AI Weekly: What can AI tell us about social unrest, virus structures, and carbon emissions? – VentureBeat

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Applying data science to predict unrest. AI that can anticipate the next variant of COVID-19s structure. Reducing carbon emissions from planes using algorithms. Thats a few of the headlines in AI this week, which ran the gamut from the dour (how AI might prevent the next attack on the U.S. Capitol) to the uplifting (making air travel greener). Its caveated optimism, but nonetheless a breath of fresh air in a community thats becoming increasingly cynical about the technologys potential to do good.

Wired first reported that a researcher at the University of North Carolina ran simulations using AI systems, including Alphabet-owned DeepMinds AlphaFold and the University of Washingtons RoseTTAFold, to predict the protein structure of the Omicron variant of COVID-19. Ford managed to predict one structure that was pretty much right an impressive feat, given that he arrived at his conclusions before scientists were able to map Omicrons structure properly.

AI promises to expedite certain processes in drug discovery and virology, for example identifying compounds to treat conditions for which medications remain elusive. But as Sriram Subramaniam, a professor at the University of British Columbia who studied Omicron samples, told The Register, having access to a real sample still beats algorithmic models. AI still cant predict things like the strength of new virus variants binding to host cells, for instance, or the infectiousness of those variants.

Could AI perhaps predict events like the January 6 attack on the U.S. Capitol? A piece in The Washington Post this week investigates the premise. While the consensus is mixed, some researchers believe that algorithms can serve as early indicators of violence in regions ahead of major political conflicts.

Unrest prediction, also known as conflict prediction, is a burgeoning field in academia and industry. It and its practitioners, such as the University of Central Floridas CoupCast, aim to design systems that consider variables (e.g., the role of a leader encouraging a mob, long-term democratic history) to determine whether, for example, electoral violence might occur.

Those who are bullish about the technology say that its already revealed surprising insights, like the fact that social media conflict is an unreliable indicator of real-world unrest. But others caution that its little better than chance in terms of accuracy and that it could be used to justify crackdowns on peaceful protests.

Actors react, Roudabeh Kishi, director of innovation at the nonprofit Armed Conflict Location & Event Data Project, a group engaged in conflict prediction research, told The Post. If people are shifting their tactics, a model trained on historical data will miss it.

The global aviation industry produces around 2% of all human-generated carbon dioxide emissions. If they were a country, all the airlines in the industry some of which run thousands of nearly-empty flights to keep valuable airport slots would rank among the top ten in the world.

Like other greenhouse gases, carbon dioxide drives climate change, leading to extreme weather, larger wildfires, disease from smog and air pollution, food supply disruptions, and other effects. In an effort to combat this, some airlines, including Air France, Norwegian, Malaysia Airlines, Cebu Pacific, Go Air, and Atlas Air, are turning to algorithms trained on data from billions of flights to identify emissions-reducing opportunities. Openairlines SkyBreathe the system recently adopted by Air France can reportedly reduce total fuel consumption by up to 5%.

Other startups, like Flyways, are creating AI-powered platforms that attempt to optimize aircraft routing, giving suggestions on how and where to fly planes. During a six-month pilot program at Alaska Airlines, Flyways claims to have shaved off five minutes from flights and saved 480-thousand gallons of jet fuel on average.

Some critics argue that airlines arent going far enough; they call for a phase-out of short-haul flights in Europe, among other footprint-reducing measures. But considering the long road ahead to meaningfully cutting the worlds carbon output, every bit helps.

If you went a teeny bit slower, you were on time, you had a gate, and because you went a teeny bit slower the airplane actually burned less fuel, that might be a win/win combination for both the guest and the operation and sustainability impact, Diana Birkett Rakow, senior VP of sustainability at Alaska Airlines, told ABC News.

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Kyle Wiggers

AI Staff Writer

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AI Weekly: What can AI tell us about social unrest, virus structures, and carbon emissions? - VentureBeat