Tag Archives: feedback

#431592 Reactive Content Will Get to Know You ...

Posted on November 23, 2017 by Android

The best storytellers react to their audience. They look for smiles, signs of awe, or boredom; they simultaneously and skillfully read both the story and their sitters. Kevin Brooks, a seasoned storyteller working for Motorola’s Human Interface Labs, explains, “As the storyteller begins, they must tune in to… the audience’s energy. Based on this energy, the storyteller will adjust their timing, their posture, their characterizations, and sometimes even the events of the story. There is a dialog between audience and storyteller.”
Shortly after I read the script to Melita, the latest virtual reality experience from Madrid-based immersive storytelling company Future Lighthouse, CEO Nicolas Alcalá explained to me that the piece is an example of “reactive content,” a concept he’s been working on since his days at Singularity University.

For the first time in history, we have access to technology that can merge the reactive and affective elements of oral storytelling with the affordances of digital media, weaving stunning visuals, rich soundtracks, and complex meta-narratives in a story arena that has the capability to know you more intimately than any conventional storyteller could.
It’s no understatement to say that the storytelling potential here is phenomenal.
In short, we can refer to content as reactive if it reads and reacts to users based on their body rhythms, emotions, preferences, and data points. Artificial intelligence is used to analyze users’ behavior or preferences to sculpt unique storylines and narratives, essentially allowing for a story that changes in real time based on who you are and how you feel.
The development of reactive content will allow those working in the industry to go one step further than simply translating the essence of oral storytelling into VR. Rather than having a narrative experience with a digital storyteller who can read you, reactive content has the potential to create an experience with a storyteller who knows you.
This means being able to subtly insert minor personal details that have a specific meaning to the viewer. When we talk to our friends we often use experiences we’ve shared in the past or knowledge of our audience to give our story as much resonance as possible. Targeting personal memories and aspects of our lives is a highly effective way to elicit emotions and aid in visualizing narratives. When you can do this with the addition of visuals, music, and characters—all lifted from someone’s past—you have the potential for overwhelmingly engaging and emotionally-charged content.
Future Lighthouse inform me that for now, reactive content will rely primarily on biometric feedback technology such as breathing, heartbeat, and eye tracking sensors. A simple example would be a story in which parts of the environment or soundscape change in sync with the user’s heartbeat and breathing, or characters who call you out for not paying attention.
The next step would be characters and situations that react to the user’s emotions, wherein algorithms analyze biometric information to make inferences about states of emotional arousal (“why are you so nervous?” etc.). Another example would be implementing the use of “arousal parameters,” where the audience can choose what level of “fear” they want from a VR horror story before algorithms modulate the experience using information from biometric feedback devices.
The company’s long-term goal is to gather research on storytelling conventions and produce a catalogue of story “wireframes.” This entails distilling the basic formula to different genres so they can then be fleshed out with visuals, character traits, and soundtracks that are tailored for individual users based on their deep data, preferences, and biometric information.
The development of reactive content will go hand in hand with a renewed exploration of diverging, dynamic storylines, and multi-narratives, a concept that hasn’t had much impact in the movie world thus far. In theory, the idea of having a story that changes and mutates is captivating largely because of our love affair with serendipity and unpredictability, a cultural condition theorist Arthur Kroker refers to as the “hypertextual imagination.” This feeling of stepping into the unknown with the possibility of deviation from the habitual translates as a comforting reminder that our own lives can take exciting and unexpected turns at any moment.
The inception of the concept into mainstream culture dates to the classic Choose Your Own Adventure book series that launched in the late 70s, which in its literary form had great success. However, filmic takes on the theme have made somewhat less of an impression. DVDs like I’m Your Man (1998) and Switching (2003) both use scene selection tools to determine the direction of the storyline.
A more recent example comes from Kino Industries, who claim to have developed the technology to allow filmmakers to produce interactive films in which viewers can use smartphones to quickly vote on which direction the narrative takes at numerous decision points throughout the film.
The main problem with diverging narrative films has been the stop-start nature of the interactive element: when I’m immersed in a story I don’t want to have to pick up a controller or remote to select what’s going to happen next. Every time the audience is given the option to take a new path (“press this button”, “vote on X, Y, Z”) the narrative— and immersion within that narrative—is temporarily halted, and it takes the mind a while to get back into this state of immersion.
Reactive content has the potential to resolve these issues by enabling passive interactivity—that is, input and output without having to pause and actively make decisions or engage with the hardware. This will result in diverging, dynamic narratives that will unfold seamlessly while being dependent on and unique to the specific user and their emotions. Passive interactivity will also remove the game feel that can often be a symptom of interactive experiences and put a viewer somewhere in the middle: still firmly ensconced in an interactive dynamic narrative, but in a much subtler way.
While reading the Melita script I was particularly struck by a scene in which the characters start to engage with the user and there’s a synchronicity between the user’s heartbeat and objects in the virtual world. As the narrative unwinds and the words of Melita’s character get more profound, parts of the landscape, which seemed to be flashing and pulsating at random, come together and start to mimic the user’s heartbeat.
In 2013, Jane Aspell of Anglia Ruskin University (UK) and Lukas Heydrich of the Swiss Federal Institute of Technology proved that a user’s sense of presence and identification with a virtual avatar could be dramatically increased by syncing the on-screen character with the heartbeat of the user. The relationship between bio-digital synchronicity, immersion, and emotional engagement is something that will surely have revolutionary narrative and storytelling potential.
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Posted in Human Robots

