Tag Archives: humans
#439040 Ready for duty: Healthcare robots get ...
Not long after the 1918 Spanish flu pandemic, Czech writer Karel Čapek first introduced the term “robot” to describe artificial people in his 1921 sci-fi play R.U.R. While we have not yet created the highly intelligent humanoid robots imagined by Čapek, the robots most commonly used today are complex systems that work alongside humans, assisting with an ever-expanding set of tasks. Continue reading
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#439032 To Learn To Deal With Uncertainty, This ...
AI is endowing robots, autonomous vehicles and countless of other forms of tech with new abilities and levels of self-sufficiency. Yet these models faithfully “make decisions” based on whatever data is fed into them, which could have dangerous consequences. For instance, if an autonomous car is driving down a highway and the sensor picks up a confusing signal (e.g., a paint smudge that is incorrectly interpreted as a lane marking), this could cause the car to swerve into another lane unnecessarily.
But in the ever-evolving world of AI, researchers are developing new ways to address challenges like this. One group of researchers has devised a new algorithm that allows the AI model to account for uncertain data, which they describe in a study published February 15 in IEEE Transactions on Neural Networks and Learning Systems.
“While we would like robots to work seamlessly in the real world, the real world is full of uncertainty,” says Michael Everett, a post-doctoral associate at MIT who helped develop the new approach. “It's important for a system to be aware of what it knows and what it is unsure about, which has been a major challenge for modern AI.”
His team focused on a type of AI called reinforcement learning (RL), whereby the model tries to learn the “value” of taking each action in a given scenario through trial-and-error. They developed a secondary algorithm, called Certified Adversarial Robustness for deep RL (CARRL), that can be built on top of an existing RL model.
“Our key innovation is that rather than blindly trusting the measurements, as is done today [by AI models], our algorithm CARRL thinks through all possible measurements that could have been made, and makes a decision that considers the worst-case outcome,” explains Everett.
In their study, the researchers tested CARRL across several different tasks, including collision avoidance simulations and Atari pong. For younger readers who may not be familiar with it, Atari pong is a classic computer game whereby an electronic paddle is used to direct a ping pong on the screen. In the test scenario, CARRL helped move the paddle slightly higher or lower to compensate for the possibility that the ball could approach at a slightly different point than what the input data indicated. All the while, CARRL would try to ensure that the ball would make contact with at least some part of paddle.
Gif: MIT Aerospace Controls Laboratory
In a perfect world, the information that an AI model is fed would be accurate all the time and AI model will perform well (left). But in some cases, the AI may be given inaccurate data, causing it to miss its targets (middle). The new algorithm CARRL helps AIs account for uncertainty in its data inputs, yielding a better performance when relying on poor data (right).
Across all test scenarios, the RL model was better at compensating for potential inaccurate or “noisy” data with CARRL, than without CARRL.
But the results also show that, like with humans, too much self-doubt and uncertainty can be unhelpful. In the collision avoidance scenario, for example, indulging in too much uncertainty caused the main moving object in the simulation to avoid both the obstacle and its goal. “There is definitely a limit to how ‘skeptical’ the algorithm can be without becoming overly conservative,” Everett says.
This research was funded by Ford Motor Company, but Everett notes that it could be applicable under many other commercial applications requiring safety-aware AI, including aerospace, healthcare, or manufacturing domains.
“This work is a step toward my vision of creating ‘certifiable learning machines’—systems that can discover how to explore and perform in the real world on their own, while still having safety and robustness guarantees,” says Everett. “We'd like to bring CARRL into robotic hardware while continuing to explore the theoretical challenges at the interface of robotics and AI.” Continue reading
Posted in Human Robots
#439030 How tiny machines become capable of ...
Living organisms, from bacteria to animals and humans, can perceive their environment and process, store and retrieve this information. They learn how to react to later situations using appropriate actions. A team of physicists at Leipzig University led by Professor Frank Cichos, in collaboration with colleagues at Charles University Prague, have developed a method for giving tiny artificial microswimmers a certain ability to learn using machine learning algorithms. They recently published a paper on this topic in the journal Science Robotics. Continue reading
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#439023 In ‘Klara and the Sun,’ We Glimpse ...
