known as machine learning (ML), were already causing widespread disruption in almost every industry.

The 4 Top Artificial Intelligence Trends For 2021
The 4 Top Artificial Intelligence Trends For 2021 ADOBE STOCK

The Covid-19 pandemic has impacted many aspects of how we do business, but it hasn’t diminished the impact AI is having on our lives. In fact, it’s become apparent that self-teaching algorithms and smart machines will play a big part in the ongoing fight against this outbreak as well as others we may face in the future.

AI undoubtedly remains a key trend when it comes to picking the technologies that will change how we live, work, and play in the near future. So, here’s an overview of what we can expect during what will be a year of rebuilding our lives as well as rethinking business strategies and priorities.https://cdn.embedly.com/widgets/media.html?src=https%3A%2F%2Fwww.youtube.com%2Fembed%2FO0hUGWr2q6s%3Ffeature%3Doembed&display_name=YouTube&url=https%3A%2F%2Fwww.youtube.com%2Fwatch%3Fv%3DO0hUGWr2q6s&image=https%3A%2F%2Fi.ytimg.com%2Fvi%2FO0hUGWr2q6s%2Fhqdefault.jpg&key=cfc0fb0733504c77aa4a6ac07caaffc7&type=text%2Fhtml&schema=youtubeRecommended For You

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During this ongoing pandemic, we’ve seen first-hand the urgent need to quickly analyze and interpret data on the spread of viruses around the world. Governments, global health bodies, academic research centers, and industry have come together to develop new ways that information can be collected, aggregated, and worked with. We’ve become used to seeing the results of this on the news every night, when the latest infection or death rates are given for our own regions.

Technological advancement is the main reason that this pandemic hasn’t (yet) killed as many as, for example, the 1918 Spanish Flu outbreak that claimed up to 50 million lives. From advancement in medical technology and standards of care, to advances in communication technology that enabled outbreaks to be spotted more quickly and lockdowns imposed. Over the next year, AI will be added to the list of technological developments that are enabling us to more effectively deal with pandemics.

The growth in the amount of scientific and medical literature alone is enormous, with more than 28,000 papers published by April this year relating to Covid-19. A dedicated search engine powered by natural language processing (NLP) algorithms has already been made available, so anyone can get AI assistance when investigating this massive dataset.

Work is also ongoing to develop AI solutions to help deal with the huge backlog of other medical issues, such as cancer, where treatment has been affected as resources are diverted to fight Covid-19. Over the next year, we are likely to see the accelerated adoption of AI across many other areas of healthcare, not only related to tackling viruses.

 By developing our ability to apply machine learning problem-solving to these massive, real-time global datasets, we will spot outbreaks more easily, track contact between infected people, enable more accurate diagnoses, and, by predicting ways that a virus might evolve in the future, develop more effective and lasting vaccinations.

Automated Detection and Prevention

We have already seen the use of drones in several jurisdictions, including the US, to at least test the possibility that they can be used to monitor whether social distancing guidelines are being followed. More advanced applications are on the horizon – such as drones with the capability of detecting COVID symptoms such as high temperature in individuals within a crowd. These systems use computer vision technology to analyze data captured by cameras on the drones and inform authorities or local administrators of statistics and probabilities around the spread of the virus. 

Another related growth area will be the use of facial recognition technology, also powered by computer vision algorithms. Somewhat more controversial as it focuses on the identification of individuals, rather than patterns among groups of people, facial recognition has been used by police to detect lockdown and quarantine-avoiders, as well as to track the movements of individuals displaying symptoms within a crowd.

The evidence seems to suggest that the public has become more tolerant of surveillance tactics that would previously have been considered overly draconian, due to the health risks posed by the virus. This tolerance is likely to be further tested over the coming 18 months as technologists become more adept at AI-driven surveillance and even enforcement.

Business on the rebound – predicting behavioral transformation

The way we live, work, and socialize has been hugely impacted by the spread of Covid-19. While there has been a steady, strong trend towards digital in many aspects of society, this year, we’ve witnessed a stampede. Amazon’s sales during the second quarter of 2020 were up 40% on the same period last year, as even those who have so far shunned online retail were forced to re-assess their options.

AI tools and platforms are already in place to help businesses understand the way their customers are adapting to a new reality. Organizations that were previously lagging in their uptake of digital channels for commerce and relationship nurturing have come to understand the urgency of the situation and are quickly getting to grips with concepts such as behavioral analytics and personalization. Tools providing organizations with self-service access to this technology will become increasingly prevalent throughout 2021, as small and medium-sized enterprises are seeking to establish their competitive edge.

Shutting down the next pandemic before it even starts

Most AI algorithms are geared towards prediction, and the holy grail of AI-assisted epidemiology will be to build systems that can accurately predict when and where future outbreaks will take place. This research has been ongoing for some time, and in fact, some of the earliest alerts about the current outbreak were generated by AI. Toronto-based BlueDot’s tool was already scanning 100,000 governmental and media data sources daily when it issued an alert about a potential outbreak in Wuhan, China, on December 31, 2019.

We can expect AI research to yield further breakthroughs over the coming 18 months that will increase our ability to spot and react to the danger of viral outbreaks. For this to happen, though, it will also require ongoing global cooperation between governments and private industry. How this plays out will most likely be affected by global politics and legislators, as well as the course of technological development. For this reason, issues such as access to medical datasets and barriers to the international exchange of information will also be hot topics over the coming year.

Source: https://www.forbes.com/sites/bernardmarr/2020/09/21/the-4-top-artificial-intelligence-trends-for-2021/#79521c041c2a

How do pandemics usually end?

How do pandemics usually end? And how will this one finish?

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A group of nurses wear face masks during the 1919 Spanish Flu outbreak.
Masks were a common sight during the 1918 influenza pandemic, and again now, just over a century later.(State Library Of Queensland)
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Just over 100 years ago, a new strain of influenza infected a third of the world’s population — but within just three years, the threat of this deadly flu had all but passed.

This was a time before modern medical care and even before humans understood what viruses were. So what’s changed since then?

It’s a question plenty of you have asked in recent months: how do pandemics end? And how will the one we’re currently living through end?

Three ingredients for a pandemic

An infectious agent needs three conditions to cause a pandemic, says virologist Kirsty Short from the University of Queensland:

  1. 1.It needs to cause disease in humans
  2. 2.It needs to be highly transmissible
  3. 3.We need to have no pre-existing immunity to it

“For example, we live with MERS today,” says Dr Short, referring to Middle Eastern respiratory syndrome, a coronavirus that is related to the one that causes COVID-19.

“It hasn’t caused a pandemic yet because it’s not highly transmissible from person to person.

“In contrast, the seasonal coronaviruses that we get, probably at one point were a pandemic, and they’ve just become these seasonal colds that we don’t really care about because we’ve evolved immunity to them.”

In terms of the three ingredients that make a pandemic, when it comes to COVID-19 there’s not much we can do to stop the coronavirus from infecting us, because that’s based on the biology of the virus and us as humans.

With physical distancing and masks, we are somewhat able to pull that second lever of not allowing the virus to transmit as much.

But the big thing that stops a virus becoming a pandemic — that is, a large-scale outbreak affecting multiple countries or continents — is the third factor: immunity.

“Herd immunity can be achieved through natural infection or vaccination,” Dr Short says.