#431389 Tech Is Becoming Emotionally ...

Posted on November 2, 2017 by Android

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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Posted in Human Robots

#430855 Why Education Is the Hardest Sector of ...

Posted on August 13, 2017 by Android

We’ve all heard the warning cries: automation will disrupt entire industries and put millions of people out of jobs. In fact, up to 45 percent of existing jobs can be automated using current technology.
However, this may not necessarily apply to the education sector. After a detailed analysis of more than 2,000-plus work activities for more than 800 occupations, a report by McKinsey & Co states that of all the sectors examined, “…the technical feasibility of automation is lowest in education.”
There is no doubt that technological trends will have a powerful impact on global education, both by improving the overall learning experience and by increasing global access to education. Massive open online courses (MOOCs), chatbot tutors, and AI-powered lesson plans are just a few examples of the digital transformation in global education. But will robots and artificial intelligence ever fully replace teachers?
The Most Difficult Sector to Automate
While various tasks revolving around education—like administrative tasks or facilities maintenance—are open to automation, teaching itself is not.
Effective education involves more than just transfer of information from a teacher to a student. Good teaching requires complex social interactions and adaptation to the individual student’s learning needs. An effective teacher is not just responsive to each student’s strengths and weaknesses, but is also empathetic towards the student’s state of mind. It’s about maximizing human potential.
Furthermore, students don’t just rely on effective teachers to teach them the course material, but also as a source of life guidance and career mentorship. Deep and meaningful human interaction is crucial and is something that is very difficult, if not impossible, to automate.
Automating teaching is an example of a task that would require artificial general intelligence (as opposed to narrow or specific intelligence). In other words, this is the kind of task that would require an AI that understands natural human language, can be empathetic towards emotions, plan, strategize and make impactful decisions under unpredictable circumstances.
This would be the kind of machine that can do anything a human can do, and it doesn’t exist—at least, not yet.
We’re Getting There
Let’s not forget how quickly AI is evolving. Just because it’s difficult to fully automate teaching, it doesn’t mean the world’s leading AI experts aren’t trying.
Meet Jill Watson, the teaching assistant from Georgia Institute of Technology. Watson isn’t your average TA. She’s an IBM-powered artificial intelligence that is being implemented in universities around the world. Watson is able to answer students’ questions with 97 percent certainty.
Technologies like this also have applications in grading and providing feedback. Some AI algorithms are being trained and refined to perform automatic essay scoring. One project has achieved a 0.945 correlation with human graders.
All of this will have a remarkable impact on online education as we know it and dramatically increase online student retention rates.

