If you’re of a certain generation, you might remember the Tamagotchi; the Japanese pocket-sized “pet simulation game” that became the chief obsession of 90s kids bored of yo-yos and other fleeting trends. The Tamagotchi lived mostly in the grubby hands or lint-filled pockets of its owners but, for social currency, could be paraded before envious or competitive enthusiasts.
Oddly, these oviparous virtual critters weren’t remotely animallike in their appearance, and could be intolerably demanding at times. Neglect to feed them, clean up after them, or tend to them when sick and — as many of us found out — very soon you’d be left with nothing but a dead LCD blob. But even the best cared-for Tamagotchi(s?) had certain obsolescence looming in their futures, once their needlessly complex lifecycle was complete: egg, baby, child, teen, adult, death.
In other words, you don’t have to move. You can just *think* your movements.
You’d be forgiven for wondering if we’ve evolved too far..
A jazzy, high production video features grinning young San Francisco-type execs describing this new, immersive experience. They’ve invented it, and they’ll be damned if they aren’t going to foist it upon us. “The wrist is a great starting point for us technologically,” one chirps, “because it opens up new and dynamic forms of control.” Quite.
Radiologists assessing the pain experienced by osteoarthritis patients typically use a scale called the Kellgren-Lawrence Grade (KLG). The KLG calculates pain levels based on the presence of certain radiographic features, like missing cartilage or damage. But data from the National Institute of Health revealed a disparity between the level of pain as calculated by the KLG and Black patients’ self-reported experience of pain.
The MIT Technology Review explains: “Black patients who show the same amount of missing cartilage as white patients self-report higher levels of pain.”
Midway through a podcast, a high-energy commercial chirps out all the advantages of using a particular learning system for languages. They are familiar: Babbel can get you conversing in just three weeks, it teaches you phrases you’ll actually use in the real world, lessons are designed to help you remember.
Of course, you’ve heard this story many, many times before. An older woman looking for love and companionship meets a predator posing as a lonely heart, only to be duped out of thousands of dollars. Sometimes these cases can be frustrating, and leave us asking how the victim missed all of the glaring red flags.
In February last year, the world baulked as the media reported that a South Korean broadcaster had used virtual reality technology to “reunite” a grieving mother with the 7-year old child she lost in 2016.
As part of a documentary entitled I Met You, Jang Ji-sung was confronted by an animated and lifelike vision of her daughter Na-yeon as she played in a neighborhood park in her favorite dress. It was an emotionally charged scene, with the avatar asking the tearful woman, “Mom, where have you been? Have you been thinking of me?”.
“Always”, the mother replied.
Remarkably, documentary makers saw this scene as “heartwarming”, but many felt that something was badly wrong. Ethicists, like Dr. Blaby Whitby from the University of Sussex, cautioned the media: “We just don’t know the psychological effects of being “reunited” with someone in this way.”
It is our human inclination to want to look good. Our desire to impress keeps the fashion industry alive, it also motivates many of us to work or study hard, and there are billions of dollars to be made from our desperation to look visibly fit and healthy. So, it should come as no surprise that as algorithms hold more and more sway over decision-making and the conferral of status (e.g. via credit or hiring decisions), many of us are keen to put our best foot forward and play into their discernible preferences.
On November 3, two oppositional forces went head to head and the results were…divisive. With commentators and pundits still reeling from the poor performance of US election pollsters, it seems fitting to ask — can AI (ultimately) solve a problem like election prediction?
At least this time around, the answer seems to be no, not really. But not necessarily for the reasons you might think.
“The degree to which this diversity criminal acts may be enhanced by use of AI depends significantly on how embedded they are in a computational environment: robotics is rapidly advancing, but AI is better suited to participate in a bank fraud than a pub brawl. This preference for the digital rather than the physical world is a weak defence though as contemporary society is profoundly dependent on complex computational networks.”
AI-enabled future crime report
The field of AI ethics has received much (very worthy) attention of late. Once an obscure topic relegated to the sidelines of both tech and ethics conversations, the subject is now at the heart of a lively dialogue among the media, politicians, and even the general public. Everyone now has a perspective on how new technologies can harm human lives, and this can only have a preventative effect in the longterm.
But whether it’s algorithmic bias, intrusive surveillance technology, or social engineering by coercive online platforms, the current discourse tends to center on the overzealous, questionable or destructive use of new tech, rather than outright criminality. Yet it would be foolish to discount the very real prospect of AI being systematically weaponized for unequivocally criminal purposes.
As AI technology refines and multiplies, so do the methods of would-be attackers and fraudsters. And as our world becomes more networked, the attack surface grows and grows.
In short, it is a very exciting time to be a technically-minded crook.
In 2000, a group of researchers at Georgia Tech launched a project they called “The Aware Home.” The collective of computer scientists and engineers built a three-story experimental home with the intent of producing an environment that was “capable of knowing information about itself and the whereabouts and activities of its inhabitants.” The team installed a vast network of “context aware sensors” throughout the house and on wearable computers worn by the home’s occupants. The hope was to establish an entirely new domain of knowledge — one that would create efficiencies in home management, improve health and well-being, and provide support for groups like the elderly.