In a store in the center of an unnamed city, humanoid robots are displayed alongside housewares and magazines. They watch the fast-moving world outside the window, anxiously awaiting the arrival of customers who might buy them and take them home. Among them is Klara, a particularly astute robot who loves the sun and wants to learn as much as possible about humans and the world they live in.
So begins Kazuo Ishiguro’s new novel Klara and the Sun, published earlier this month. The book, told from Klara’s perspective, portrays an eerie future society in which intelligent machines and other advanced technologies have been integrated into daily life, but not everyone is happy about it.
Technological unemployment, the progress of artificial intelligence, inequality, the safety and ethics of gene editing, increasing loneliness and isolation—all of which we’re grappling with today—show up in Ishiguro’s world. It’s like he hit a fast-forward button, mirroring back to us how things might play out if we don’t approach these technologies with caution and foresight.
The wealthy genetically edit or “lift” their children to set them up for success, while the poor have to make do with the regular old brains and bodies bequeathed them by evolution. Lifted and unlifted kids generally don’t mix, and this is just one of many sinister delineations between a new breed of haves and have-nots.
There’s anger about robots’ steady infiltration into everyday life, and questions about how similar their rights should be to those of humans. “First they take the jobs. Then they take the seats at the theater?” one woman fumes.
References to “changes” and “substitutions” allude to an economy where automation has eliminated millions of jobs. While “post-employed” people squat in abandoned buildings and fringe communities arm themselves in preparation for conflict, those whose livelihoods haven’t been destroyed can afford to have live-in housekeepers and buy Artificial Friends (or AFs) for their lonely children.
“The old traditional model that we still live with now—where most of us can get some kind of paid work in exchange for our services or the goods we make—has broken down,” Ishiguro said in a podcast discussion of the novel. “We’re not talking just about the difference between rich and poor getting bigger. We’re talking about a gap appearing between people who participate in society in an obvious way and people who do not.”
He has a point; as much as techno-optimists claim that the economic changes brought by automation and AI will give us all more free time, let us work less, and devote time to our passion projects, how would that actually play out? What would millions of “post-employed” people receiving basic income actually do with their time and energy?
In the novel, we don’t get much of a glimpse of this side of the equation, but we do see how the wealthy live. After a long wait, just as the store manager seems ready to give up on selling her, Klara is chosen by a 14-year-old girl named Josie, the daughter of a woman who wears “high-rank clothes” and lives in a large, sunny home outside the city. Cheerful and kind, Josie suffers from an unspecified illness that periodically flares up and leaves her confined to her bed for days at a time.
Her life seems somewhat bleak, the need for an AF clear. In this future world, the children of the wealthy no longer go to school together, instead studying alone at home on their digital devices. “Interaction meetings” are set up for them to learn to socialize, their parents carefully eavesdropping from the next room and trying not to intervene when there’s conflict or hurt feelings.
Klara does her best to be a friend, aide, and confidante to Josie while continuing to learn about the world around her and decode the mysteries of human behavior. We surmise that she was programmed with a basic ability to understand emotions, which evolves along with her other types of intelligence. “I believe I have many feelings. The more I observe, the more feelings become available to me,” she explains to one character.
Ishiguro does an excellent job of representing Klara’s mind: a blend of pre-determined programming, observation, and continuous learning. Her narration has qualities both robotic and human; we can tell when something has been programmed in—she “Gives Privacy” to the humans around her when that’s appropriate, for example—and when she’s figured something out for herself.
But the author maintains some mystery around Klara’s inner emotional life. “Does she actually understand human emotions, or is she just observing human emotions and simulating them within herself?” he said. “I suppose the question comes back to, what are our emotions as human beings? What do they amount to?”
Klara is particularly attuned to human loneliness, since she essentially was made to help prevent it. It is, in her view, peoples’ biggest fear, and something they’ll go to great lengths to avoid, yet can never fully escape. “Perhaps all humans are lonely,” she says.
