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Many people get frustrated with technology when it malfunctions or is counterintuitive. The last thing people might expect is for that same technology to pick up on their emotions and engage with them differently as a result.
All of that is now changing. Computers are increasingly able to figure out what we’re feeling—and it’s big business.
A recent report predicts that the global affective computing market will grow from $12.2 billion in 2016 to $53.98 billion by 2021. The report by research and consultancy firm MarketsandMarkets observed that enabling technologies have already been adopted in a wide range of industries and noted a rising demand for facial feature extraction software.
Affective computing is also referred to as emotion AI or artificial emotional intelligence. Although many people are still unfamiliar with the category, researchers in academia have already discovered a multitude of uses for it.
At the University of Tokyo, Professor Toshihiko Yamasaki decided to develop a machine learning system that evaluates the quality of TED Talk videos. Of course, a TED Talk is only considered to be good if it resonates with a human audience. On the surface, this would seem too qualitatively abstract for computer analysis. But Yamasaki wanted his system to watch videos of presentations and predict user impressions. Could a machine learning system accurately evaluate the emotional persuasiveness of a speaker?
Yamasaki and his colleagues came up with a method that analyzed correlations and “multimodal features including linguistic as well as acoustic features” in a dataset of 1,646 TED Talk videos. The experiment was successful. The method obtained “a statistically significant macro-average accuracy of 93.3 percent, outperforming several competitive baseline methods.”
A machine was able to predict whether or not a person would emotionally connect with other people. In their report, the authors noted that these findings could be used for recommendation purposes and also as feedback to the presenters, in order to improve the quality of their public presentation. However, the usefulness of affective computing goes far beyond the way people present content. It may also transform the way they learn it.
Researchers from North Carolina State University explored the connection between students’ affective states and their ability to learn. Their software was able to accurately predict the effectiveness of online tutoring sessions by analyzing the facial expressions of participating students. The software tracked fine-grained facial movements such as eyebrow raising, eyelid tightening, and mouth dimpling to determine engagement, frustration, and learning. The authors concluded that “analysis of facial expressions has great potential for educational data mining.”
This type of technology is increasingly being used within the private sector. Affectiva is a Boston-based company that makes emotion recognition software. When asked to comment on this emerging technology, Gabi Zijderveld, chief marketing officer at Affectiva, explained in an interview for this article, “Our software measures facial expressions of emotion. So basically all you need is our software running and then access to a camera so you can basically record a face and analyze it. We can do that in real time or we can do this by looking at a video and then analyzing data and sending it back to folks.”
The technology has particular relevance for the advertising industry.
Zijderveld said, “We have products that allow you to measure how consumers or viewers respond to digital content…you could have a number of people looking at an ad, you measure their emotional response so you aggregate the data and it gives you insight into how well your content is performing. And then you can adapt and adjust accordingly.”
Zijderveld explained that this is the first market where the company got traction. However, they have since packaged up their core technology in software development kits or SDKs. This allows other companies to integrate emotion detection into whatever they are building.
By licensing its technology to others, Affectiva is now rapidly expanding into a wide variety of markets, including gaming, education, robotics, and healthcare. The core technology is also used in human resources for the purposes of video recruitment. The software analyzes the emotional responses of interviewees, and that data is factored into hiring decisions.
Richard Yonck is founder and president of Intelligent Future Consulting and the author of a book about our relationship with technology. “One area I discuss in Heart of the Machine is the idea of an emotional economy that will arise as an ecosystem of emotionally aware businesses, systems, and services are developed. This will rapidly expand into a multi-billion-dollar industry, leading to an infrastructure that will be both emotionally responsive and potentially exploitive at personal, commercial, and political levels,” said Yonck, in an interview for this article.
According to Yonck, these emotionally-aware systems will “better anticipate needs, improve efficiency, and reduce stress and misunderstandings.”
Affectiva is uniquely positioned to profit from this “emotional economy.” The company has already created the world’s largest emotion database. “We’ve analyzed a little bit over 4.7 million faces in 75 countries,” said Zijderveld. “This is data first and foremost, it’s data gathered with consent. So everyone has opted in to have their faces analyzed.”
The vastness of that database is essential for deep learning approaches. The software would be inaccurate if the data was inadequate. According to Zijderveld, “If you don’t have massive amounts of data of people of all ages, genders, and ethnicities, then your algorithms are going to be pretty biased.”
This massive database has already revealed cultural insights into how people express emotion. Zijderveld explained, “Obviously everyone knows that women are more expressive than men. But our data confirms that, but not only that, it can also show that women smile longer. They tend to smile more often. There’s also regional differences.”
Yonck believes that affective computing will inspire unimaginable forms of innovation and that change will happen at a fast pace.
He explained, “As businesses, software, systems, and services develop, they’ll support and make possible all sorts of other emotionally aware technologies that couldn’t previously exist. This leads to a spiral of increasingly sophisticated products, just as happened in the early days of computing.”
Those who are curious about affective technology will soon be able to interact with it.
