Artificial Intelligence

IBM, Pearson and the Cognitive Infrastructure of Education

Monday, November 28, 2016 Comment watson

The world’s largest edu-business, Pearson, partnered with one of the world’s largest computing companies, IBM, at the end of October 2016 to develop new approaches to education in the “cognitive era.” Their partnership was anticipated earlier in the year when both organizations produced reports about the future trajectories of cognitive computing and artificial intelligence for personalizing learning. I wrote a piece highlighting the key claims of both at the time, and have previously published some articles tracing both Pearson’s interests in big data and IBM’s development of cognitive systems for learning. The announcement of their partnership


Artificial Intelligence, Cognitive Systems and the Learning Brain

Monday, May 30, 2016 Comment hand holding multi-colored wires

New ideas about artificial intelligence and cognitive computing systems in education have been advanced this year by major computing and educational businesses, including Pearson and IBM. Pearson’s promotion of AI reflects its growing interests in data analytics and other digital methods while IBM is seeking to extend its existing R&D on cognitive computing into the education sector. AI has been the subject of serious debate recently. High profile figures including Stephen Hawking, Bill Gates and Elon Musk have voiced concern about the threats it poses, while awareness about cognitive computing has been fueled by widespread media


Computing Brains: Neuroscience, Machine Intelligence and Big Data in the Cognitive Classroom

Monday, December 08, 2014 Comment detailed graphic of human brain function lights numbers

The human brain has become a major topic in education. The field of educational neuroscience, or neuroeducation, is flourishing. At the same time, a number of initiatives based in computer science departments and major technology companies are also taking the brain seriously. Computer scientists talk of developing new brain-inspired cognitive learning systems, or of developing new theoretical and computational understandings of the brain in order to then build new and more effective forms of machine intelligence. The important aspect of these synchronous developments in neuroscience and brain-based systems is that they are beginning to come together