April 20, 2017 9am-5pm
Sense-Making and Making Sense
Technology augments our sense-making - helping us filter signals, manipulate data and create representations. How does the interactive human-machine sense-making process work? How might technology align with human scale, timing and representation to make it work better? How might human fundamentals help us create technologies that will enhance the human experience?
On April 20th, the #mediaX2017 Conference will delve into the human mind as a sense-making organ, keeping as context the whole body, the whole person, in community. The communication and social sciences are already in fast pursuit of key questions, fueled by massive data. The learning, cognitive and neurosciences are entering a period of accelerated development. We start with people – how they sense, feel, think and learn.
We’ll apply knowledge about human sense-making to our explorations of sensors and signals, information processing, analysis, and reasoning by machines. Fast-moving research at the cutting edge of visual, audio and haptic technology development provides insights on new ways to deliver input to the human senses for sense-making.
We’ll add several dimensions of humanity to the human-machine interface in order to leverage both sides of the sense-making question. We'll scale up to integrate findings from several fields and develop a unified understanding with broad applicability in complex settings. We'll scale down to articulate fundamental phenomena and explore them with disciplinary rigor. Each lens produces a unique perspective.
With multidisciplinary resources drawn from Stanford University and horizon questions of global importance contributed by our member organizations, inquiring minds in the mediaX community are continually asking and answering, giving feedback and receiving it, in pursuit of discovery, always learning.
Join us on April 20th as we share what we know and develop new discovery collaborations.
Registration Required. For any questions, please email Addy Dawes.
Michal Kosinski is an Assistant Professor in Organizational Behavior at the Graduate School of Business, Stanford University. Kosinski’s research has had a significant impact on both academia and the industry. His findings featured in The Economist, inspired two TED talks, and prompted a discussion in the EU Parliament. In 2013, Kosinski was listed among the 50 most influential people in Big Data by DataIQ and IBM, while three of his papers were placed among Altmetrics' “Top 100 Papers That Most Caught the Public Imagination”.
Paul Saffo is a forecaster with over two decades experience exploring the dynamics of large-scale, long-term change. He teaches at Stanford University and is a researcher through mediaX at Stanford University. Paul’s essays have appeared in a wide range of publications including The Harvard Business Review, Fortune, Wired, The Los Angeles Times, Newsweek, The New York Times, and the Washington Post. Paul holds degrees from Harvard College, Cambridge University and Stanford University.
Allison Okamura is a Professor in the mechanical engineering department at Stanford University, with a courtesy appointment in computer science. She was previously Professor and Vice Chair of mechanical engineering at Johns Hopkins University. Her research focuses on developing the principles and tools needed to realize advanced robotic and human-machine systems capable of haptic (touch) interaction, particularly for biomedical applications. Haptic systems are designed and studied using both analytical and experimental approaches.
Bill Newsome is an Investigator of the Howard Hughes Medical Institute and Professor of Neurobiology at the Stanford University School of Medicine. Dr. Newsome is a leading investigator in systems and cognitive neuroscience. He has made fundamental contributions to our understanding of the neural mechanisms underlying visual perception and simple forms of decision making. Newsome recently co-chaired the NIH BRAIN working group, charged with forming a national plan for the coming decade of neuroscience research in the United States.