This edited volume includes a collection of expanded papers from the 2019 Sino-German Symposium on AI-supported educational technologies, which was held in Wuhan, China, March, 2019. The contributors are distinguished researchers from computer science and learning science.
I am an AI researcher, and I’m worried about some of the societal impacts that we’re already seeing. In particular, these 5 things scare me about AI: 1. Algorithms are often implemented without ways to address mistakes. 2. AI makes it easier to not feel responsible. 3. AI encodes & magnifies bias. 4. Optimizing metrics above all else leads to negative outcomes. 5. There is no accountability for big tech companies.
Here at Trail of Bits we review a lot of code. From major open source projects to exciting new proprietary software, we’ve seen it all. But one common denominator in all of these systems is that for some inexplicable reason people still seem to think RSA is a good cryptosystem to use. Let me save…
Scalable learning is a key differentiator for modern enterprise business. The theory states that the institutions most likely to thrive in today’s changing economic environments will be those that provide opportunities not only to learn faster as a whole organization, but also to learn from other individuals and organizations to create new knowledge.
S. Dughmi. (2009)cite arxiv:0912.0322Comment: This revision corrects an error in definition 2.2, as well as provides additional intuition regarding the definitions of convex closure and concave closure.
E. Alotaibi. Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, page 158–160. Richland, SC, International Foundation for Autonomous Agents and Multiagent Systems, (2019)