"It's definitely been a paradigm shift in where you might find life," says Cassini project scientist Linda Spilker. Icy geysers fueled by Enceladus's ocean shoot out from cracks in the moon's surface, allowing the Cassini spacecraft to sample them directly during flybys. But that doesn't mean some exotic form of life couldn't be swimming through Titan's methane lakes. With its own watery geysers, Jupiter's moon Europa is another exciting ocean world outside the Goldilocks zone, and is the subject of a coming NASA mission, called Europa Clipper, planned to launch in the 2020s.
Holly Yanco, computer science professor at the University of Massachusetts, Lowell, suggests early measures could be as simple as equipping robots with universal icons. Dr. Shah heads MIT's Interactive Robotics Group, a lab focused on giving robots mental and sensory flexibility to complement their physical prowess. Her team also harnesses machine learning and biophysical modeling to help robots read human body language, and predict where a teammate will move next. A collaboration between CSAIL and Dr. Guenther's lab succeeded in designing a system that let a Baxter robot sort paint cans and wire spools into two buckets by "listening" for error potentials, randomly guessing at first and then self-correcting if it noticed the user thinking it made a mistake.
After all, compared to mammals, birds have small brains relative to their bodies, and bird brains lack a neocortex, which in mammals is thought to be the seat of higher-order thinking such as reasoning, problem-solving, language, and delaying gratification. In one version of the experiment, Osvath and Mr. Kabadayi trained ravens to use a tool to open a box containing a piece of dog kibble, a popular treat among ravens. When presented with the box containing the kibble fifteen minutes later, the ravens passed on the smaller reward 86 percent of the time, ignoring the distractors, and picking the correct tool to open the box. The last common ancestor of humans and birds lived some 320 million years ago, suggesting that these advanced cognitive traits emerged independently in hominids and corvids, using very different brains.
"This is a collaborative endeavor that anyone could get involved in," says Chris Lintott, an Oxford University astrophysicist and cofounder of Zooniverse, a platform that hosts dozens of citizen science projects. As long as pattern recognition is involved, there are no limits to what can become a citizen science project, Dr. Lintott says. For centuries before science became professionalized, regular people looked for patterns in the world around them. As a professional scientist himself, Lintott says, "people think that we're intelligent, but science is easy and we need your help."
A new study reveals the mathematics underlying this phenomenon, modeling how information overload can erode an individual's ability to distinguish high-quality information from its opposite, causing falsehoods to propagate. "It was the first paper I've seen in this area that quantifies what many people thought was happening, and that's basically with limited attention we're unable to see the full range of potential arguments or sides of the story," says Dr. Uzzi, who has studied how social media users isolate themselves into echo chambers. The researchers suggest that social networks could curb information overload by aggressively limiting content shared by so-called bot accounts, software agents that flood social networks with low-quality information. The research reveals some of the math that drives what psychologists have long known: Information overload makes it harder to make decisions.
It pushes people who find themselves isolated back into the social fold. And those who scored higher on self-centeredness one year would report greater feelings of loneliness the following year. "People sort of step back, falling in with an old American tradition of kind of admiring self-sufficiency too much," she says. Previous analysis by Cacioppo and his colleagues suggests that targeting social cognition – that is, re-training the way lonely people think about others – can be more effective at combating loneliness than targeting shyness, building social skills, or increasing opportunities for social contact.
Such optimism often leads to underestimating the chance of unknown unknowns derailing your project, so planning experts suggest a technique called reference class forecasting, where project planners learn from past risk by predicting overruns based on how similarly complex projects fared before. Virgin Galactic doesn't release public estimates, but according to the US Government Accountability Office's annual review, NASA's large project costs have overrun budget by between 10 percent and 50 percent in each of the last nine years, a figure dominated by the ballooning costs of the JWST. Not one to back down from a challenge, NASA in 2013 and 2014 developed the Technology Cost and Schedule Estimating (TCASE) software, which uses reference class forecasting tenets to predict the most uncertain of undertakings: creating new technology. But to make matters worse, even if reference class forecasting could roughly estimate the chance of unknown unknowns cropping up, it's hard to get advance funding for what-if scenarios.
From Apis Cor's 3-D printed house to the MIT Media Lab's new multipurpose robotic arm, startups and research teams alike aim to spark a digital revolution in an analog industry that has thus far proved resistant to disruption. MIT hopes its Digital Construction Platform (DCP), which it presented in the journal Science Robotics in April, will lay the foundation for future buildings. As such, the construction industry has proven understandably reluctant to innovate, explains Dr. Keating in a phone interview. In February, recent startup Apis Cor's robotic arm built up layers of quick-drying concrete into the walls of what it calls the first on-site 3-D printed home.
When the odds posted by the track are different from the odds determined using insider information, Kelly's formula explains how to take those differences and place the best bets possible, mathematically speaking. There may be simple patterns that organize seemingly chaotic events, but complicated limits to prediction in rather simple systems. And while predicting what an individual might do is sometimes next to impossible, as we've seen throughout this series in The Christian Science Monitor, complex social systems can exhibit highly predictable behavior at large scales. Finding predictable patterns that emerge from the complicated interactions of many individual parts is the norm when studying complex systems.
As the role of artificial intelligence in society grows, computer scientists and policymakers are moving from constructing these systems to harnessing their power for the good of society. "Yes, I think much improved global governance may be necessary to deal with not only advanced AI, but also some of the other big challenges that lie ahead for our species," writes Nick Bostrom, a professor at the University of Oxford who is the founding director of the university's Future of Humanity Institute, in an email to The Christian Science Monitor. "There are two main economic risks: first, that a mismatch may develop between the skills that workers have and the skills that the future workplace demands; and second, that AI may increase economic inequality by increasing the return to owners of capital and some higher-skill workers," Edward Felten, a professor of computer science and public affairs at Princeton University who is the founding director of the university's Center for Information Technology Policy, tells the Monitor in an email. There is a small but growing field of research addressing these problems, these commentators explain – and world government or international harmonization of AI laws may be one approach.