Will AI Rule The World?

Employing machine learning and computer vision for detection and classification of various “safety events,” the shoebox-sized device doesn’t see all, but it sees plenty.

Like which way the driver is looking as he operates the vehicle, how fast he’s driving, where he’s driving, locations of the people around him and how other forklift operators are maneuvering their vehicles. IFM’s software automatically detects safety violations (for example, cell phone use) and notifies warehouse managers so they can take immediate action. The main goals are to prevent accidents and increase efficiency. The mere knowledge that one of IFM’s devices is watching, Gyongyosi claims, has had “a huge effect.” “If you think about a camera, it really is the richest sensor available to us today at a very interesting price point,” he says. “Because of smartphones, camera and image sensors have become incredibly inexpensive, yet we capture a lot of information. From an image, we might be able to infer 25 signals today, but six months from now we’ll be able to infer 100 or 150 signals from that same image. The only difference is the software that’s looking at the image. And that’s why this is so compelling, because we can offer a very important core feature set today, but then over time all our systems are learning from each other. Every customer is able to benefit from every other customer that we bring on board because our systems start to see and learn more processes and detect more things that are important and relevant.”

Some sectors are at the start of their AI journey, others are veteran travelers. Both have a long way to go. Regardless, the impact artificial intelligence is having on our present day lives is hard to ignore:

• Transportation: Although it could take a decade or more to perfect them, autonomous cars will one day ferry us from place to place.
• Manufacturing: AI powered robots work alongside humans to perform a limited range of tasks like assembly and stacking, and predictive analysis sensors keep equipment running smoothly.
• Healthcare: In the comparatively AI-nascent field of healthcare, diseases are more quickly and accurately diagnosed, drug discovery is sped up and streamlined, virtual nursing assistants monitor patients and big data analysis helps to create a more personalized patient experience.
• Education: Textbooks are digitized with the help of AI, early-stage virtual tutors assist human instructors and facial analysis gauges the emotions of students to help determine who’s struggling or bored and better tailor the experience to their individual needs.
• Media: Journalism is harnessing AI, too, and will continue to benefit from it. Bloomberg uses Cyborg technology to help make quick sense of complex financial reports. The Associated Press employs the natural language abilities of Automated Insights to produce 3,700 earning reports stories per year — nearly four times more than in the recent past.
• Customer Service: Last but hardly least, Google is working on an AI assistant that can place human-like calls to make appointments at, say, your neighborhood hair salon. In addition to words, the system understands context and nuance.

But those advances (and numerous others, including this crop of new ones) are only the beginning; there’s much more to come — more than anyone, even the most prescient prognosticators, can fathom.

“I think anybody making assumptions about the capabilities of intelligent software capping out at some point are mistaken,” says David Vandegrift, CTO and co-founder of the customer relationship management firm 4Degrees.

With companies spending nearly $20 billion collective dollars on AI products and services annually, tech giants like Google, Apple, Microsoft and Amazon spending billions to create those products and services, universities making AI a more prominent part of their respective curricula (MIT alone is dropping $1 billion on a new college devoted solely to computing, with an AI focus), and the U.S. Department of Defense upping its AI game, big things are bound to happen. Some of those developments are well on their way to being fully realized; some are merely theoretical and might remain so. All are disruptive, for better and potentially worse, and there’s no downturn in sight.

AI’S NEAR-FUTURE RAMIFICATIONS

In Mendelson’s view, some of the most intriguing AI research and experimentation that will have near-future ramifications is happening in two areas: “reinforcement” learning, which deals in rewards and punishment rather than labeled data; and generative adversarial networks (GAN for short) that allow computer algorithms to create rather than merely assess by pitting two nets against each other. The former is exemplified by the Go-playing prowess of Google DeepMind’s Alpha Go Zero, the latter by original image or audio generation that’s based on learning about a certain subject like celebrities or a particular type of music.

On a far grander scale, AI is poised to have a major effect on sustainability, climate change and environmental issues. Ideally and partly through the use of sophisticated sensors, cities will become less congested, less polluted and generally more livable. Inroads are already being made.

“Once you predict something, you can prescribe certain policies and rules,” Nahrstedt says. Such as sensors on cars that send data about traffic conditions could predict potential problems and optimize the flow of cars. “This is not yet perfected by any means,” she says. “It’s just in its infancy. But years down the road, it will play a really big role.”

“If implemented responsibly, AI can benefit society. However, as is the case with most emerging technology, there is a real risk that commercial and state use has a detrimental impact on human rights.”