Technology is transforming what happens when a child goes to school

This article argues that technology-enabled 'personalized learning' offers huge promise to advance education across subjects and student circumstances. Advances in AI and other "ed tech" technologies are making it possible to craft compelling learning experiences that are responsive to a student's needs and interests.  

EC agrees with the underlying premise of 'responsive learning', namely that a student's learning experience is enriched and furthered by an active, responsive dialogue over the topic. Just as a good teacher would tailor his/her direction based on a child's response, so too should good education technology. In our pursuit to advance AI over natural human language, we believe we will make contributions relevant to the education field.
Education Technology Responsive Learning
 

This article argues that technology-enabled 'personalized learning' offers huge promise to advance education across subjects and student circumstances. Advances in AI and other "ed tech" technologies are making it possible to craft compelling learning experiences that are responsive to a student's needs and interests.  

EC agrees with the underlying premise of 'responsive learning', namely that a student's learning experience is enriched and furthered by an active, responsive dialogue over the topic. Just as a good teacher would tailor his/her direction based on a child's response, so too should good education technology. In our pursuit to advance AI over natural human language, we believe we will make contributions relevant to the education field.
Education Technology Responsive Learning
 

 

Machines as thought partners

David Ferrucci thinks big when he looks at the potential of artificial intelligence. He sees a future in which AI will become a powerful amplifier of human creative potential – a system based not on machine learning but natural learning that will enable humans and machines to explore, collaborate and ask "why" together.

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AI needs to answer "Why?" Language understanding Collaborative thought partner
PopTech
 

David Ferrucci thinks big when he looks at the potential of artificial intelligence. He sees a future in which AI will become a powerful amplifier of human creative potential – a system based not on machine learning but natural learning that will enable humans and machines to explore, collaborate and ask "why" together.

Watch Video

AI needs to answer "Why?" Language understanding Collaborative thought partner
PopTech
 

 

The Lack of Intelligence About Artificial Intelligence

This article argues that in the coming years, AI advances will lead to transition and displacement, and the emerging crisis will be about reaction and replacement policy. Lots of pundits talk about the industries most likely to be impacted by AI, but very few talk about the small number of humans who create the technology, how the technology will inevitably become just another black box appliance, or how the transition to machines will be managed.

This article supports EC's position that AI needs to be able to give us rational answers that explain outputs. If/when humans are displaced by AI, the danger is that AI will make important decisions without explanation.
AI needs to answer "Why?"
Josep Lago / AFP / Getty Images
 

This article argues that in the coming years, AI advances will lead to transition and displacement, and the emerging crisis will be about reaction and replacement policy. Lots of pundits talk about the industries most likely to be impacted by AI, but very few talk about the small number of humans who create the technology, how the technology will inevitably become just another black box appliance, or how the transition to machines will be managed.

This article supports EC's position that AI needs to be able to give us rational answers that explain outputs. If/when humans are displaced by AI, the danger is that AI will make important decisions without explanation.
AI needs to answer "Why?"
Josep Lago / AFP / Getty Images
 

 

Why this company will help change the future of artificial intelligence

"Elemental Cognition's technology seems to be aimed at the problem of going beyond the simple recognition/response models that dominate the A.I. landscape right now. I suspect Ferrucci is building out a technology that will combine outputs of deep learning and other machine-learning systems with the ability to draw inferences from, reason about and support decisions using the facts that they generate."

AI needs to answer "Why?" Language understanding
 

"Elemental Cognition's technology seems to be aimed at the problem of going beyond the simple recognition/response models that dominate the A.I. landscape right now. I suspect Ferrucci is building out a technology that will combine outputs of deep learning and other machine-learning systems with the ability to draw inferences from, reason about and support decisions using the facts that they generate."

AI needs to answer "Why?" Language understanding
 

 

Technology Quarterly: Finding A Voice

Computers have got much better at translation, voice recognition and speech synthesis, ... But they still don’t understand the meaning of language.

Language understanding AI needs to answer "Why?"
 

Computers have got much better at translation, voice recognition and speech synthesis, ... But they still don’t understand the meaning of language.

Language understanding AI needs to answer "Why?"
 

 

AI's Language Problem

Machines that truly understand language would be incredibly useful. But we don’t know how to build them.

Language understanding
 

Machines that truly understand language would be incredibly useful. But we don’t know how to build them.

Language understanding
 

 

The Man Who Would Teach Machines to Think

This, then, is the trillion-dollar question: Will the approach undergirding AI today—an approach that borrows little from the mind, that’s grounded instead in big data and big engineering—get us to where we want to go? How do you make a search engine that understands if you don’t know how you understand? 

Language understanding
 

This, then, is the trillion-dollar question: Will the approach undergirding AI today—an approach that borrows little from the mind, that’s grounded instead in big data and big engineering—get us to where we want to go? How do you make a search engine that understands if you don’t know how you understand? 

Language understanding
 

 

Q&A: Should artificial intelligence be legally required to explain itself?

As artificial intelligence (AI) becomes more sophisticated, it also becomes more opaque. Machine-learning algorithms can grind through massive amounts of data, generating predictions and making decisions without the ability to explain to humans what it’s doing. In matters of consequence—from hiring decisions to criminal sentencing—should we require justifications? A commentary published today in Science Robotics discusses regulatory efforts to make AI more transparent, explainable, and accountable. Science spoke with the article’s primary author, Sandra Wachter, a researcher in data ethics at the University of Oxford in the United Kingdom and the Alan Turing Institute.

AI needs to answer "Why?"
 

As artificial intelligence (AI) becomes more sophisticated, it also becomes more opaque. Machine-learning algorithms can grind through massive amounts of data, generating predictions and making decisions without the ability to explain to humans what it’s doing. In matters of consequence—from hiring decisions to criminal sentencing—should we require justifications? A commentary published today in Science Robotics discusses regulatory efforts to make AI more transparent, explainable, and accountable. Science spoke with the article’s primary author, Sandra Wachter, a researcher in data ethics at the University of Oxford in the United Kingdom and the Alan Turing Institute.

AI needs to answer "Why?"
 

 

FINGER POINTING: When artificial intelligence botches your medical diagnosis, who’s to blame?

This inability arises from the opacity of AI systems, which—as a side effect of how machine-learning algorithms work—operate as black boxes. It’s impossible to understand why an AI has made the decision it has, merely that it has done so based upon the information it’s been fed. Even if it were possible for a technically literate doctor to inspect the process, many AI algorithms are unavailable for review, as they are treated as protected proprietary information. Further still, the data used to train the algorithms is often similarly protected or otherwise publicly unavailable for privacy reasons. This will likely be complicated further as doctors come to rely on AI more and more and it becomes less common to challenge an algorithm’s result.

AI needs to answer "Why?" Collaborative thought partner
 

This inability arises from the opacity of AI systems, which—as a side effect of how machine-learning algorithms work—operate as black boxes. It’s impossible to understand why an AI has made the decision it has, merely that it has done so based upon the information it’s been fed. Even if it were possible for a technically literate doctor to inspect the process, many AI algorithms are unavailable for review, as they are treated as protected proprietary information. Further still, the data used to train the algorithms is often similarly protected or otherwise publicly unavailable for privacy reasons. This will likely be complicated further as doctors come to rely on AI more and more and it becomes less common to challenge an algorithm’s result.

AI needs to answer "Why?" Collaborative thought partner