Any student with a smartphone can access a wealth of information and free courses from universities around the world. MOOCs have allowed valuable courses to become available to millions of students. But at the moment, not all participants can receive customized feedback for their work. Currently, this is limited by manpower, but in the future that may not be the case.
What chatbots like Jill Watson allow is the opportunity for hundreds of thousands, if not millions, of students to have their work reviewed and all their questions answered at a minimal cost.
AI algorithms also have a significant role to play in personalization of education. Every student is unique and has a different set of strengths and weaknesses. Data analysis can be used to improve individual student results, assess each student’s strengths and weaknesses, and create mass-customized programs. Algorithms can analyze student data and consequently make flexible programs that adapt to the learner based on real-time feedback. According to the McKinsey Global Institute, all of this data in education could unlock between $900 billion and $1.2 trillion in global economic value.
Beyond Automated Teaching
It’s important to recognize that technological automation alone won’t fix the many issues in our global education system today. Dominated by outdated curricula, standardized tests, and an emphasis on short-term knowledge, many experts are calling for a transformation of how we teach.
It is not enough to simply automate the process. We can have a completely digital learning experience that continues to focus on outdated skills and fails to prepare students for the future. In other words, we must not only be innovative with our automation capabilities, but also with educational content, strategy, and policies.
Are we equipping students with the most important survival skills? Are we inspiring young minds to create a better future? Are we meeting the unique learning needs of each and every student? There’s no point automating and digitizing a system that is already flawed. We need to ensure the system that is being digitized is itself being transformed for the better.
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Posted in Human Robots

#430667 Welcome to a More Discoverable ...

Posted on July 13, 2017 by Android

This week we’ve rolled out our first major round of improvements to Singularity Hub since our ground-up redesign last December. If we did it right, you’ll find that discovering the technological goodies you come here for is much easier, and so too are other Singularity University offerings you might be interested in.
The first and most major change is in the way Hub’s navigation is structured.
The previous categories in our header (Tech, Future, Health, Science) have been replaced by a single page, Topics, which profiles the most popular tech topics across our site. The featured topics in this menu will be updated regularly based on article performance, so you can keep up with what’s trending in AI, biotech, neuroscience, robotics, or whatever is making the biggest splash most recently.
Rolling our hottest topic category tags into one header dropdown allowed us to create greater focus on some of our newest and best offerings.
Our header now prominently features In Focus, which includes articles on how leaders can make the most of today’s accelerating pace of change by learning to think like futurists, innovators, technologists, and humanitarians. We’ve always been technological optimists, and we want to to make it easy for leaders to find the stories that help make hopeful problem-solvers of us all.
We’ve added a section for Experts, which features leaders in the Singularity University community and showcases their thought leadership including interviews and books. In Events, we highlight Singularity University’s global library of local happenings and summits.
Lastly, we’re excited that our growing original video efforts—from our Ray Kurzweil series to our weekly tech news roundup posts—now live under a central Videos section on Hub. This also gives us a place to highlight our favorite video posts from around the web, including the sci-fi shorts we love so much.
Cruising through the rest of Hub, particularly our homepage, you’ll find a much greater variety of content options, including new stories, top stories, event coverage, and videos. In short, it’s everything a homepage should be. On posts, we’ve tried to keep things as clean as possible, and we put a lot of hours into laboriously streamlining our content tagging structure, making it much easier for you to click through category tags into other stories you might like.

