Consumer’s Information Privacy and Security Concerns and Use of Intelligent Technology

A Review of Recent Deep Learning Approaches in Human-Centered Machine Learning

“…The breadth of our HCML definition also includes work done in areas such as explainable AI (XAI) and data privacy. Sub-research areas such as these have a number of researchers creating different research avenues [ 11 , 12 , 15 , 17 , 20 , 26 , 28 , 32 , 38 , 39 , 40 , 41 ]. For instance, there are works on developing algorithms and novel DL architectures in XAI to add explainability to the models [ 42 , 43 , 44 , 45 , 46 ].…”

“…However, all these terms' underlying principle remains the same, which is developing usable and adaptable, 'Human-in-the-Loop' machine learning systems. Some of the most common non-expert-user issues are explainability [6][7][8][9][10], interpretability [11][12][13][14], privacy and security [15][16][17][18][19][20], reliability [21][22][23][24][25], and fairness [26][27][28][29][30][31]. These categories emerged as contributing research areas of HCML, and each plays a role in the broader goal of improving the usability and adoptability of AI systems.…”

“…Features of AI models addressing the concerns of users to improve the usability and adoptability of AI systems such as explainability, interpretability, privacy, and fairness have been the focus of many HCML related work [6,12,20,26,58,73,76,81,104,178,219]. This is not surprising, given the history of XAI research area dates back to 1980s [220,221].…”