Hubble Connected unveiled the Hubble Hugo at multiple trade shows this year. Hugo is billed as “the world’s first smart camera,” with emotion AI video analytics powered by Affectiva. The product can identify individuals, figure out how they’re feeling, receive voice commands, video monitor your home, and act as a photographer and videographer of events. Media can then be transmitted to the cloud. The company’s website describes Hugo as “a fun pal to have in the house.”
Although he sees the potential for improved efficiencies and expanding markets, Richard Yonck cautions that AI technology is not without its pitfalls.
“It’s critical that we understand we are headed into very unknown territory as we develop these systems, creating problems unlike any we’ve faced before,” said Yonck. “We should put our focus on ensuring AI develops in a way that represents our human values and ideals.”
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May 17, 2016 — When Jacqueline Leonard proposed a program that would introduce gaming and robotics into public school classes to help improve mathematics learning, the University of Wyoming College of Education professor hoped it would be a tool for students to become interested in college careers.
Three years later, the project has shown positive results among the original eight Wyoming schools that were introduced to the Innovative Technology Experiences for Students and Teachers (ITEST) program. The National Science Foundation (NSF) supported the three-year, $1.2 million grant.
The “Visualization Basics: uGame-iCompute Project” was designed to help teachers engage fifth- through ninth-graders in gaming and robotics to promote interest in science, technology, engineering and mathematics (STEM) programs.
UW’s project has engaged elementary and middle school students in at least 24 Wyoming schools since the ITEST program was first introduced in 2013. Some school districts have participated in the program since year one of the three-year project, and nearly 900 students have participated during that time.
The eight original schools participating were Arapahoe Middle School, Laramie Junior High School, Powell Middle School, University Park Elementary School (Casper), UW Lab School, Wheatland Middle School, Worland Middle School and Wyoming Indian Middle School. Since then, seven and nine school districts, respectively, have joined the program in years two and three.
“Robotics and game design were used as a hook to enhance children’s interest in STEM and STEM careers. We also were interested in developing computational thinking skills and the processes that we know students need to be successful in computer science and engineering,” Leonard says. “Finally, we wanted children to understand how mathematics, technology and communication are critical to 21st century careers.”
Leonard, UW Science and Mathematics Teaching Center director, originally put together a multidisciplinary team from the UW colleges of Education, Engineering and Applied Science, and Arts and Sciences to research a question that has been part of her research agenda for several years: Can gaming and robotics be used to teach computational thinking skills to students in culturally sensitive ways?
“I am so thankful for this program. What a great way to get students prepared for possible careers in their future. Many of the jobs that students will have after they graduate haven’t even been created yet,” says Kait Quinton, who teaches seventh-grade math at Rock Springs Junior High School. “This program helps to enhance students’ critical thinking skills in a way that is fun and interactive. They learn so quickly. It is incredible, because I feel like I teach them the foundation of robotics and game design, and they just take it and run. By the end, they are the ones teaching me.”
During the multiphase project, team members first trained teachers to develop mathematical and scientific lessons that were culturally relevant to their students. Leonard and her supporters worked with the teachers to analyze the impact on students’ overall learning. The research team also worked with participants interested in becoming peer trainers to help extend the project’s reach after the grant period ended.
Program’s Positive Results
“The data reveal that using intact classrooms at the middle school level and elementary students during after-school programs reduced student attrition and ensured broader participation of girls and underrepresented minority students,” Leonard says.
Additionally, UW researchers have observed improved student development of computational thinking skills and problem-solving skills. Leonard says, early in the project, there was a learning curve that teachers and students had to overcome to learn the programming and software.
“Overall, students learned how to make their own games, which involved formulating problems, abstraction, use of algorithms, logical thinking, analyzing and debugging, and generalizing and transfer of knowledge,” Leonard says. “They also learned to use 21st century skills as they worked in teams to solve problems and created products for self-enjoyment and competition.”
Ty Ruby, who is a fourth- and fifth-grade special education instructor at North Evanston Elementary School, says the robotics and gaming program taught his students to work together on projects. He introduced the robotics class at Clark Elementary School.
“I believe this is a great program for students. I was so impressed with how the students worked together. Their conversations about how to solve issues or problems they were having were the best,” he says. “This provides a safe environment for students to talk about ideas with programming and working together. The students reacted really well to the program. They were excited to come to school and work with their robots.”
Robotics teams compete at local competitions, and gaming teams have taken field trips to the National Center for Atmospheric Research-Wyoming Supercomputing Center in Cheyenne. Teachers accepted into the program enrolled in continuing education courses, led after-school programs, and further developed instructional skills on how to incorporate cultural uniqueness into fun science and technology projects.
The NSF-sponsored grant has ended this semester, but Leonard says her research team has actually been granted a “no-cost extension,” meaning that the project will end during September 2017. Planning for the next phase of the program is underway, she adds.
“We intend to go to more school districts and work with both elementary and middle school students,” Leonard says. “It has been a pleasure working with teachers and students in Wyoming. The excitement and energy observed in the classrooms and after-school clubs were infectious. The students loved the program and learned a great deal.”
For more information about the program, visit the website at www.ugameicompute.com/ or contact Leonard at (307) 766-3776 or firstname.lastname@example.org.
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