Here’s what @singularityhub looked like 2 years ago, 2 weeks ago, & today. Check it out: https://t.co/7cmlTJwc7d pic.twitter.com/jDayIEIFNv
— Singularity Hub (@singularityhub) July 13, 2017

You’ll also see greater visibility into Singularity University events, along with clearer ways to keep up with Hub and SU both, from simple email newsletter signups to callouts for the SingularityU Hub iOS app and events like SU’s Experts on Air series.
We hope you enjoy the ever-evolving, ever-improving Singularity Hub, and we’d love to hear your feedback. Feel free to tweet us, and let us know your thoughts. You can also pitch us or email us. And as always, thank you for your support. Continue reading →

Posted in Human Robots

#430649 Robotherapy for children with autism

Posted on July 11, 2017 by Android

New Robotherapy for children with autism could reduce patient supervision by therapists.
05.07.2017
Autism treatments and therapies routinely make headlines. With robot enhanced therapies on the rise, often overlooked though, is the mental stress and physical toll the procedures take on therapists. As autism treatments can be taxing on both patient and therapists, few realize the stress and workload of those working with autistic patients.
It is against this backdrop, that researchers from the Vrije Universiteit Brussel are pioneering a new technology to aid behavioural therapy, and one with a very deliberate aspect: they are using robots to boost the basic social learning skills of children with ASD and while doing so, they hope to make the therapists’ job substantially easier.
A study, just published in PALADYN – Journal of Behavioural Robotics examines the use of social robots as tools in clinical situations by addressing the challenge of increasing robot autonomy.
The growing deployment of robot-assisted therapies in recent decades means children with Autism Spectrum Disorder (ASD) can develop and nurture social behaviour and cognitive skills. Learning skills that hold out in real life is the first and foremost goal of all autism therapies, including the Robot-Assisted Therapy (RAT), with effectiveness always considered a key concern. However, this time round the scientists have set off on the additional mission to take the load off the human therapists by letting parts of the intervention be taken over by the supervised yet autonomous robots.
The researchers developed a complete system of robot-enhanced therapy (RET) for children with ASD. The therapy works by teaching behaviours during repeated sessions of interactive games. Since the individuals with ASD tend to be more responsive to feedback coming from an interaction with technology, robots are often used for this therapy. In this approach, the social robot acts as a mediator and typically remains remote-controlled by a human operator. The technique, called Wizard of Oz, requires the robot to be operated by an additional person and the robot is not recording the performance during the therapy. In order to reduce operator workload, authors introduced a system with a supervised autonomous robot – which is able to understand the psychological disposition of the child and use it to select actions appropriate to the current state of the interaction.
Admittedly, robots with supervised autonomy can substantially benefit behavioural therapy for children with ASD – diminishing the therapist workload on the one hand, and achieving more objective measurements of therapy outcomes on the other. Yet, complex as it is, this therapy requires a multidisciplinary approach, as RET provides mixed effectiveness for primary tasks: the turn-taking, joint attention and imitation task comparing to Standard Human Treatment (SHT).
Results are likely to prompt a further development of the robot assisted therapy with increasing robot’s autonomy. With many outstanding conceptual and technical issues yet to tackle –it is definitely the ethical questions that pose one of the major challenges as far as the potential and maximal degree of robot autonomy is concerned.
The article is fully available in open access to read, download and share on De Gruyter Online.
Research was conducted as a part of DREAM (Development of Robot-Enhanced therapy for children with Autism spectrum disorders) project.
DOI: 10.1515/pjbr-2017-0002
Image credit: P.G. Esteban
About the Journal: PALADYN – Journal of Behavioural Robotics is a fully peer-reviewed, electronic-only journal that publishes original, high-quality research on topics broadly related to neuronally and psychologically inspired robots and other behaving autonomous systems.
About De Gruyter Open: De Gruyter Open is a leading publisher of Open Access academic content. Publishing in all major disciplines, De Gruyter Open is home to more than 500 scholarly journals and over 100 books. The company is part of the De Gruyter Group (www.degruyter.com) and a member of the Association of Learned and Professional Society Publishers (ALPSP). De Gruyter Open’s book and journal programs have been endorsed by the international research community and some of the world’s top scientists, including Nobel laureates. The company’s mission is to make the very best in academic content freely available to scholars and lay readers alike.
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Posted in Human Robots