professor lo
Defending smart systems on the machine learning framework level
While smart cities and smart homes have become mainstream buzzwords, few people outside the IT and machine learning communities know about TensorFlow, PyTorch, or Theano. These are the open-source machine learning (ML) frameworks on which smart systems are built to integrate Internet of Things (IoT) devices among other things. ML algorithms and code are often found in publically available repositories, or data stores, that draw heavily on the aforementioned frameworks. In a December 2019 analysis of code hosting site GitHub, SMU Professor of Information Systems David Lo found over 46,000 repositories that were dependent on TensorFlow, and over 15,000 used PyTorch. Because of these frameworks' popularity, any vulnerability in them can be exposed to cause widespread damage.
Bringing AI into the real world
Even before countries began rolling out their vaccination campaigns, Pfizer, Moderna and AstraZeneca's announcements had already proved fortifying shots. Stocks rallied and healthcare workers celebrated in the wake of the vaccine news late last year. But months on, that early euphoria has evaporated, replaced by uncertainty and debate over vaccine safety, possible side effects and varying degrees of citizen reluctance. Artificial intelligence (AI) researchers and health experts modeling COVID-19's spread have warned that for vaccines to be useful in curbing the pandemic, a significant percentage of the population must be vaccinated to reach herd immunity. But, as SMU's Vice Provost of Research Professor Archan Misra pointed out at an AI-centered panel discussion, held in conjunction with the SMU- Global Young Scientists Summit (GYSS) on 15 January 2021, from a purely self-interested point of view, each person would be best served if all the others got vaccinated and they themselves did not have to vaccinate--because that would stop the spread of the virus without their having to take on the possible risks of side effects. To account for these considerations, Professor Misra explained, the most powerful AI-based epidemiology models actually need to incorporate concepts from the behavioral sciences and game theory.