Warding off loneliness through technology isn’t a futuristic idea, it’s something we’ve been doing for a long time, with the technologies at hand growing more and more sophisticated. Products like AFs already exist. There’s XiaoIce, a chatbot that uses “sentiment analysis” to keep its 660 million users engaged, and Azuma Hikari, a character-based AI designed to “bring comfort” to users whose lives lack emotional connection with other humans.
The mere existence of these tools would be sinister if it wasn’t for their widespread adoption; when millions of people use AIs to fill a void in their lives, it raises deeper questions about our ability to connect with each other and whether technology is building it up or tearing it down.
This isn’t the only big question the novel tackles. An overarching theme is one we’ve been increasingly contemplating as computers start to acquire more complex capabilities, like the beginnings of creativity or emotional awareness: What is it that truly makes us human?
“Do you believe in the human heart?” one character asks. “I don’t mean simply the organ, obviously. I’m speaking in the poetic sense. The human heart. Do you think there is such a thing? Something that makes each of us special and individual?”
The alternative, at least in the story, is that people don’t have a unique essence, but rather we’re all a blend of traits and personalities that can be reduced to strings of code. Our understanding of the brain is still elementary, but at some level, doesn’t all human experience boil down to the firing of billions of neurons between our ears? Will we one day—in a future beyond that painted by Ishiguro, but certainly foreshadowed by it—be able to “decode” our humanity to the point that there’s nothing mysterious left about it? “A human heart is bound to be complex,” Klara says. “But it must be limited.”
Whether or not you agree, Klara and the Sun is worth the read. It’s both a marvelous, engaging story about what it means to love and be human, and a prescient warning to approach technological change with caution and nuance. We’re already living in a world where AI keeps us company, influences our behavior, and is wreaking various forms of havoc. Ishiguro’s novel is a snapshot of one of our possible futures, told through the eyes of a robot who keeps you rooting for her to the end.
Image Credit: Marion Wellmann from Pixabay Continue reading
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#438998 Foam Sword Fencing With a PR2 Is the ...
Most of what we cover in the Human Robot Interaction (HRI) space involves collaboration, because collaborative interactions tend to be productive, positive, and happy. Yay! But sometimes, collaboration is not what you want. Sometimes, you want competition.
Competition between humans and robots doesn’t have to be a bad thing, in the same way that competition between humans and humans doesn’t have to be a bad thing. There are all kinds of scenarios in which humans respond favorably to competition, and exercise is an obvious example.
Studies have shown that humans can perform significantly better when they’re exercising competitively as opposed to when they’re exercising individually. And while researchers have looked at whether robots can be effective exercise coaches (they can be), there hasn’t been a lot of exploration of physical robots actually competing directly with humans. Roboticists from the University of Washington decided to put adversarial exercise robots to the test, and they did it by giving a PR2 a giant foam sword. Awesome.
This exercise game matches a PR2 with a human in a zero-sum competitive fencing game with foam swords. Expecting the PR2 to actually be a competitive fencer isn’t realistic because, like, it’s a PR2. Instead, the objective of the game is for the human to keep their foam sword within a target area near the PR2 while also avoiding the PR2’s low-key sword-waving. A VR system allows the user to see the target area, while also giving the system a way to track the user’s location and pose.
Looks like fun, right? It’s also exercise, at least in the sense that the user’s heart rate nearly doubled over their resting heart rate during the highest scoring game. This is super preliminary research, though, and there’s still a lot of work to do. It’ll be important to figure out how skilled a competitive robot should be in order to keep providing a reasonable challenge to a human who gradually improves over time, while also being careful to avoid generating any negative reactions. For example, the robot should probably not beat you over the head with its foam sword, even if that’s a highly effective strategy for getting your heart rate up.
Competitive Physical Human-Robot Game Play, by Boling Yang, Xiangyu Xie, Golnaz Habibi, and Joshua R. Smith from the University of Washington and MIT, was presented as a late-breaking report at the ACM/IEEE International Conference on Human-Robot Interaction. Continue reading
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