Dean's Message

During the nineteen eighties, the world of computing was dominated by the hype surrounding Fifth Generation Computing, a research and development initiative that was started by the government of Japan, and quickly followed by other jurisdictions, such as the USA, Canada and Europe.  The focus of Fifth Generation Computing was Artificial Intelligence (AI), and the parallel architectures that support its computing needs.  Artificial Intelligence failed to deliver on the promises attributed to it by the Fifth Generation initiative, and interest in AI faded by the end of that decade, only to roar back to life in the last few years on the basis of new paradigms in neural nets, machine learning, and data science.

Today artificial intelligence is all the rage, as it is the basis for the most spectacular achievements of computing, from driving vehicles to controlling robots to composing music to face recognition to medical diagnosis to composing paintings to writing speeches to language translation, etc.  The same technology can also be used for less benevolent purposes such as generating fake videos, deploying surveillance programs, spreading misinformation, mounting cybersecurity attacks and (while this is not the most malicious application, it is of much concern to us) writing student homeworks and programming assignments.  This evolution is happening at such great speed that what was in the realm of science fiction just a few months ago is now well within the capability of the latest AI tools.

This transition from traditional computing to AI-based, machine-learning based computing is taking place under the radar / behind the scenes, but it represents a significant paradigm shift in computing.  Whereas in traditional computing, systems are developed through meticulous programming, in the new paradigm, systems are developed through training:  with a sufficiently sophisticated machine learning algorithm, we can generate a system to acquire any skill, provided we feed it sufficient amounts of relevant learning data.  From a behavioral standpoint, the contrast between traditional computing and AI-based computing can be compared to the contrast between the human left brain (logical, analytical, predictable) and the human right brain (driven by creativity, intuition, emotion).   AI’s latter attribute is, understandably, the source of much anxiety.

Like any technology, but perhaps more than any technology, AI carries with it much promise but also much potential peril.  The Ying Wu College of Computing has the expertise, human resources and organizational aptitude to mount a savvy, disciplined, levelheaded response to both the promise and the peril of this important technology.  The Department of Computer Science and the Department of Data Science provide the necessary expertise in artificial intelligence, machine learning and data science to leverage the promise of this technology and capitalize on its potential; the Department of Informatics has the necessary expertise in system analysis, human computer interaction, and societal impacts of computing to assess, model and address the perils of this technology.

The Ying Wu College of Computing takes its educational and research mission to heart, and is committed to offer students and scholars a vibrant intellectual environment for learning, scholarship and personal growth.

Ali Mili

Interim Dean