As part of ACT’s delegation to the Corridor Business Journal’s inaugural Future of Technology luncheon on March 6, our group got a firsthand look at some of the exciting work taking place in our own backyard. Our CEO, Marten Roorda, welcomed attendees and noted our company’s efforts with AI and machine learning, in addition to our recent investment in Smart Sparrow, toward advancing the state of adaptive, personalized education. ACTNext’s own Ada Woo spoke about our endeavors toward adaptive learning and our work to date with the Educational Companion app, offering up tailored open-source educational resources.
The panelists all presented cutting edge work, from VR in classrooms to autonomous medical diagnostic robots, but I was particularly struck by the discussion of autonomous vehicles. Jim Shaw, VP of engineering with Crystal Group, detailed his company’s efforts on hardware, software, and network development that will further enable the self-driving cars already navigating some US cities. It might not seem like it, but self-driving cars and adaptive learning share some key characteristics. One enters an autonomous vehicle with the intention of being taken to a particular destination. A combination of sensors, algorithms, and data allow the vehicle to create this tailored path and then navigate you to where you want to go. Origin and destination (and by extension, pathway) varies tremendously among riders.
Likewise, learners have starting points, educational goals (pathways), and career choices (destinations). Obtain a particular job, attend college, or simply gaining knowledge about a certain subject are all possible examples. No two people have an identical starting point, nor path to get there. We want to be able to provide scaffolding, guidance, and resources to learners while making constant adjustments along the way via evidence presented and assessments to reach these goals. In fact, we’re already working on doing this with sensors (responses, click stream event logging, audio/video/biometric devices), algorithms, and data. Sound a bit like the autonomous vehicle world?
Bearing these similarities in mind, it is worthwhile to take a clear-eyed look at lessons we’ve learned and are still learning from both areas. Very recently, a first fatality occurred involving an autonomous vehicle. It’s still unfolding and the root cause is under investigation. But we have to be mindful of the unique challenges we’ll face in a future where the decision processes that guide us along our pathways won’t always be immediately evident. While work on adaptive learning and assessment would have to take a pretty drastic turn to result in such a grim end, it can still have an enormous impact on an individual’s life. An adaptive, personalized future, has already arrived in many respects, but we’re just at the edge of the forest. As the researchers and technologists working to forge ahead, clear the pathways and serve as guides, we must recognize the responsibility that entails.
Artificial Intelligence and Machine Learning